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  • 1.
    Abadpour, Shadab
    et al.
    Oslo Univ Hosp, Norway; Univ Oslo, Norway.
    Tyrberg, Bjorn
    AstraZeneca, Sweden.
    Schive, Simen W.
    Oslo Univ Hosp, Norway.
    Wennberg Huldt, Charlotte
    AstraZeneca, Sweden.
    Gennemark, Peter
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. AstraZeneca, Sweden.
    Ryberg, Erik
    AstraZeneca, Sweden.
    Ryden-Bergsten, Tina
    AstraZeneca, Sweden.
    Smith, David M.
    AstraZeneca, Sweden; AstraZeneca, England.
    Korsgren, Olle
    Uppsala Univ, Sweden.
    Skrtic, Stanko
    AstraZeneca, Sweden; Univ Gothenburg, Sweden.
    Scholz, Hanne
    Oslo Univ Hosp, Norway; Univ Oslo, Norway.
    Winzell, Maria Sorhede
    AstraZeneca, Sweden.
    Inhibition of the prostaglandin D-2-GPR44/DP2 axis improves human islet survival and function2020In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 63, no 7, p. 1355-1367Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis Inflammatory signals and increased prostaglandin synthesis play a role during the development of diabetes. The prostaglandin D-2 (PGD(2)) receptor, GPR44/DP2, is highly expressed in human islets and activation of the pathway results in impaired insulin secretion. The role of GPR44 activation on islet function and survival rate during chronic hyperglycaemic conditions is not known. In this study, we investigate GPR44 inhibition by using a selective GPR44 antagonist (AZ8154) in human islets both in vitro and in vivo in diabetic mice transplanted with human islets. Methods Human islets were exposed to PGD(2) or proinflammatory cytokines in vitro to investigate the effect of GPR44 inhibition on islet survival rate. In addition, the molecular mechanisms of GPR44 inhibition were investigated in human islets exposed to high concentrations of glucose (HG) and to IL-1 beta. For the in vivo part of the study, human islets were transplanted under the kidney capsule of immunodeficient diabetic mice and treated with 6, 60 or 100 mg/kg per day of a GPR44 antagonist starting from the transplantation day until day 4 (short-term study) or day 17 (long-term study) post transplantation. IVGTT was performed on mice at day 10 and day 15 post transplantation. After termination of the study, metabolic variables, circulating human proinflammatory cytokines, and hepatocyte growth factor (HGF) were analysed in the grafted human islets. Results PGD(2) or proinflammatory cytokines induced apoptosis in human islets whereas GPR44 inhibition reversed this effect. GPR44 inhibition antagonised the reduction in glucose-stimulated insulin secretion induced by HG and IL-1 beta in human islets. This was accompanied by activation of the Akt-glycogen synthase kinase 3 beta signalling pathway together with phosphorylation and inactivation of forkhead box O-1and upregulation of pancreatic and duodenal homeobox-1 and HGF. Administration of the GPR44 antagonist for up to 17 days to diabetic mice transplanted with a marginal number of human islets resulted in reduced fasting blood glucose and lower glucose excursions during IVGTT. Improved glucose regulation was supported by increased human C-peptide levels compared with the vehicle group at day 4 and throughout the treatment period. GPR44 inhibition reduced plasma levels of TNF-alpha and growth-regulated oncogene-alpha/chemokine (C-X-C motif) ligand 1 and increased the levels of HGF in human islets. Conclusions/interpretation Inhibition of GPR44 in human islets has the potential to improve islet function and survival rate under inflammatory and hyperglycaemic stress. This may have implications for better survival rate of islets following transplantation.

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  • 2.
    Abbott, Rebecca
    et al.
    Northwestern Univ, IL 60611 USA.
    Peolsson, Anneli
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    West, Janne
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Elliott, James M.
    Northwestern Univ, IL 60611 USA; Univ Queensland, Australia; Zurich Univ Appl Sci, Switzerland.
    Åslund, Ulrika
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging2018In: The spine journal, ISSN 1529-9430, E-ISSN 1878-1632, Vol. 18, no 5, p. 717-725Article in journal (Refereed)
    Abstract [en]

    BACKGROUND CONTEXT: The development of muscle fat infiltration (MFI) in the neck muscles is associated with poor functional recovery following whiplash injury. Custom software and time-consuming manual segmentation of magnetic resonance imaging (MRI) is required for quantitative analysis and presents as a barrier for clinical translation. PURPOSE: The purpose of this work was to establish a qualitative MRI measure for MFI and evaluate its ability to differentiate between individuals with severe whiplash-associated disorder (WAD), mild or moderate WAD, and healthy controls. STUDY DESIGN/SETTING: This is a cross-sectional study. PATIENT SAMPLE: Thirty-one subjects with WAD and 31 age-and sex-matched controls were recruited from an ongoing randomized controlled trial. OUTCOME MEASURES: The cervical multifidus was visually identified and segmented into eighths in the axial fat/water images (C4-C7). Muscle fat infiltration was assessed on a visual scale: 0 for no or marginal MFI, 1 for light MFI, and 2 for distinct MFI. The participants with WAD were divided in two groups: mild or moderate and severe based on Neck Disability Index % scores. METHODS: The mean regional MFI was compared between the healthy controls and each of the WAD groups using the Mann-Whitney U test. Receiver operator characteristic (ROC) analyses were carried out to evaluate the validity of the qualitative method. RESULTS: Twenty (65%) patients had mild or moderate disability and 11 (35%) were considered severe. Inter- and intra-rater reliability was excellent when grading was averaged by level or when frequency of grade II was considered. Statistically significant differences (pamp;lt;.05) in regional MFI were particularly notable between the severe WAD group and healthy controls. The ROC curve, based on detection of distinct MFI, showed an area-under-the curve of 0.768 (95% confidence interval 0.59-0.94) for discrimination of WAD participants. CONCLUSIONS: These preliminary results suggest a qualitative MRI measure for MFI is reliable and valid, and may prove useful toward the classification of WAD in radiology practice. (C) 2017 Elsevier Inc. All rights reserved.

  • 3. Order onlineBuy this publication >>
    Abramian, David
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Modern multimodal methods in brain MRI2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Magnetic resonance imaging (MRI) is one of the pillars of modern medical imaging, providing a non-invasive means to generate 3D images of the body with high soft-tissue contrast. Furthermore, the possibilities afforded by the design of MRI sequences enable the signal to be sensitized to a multitude of physiological tissue properties, resulting in a wide variety of distinct MRI modalities for clinical and research use. 

    This thesis presents a number of advanced brain MRI applications, which fulfill, to differing extents, two complementary aims. On the one hand, they explore the benefits of a multimodal approach to MRI, combining structural, functional and diffusion MRI, in a variety of contexts. On the other, they emphasize the use of advanced mathematical and computational tools in the analysis of MRI data, such as deep learning, Bayesian statistics, and graph signal processing. 

    Paper I introduces an anatomically-adapted extension to previous work in Bayesian spatial priors for functional MRI data, where anatomical information is introduced from a T1-weighted image to compensate for the low anatomical contrast of functional MRI data. 

    It has been observed that the spatial correlation structure of the BOLD signal in brain white matter follows the orientation of the underlying axonal fibers. Paper II argues about the implications of this fact on the ideal shape of spatial filters for the analysis of white matter functional MRI data. By using axonal orientation information extracted from diffusion MRI, and leveraging the possibilities afforded by graph signal processing, a graph-based description of the white matter structure is introduced, which, in turn, enables the definition of spatial filters whose shape is adapted to the underlying axonal structure, and demonstrates the increased detection power resulting from their use. 

    One of the main clinical applications of functional MRI is functional localization of the eloquent areas of the brain prior to brain surgery. This practice is widespread for various invasive surgeries, but is less common for stereotactic radiosurgery (SRS), a non-invasive surgical procedure wherein tissue is ablated by concentrating several beams of high-energy radiation. Paper III describes an analysis and processing pipeline for functional MRI data that enables its use for functional localization and delineation of organs-at-risk for Elekta GammaKnife SRS procedures. 

    Paper IV presents a deep learning model for super-resolution of diffusion MRI fiber ODFs, which outperforms standard interpolation methods in estimating local axonal fiber orientations in white matter. Finally, Paper V demonstrates that some popular methods for anonymizing facial data in structural MRI volumes can be partially reversed by applying generative deep learning models, highlighting one way in which the enormous power of deep learning models can potentially be put to use for harmful purposes. 

    List of papers
    1. Anatomically Informed Bayesian Spatial Priors for FMRI Analysis
    Open this publication in new window or tab >>Anatomically Informed Bayesian Spatial Priors for FMRI Analysis
    Show others...
    2020 (English)In: ISBI 2020: IEEE International Symposium on Biomedical Imaging / [ed] IEEE, IEEE, 2020Conference paper, Published paper (Refereed)
    Abstract [en]

    Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical boundaries. We propose two anatomically informed Bayesian spatial models for fMRI data with local smoothing in each voxel based on a tensor field estimated from a T1-weighted anatomical image. We show that our anatomically informed Bayesian spatial models results in posterior probability maps that follow the anatomical structure.

    Place, publisher, year, edition, pages
    IEEE, 2020
    Series
    IEEE International Symposium on Biomedical Imaging, ISSN 1945-7928, E-ISSN 1945-8452
    Keywords
    Bayesian statistics, functional MRI, activation mapping, adaptive smoothing
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:liu:diva-165856 (URN)10.1109/ISBI45749.2020.9098342 (DOI)000578080300208 ()978-1-5386-9330-8 (ISBN)
    Conference
    IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 3-7 April 2020
    Funder
    Swedish Research Council, 2017- 04889
    Note

    Funding agencies:  Swedish Research CouncilSwedish Research Council [201704889]; Center for Industrial Information Technology (CENIIT) at Linkoping University

    Available from: 2020-05-29 Created: 2020-05-29 Last updated: 2023-03-31Bibliographically approved
    2. Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters
    Open this publication in new window or tab >>Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters
    Show others...
    2021 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 237, article id 118095Article in journal (Refereed) Published
    Abstract [en]

    Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detachability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject’s unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project’s 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

    Place, publisher, year, edition, pages
    Elsevier, 2021
    Keywords
    functional MRI, diffusion MRI, white matter, graph signal processing, anisotropy
    National Category
    Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
    Identifiers
    urn:nbn:se:liu:diva-175762 (URN)10.1016/j.neuroimage.2021.118095 (DOI)000671134200006 ()34000402 (PubMedID)
    Funder
    Swedish Research Council, 2018-06689Swedish Research Council, 2017- 04889Vinnova, 2018-02230NIH (National Institute of Health), K01DK101631NIH (National Institute of Health), R56AG068261
    Note

    Funding: McDonnell Center for Systems Neuroscience at Washington University; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2017-04889, 2018-06689]; Royal Physiographic Society of Lund; Thorsten and Elsa Segerfalk Foundation; Hans Werthen Foundation; ITEA3/VINNOVA; Center for Industrial Information Technology (CENIIT) at Linkoping University; BrightFocus FoundationBrightFocus Foundation [A2016172S]; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA; National Institute of Diabetes and Digestive and Kidney DiseasesUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) [K01DK101631]; National Institute on AgingUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Aging (NIA) [R56AG068261];  [1U54MH091657]

    Available from: 2021-05-19 Created: 2021-05-19 Last updated: 2023-03-31
    3. REFACING: RECONSTRUCTING ANONYMIZED FACIAL FEATURES USING GANS
    Open this publication in new window or tab >>REFACING: RECONSTRUCTING ANONYMIZED FACIAL FEATURES USING GANS
    2019 (English)In: 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), IEEE , 2019, p. 1104-1108Conference paper, Published paper (Refereed)
    Abstract [en]

    Anonymization of medical images is necessary for protecting the identity of the test subjects, and is therefore an essential step in data sharing. However, recent developments in deep learning may raise the bar on the amount of distortion that needs to be applied to guarantee anonymity. To test such possibilities, we have applied the novel CycleGAN unsupervised image-to-image translation framework on sagittal slices of T1 MR images, in order to reconstruct, facial features from anonymized data. We applied the CycleGAN framework on both face-blurred and face-removed images. Our results show that face blurring may not provide adequate protection against malicious attempts at identifying the subjects, while face removal provides more robust anonymization, but is still partially reversible.

    Place, publisher, year, edition, pages
    IEEE, 2019
    Series
    IEEE International Symposium on Biomedical Imaging, ISSN 1945-7928, E-ISSN 1945-8452
    Keywords
    MRI; anonymization; GANs; image-to-image translation
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Identifiers
    urn:nbn:se:liu:diva-160633 (URN)10.1109/ISBI.2019.8759515 (DOI)000485040000234 ()978-1-5386-3641-1 (ISBN)
    Conference
    16th IEEE International Symposium on Biomedical Imaging (ISBI)
    Note

    Funding Agencies|Swedish research councilSwedish Research Council [201704889]; Center for Industrial Information Technology (CENIIT) at Linkoping University; Knut and Alice Wallenberg foundationKnut & Alice Wallenberg Foundation

    Available from: 2019-10-10 Created: 2019-10-10 Last updated: 2023-03-31
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  • 4.
    Abramian, David
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Blystad, Ida
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Division of Medical Informatics, Department of Biomedical Engineering Linköping University Linköping Sweden;Center for Medical Image Science and Visualization (CMIV) Linköping University Linköping Sweden;Division of Statistics & Machine Learning, Department of Computer and Information Science Linköping University Linköping Sweden.
    Evaluation of inverse treatment planning for gamma knife radiosurgery using fMRI brain activation maps as organs at risk2023In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 50, no 9, p. 5297-5311Article in journal (Refereed)
    Abstract [en]

    Background: Stereotactic radiosurgery (SRS) can be an effective primary or adjuvant treatment option for intracranial tumors. However, it carries risks of various radiation toxicities, which can lead to functional deficits for the patients. Current inverse planning algorithms for SRS provide an efficient way for sparing organs at risk (OARs) by setting maximum radiation dose constraints in the treatment planning process.Purpose: We propose using activation maps from functional MRI (fMRI) to map the eloquent regions of the brain and define functional OARs (fOARs) for Gamma Knife SRS treatment planning.Methods: We implemented a pipeline for analyzing patient fMRI data, generating fOARs from the resulting activation maps, and loading them onto the GammaPlan treatment planning software. We used the Lightning inverse planner to generate multiple treatment plans from open MRI data of five subjects, and evaluated the effects of incorporating the proposed fOARs.Results: The Lightning optimizer designs treatment plans with high conformity to the specified parameters. Setting maximum dose constraints on fOARs successfully limits the radiation dose incident on them, but can have a negative impact on treatment plan quality metrics. By masking out fOAR voxels surrounding the tumor target it is possible to achieve high quality treatment plans while controlling the radiation dose on fOARs.Conclusions: The proposed method can effectively reduce the radiation dose incident on the eloquent brain areas during Gamma Knife SRS of brain tumors.

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  • 5.
    Abramian, David
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    REFACING: RECONSTRUCTING ANONYMIZED FACIAL FEATURES USING GANS2019In: 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), IEEE , 2019, p. 1104-1108Conference paper (Refereed)
    Abstract [en]

    Anonymization of medical images is necessary for protecting the identity of the test subjects, and is therefore an essential step in data sharing. However, recent developments in deep learning may raise the bar on the amount of distortion that needs to be applied to guarantee anonymity. To test such possibilities, we have applied the novel CycleGAN unsupervised image-to-image translation framework on sagittal slices of T1 MR images, in order to reconstruct, facial features from anonymized data. We applied the CycleGAN framework on both face-blurred and face-removed images. Our results show that face blurring may not provide adequate protection against malicious attempts at identifying the subjects, while face removal provides more robust anonymization, but is still partially reversible.

    Download full text (pdf)
    fulltext
  • 6.
    Abramian, David
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Larsson, Martin
    Centre of Mathematical Sciences, Lund University, Lund, Sweden.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Aganj, Iman
    Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA.
    Westin, Carl-Fredrik
    Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA.
    Behjat, Hamid
    Department of Biomedical Engineering, Lund University, Lund, Sweden; Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
    Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters2021In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 237, article id 118095Article in journal (Refereed)
    Abstract [en]

    Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detachability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject’s unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project’s 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

    Download full text (pdf)
    fulltext
  • 7.
    Abramian, David
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Larsson, Martin
    Centre for Mathematical Sciences, Lund University, Sweden.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Behjat, Hamid
    Department of Biomedical Engineering, Lund University, Sweden.
    Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering2020In: ISBI 2020: IEEE International Symposium on Biomedical Imaging, IEEE, 2020Conference paper (Refereed)
    Abstract [en]

    Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is highly anisotropic, and related to the diffusion tensor in shape and orientation. This evidence suggests that conventional isotropic Gaussian filters are inadequate for denoising white matter fMRI data, since they are incapable of adapting to the complex anisotropic domain of white matter axonal connections. In this paper we explore a graph-based description of the white matter developed from diffusion MRI data, which is capable of encoding the anisotropy of the domain. Based on this representation we design localized spatial filters that adapt to white matter structure by leveraging graph signal processing principles. The performance of the proposed filtering technique is evaluated on semi-synthetic data, where it shows potential for greater sensitivity and specificity in white matter activation mapping, compared to isotropic filtering.

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  • 8.
    Abramian, David
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Sidén, Per
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.
    Knutsson, Hans
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Villani, Mattias
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Statistics, Stockholm University.
    Eklund, Anders
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Anatomically Informed Bayesian Spatial Priors for FMRI Analysis2020In: ISBI 2020: IEEE International Symposium on Biomedical Imaging / [ed] IEEE, IEEE, 2020Conference paper (Refereed)
    Abstract [en]

    Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical boundaries. We propose two anatomically informed Bayesian spatial models for fMRI data with local smoothing in each voxel based on a tensor field estimated from a T1-weighted anatomical image. We show that our anatomically informed Bayesian spatial models results in posterior probability maps that follow the anatomical structure.

    Download full text (pdf)
    fulltext
  • 9.
    Afshari, Ali
    et al.
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Saager, Rolf B.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Burgos, David
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Vogt, William
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Wang, Jianting
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Mendoza, Gonzalo
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Weininger, Sandy
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Sung, Kung-Bin
    National Taiwan University, Graduate Institute of Biomedical Electronics and Bioinformatics, Taipei, Taiwan.
    Durkin, Anthony
    Department of Biomedical Engineering, University of California, Irvine, Natural Sciences II, Irvine, California, USA; Beckman Laser Institute & Medical Clinic, University of California, Irvine, East Irvine, California, USA.
    Pfefer, T. Joshua
    Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
    Evaluation of the robustness of cerebral oximetry to variations in skin pigmentation using a tissue-simulating phantom2022In: Biomedical Optics Express, E-ISSN 2156-7085, Vol. 13, no 5, p. 2909-2928Article in journal (Refereed)
    Abstract [en]

    Clinical studies have demonstrated that epidermal pigmentation level can affect cerebral oximetry measurements. To evaluate the robustness of these devices, we have developed a phantom-based test method that includes an epidermis-simulating layer with several melanin concentrations and a 3D-printed cerebrovascular module. Measurements were performed with neonatal, pediatric and adult sensors from two commercial oximeters, where neonatal probes had shorter source-detector separation distances. Referenced blood oxygenation levels ranged from 30 to 90%. Cerebral oximeter outputs exhibited a consistent decrease in saturation level with simulated melanin content; this effect was greatest at low saturation levels, producing a change of up to 15%. Dependence on pigmentation was strongest in a neonatal sensor, possibly due to its high reflectivity. Overall, our findings indicate that a modular channel-array phantom approach can provide a practical tool for assessing the impact of skin pigmentation on cerebral oximeter performance and that modifications to algorithms and/or instrumentation may be needed to mitigate pigmentation bias.

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  • 10.
    Afzali, Maryam
    et al.
    Cardiff Univ, Wales; Univ Leeds, England.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Özarslan, Evren
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Jones, Derek K.
    Cardiff Univ, Wales.
    Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques2021In: Scientific Reports, E-ISSN 2045-2322, Vol. 11, no 1, article id 14345Article in journal (Refereed)
    Abstract [en]

    Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or shell), computing the orientationally-averaged signal through simple arithmetic averaging. One challenge with this approach is that not all acquisition schemes have gradient sampling vectors distributed over perfect spheres. To ameliorate this challenge, alternative averaging methods include: weighted signal averaging; spherical harmonic representation of the signal in each shell; and using Mean Apparent Propagator MRI (MAP-MRI) to derive a three-dimensional signal representation and estimate its isotropic part. Here, these different methods are simulated and compared under different signal-to-noise (SNR) realizations. With sufficiently dense sampling points (61 orientations per shell), and isotropically-distributed sampling vectors, all averaging methods give comparable results, (MAP-MRI-based estimates give slightly higher accuracy, albeit with slightly elevated bias as b-value increases). As the SNR and number of data points per shell are reduced, MAP-MRI-based approaches give significantly higher accuracy compared with the other methods. We also apply these approaches to in vivo data where the results are broadly consistent with our simulations. A statistical analysis of the simulated data shows that the orientationally-averaged signals at each b-value are largely Gaussian distributed.

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  • 11.
    Afzali, Maryam
    et al.
    University of Leeds, Leeds, United Kingdom; University of Cardiff, United Kingdom.
    Pieciak, Tomasz
    Universidad de Valladolid, Spain.
    Jones, Derek K.
    Cardiff University, United Kingdom.
    Schneider, Jürgen E.
    Leeds University, United Kingdom.
    Özarslan, Evren
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Cumulant expansion with localization: A new representation of the diffusion MRI signal2022In: Frontiers in Neuroimaging, E-ISSN 2813-1193, Vol. 1Article in journal (Refereed)
    Abstract [en]

    Diffusion MR is sensitive to the microstructural features of a sample. Fine-scale characteristics can be probed by employing strong diffusion gradients while the low b-value regime is determined by the cumulants of the distribution of particle displacements. A signal representation based on the cumulants, however, suffers from a finite convergence radius and cannot represent the ‘localization regime' characterized by a stretched exponential decay that emerges at large gradient strengths. Here, we propose a new representation for the diffusion MR signal. Our method provides not only a robust estimate of the first three cumulants but also a meaningful extrapolation of the entire signal decay.

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  • 12.
    Afzali, Maryam
    et al.
    Cardiff Univ, Wales.
    Pieciak, Tomasz
    AGH Univ Sci & Technol, Poland; Univ Valladolid, Spain.
    Newman, Sharlene
    Indiana Univ, IN 47405 USA; Indiana Univ, IN 47405 USA.
    Garyfallidis, Eleftherios
    Indiana Univ, IN 47405 USA; Indiana Univ, IN 47408 USA.
    Özarslan, Evren
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Cheng, Hu
    Indiana Univ, IN 47405 USA; Indiana Univ, IN 47405 USA.
    Jones, Derek K.
    Cardiff Univ, Wales.
    The sensitivity of diffusion MRI to microstructural properties and experimental factors2021In: Journal of Neuroscience Methods, ISSN 0165-0270, E-ISSN 1872-678X, Vol. 347, article id 108951Article, review/survey (Refereed)
    Abstract [en]

    Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.

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  • 13.
    Aghajary, Mohammad Mahdi
    et al.
    Natl Iranian Gas Co, Iran.
    Gharehbaghi, Arash
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    A novel adaptive control design method for stochastic nonlinear systems using neural network2021In: Neural Computing & Applications, ISSN 0941-0643, E-ISSN 1433-3058, Vol. 33, no 15, p. 9259-9287Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel method for designing an adaptive control system using radial basis function neural network. The method is capable of dealing with nonlinear stochastic systems in strict-feedback form with any unknown dynamics. The proposed neural network allows the method not only to approximate any unknown dynamic of stochastic nonlinear systems, but also to compensate actuator nonlinearity. By employing dynamic surface control method, a common problem that intrinsically exists in the back-stepping design, called "explosion of complexity", is resolved. The proposed method is applied to the control systems comprising various types of the actuator nonlinearities such as Prandtl-Ishlinskii (PI) hysteresis, and dead-zone nonlinearity. The performance of the proposed method is compared to two different baseline methods: a direct form of backstepping method, and an adaptation of the proposed method, named APIC-DSC, in which the neural network is not contributed in compensating the actuator nonlinearity. It is observed that the proposed method improves the failure-free tracking performance in terms of the Integrated Mean Square Error (IMSE) by 25%/11% as compared to the backstepping/APIC-DSC method. This depression in IMSE is further improved by 76%/38% and 32%/49%, when it comes with the actuator nonlinearity of PI hysteresis and dead-zone, respectively. The proposed method also demands shorter adaptation period compared with the baseline methods.

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  • 14.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd & Transport Res Inst, S-58195 Linkoping, Sweden.
    Diederichs, Frederik
    Fraunhofer Inst Optron, Germany.
    Teichmann, Daniel
    Univ Southern Denmark, Denmark; MIT, MA 02139 USA.
    Technologies for Risk Mitigation and Support of Impaired Drivers2022In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 5, p. 4736-4738Article in journal (Other academic)
    Abstract [en]

    This editorial serves as an extended introduction to the Special Issue on Technologies for Risk Mitigation and Support of Impaired Drivers. It gives the context to recent advances in assisted and automated driving and the new challenges that arise when modern technology meets human users. The Special Issue focuses on the development of robust sensors and detection algorithms for driver state monitoring of fatigue, stress, and inattention, and on the development of personalized multimodal, user-oriented, and adaptive information, warning, actuation, and handover strategies. A summary of more recent developments serves as a motivation for each article that follows.

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  • 15.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Georgoulas, George
    Univ Patras, Greece; DataWise Data Engn LLC, GA 30318 USA.
    Kircher, Katja
    Linköping University, Department of Behavioural Sciences and Learning, Psychology. Linköping University, Faculty of Arts and Sciences.
    Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm2022In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 5, p. 4778-4790Article in journal (Refereed)
    Abstract [en]

    This paper presents initial work on a context-dependent driver distraction detection algorithm called AttenD2.0, which extends the original AttenD algorithm with elements from the Minimum Required Attention (MiRA) theory. Central to the original AttenD algorithm is a time buffer which keeps track of how often and for how long the driver looks away from the forward roadway. When the driver looks away the buffer is depleted and when looking back the buffer fills up. If the buffer runs empty the driver is classified as distracted. AttenD2.0 extends this concept by adding multiple buffers, thus integrating situation dependence and visual time-sharing behaviour in a transparent manner. Also, the increment and decrement of the buffers are now controlled by both static requirements (e.g. the presence of an on-ramp increases the need to monitor the sides and the mirrors) as well as dynamic requirements (e.g., reduced speed lowers the need to monitor the speedometer). The algorithm description is generic, but a real-time implementation with concrete values for different parameters is showcased in a driving simulator experiment with 16 bus drivers, where AttenD2.0 was used to ensure that drivers are attentive before taking back control after an automated bus stop docking and depot procedure. The scalability of AttenD2.0 relative to available data sources and the level of vehicle automation is demonstrated. Future work includes expanding the concept to real-world environments by automatically integrating situational information from the vehicles environmental sensing and from digital maps.

  • 16.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden.
    van Leeuwen, Wessel
    Stockholm Univ, Sweden.
    Krupenia, Stas
    Scania CV AB, Sweden.
    Jansson, Herman
    Smart Eye AB, Sweden.
    Finer, Svitlana
    Smart Eye AB, Sweden.
    Anund, Anna
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden; Stockholm Univ, Sweden.
    Kecklund, Goran
    Stockholm Univ, Sweden.
    Real-Time Adaptation of Driving Time and Rest Periods in Automated Long-Haul Trucking: Development of a System Based on Biomathematical Modelling, Fatigue and Relaxation Monitoring2022In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 5, p. 4758-4766Article in journal (Refereed)
    Abstract [en]

    Hours of service regulations govern the working hours of commercial motor vehicle drivers, but these regulations may become more flexible as highly automated vehicles have the potential to afford periods of in-cab rest or even sleep while the vehicle is moving. A prerequisite is robust continuous monitoring of when the driver is resting (to account for reduced time on task) or sleeping (to account for the reduced physiological drive to sleep). The overall aims of this paper are to raise a discussion of whether it is possible to obtain successful rest during automated driving, and to present initial work on a hypothetical data driven algorithm aimed to estimate if it is possible to gain driving time after resting under fully automated driving. The presented algorithm consists of four central components, a heart rate-based relaxation detection algorithm, a camera-based sleep detection algorithm, a fatigue modelling component taking time awake, time of day and time on task into account, and a component that estimates gained driving time. Real-time assessment of driver fitness is complicated, especially when it comes to the recuperative value of in-cab sleep and rest, as it depends on sleep quality, time of day, homeostatic sleep pressure and on the activities that are carried out while resting. The monotony that characterizes for long-haul truck driving is clearly interrupted for a while, but the long-term consequences of extended driving times, including user acceptance of the key stakeholders, requires further research.

  • 17.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd & Transport Res Inst VTI, Linkoping, Sweden; VTI, Olaus Magnus vag 35, S-58330 Linkoping, Sweden.
    Zemblys, Raimondas
    SmartEye AB, Sweden.
    Finer, Svitlana
    SmartEye AB, Sweden.
    Kircher, Katja
    Swedish Natl Rd & Transport Res Inst VTI, Linkoping, Sweden.
    Alcohol impairs driver attention and prevents compensatory strategies2023In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 184, article id 107010Article in journal (Refereed)
    Abstract [en]

    While the negative effects of alcohol on driving performance are undisputed, it is unclear how driver attention, eye movements and visual information sampling are affected by alcohol consumption. A simulator study with 35 participants was conducted to investigate whether and how a drivers level of attention is related to self-paced non-driving related task (NDRT)-engagement and tactical aspects of undesirable driver behaviour under increasing levels of breath alcohol concentration (BrAC) up to 1.0 %o. Increasing BrAC levels lead to more frequent speeding, short time headways and weaving, and higher NDRT engagement. Instantaneous distraction events become more frequent, with more and longer glances to the NDRT, and a general decline in visual attention to the forward roadway. With alcohol, the compensatory behaviour that is typically seen when drivers engage in NDRTs did not appear. These findings support the theory that alcohol reduces the ability to shift attention between multiple tasks. To conclude, the independent reduction in safety margins in combination with impaired attention and an increased willingness to engage in NDRTs is likely the reason behind increased crash risk when driving under the influence of alcohol.

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  • 18.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd & Transport Res Inst VTI, Olaus Magnus Vag 35, SE-58330 Linkoping, Sweden.
    Zemblys, Raimondas
    SmartEye AB, Sweden.
    Jansson, Herman
    SmartEye AB, Sweden.
    Forsberg, Christian
    Autol Dev AB, Sweden.
    Karlsson, Johan
    Autol Dev AB, Sweden.
    Anund, Anna
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish Natl Rd & Transport Res Inst VTI, Olaus Magnus Vag 35, SE-58330 Linkoping, Sweden; Stockholm Univ, Sweden.
    Effects of partially automated driving on the development of driver sleepiness2021In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 153, article id 106058Article in journal (Refereed)
    Abstract [en]

    The objective of this study was to compare the development of sleepiness during manual driving versus level 2 partially automated driving, when driving on a motorway in Sweden. The hypothesis was that partially auto-mated driving will lead to higher levels of fatigue due to underload. Eighty-nine drivers were included in the study using a 2 ? 2 design with the conditions manual versus partially automated driving and daytime (full sleep) versus night-time (sleep deprived). The results showed that night-time driving led to markedly increased levels of sleepiness in terms of subjective sleepiness ratings, blink durations, PERCLOS, pupil diameter and heart rate. Partially automated driving led to slightly higher subjective sleepiness ratings, longer blink durations, decreased pupil diameter, slower heart rate, and higher EEG alpha and theta activity. However, elevated levels of sleepiness mainly arose from the night-time drives when the sleep pressure was high. During daytime, when the drivers were alert, partially automated driving had little or no detrimental effects on driver fatigue. Whether the negative effects of increased sleepiness during partially automated driving can be compensated by the positive effects of lateral and longitudinal driving support needs to be investigated in further studies.

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  • 19.
    Akbarian-Tefaghi, Ladan
    et al.
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Akram, Harith
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Johansson, Johannes
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Zrinzo, Ludvic
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Kefalopoulou, Zinovia
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Limousin, Patricia
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Joyce, Eileen
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Hariz, Marwan
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Foltynie, Tom
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Refining the Deep Brain Stimulation Target within the Limbic Globus Pallidus Internus for Tourette Syndrome2017In: Stereotactic and Functional Neurosurgery, ISSN 1011-6125, E-ISSN 1423-0372, Vol. 95, no 4, p. 251-258Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Deep brain stimulation (DBS) in patients with severe, refractory Tourette syndrome (TS) has demonstrated promising but variable results thus far. The thalamus and anteromedial globus pallidus internus (amGPi) have been the most commonly stimulated sites within the cortico-striato thalamic circuit, but an optimal target is yet to be elucidated.

    OBJECTIVES: This study of 15 patients with long-term amGPi DBS for severe TS investigated whether a specific anatomical site within the amGPi correlated with optimal clinical outcome for the measures of tics, obsessive compulsive behaviour (OCB), and mood.

    METHODS: Validated clinical assessments were used to measure tics, OCB, quality of life, anxiety, and depression before DBS and at the latest follow-up (17-82 months). Electric field simulations were created for each patient using information on electrode location and individual stimulation parameters. A subsequent regression analysis correlated these patient-specific simulations to percentage changes in outcome measures in order to identify any significant voxels related to clinical improvement.

    RESULTS: A region within the ventral limbic GPi, specifically on the medial medullary lamina in the pallidum at the level of the AC-PC, was significantly associated with improved tics but not mood or OCB outcome.

    CONCLUSIONS: This study adds further support to the application of DBS in a tic-related network, though factors such as patient sample size and clinical heterogeneity remain as limitations and replication is required.

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  • 20.
    Ali, Zaheer
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Islam, Anik
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Sherrell, Peter
    Imperial Coll London, England.
    Le-Moine, Mark
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Lolas, Georgios
    Univ Athens, Greece.
    Syrigos, Konstantinos
    Univ Athens, Greece.
    Rafat, Mehrdad
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Jensen, Lasse
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Pharmacology.
    Adjustable delivery of pro-angiogenic FGF-2 by alginate: collagen microspheres2018In: BIOLOGY OPEN, ISSN 2046-6390, Vol. 7, no 3, article id UNSP bio027060Article in journal (Refereed)
    Abstract [en]

    Therapeutic induction of blood vessel growth (angiogenesis) in ischemic tissues holds great potential for treatment of myocardial infarction and stroke. Achieving sustained angiogenesis and vascular maturation has, however, been highly challenging. Here, we demonstrate that alginate: collagen hydrogels containing therapeutic, pro-angiogenic FGF-2, and formulated as microspheres, is a promising and clinically relevant vehicle for therapeutic angiogenesis. By titrating the amount of readily dissolvable and degradable collagen with more slowly degradable alginate in the hydrogel mixture, the degradation rates of the biomaterial controlling the release kinetics of embedded proangiogenic FGF-2 can be adjusted. Furthermore, we elaborate a microsphere synthesis protocol allowing accurate control over sphere size, also a critical determinant of degradation/release rate. As expected, alginate: collagen microspheres were completely biocompatible and did not cause any adverse reactions when injected in mice. Importantly, the amount of pro-angiogenic FGF-2 released from such microspheres led to robust induction of angiogenesis in zebrafish embryos similar to that achieved by injecting FGF-2-releasing cells. These findings highlight the use of microspheres constructed from alginate: collagen hydrogels as a promising and clinically relevant delivery system for pro-angiogenic therapy.

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  • 21.
    Alirezaie, Marjan
    et al.
    Institutionen för naturvetenskap och teknik , Örebro Universitet.
    Hammar, Karl
    Högskolan i Jönköping, JTH, Datateknik och informatik.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    SmartEnv Ontology in E-care@home2018In: SSN 2018 - Semantic Sensor Networks Workshop: Proceedings of the 9th International Semantic Sensor Networks Workshopco-located with 17th International Semantic Web Conference (ISWC 2018) / [ed] Maxime Lefrançois, Raúl Garcia Castro, Amélie Gyrard, Kerry Taylor, CEUR-WS , 2018, Vol. 2213, p. 72-79Conference paper (Refereed)
    Abstract [en]

    In this position paper we briefly introduce SmartEnv ontology which relies on SEmantic Sensor Network (SSN) ontology and is used to represent different aspects of smart and sensorized environments. We will also talk about E-carehome project aiming at providing an IoT-based health-care system for elderly people at their homes. Furthermore, we refer to the role of SmartEnv in Ecarehome and how it needs to be further extended to achieve semantic interoperability as one of the challenges in development of autonomous health care systems at home.

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    SmartEnv Ontology in E-care@home
  • 22.
    Almquist, Joachim
    et al.
    AstraZeneca, Sweden; Fraunhofer Chalmers Ctr, Sweden; AstraZeneca, Sweden.
    Rikard, S. Michaela
    Univ Virginia, VA USA.
    Wagberg, Maria
    AstraZeneca, Sweden.
    Bruce, Anthony C.
    Univ Virginia, VA USA.
    Gennemark, Peter
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. AstraZeneca, Sweden.
    Fritsche-Danielson, Regina
    AstraZeneca, Sweden.
    Chien, Kenneth R.
    Karolinska Inst, Sweden.
    Peirce, Shayn M.
    Univ Virginia, VA USA.
    Hansson, Kenny
    AstraZeneca, Sweden.
    Lundahl, Anna
    AstraZeneca, Sweden.
    Model-Based Analysis Reveals a Sustained and Dose-Dependent Acceleration of Wound Healing by VEGF-A mRNA (AZD8601)2020In: CPT: Pharmacometrics and Systems Pharmacology (PSP), E-ISSN 2163-8306, Vol. 9, no 7, p. 384-394Article in journal (Refereed)
    Abstract [en]

    Intradermal delivery of AZD8601, an mRNA designed to produce vascular endothelial growth factor A (VEGF-A), has previously been shown to accelerate cutaneous wound healing in a murine diabetic model. Here, we develop population pharmacokinetic and pharmacodynamic models aiming to quantify the effect of AZD8601 injections on the dynamics of wound healing. A dataset of 584 open wound area measurements from 131 mice was integrated from 3 independent studies encompassing different doses, dosing timepoints, and number of doses. Evaluation of several candidate models showed that wound healing acceleration is not likely driven directly by time-dependent VEGF-A concentration. Instead, we found that administration of AZD8601 induced a sustained acceleration of wound healing depending on the accumulated dose, with a dose producing 50% of the maximal effect of 92 mu g. Simulations with this model showed that a single dose of 200 mu g AZD8601 can reduce the time to reach 50% wound healing by up to 5 days.

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  • 23.
    Alonso, Fabiola
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Deep brain stimulation: Patient-specific modelling, simulation and visualization of  DBS electric field2019Conference paper (Other (popular science, discussion, etc.))
  • 24. Order onlineBuy this publication >>
    Alonso, Fabiola
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Models and Simulations of the Electric Field in Deep Brain Stimulation: Comparison of Lead Designs, Operating Modes and Tissue Conductivity2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Deep brain stimulation (DBS) is an established surgical therapy for movement disorders such as Parkinson’s disease (PD) and essential tremor (ET). A thin electrode is implanted in a predefined area of the brain with the use of stereotactic neurosurgery. In the last few years new DBS electrodes and systems have been developed with possibilities for using more parameters for control of the stimulation volume.

    In this thesis, simulations using the finite element method (FEM) have been developed and used for investigation of the electric field (EF) extension around different types of DBS lead designs (symmetric, steering) and stimulation modes (voltage, current). The electrode surrounding was represented either with a homogeneous model or a patient-specific model based on individual preoperative magnetic resonance imaging (MRI). The EF was visualized and compared for different lead designs and operating modes.

    In Paper I, the EF was quantitatively investigated around two lead designs (3389 and 6148) simulated to operate in voltage and current mode under acute and chronic time points following implantation.Simulations showed a major impact on the EF extension between postoperative time points which may explain the clinical decisions to change the stimulation amplitude weeks after implantation. In Paper II, the simulations were expanded to include two leads having steering function (6180, Surestim1) and patient-specific FEM simulations in the zona incerta. It was found that both the heterogeneity of the tissue and the operating mode, influence the EF distribution and that equivalent contact configurations of the leads result in similar EF. The steering mode presented larger volumes in current mode when using equivalent amplitudes. Simulations comparing DBS and intraoperative stimulation test using a microelectrode recording (MER) system (Paper III), showed that several parallel MER leads and the presence of the non-active DBS contacts influence the EF distribution and that the DBS EF volume can cover, but also extend to, other anatomical areas.

    Paper IV introduces a method for an objective exploitation of intraoperative stimulation test data in order to identify the optimal implant position in the thalamus of the chronic DBS lead. Patient-specific EF simulations were related to the anatomy with the help of brain atlases and the clinical effects which were quantified by accelerometers. The first results indicate that the good clinical effect in ET is due to several structures around the ventral intermediate nucleus of the thalamus.

    List of papers
    1. Influence on Deep Brain Stimulation from Lead Design, Operating Mode and Tissue Impedance Changes – A Simulation Study
    Open this publication in new window or tab >>Influence on Deep Brain Stimulation from Lead Design, Operating Mode and Tissue Impedance Changes – A Simulation Study
    2015 (English)In: Brain Disorders and Therapy, ISSN 2168-975X, Vol. 4, no 3, article id 1000169Article in journal (Refereed) Published
    Abstract [en]

    Background: Deep brain stimulation (DBS) systems in current mode and new lead designs are recently available. To switch between DBS-systems remains complicated as clinicians may lose their reference for programming. Simulations can help increase the understanding.

    Objective: To quantitatively investigate the electric field (EF) around two lead designs simulated to operate in voltage and current mode under two time points following implantation.

    Methods: The finite element method was used to model Lead 3389 (Medtronic) and 6148 (St Jude) with homogenous surrounding grey matter and a peri-electrode space (PES) of 250 μm. The PES-impedance mimicked the acute (extracellular fluid) and chronic (fibrous tissue) time-point. Simulations at different amplitudes of voltage and current (n=236) were performed using two different contacts. Equivalent current amplitudes were extracted by matching the shape and maximum EF of the 0.2 V/mm isolevel.

    Results: The maximum EF extension at 0.2 V/mm varied between 2-5 mm with a small difference between the leads. In voltage mode EF increased about 1 mm at acute compared to the chronic PES. Current mode presented the opposite relationship. Equivalent EFs for lead 3389 at 3 V were found for 7 mA (acute) and 2.2 mA (chronic).

    Conclusions: Simulations showed a major impact on the electric field extension between postoperative time points. This may explain the clinical decisions to reprogram the amplitude weeks after implantation. Neither the EF extension nor intensity is considerably influenced by the lead design.

    Place, publisher, year, edition, pages
    Los Angeles, CA, USA: Omics Publishing Group, 2015
    Keywords
    deep brain stimulation (DBS), voltage and current stimulation, finite element method
    National Category
    Other Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-120680 (URN)10.4172/2168-975X.1000169 (DOI)
    Funder
    Swedish Research Council, 621-2013-6078
    Available from: 2015-08-21 Created: 2015-08-20 Last updated: 2018-09-10Bibliographically approved
    2. Investigation into Deep Brain Stimulation Lead Designs: A Patient-Specific Simulation Study
    Open this publication in new window or tab >>Investigation into Deep Brain Stimulation Lead Designs: A Patient-Specific Simulation Study
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    2016 (English)In: Brain Sciences, ISSN 2076-3425, E-ISSN 2076-3425, Vol. 6, no 3, p. 1-16Article in journal (Refereed) Published
    Abstract [en]

    New deep brain stimulation (DBS) electrode designs offer operation in voltage and current mode and capability to steer the electric field (EF). The aim of the study was to compare the EF distributions of four DBS leads at equivalent amplitudes (3 V and 3.4 mA). Finite element method (FEM) simulations (n = 38) around cylindrical contacts (leads 3389, 6148) or equivalent contact configurations (leads 6180, SureStim1) were performed using homogeneous and patient-specific (heterogeneous) brain tissue models. Steering effects of 6180 and SureStim1 were compared with symmetric stimulation fields. To make relative comparisons between simulations, an EF isolevel of 0.2 V/mm was chosen based on neuron model simulations (n = 832) applied before EF visualization and comparisons. The simulations show that the EF distribution is largely influenced by the heterogeneity of the tissue, and the operating mode. Equivalent contact configurations result in similar EF distributions. In steering configurations, larger EF volumes were achieved in current mode using equivalent amplitudes. The methodology was demonstrated in a patient-specific simulation around the zona incerta and a “virtual” ventral intermediate nucleus target. In conclusion, lead design differences are enhanced when using patient-specific tissue models and current stimulation mode.

    Place, publisher, year, edition, pages
    MDPI, 2016
    Keywords
    deep brain stimulation (DBS), steering, patient-specific, electric field, finite element method, neuron model, brain model, zona incerta (ZI), electrode design
    National Category
    Medical Engineering
    Identifiers
    urn:nbn:se:liu:diva-131863 (URN)10.3390/brainsci6030039 (DOI)27618109 (PubMedID)
    Available from: 2016-10-11 Created: 2016-10-11 Last updated: 2019-11-11Bibliographically approved
    3. Electric Field Comparison between Microelectrode Recording and Deep Brain Stimulation Systems: A Simulation Study
    Open this publication in new window or tab >>Electric Field Comparison between Microelectrode Recording and Deep Brain Stimulation Systems: A Simulation Study
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    2018 (English)In: Brain Sciences, ISSN 2076-3425, E-ISSN 2076-3425, Vol. 8, no 2, article id 28Article in journal (Refereed) Published
    Abstract [en]

    The success of deep brain stimulation (DBS) relies primarily on the localization of the implanted electrode. Its final position can be chosen based on the results of intraoperative microelectrode recording (MER) and stimulation tests. The optimal position often differs from the final one selected for chronic stimulation with the DBS electrode. The aim of the study was to investigate, using finite element method (FEM) modeling and simulations, whether lead design, electrical setup, and operating modes induce differences in electric field (EF) distribution and in consequence, the clinical outcome. Finite element models of a MER system and a chronic DBS lead were developed. Simulations of the EF were performed for homogenous and patient-specific brain models to evaluate the influence of grounding (guide tube vs. stimulator case), parallel MER leads, and non-active DBS contacts. Results showed that the EF is deformed depending on the distance between the guide tube and stimulating contact. Several parallel MER leads and the presence of the non-active DBS contacts influence the EF distribution. The DBS EF volume can cover the intraoperatively produced EF, but can also extend to other anatomical areas. In conclusion, EF deformations between stimulation tests and DBS should be taken into consideration as they can alter the clinical outcome

    Place, publisher, year, edition, pages
    MDPI, 2018
    Keywords
    microelectrode recording (MER); finite element method (FEM); deep brain stimulation (DBS); brain model; Dice coefficient; patient-specific
    National Category
    Medical Engineering
    Identifiers
    urn:nbn:se:liu:diva-145112 (URN)10.3390/brainsci8020028 (DOI)000427646200009 ()
    Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2022-05-04
    4. Patient-Specific Electric Field Simulations and Acceleration Measurements for Objective Analysis of Intraoperative Stimulation Tests in the Thalamus
    Open this publication in new window or tab >>Patient-Specific Electric Field Simulations and Acceleration Measurements for Objective Analysis of Intraoperative Stimulation Tests in the Thalamus
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    2016 (English)In: Frontiers in Human Neuroscience, E-ISSN 1662-5161, Vol. 10, p. 1-14, article id 577Article in journal (Refereed) Published
    Abstract [en]

    Despite an increasing use of deep brain stimulation (DBS) the fundamental mechanisms of action remain largely unknown. Simulation of electric entities has previously been proposed for chronic DBS combined with subjective symptom evaluations, but not for intraoperative stimulation tests. The present paper introduces a method for an objective exploitation of intraoperative stimulation test data to identify the optimal implant position of the chronic DBS lead by relating the electric field (EF) simulations to the patient-specific anatomy and the clinical effects quantified by accelerometry. To illustrate the feasibility of this approach, it was applied to five patients with essential tremor bilaterally implanted in the ventral intermediate nucleus (VIM). The VIM and its neighborhood structures were preoperatively outlined in 3D on white matter attenuated inversion recovery MR images. Quantitative intraoperative clinical assessments were performed using accelerometry. EF simulations (n = 272) for intraoperative stimulation test data performed along two trajectories per side were set-up using the finite element method for 143 stimulation test positions. The resulting EF isosurface of 0.2 V/mm was superimposed to the outlined anatomical structures. The percentage of volume of each structure’s overlap was calculated and related to the corresponding clinical improvement. The proposed concept has been successfully applied to the five patients. For higher clinical improvements, not only the VIM but as well other neighboring structures were covered by the EF isosurfaces. The percentage of the volumes of the VIM, of the nucleus intermediate lateral of the thalamus and the prelemniscal radiations within the prerubral field of Forel increased for clinical improvements higher than 50% compared to improvements lower than 50%. The presented new concept allows a detailed and objective analysis of a high amount of intraoperative data to identify the optimal stimulation target. First results indicate agreement with published data hypothesizing that the stimulation of other structures than the VIM might be responsible for good clinical effects in essential tremor. (Clinical trial reference number: Ref: 2011-A00774-37/AU905)

    Place, publisher, year, edition, pages
    Frontiers Research Foundation, 2016
    Keywords
    deep brain stimulation (DBS), intraoperative stimulation tests, essential tremor, acceleration measurements, finite element method (FEM) simulations, ventral intermediate nucleus (VIM), patient-specific brain maps
    National Category
    Medical Engineering
    Identifiers
    urn:nbn:se:liu:diva-132790 (URN)10.3389/fnhum.2016.00577 (DOI)000388426400001 ()
    Available from: 2016-11-25 Created: 2016-11-25 Last updated: 2024-01-17Bibliographically approved
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    Models and Simulations of the Electric Field in Deep Brain Stimulation: Comparison of Lead Designs, Operating Modes and Tissue Conductivity
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  • 25.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Vogel, Dorian
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Hemm-Ode, Simone
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Institute for Medical and Analytical Technologies and Department of Biomedical Engineering, University of Applied Sciences and Art Northwestern Switzerland.
    Comparison between intraoperative and chronic and deep brain stimulation2017Conference paper (Refereed)
    Abstract [en]

    INTRODUCTION

    The success of the deep brain stimulation (DBS) therapy relies primarily in the localization of the implanted electrode, implying the need of utmost accuracy in the targeting process. Intraoperative microelectrode recording and stimulation tests are a common procedure before implanting the permanent DBS lead to determine the optimal position with a large therapeutic window where side effects are avoided and the best improvement of the symptoms is achieved. Differences in dimensions and operating modes exist between the exploration and the permanent DBS electrode which might lead to different stimulation fields, even when ideal placement is achieved. The aim of this investigation is to compare the electric field (EF) distribution around the intraoperative and the chronic electrode, assuming that both have exactly the same position.

    METHODS

    3D models of the intraoperative exploration electrode and the chronically implanted DBS lead 3389 (Medtronic Inc., USA) were developed using COMSOL 5.2 (COMSOL AB, Sweden). Patient-specific MR images were used to determine the conductive medium around the electrode. The exploration electrode and the first DBS contact were set to current and voltage respectively (0.2mA(V) - 3 mA(V) in 0.1 mA(V) steps). The intraoperative model included the grounded guide tube used to introduce the exploration electrode; for the chronic DBS model, the outer boundaries were grounded and the inactive contacts were set to floating potential considering a monopolar configuration. The localization of the exploration and the chronic electrode was set according to the planned trajectory. The EF was visualized and compared in terms of volume and extension using a fixed isocontour of 0.2 V/mm.

    RESULTS

    The EF distribution simulated for the exploration electrode showed the influence of the parallel trajectory and the grounded guide tube. For an amplitude of e.g. 2 mA/2 V, the EF extension of the intraoperative was 0.6 mm larger than the chronic electrode at the target level; the corresponding difference in volume was 76.1 mm3.

    CONCLUSION

    Differences in the EF shape between the exploration and the chronic DBS electrode have been observed using patient-specific models. The larger EF extension obtained for the exploration electrode responds to its higher impedance and the use of current controlled stimulation. The presence of EF around the guide tube and the influence of the parallel trajectory require further experimental and clinical evaluation.

  • 26.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Zsigmond, Peter
    Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Influence of Virchow-Robin spaces in the Electric Field Distribution in Subthalamic Nucleus Deep Brain Stimulation2019Conference paper (Refereed)
    Abstract [en]

    Objectives: Previous investigations have shown the appearance of cysts i.e. Virchow-Robin spaces (VR) in the basal ganglia and their relationship with parkinsonian symptoms [1-3]. Simulations [4]using the finite element method (FEM) suggests that VR affects the electric field around deep brain stimulation (DBS) electrodes. The aim of the study was to evaluate how the electric field is modified by the presence of cysts in the STN. Methods: The effect of cysts on the electric field around the DBS lead placed in the STN was evaluated using FEM. 3D patient-specific brain models were built with COMSOL 5.2 (COMSOL AB, Sweden) and an in-house developed software [5] to convert a T2 weighted MRI of Parkinsonian patients (ethics approval no: 2012/434-3) into electrical conductivity matrix readable by FEM software. VR was classified as CSF [6]assigning a high electrical conductivity (2.0 S/m). The stimulation amplitudes were set to the clinically programmed values. Depending on the lead used, the stimulation was set to voltage control (3389) or current control (6180, ring mode). The coordinates corresponding to the lowest (first) electrode and the third higher up in the lead, taken from the postoperative CT electrode artefact, were used to localize the leads in the brain model [7]. The electric field was visualized with a 0.2V/mm isosurface. Results: Simulations showed that the electric field distribution is affected by the cysts. The higher conductivity at these regions in the vicinity of the electrode redistributes the electric field pushing it away from the cyst. The same effect occurs regardless of the operating mode or the lead design as long as the directional lead is configured in ring mode. Conclusions: The use of patient-specific models has shown the importance of considering nuances of the patients’ anatomy in the STN. This information can be used to determine the stimulation parameter and to support the analysis of side effects induced by the stimulation. The potential advantage of directional leads can also be assessed by including in the model patient-specific data.

  • 27.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Zsigmond, Peter
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Influence of Virchow-Robin spaces on the electric field distribution in subthalamic nucleus deep brain stimulation2021In: Clinical neurology and neurosurgery, ISSN 0303-8467, E-ISSN 1872-6968, Vol. 204, article id 106596Article in journal (Refereed)
    Abstract [en]

    Patient MRI from DBS implantations in the subthalamic nucleus (STN) were reviewed and it was found that around 10% had Virchow-Robin spaces (VRS). Patient-specific models were developed to evaluate changes in the electric field (EF) around DBS leads. The patients (n = 7) were implanted bilaterally either with the standard voltage-controlled lead 3389 or with the directional current-controlled lead 6180. The EF distribution was evaluated by comparing simulations using patient-specific models with homogeneous models without VRS. The EF, depicted with an isocontour of 0.2 V/mm, showed a deformation in the presence of the VRS around the DBS lead. For patient-specific models, the radial extension of the EF isocontours was enlarged regardless of the operating mode or the DBS lead used. The location of the VRS in relation to the active contact and the stimulation amplitude, determined the changes in the shape and extension of the EF. It is concluded that it is important to take the patients? brain anatomy into account as the high conductivity in VRS will alter the electric field if close to the DBS lead. This can be a cause of unexpected side effects.

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  • 28.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Zsigmond, Peter
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Virchow-Robin spaces in subthalamic nucleus Deep Brain Stimulation - Influence in the electric field2019Conference paper (Other academic)
  • 29.
    Andersson, Thord
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Dept. of C4ISR, Swedish Defence Research Agency, Linköping, Sweden, .
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Geodesic registration for interactive atlas-based segmentation using learned multi-scale anatomical manifolds2018In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 112, p. 340-345Article in journal (Refereed)
    Abstract [en]

    Atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation.

  • 30.
    Applegate, Matthew B.
    et al.
    Boston Univ., United States.
    Karrobi, Kavon
    Boston Univ., United States.
    Angelo Jr., Joseph P.
    Univ. de Strasbourg, France.
    Austin, Wyatt M.
    The Univ. of Maine, United States.
    Tabassum, Syeda M.
    Boston Univ., United States.
    Aguénounon, Enagnon
    Univ. de Strasbourg, France.
    Tilbury, Karissa
    The Univ. of Maine, United States.
    Saager, Rolf B.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Gioux, Sylvain
    Univ. de Strasbourg, France.
    Roblyer, Darren M.
    Boston Univ., United States.
    OpenSFDI: an open-source guide for constructing a spatial frequency domain imaging system2020In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 25, no 1Article in journal (Refereed)
    Abstract [en]

    Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (μa) and reduced scattering (μ0 s) on a pixelby-pixel basis. Measurements of μa at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, threewavelength SFDI system capable of quantifying μa and μ0 s as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system. Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website. Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of μa and μ0 s with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h. Results: The openSFDI systems had an error of 0 6% in μa and −2 3% in μ0 s, compared to a commercial SFDI system. Bland–Altman analysis revealed the limits of agreement between the two systems to be 0.004 mm−1 for μa and −0.06 to 0.1 mm−1 for μ0 s. The openSFDI system had low drift with an average standard deviation of 0.0007 mm−1 and 0.05 mm−1 in μa and μ0 s, respectively. Conclusion: The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging.

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    fulltext
  • 31.
    Asadi, Mehdi
    et al.
    Tarbiat Modares Univ, Iran.
    Poursalim, Fatemeh
    Shiraz Univ Med Sci, Iran.
    Loni, Mohammad
    Malardalen Univ, Sweden.
    Daneshtalab, Masoud
    Malardalen Univ, Sweden.
    Sjodin, Mikael
    Malardalen Univ, Sweden.
    Gharehbaghi, Arash
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Accurate detection of paroxysmal atrial fibrillation with certified-GAN and neural architecture search2023In: Scientific Reports, E-ISSN 2045-2322, Vol. 13, no 1, article id 11378Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel machine learning framework for detecting PxAF, a pathological characteristic of electrocardiogram (ECG) that can lead to fatal conditions such as heart attack. To enhance the learning process, the framework involves a generative adversarial network (GAN) along with a neural architecture search (NAS) in the data preparation and classifier optimization phases. The GAN is innovatively invoked to overcome the class imbalance of the training data by producing the synthetic ECG for PxAF class in a certified manner. The effect of the certified GAN is statistically validated. Instead of using a general-purpose classifier, the NAS automatically designs a highly accurate convolutional neural network architecture customized for the PxAF classification task. Experimental results show that the accuracy of the proposed framework exhibits a high value of 99.0% which not only enhances state-of-the-art by up to 5.1%, but also improves the classification performance of the two widely-accepted baseline methods, ResNet-18, and Auto-Sklearn, by 2.2% and 6.1%.

  • 32.
    Aserod, Hanne
    et al.
    Univ Bergen, Norway.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Univ Bergen, Norway.
    Designing a mobile system for safety reporting of arthroplasty adverse events2018In: EMBEC and NBC 2017, SPRINGER-VERLAG SINGAPORE PTE LTD , 2018, Vol. 65, p. 571-574Conference paper (Refereed)
    Abstract [en]

    This paper presents a mobile software application development for safety reporting of adverse events within the field of arthroplasty. Proposed user interface enables entry of data specific for adverse events of the knee and hip implants. Besides the patient data, the system supports entry of the event, its classification (serious, non-serious), its follow up, as well as a connection to the database maintained within the Helse Bergen hospital information system. Safety reports can be initiated and retrieved on request and depending on the adjudication of the event; suspected severe events should be followed up until their resolution. Expert evaluation of the first design solution was performed using low fidelity prototype. It has shown that design was relevant, straightforward, done in a way that official reporting would commence. Some users were positive to the reporting, some felt it would demand more work. A comprehensive evaluation with different potential user groups is planned to meet their needs and understand their views.

  • 33.
    Aserod, Hanne
    et al.
    Univ Bergen, Norway.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Univ Bergen, Norway.
    Pharmacovigilance Mobile Tool Design in the Field of Arhroplasty2017In: INFORMATICS EMPOWERS HEALTHCARE TRANSFORMATION, IOS PRESS , 2017, Vol. 238, p. 104-107Conference paper (Refereed)
    Abstract [en]

    Pharmacovigilance is an important part of the patient safety and it has a great appeal to physicians. It is concerned with the safety of medical devices and treatments in the light of understanding the risks and dangers based on the already reported safety issues. Internet resources such as the Manufacturer And User Facility Device Experience (MAUDE) web-site are often retrieved due to the lack of internal, local safety databases. The research looked at how Human Computer Interaction could improve user experience. We have designed data entry for safety reporting and pharmacovigilance based on the web-bases system called WebBISS (Web-based implant search system). The expectation is not only to improve usability, but also to stimulate physicians to enter their safety data and become also contributors, and not only users of information. The expert evaluation has been generally positive and encouraged stronger help and error reporting functions. The high fidelity design has given a good impression of the future mobile solution.

  • 34.
    Bakker, Bram
    et al.
    Cygnify BV, Netherlands.
    Zablocki, Bartosz
    Cygnify BV, Netherlands; Bolcom, Netherlands.
    Baker, Angela
    Shell Int, Netherlands.
    Riethmeister, Vanessa
    Shell Int, Netherlands.
    Marx, Bernd
    Shell Int, Netherlands.
    Iyer, Girish
    Shell Trading & Supply, England.
    Anund, Anna
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden; Stockholm Univ, Sweden.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden.
    A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions2022In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 5, p. 4791-4800Article in journal (Refereed)
    Abstract [en]

    Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1-9 or a binary decision as alert (defined as KSS 1-6) or sleepy (defined as KSS 7-9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.

  • 35.
    Bardolet Pettersson, Susana
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Managing imbalanced training data by sequential segmentation in machine learning2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Imbalanced training data is a common problem in machine learning applications. Thisproblem refers to datasets in which the foreground pixels are significantly fewer thanthe background pixels. By training a machine learning model with imbalanced data, theresult is typically a model that classifies all pixels as the background class. A result thatindicates no presence of a specific condition when it is actually present is particularlyundesired in medical imaging applications. This project proposes a sequential system oftwo fully convolutional neural networks to tackle the problem. Semantic segmentation oflung nodules in thoracic computed tomography images has been performed to evaluate theperformance of the system. The imbalanced data problem is present in the training datasetused in this project, where the average percentage of pixels belonging to the foregroundclass is 0.0038 %. The sequential system achieved a sensitivity of 83.1 % representing anincrease of 34 % compared to the single system. The system only missed 16.83% of thenodules but had a Dice score of 21.6 % due to the detection of multiple false positives. Thismethod shows considerable potential to be a solution to the imbalanced data problem withcontinued development.

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  • 36.
    Behjat, Hamid
    et al.
    Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Department of Biomedical Engineering, Lund University, Lund, Sweden.
    Aganj, Iman
    Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA.
    Abramian, David
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Westin, Carl-Fredrik
    Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA.
    Characterization of Spatial Dynamics of Fmri Data in White Matter Using Diffusion-Informed White Matter Harmonics2021In: 2021 IEEE 18th International Symposium On Biomedical Imaging (ISBI), Institute of Electrical and Electronics Engineers (IEEE), 2021Conference paper (Refereed)
    Abstract [en]

    In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusionweighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure.

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  • 37.
    Behjat, Hamid
    et al.
    Neuro-X Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland; Department of Biomedical Engineering, Lund University, Sweden.
    Tarun, Anjali
    Center for Neuroprosthetics, Institute of Bioengineering, EPFL, Switzerland.
    Abramian, David
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Larsson, Martin
    Centre for Mathematical Sciences, Lund University, Sweden.
    Ville, Dimitri Van De
    Neuro-X Institute, EPFL, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Switzerland.
    Voxel-Wise Brain Graphs From Diffusion MRI: Intrinsic Eigenspace Dimensionality and Application to Functional MRI2023In: IEEE Open Journal of Engineering in Medicine and Biology, E-ISSN 2644-1276, p. 1-12Article in journal (Refereed)
    Abstract [en]

    Goal: Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas,with edges reflecting the density of axonal projections between pairs of nodes. Here we explicitly model the entire set of voxels within a brain mask as nodes of high-resolution, subject-specific graphs. Methods: We define the strength of local voxel-to-voxel connections using diffusion tensors and orientation distribution functions derived from diffusion MRI data. We study the graphs’ Laplacian spectral properties on data from the Human Connectome Project. We then assess the extent of inter-subject variability of the Laplacian eigenmodes via a procrustes validation scheme. Finally, we demonstrate the extent to which functional MRI data are shaped by the underlying anatomical structure via graph signal processing. Results: The graph Laplacian eigenmodes manifest highly resolved spatial profiles, reflecting distributed patterns that correspond to major white matter pathways. We show that the intrinsic dimensionality of the eigenspace of such high-resolution graphs is only a mere fraction of the graph dimensions. By projecting task and resting-state data on low frequency graph Laplacian eigenmodes, we show that brain activity can be well approximated by a small subset of low frequency components. Conclusions: The proposed graphs open new avenues in studying the brain, be it, by exploring their organisational properties via graph or spectral graph theory, or by treating them as the scaffold on which brain function is observed at the individual level.

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  • 38. Order onlineBuy this publication >>
    Belcastro, Luigi
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Multi-frequency SFDI: depth-resolved scattering models of wound healing2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    With optical techniques, we refer to a group of methods that use of light to perform measurements on matter. Spatial frequency domain imaging (SFDI) is an optical technique that operates in the spatial frequency domain. The technique involves using sinusoidal patterns of light for illumination, to study the reflectance of the target based on the spatial frequency (ƒx) of the patterns. By analysing the frequency-specific response with the aid of light transport models, we are able to determine the intrinsic optical properties of the material, such as the absorption coefficient (μa) and reduced scattering coefficient (μ's) In biological applications, these optical properties can be correlated to physiological structures and molecules, providing a useful tool for researchers and clinicians alike in understanding the phenomena happening in biological tissue. The objective of this work is to contribute to the development of SFDI, so that the technique can be used as a diagnostic tool to study the process of wound healing in tissue. In paper I we introduce the concept of cross-channels, given by the spectral overlap of the broadband LED light sources and the RGB camera sensors used in the SFDI instrumentation. The purpose of cross-channels is to improve the limited spectral information of RGB devices, allowing to detect a larger number of biological molecules. One of the biggest limitations of SFDI is that it works on the assumption of light diffusing through a homogeneous, thick layer of material. This assumption loses validity when we want to examine biological tissue, which comprises multiple thin layers with different properties. In paper IV we have developed a new method to process SFDI data that we call multi-frequency SFDI. In this new approach, we make use of the different penetration depth of the light patterns depending on their ƒx to obtain depth-sensitive measurements. We also defined a 2-layer model of light scattering that imitates the physiology of a wound, to calculate the partial volume contributions to μ's of the single layers. The 2-layer model is based on analytical formulations of light fluence. We compared the performance of three fluence models, one of which we have derived ourselves as an improvement over an existing formulation. In paper II we were able to test our new multi-frequency SFDI method by participating in an animal study on stem-cells based regenerative therapies. We contributed by performing SFDI measurements on healing wounds, in order to provide an additional evaluation metric that complemented the clinical evaluation and cell histology performed in the study. The analysis of the SFDI data at different ƒx highlighted different processes happening on the surface compared to the deeper tissue. In paper V we further refine the technique introduced in paper IV by developing an inverse solver algorithm to isolate the thickness of the thin layer and the layer-specific μ's. The reconstructed parameters were tested both on thin silicone optical phantoms and ex-vivo burn wounds treated with stem cells. 

    List of papers
    1. Handheld multispectral imager for quantitative skin assessment in low resource settings
    Open this publication in new window or tab >>Handheld multispectral imager for quantitative skin assessment in low resource settings
    2020 (English)In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 25, no 8, article id 082702Article in journal (Refereed) Published
    Abstract [en]

    Significance: Spatial frequency domain imaging (SFDI) is a quantitative imaging method to measure absorption and scattering of tissue, from which several chromophore concentrations (e.g., oxy-/deoxy-/meth-hemoglobin, melanin, and carotenoids) can be calculated. Employing a method to extract additional spectral bands from RGB components (that we named cross-channels), we designed a handheld SFDI device to account for these pigments, using low-cost, consumer-grade components for its implementation and characterization.

    Aim: With only three broad spectral bands (red, green, blue, or RGB), consumer-grade devices are often too limited. We present a methodology to increase the number of spectral bands in SFDI devices that use RGB components without hardware modification.

    Approach: We developed a compact low-cost RGB spectral imager using a color CMOS camera and LED-based mini projector. The components’ spectral properties were characterized and additional cross-channel bands were calculated. An alternative characterization procedure was also developed that makes use of low-cost equipment, and its results were compared. The device performance was evaluated by measurements on tissue-simulating optical phantoms and in-vivo tissue. The measurements were compared with another quantitative spectroscopy method: spatial frequency domain spectroscopy (SFDS).

    Results: Out of six possible cross-channel bands, two were evaluated to be suitable for our application and were fully characterized (520  ±  20  nm; 556  ±  18  nm). The other four cross-channels presented a too low signal-to-noise ratio for this implementation. In estimating the optical properties of optical phantoms, the SFDI data have a strong linear correlation with the SFDS data (R2  =  0.987, RMSE  =  0.006 for μa, R2  =  0.994, RMSE  =  0.078 for μs′).

    Conclusions: We extracted two additional spectral bands from a commercial RGB system at no cost. There was good agreement between our device and the research-grade SFDS system. The alternative characterization procedure we have presented allowed us to measure the spectral features of the system with an accuracy comparable to standard laboratory equipment.

    Place, publisher, year, edition, pages
    SPIE - The International Society for Optics and Photonics, 2020
    Keywords
    multispectral imaging; spatial frequency domain imaging; low-resource settings; digital micromirror device; skin; phantoms
    National Category
    Medical Engineering
    Identifiers
    urn:nbn:se:liu:diva-169868 (URN)10.1117/1.JBO.25.8.082702 (DOI)000590144000002 ()32755076 (PubMedID)2-s2.0-85089133009 (Scopus ID)
    Funder
    Wallenberg Foundations
    Note

    Funding agencies:  Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation

    Available from: 2020-09-22 Created: 2020-09-22 Last updated: 2023-11-14Bibliographically approved
    2. Beneath the skin: multi-frequency SFDI to detect thin layers of skin using light scattering
    Open this publication in new window or tab >>Beneath the skin: multi-frequency SFDI to detect thin layers of skin using light scattering
    Show others...
    2023 (English)In: PHOTONICS IN DERMATOLOGY AND PLASTIC SURGERY 2023, SPIE-INT SOC OPTICAL ENGINEERING , 2023, Vol. 12352, article id 1235209Conference paper, Published paper (Refereed)
    Abstract [en]

    Wound healing assessment is usually performed visually by a trained physician. This type of evaluation is very subjective and returns limited information about the wound progression. In contrast, optical imaging techniques are non-invasive ways to quantitatively measure biological parameters. Spatial frequency domain imaging (SFDI) is an optical technique that exploits sinusoidal patterns of light with multiple spatial frequencies to measure the tissue frequency-specific response, from which the absorption and scattering coefficient of the material can be derived. While SFDI is based on models of light transport that assume the tissue is homogeneous, skin is composed by several layer with very different optical properties. An underutilized property of SFDI, however, is that the spatial frequency of the patterns determines the penetration depth of photons in the tissue. By using multiple ranges of spatial frequencies, we are developing a means to obtain morphological data from different volumes of tissue. This data is used to reconstruct the optical properties in depth, allowing us to differentiate between different thin layers of tissue. In this study we have developed a 2-layer optical phantom model with realistic optical properties and dimensions, that mimics the physiology of wound healing. We have used this physical model to validate the accuracy of this approach in obtaining layer specific optical properties.

    Place, publisher, year, edition, pages
    SPIE-INT SOC OPTICAL ENGINEERING, 2023
    Series
    Progress in Biomedical Optics and Imaging, ISSN 1605-7422
    Keywords
    SFDI; light scattering; wound healing; thin layers; depth reconstruction
    National Category
    Medical Laboratory and Measurements Technologies
    Identifiers
    urn:nbn:se:liu:diva-196941 (URN)10.1117/12.2648545 (DOI)001012400300008 ()9781510658097 (ISBN)9781510658103 (ISBN)
    Conference
    Conference on Photonics in Dermatology and Plastic Surgery, San Francisco, CA, jan 28-29, 2023
    Available from: 2023-08-29 Created: 2023-08-29 Last updated: 2023-11-14
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  • 39.
    Belcastro, Luigi
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Jonasson, Hanna
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Elserafy, Ahmed
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland.
    Saager, Rolf
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Beneath the skin: multi-frequency SFDI to detect thin layers of skin using light scattering2023In: PHOTONICS IN DERMATOLOGY AND PLASTIC SURGERY 2023, SPIE-INT SOC OPTICAL ENGINEERING , 2023, Vol. 12352, article id 1235209Conference paper (Refereed)
    Abstract [en]

    Wound healing assessment is usually performed visually by a trained physician. This type of evaluation is very subjective and returns limited information about the wound progression. In contrast, optical imaging techniques are non-invasive ways to quantitatively measure biological parameters. Spatial frequency domain imaging (SFDI) is an optical technique that exploits sinusoidal patterns of light with multiple spatial frequencies to measure the tissue frequency-specific response, from which the absorption and scattering coefficient of the material can be derived. While SFDI is based on models of light transport that assume the tissue is homogeneous, skin is composed by several layer with very different optical properties. An underutilized property of SFDI, however, is that the spatial frequency of the patterns determines the penetration depth of photons in the tissue. By using multiple ranges of spatial frequencies, we are developing a means to obtain morphological data from different volumes of tissue. This data is used to reconstruct the optical properties in depth, allowing us to differentiate between different thin layers of tissue. In this study we have developed a 2-layer optical phantom model with realistic optical properties and dimensions, that mimics the physiology of wound healing. We have used this physical model to validate the accuracy of this approach in obtaining layer specific optical properties.

  • 40.
    Belcastro, Luigi
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Jonasson, Hanna
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Saager, Rolf B.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Handheld multispectral imager for quantitative skin assessment in low resource settings2020In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 25, no 8, article id 082702Article in journal (Refereed)
    Abstract [en]

    Significance: Spatial frequency domain imaging (SFDI) is a quantitative imaging method to measure absorption and scattering of tissue, from which several chromophore concentrations (e.g., oxy-/deoxy-/meth-hemoglobin, melanin, and carotenoids) can be calculated. Employing a method to extract additional spectral bands from RGB components (that we named cross-channels), we designed a handheld SFDI device to account for these pigments, using low-cost, consumer-grade components for its implementation and characterization.

    Aim: With only three broad spectral bands (red, green, blue, or RGB), consumer-grade devices are often too limited. We present a methodology to increase the number of spectral bands in SFDI devices that use RGB components without hardware modification.

    Approach: We developed a compact low-cost RGB spectral imager using a color CMOS camera and LED-based mini projector. The components’ spectral properties were characterized and additional cross-channel bands were calculated. An alternative characterization procedure was also developed that makes use of low-cost equipment, and its results were compared. The device performance was evaluated by measurements on tissue-simulating optical phantoms and in-vivo tissue. The measurements were compared with another quantitative spectroscopy method: spatial frequency domain spectroscopy (SFDS).

    Results: Out of six possible cross-channel bands, two were evaluated to be suitable for our application and were fully characterized (520  ±  20  nm; 556  ±  18  nm). The other four cross-channels presented a too low signal-to-noise ratio for this implementation. In estimating the optical properties of optical phantoms, the SFDI data have a strong linear correlation with the SFDS data (R2  =  0.987, RMSE  =  0.006 for μa, R2  =  0.994, RMSE  =  0.078 for μs′).

    Conclusions: We extracted two additional spectral bands from a commercial RGB system at no cost. There was good agreement between our device and the research-grade SFDS system. The alternative characterization procedure we have presented allowed us to measure the spectral features of the system with an accuracy comparable to standard laboratory equipment.

    Download full text (pdf)
    fulltext
  • 41.
    Benosman, M. M.
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Tlemcen Univ, Biomed Engn Dept, Tilimsen 13000, Algeria.
    Bereksi-Reguig, F.
    Tlemcen Univ, Algeria.
    Salerud, Göran
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    STRONG REAL-TIME QRS COMPLEX DETECTION2017In: Journal of Mechanics in Medicine and Biology, ISSN 0219-5194, E-ISSN 1793-6810, Vol. 17, no 8, article id 1750111Article in journal (Refereed)
    Abstract [en]

    Heart rate variability (HRV) analysis is used as a marker of autonomic nervous system activity which may be related to mental and/or physical activity. HRV features can be extracted by detecting QRS complexes from an electrocardiogram (ECG) signal. The difficulties in QRS complex detection are due to the artifacts and noises that may appear in the ECG signal when subjects are performing their daily life activities such as exercise, posture changes, climbing stairs, walking, running, etc. This study describes a strong computation method for real-time QRS complex detection. The detection is improved by the prediction of the position of R waves by the estimation of the RR intervals lengths. The estimation is done by computing the intensity of the electromyogram noises that appear in the ECG signals and known here in this paper as ECG Trunk Muscles Signals Amplitude (ECG-TMSA). The heart rate (HR) and ECG-TMSA increases with the movement of the subject. We use this property to estimate the lengths of the RR intervals. The method was tested using famous databases, and also with signals acquired when an experiment with 17 subjects from our laboratory. The obtained results using ECG signals from the MIT-Noise Stress Test Database show a QRS complex detection error rate (ER) of 9.06%, a sensitivity of 95.18% and a positive prediction of 95.23%. This method was also tested against MIT-BIH Arrhythmia Database, the result are 99.68% of sensitivity and 99.89% of positive predictivity, with ER of 0.40%. When applied to the signals obtained from the 17 subjects, the algorithm gave an interesting result of 0.00025% as ER, 99.97% as sensitivity and 99.99% as positive predictivity.

  • 42.
    Bergkvist, Max
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Hand and Plastic Surgery.
    Henricson, Joakim
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Local Health Care Services in Central Östergötland, Department of Emergency Medicine in Linköping.
    Bergstrand, Sara
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Nursing Sciences and Reproductive Health. Linköping University, Faculty of Medicine and Health Sciences.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Droog Tesselaar, Erik
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics.
    Farnebo, Simon
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Hand and Plastic Surgery.
    Assessment of oxygenation with polarized light spectroscopy enables new means for detecting vascular events in the skin2020In: Microvascular Research, ISSN 0026-2862, E-ISSN 1095-9319, Vol. 130, article id 104000Article in journal (Refereed)
    Abstract [en]

    Introduction: Impaired oxygenation in the skin may occur in disease states and after reconstructive surgery. We used tissue viability imaging (TiVi) to measure changes in oxygenation and deoxygenation of haemoglobin in an in vitro model and in the dermal microcirculation of healthy individuals. Materials and methods: Oxygenation was measured in human whole blood with different levels of oxygenation. In healthy subjects, changes in red blood cell concentration (C-RBC,(TiVi)), oxygenation (Delta C-OH,(TiVi)) and deoxygenation (Delta C-DOH,(TiVi)) of haemoglobin were measured during and after arterial and venous occlusion using TiVi and were compared with measurements from the enhanced perfusion and oxygen saturation system (EPOS). Results: During arterial occlusion, C-RBC,(TiVi) remained unchanged while Delta C-OH,(TiVi) decreased to -44.2 (10.4) AU (p = 0.04), as compared to baseline. After release, C-RBC,C-TiVi increased to 39.2 (18.8) AU (p < 0.001), Delta C-OH,C-TiVi increased to 38.5. During venous occlusion, C-RBC,C-TiVi increased to 28.9 (11.2) AU (p < 0.001), Delta C-OH,C-TiVi decreased to -52.2 (46.1) AU (p < 0.001) compared to baseline after 5 min of venous occlusion. There was a significant correlation between the TiVi Oxygen Mapper and EPOS, for arterial (r = 0.92, p < 0.001) and venous occlusion (r = 0.87, p < 0.001), respectively. Conclusion: This study shows that TiVi can measure trends in oxygenation and deoxygenation of haemoglobin during arterial and venous stasis in healthy individuals.

  • 43.
    Bergqvist, Niclas
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Nyman, Elin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. AstraZeneca RandD, Sweden.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Stenkula, Karin G.
    Lund University, Sweden.
    A systems biology analysis connects insulin receptor signaling with glucose transporter translocation in rat adipocytes2017In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 292, no 27, p. 11206-11217Article in journal (Refereed)
    Abstract [en]

    Type 2 diabetes is characterized by insulin resistance, which arises from malfunctions in the intracellular insulin signaling network. Knowledge of the insulin signaling network is fragmented, and because of the complexity of this network, little consensus has emerged for the structure and importance of the different branches of the network. To help overcome this complexity, systems biology mathematical models have been generated for predicting both the activation of the insulin receptor (IR) and the redistribution of glucose transporter 4 (GLUT4) to the plasma membrane. Although the insulin signal transduction between IR and GLUT4 has been thoroughly studied with modeling and time-resolved data in human cells, comparable analyses in cells from commonly used model organisms such as rats and mice are lacking. Here, we combined existing data and models for rat adipocytes with new data collected for the signaling network between IR and GLUT4 to create a model also for their interconnections. To describe all data (amp;gt;140 data points), the model needed three distinct pathways from IR to GLUT4: (i) via protein kinase B (PKB) and Akt substrate of 160 kDa (AS160), (ii) via an AS160-independent pathway from PKB, and (iii) via an additional pathway from IR, e.g. affecting the membrane constitution. The developed combined model could describe data not used for training the model and was used to generate predictions of the relative contributions of the pathways from IR to translocation of GLUT4. The combined model provides a systems-level understanding of insulin signaling in rat adipocytes, which, when combined with corresponding models for human adipocytes, may contribute to model-based drug development for diabetes.

  • 44.
    Bergstrand, Sara
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Nursing Science. Linköping University, Faculty of Medicine and Health Sciences.
    Morales, Maria-Aurora
    CNR Inst Clin Physiol, Italy.
    Coppini, Giuseppe
    CNR Inst Clin Physiol, Italy.
    Larsson, Marcus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    The relationship between forearm skin speed-resolved perfusion and oxygen saturation, and finger arterial pulsation amplitudes, as indirect measures of endothelial function2018In: Microcirculation, ISSN 1073-9688, E-ISSN 1549-8719, Vol. 25, no 2, article id e12422Article in journal (Refereed)
    Abstract [en]

    Objective: Endothelial function is important for regulating peripheral blood flow to meet varying metabolic demands and can be measured indirectly during vascular provocations. In this study, we compared the PAT finger response (EndoPAT) after a 5-minutes arterial occlusion to that from forearm skin comprehensive microcirculation analysis (EPOS). Methods: Measurements in 16 subjects with varying cardiovascular risk factors were carried out concurrently with both methods during arterial occlusion, while forearm skin was also evaluated during local heating. Results: Peak values for EPOS skin Perf(conv) and speed-resolved total perfusion after the release of the occlusion were significantly correlated to the EndoPAT RHI (rho =.68, P = .007 and rho =.60, P = .025, respectively), mainly due to high-speed blood flow. During local heating, EPOS skin oxygen saturation, SO2, was significantly correlated to RHI (rho = .62, P =.043). This indicates that SO2 may have diagnostic value regarding endothelial function. Conclusions: We have demonstrated for the first time a significant relationship between forearm skin microcirculatory perfusion and oxygen saturation and finger PAT. Both local heating and reactive hyperemia are useful skin provocations. Further studies are needed to understand the precise regulation mechanisms of blood flow and oxygenation during these tests.

  • 45.
    Bianchessi, Tamara
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Tampu, Iulian Emil
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.
    Haj-Hosseini, Neda
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.
    Classification of pediatric brain tumors based on MR-images using deep learning2022Conference paper (Other academic)
  • 46.
    Björkman, Stina
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences.
    Lilliecreutz, Caroline
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Bladh, Marie
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Östgren, Carl Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Ekholmen. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Mahmoud, Arina
    Linköping University.
    Kafashian, Arian
    Linköping University.
    Bergstrand, Sara
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Nursing Sciences and Reproductive Health. Linköping University, Faculty of Medicine and Health Sciences.
    Sederholm Lawesson, Sofia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Microvascular dysfunction in women with a history of hypertensive disorders of pregnancy: A population-based retrospective cohort study2024In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 131, no 4, p. 433-443Article in journal (Refereed)
    Abstract [en]

    ObjectiveTo evaluate microvascular function in women with previous hypertensive disorders of pregnancy (HDP).DesignRetrospective population-based cohort study.SettingLinkoping, Sweden.PopulationWomen aged 50-65 years, participating in the Swedish CArdioPulmonary bioImage Study (SCAPIS) at one site (Linkoping) 2016-18, who underwent microcirculatory assessment (N = 1222).MethodsForearm skin comprehensive microcirculatory assessment was performed with a PeriFlux PF6000 EPOS (Enhanced Perfusion and Oxygen Saturation) system measuring oxygen saturation and total speed resolved perfusion. Obstetric records were reviewed to identify women with previous HDP. Data on cardiovascular risk factors, comorbidities, medication, lifestyle, anthropometric data, and biochemical analyses were obtained from SCAPIS. The microcirculatory data were compared between women with and without previous HDP.Main outcome measuresSkin microcirculatory oxygen saturation and total speed resolved perfusion at baseline and post-ischaemic peak.ResultsWomen with previous pre-eclampsia displayed impaired post-ischaemic peak oxygen saturation compared with women with normotensive pregnancies (88%, interquartile range [IQR] 84-89% vs 91%, IQR 87-94%, p = 0.001) 6-30 years after pregnancy. The difference remained after multivariable adjustment (& beta; -2.69, 95% CI -4.93 to -0.45).ConclusionsThe findings reveal microvascular dysfunction at long-term follow up in women with previous pre-eclampsia and strengthen the possible role of endothelial dysfunction as a link to the increased risk of cardiovascular disease in women with HDP.

  • 47.
    Black, David
    et al.
    Medical Image Computing, University of Bremen; Jacobs University, Bremen; Fraunhofer MEVIS, Bremen, Germany.
    Hahn, Horst
    Jacobs University, Bremen; Fraunhofer, MEVIS, Germany.
    Kikinis, Ron
    Brigham and Women's Hospital and Harvard Medical School, Boston, USA.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Haj-Hosseini, Neda
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Auditory display for Fluorescence-guided open brain tumor surgery2018In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 13, no 1, p. 25-35Article in journal (Refereed)
    Abstract [en]

    PURPOSE:

    Protoporphyrin (PpIX) fluorescence allows discrimination of tumor and normal brain tissue during neurosurgery. A handheld fluorescence (HHF) probe can be used for spectroscopic measurement of 5-ALA-induced PpIX to enable objective detection compared to visual evaluation of fluorescence. However, current technology requires that the surgeon either views the measured values on a screen or employs an assistant to verbally relay the values. An auditory feedback system was developed and evaluated for communicating measured fluorescence intensity values directly to the surgeon.

    METHODS:

    The auditory display was programmed to map the values measured by the HHF probe to the playback of tones that represented three fluorescence intensity ranges and one error signal. Ten persons with no previous knowledge of the application took part in a laboratory evaluation. After a brief training period, participants performed measurements on a tray of 96 wells of liquid fluorescence phantom and verbally stated the perceived measurement values for each well. The latency and accuracy of the participants' verbal responses were recorded. The long-term memorization of sound function was evaluated in a second set of 10 participants 2-3 and 7-12 days after training.

    RESULTS:

    The participants identified the played tone accurately for 98% of measurements after training. The median response time to verbally identify the played tones was 2 pulses. No correlation was found between the latency and accuracy of the responses, and no significant correlation with the musical proficiency of the participants was observed on the function responses. Responses for the memory test were 100% accurate.

    CONCLUSION:

    The employed auditory display was shown to be intuitive, easy to learn and remember, fast to recognize, and accurate in providing users with measurements of fluorescence intensity or error signal. The results of this work establish a basis for implementing and further evaluating auditory displays in clinical scenarios involving fluorescence guidance and other areas for which categorized auditory display could be useful.

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  • 48.
    Boianelli, Alessandro
    et al.
    AstraZeneca, Sweden.
    Aoki, Yasunori
    AstraZeneca, Sweden.
    Ivanov, Maxim
    AstraZeneca, Sweden.
    Dahlén, Anders
    AstraZeneca, Sweden.
    Gennemark, Peter
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. AstraZeneca, Sweden.
    Cross-Species Translation of Biophase Half-Life and Potency of GalNAc-Conjugated siRNAs2022In: Nucleic Acid Therapeutics, ISSN 2159-3337, E-ISSN 2159-3345, Vol. 32, no 6, p. 507-512Article in journal (Refereed)
    Abstract [en]

    Small interfering RNAs (siRNAs) with N-acetylgalactosamine (GalNAc) conjugation for improved liver uptake represent an emerging class of drugs to treat liver diseases. Understanding how pharmacokinetics and pharmacodynamics translate is pivotal for in vivo study design and human dose prediction. However, the literature is sparse on translational data for this modality, and pharmacokinetics in the liver is seldom measured. To overcome these difficulties, we collected time-course biomarker data for 11 GalNAc-siRNAs in various species and applied the kinetic-pharmacodynamic modeling approach to estimate the biophase (liver) half-life and the potency. Our analysis indicates that the biophase half-life is 0.6-3 weeks in mouse, 1-8 weeks in monkey, and 1.5-14 weeks in human. For individual siRNAs, the biophase half-life is 1-8 times longer in human than in mouse, and generally 1-3 times longer in human than in monkey. The analysis indicates that the siRNAs are more potent in human than in mouse and monkey.

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  • 49. Order onlineBuy this publication >>
    Boito, Deneb
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Diffusion MRI with generalised gradient waveforms: methods, models, and neuroimaging applications2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The incessant, random motion of water molecules within biological tissues reveals unique information about the tissues’ structural and functional characteristics. Diffusion magnetic resonance imaging is sensitive to this random motion, and since the mid-1990s it has been extensively employed for studying the human brain. Most notably, measurements of water diffusion allow for the early detection of ischaemic stroke and for the unveiling of the brain’s wiring via reconstruction of the neuronal connections. Ultimately, the goal is to employ this imaging technique to perform non-invasive, in vivo virtual histology to directly characterise both healthy and diseased tissue. 

    Recent developments in the field have introduced new ways to measure the diffusion process in clinically feasible settings. These new measurements, performed by employing generalised magnetic field gradient waveforms, grant access to specific features of the cellular composition and structural organisation of the tissue. Methods based on them have already proven beneficial for the assessment of different brain diseases, sparking interest in translating such techniques into clinical practice. This thesis focuses on improving the methods currently employed for the analysis of such diffusion MRI data, with the aim of facilitating their clinical adoption. 

    The first two publications introduce constrained frameworks for the estimation of parameters from diffusion MRI data acquired with generalised gradient waveforms. The constraints are dictated by mathematical and physical properties of a multi-compartment model used to represent the brain tissue, and can be efficiently enforced by employing a relatively new optimisation scheme called semidefinite programming. The developed routines are demonstrated to improve robustness to noise and imperfect data collection. Moreover, constraining the fit is shown to relax the requirements on the number of points needed for the estimation, thus allowing for faster data acquisition. 

    In the third paper, the developed frameworks are employed to study the brain’s white matter in patients previously hospitalised for COVID-19 and who still suffer from neurological symptoms months after discharge. The results show widespread alterations to the structural integrity of their brain, with the metrics available through the advanced diffusion measurements providing new insights into the damage to the white matter. 

    The fourth paper revisits the modelling paradigm currently adopted for the analysis of diffusion MRI data acquired with generalised gradient waveforms. Hitherto, the assumption of free diffusion has been employed to represent each domain in a multi-compartmental picture of the brain tissue. In this work, a model for restricted diffusion is considered instead to alleviate the paradoxical assumption of free but compartmentalised diffusion. The model is shown to perfectly capture restricted diffusion as measured with the generalised diffusion gradient waveforms, thus endorsing its use for representing each domain in the multi-compartmental model of the tissue. 

    List of papers
    1. Q-space trajectory imaging with positivity constraints (QTI plus )
    Open this publication in new window or tab >>Q-space trajectory imaging with positivity constraints (QTI plus )
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    2021 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 238, article id 118198Article in journal (Refereed) Published
    Abstract [en]

    Q-space trajectory imaging (QTI) enables the estimation of useful scalar measures indicative of the local tissue structure. This is accomplished by employing generalized gradient waveforms for diffusion sensitization alongside a diffusion tensor distribution (DTD) model. The first two moments of the underlying DTD are made available by acquisitions at low diffusion sensitivity (b-values). Here, we show that three independent conditions have to be fulfilled by the mean and covariance tensors associated with distributions of symmetric positive semidefinite tensors. We introduce an estimation framework utilizing semi-definite programming (SDP) to guarantee that these conditions are met. Applying the framework on simulated signal profiles for diffusion tensors distributed according to non-central Wishart distributions demonstrates the improved noise resilience of QTI+ over the commonly employed estimation methods. Our findings on a human brain data set also reveal pronounced improvements, especially so for acquisition protocols featuring few number of volumes. Our methods robustness to noise is expected to not only improve the accuracy of the estimates, but also enable a meaningful interpretation of contrast in the derived scalar maps. The techniques performance on shorter acquisitions could make it feasible in routine clinical practice.

    Place, publisher, year, edition, pages
    Elsevier, 2021
    Keywords
    Diffusion; MRI; Constrained; Positive definite; QTI; Multidimensional; mddMRI; Covariance; Microscopic anisotropy
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:liu:diva-178287 (URN)10.1016/j.neuroimage.2021.118198 (DOI)000677954600012 ()34029738 (PubMedID)
    Note

    Funding Agencies|Linkoping University (LiU) Center for Industrial Information Technology (CENIIT); LiU Cancer; Analytic Imaging Diagnostic Arena (AIDA); Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [RMX180056]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [201604482]; Center for Stochastic Geometry and Advanced Bioimaging - Villum Foundation (Denmark); VINNOVA/ITEA3 [17021]

    Available from: 2021-08-18 Created: 2021-08-18 Last updated: 2024-01-10
    2. Diffusivity-limited q-space trajectory imaging
    Open this publication in new window or tab >>Diffusivity-limited q-space trajectory imaging
    Show others...
    2023 (English)In: Magnetic Resonance Letters, ISSN 2772-5162, Vol. 3, no 2, p. 187-196Article in journal (Refereed) Published
    Abstract [en]

    Q-space trajectory imaging (QTI) allows non-invasive estimation of microstructural features of heterogeneous porous media via diffusion magnetic resonance imaging performed with generalised gradient waveforms. A recently proposed constrained estimation framework, called QTI+, improved QTI’s resilience to noise and data sparsity, thus increasing the reliability of the method by enforcing relevant positivity constraints. In this work we consider expanding the set of constraints to be applied during the fitting of the QTI model. We show that the additional conditions, which introduce an upper bound on the diffusivity values, further improve the retrieved parameters on a publicly available human brain dataset as well as on data acquired from healthy volunteers using a scanner-ready protocol.

    Place, publisher, year, edition, pages
    KeAi Publishing Communications, 2023
    Keywords
    Diffusion; Diffusion MRI; q-space trajectory imaging; QTI; Microstructure; Microscopic anisotropy; QTI+Constrained
    National Category
    Medical Engineering Mathematics
    Identifiers
    urn:nbn:se:liu:diva-198025 (URN)10.1016/j.mrl.2022.12.003 (DOI)
    Funder
    Swedish Foundation for Strategic ResearchVinnova
    Note

    Funding agencies: This research was funded by Sweden’s Innovation Agency (VINNOVA) ASSIST, Analytic Imaging Diagnostic Arena (AIDA), Swedish Foundation for Strategic Research (RMX18-0056), Linköping University Center for Industrial Information Technology (CENIIT), LiU Cancer Barncancerfonden, and a research grant (00028384) from VILLUM FONDEN.

    Available from: 2023-09-22 Created: 2023-09-22 Last updated: 2024-01-10Bibliographically approved
    3. MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up
    Open this publication in new window or tab >>MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up
    Show others...
    2023 (English)In: Brain Communications, E-ISSN 2632-1297, Vol. 5, no 6, article id fcad284Article in journal (Refereed) Published
    Abstract [en]

    There is mounting evidence of the long-term effects of COVID-19 on the central nervous system, with patients experiencing diverse symptoms, often suggesting brain involvement. Conventional brain MRI of these patients shows unspecific patterns, with no clear connection of the symptomatology to brain tissue abnormalities, whereas diffusion tensor studies and volumetric analyses detect measurable changes in the brain after COVID-19. Diffusion MRI exploits the random motion of water molecules to achieve unique sensitivity to structures at the microscopic level, and new sequences employing generalized diffusion encoding provide structural information which are sensitive to intravoxel features. In this observational study, a total of 32 persons were investigated: 16 patients previously hospitalized for COVID-19 with persisting symptoms of post-COVID condition (mean age 60 years: range 41–79, all male) at 7-month follow-up and 16 matched controls, not previously hospitalized for COVID-19, with no post-COVID symptoms (mean age 58 years, range 46–69, 11 males). Standard MRI and generalized diffusion encoding MRI were employed to examine the brain white matter of the subjects. To detect possible group differences, several tissue microstructure descriptors obtainable with the employed diffusion sequence, the fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, microscopic anisotropy, orientational coherence (Cc) and variance in compartment’s size (CMD) were analysed using the tract-based spatial statistics framework. The tract-based spatial statistics analysis showed widespread statistically significant differences (P < 0.05, corrected for multiple comparisons using the familywise error rate) in all the considered metrics in the white matter of the patients compared to the controls. Fractional anisotropy, microscopic anisotropy and Cc were lower in the patient group, while axial diffusivity, radial diffusivity, mean diffusivity and CMD were higher. Significant changes in fractional anisotropy, microscopic anisotropy and CMD affected approximately half of the analysed white matter voxels located across all brain lobes, while changes in Cc were mainly found in the occipital parts of the brain. Given the predominant alteration in microscopic anisotropy compared to Cc, the observed changes in diffusion anisotropy are mostly due to loss of local anisotropy, possibly connected to axonal damage, rather than white matter fibre coherence disruption. The increase in radial diffusivity is indicative of demyelination, while the changes in mean diffusivity and CMD are compatible with vasogenic oedema. In summary, these widespread alterations of white matter microstructure are indicative of vasogenic oedema, demyelination and axonal damage. These changes might be a contributing factor to the diversity of central nervous system symptoms that many patients experience after COVID-19.

    Place, publisher, year, edition, pages
    Oxford University Press, 2023
    Keywords
    MRI; Q-space trajectory imaging; microscopic fractional anisotropy; fractional anisotropy; COVID-19
    National Category
    Radiology, Nuclear Medicine and Medical Imaging Neurosciences Medical Image Processing
    Identifiers
    urn:nbn:se:liu:diva-199215 (URN)10.1093/braincomms/fcad284 (DOI)001103246200003 ()37953843 (PubMedID)
    Funder
    Vinnova, 2021-01954Wallenberg Foundations
    Note

    Funding: Analytic Imaging Diagnostic Arena (AIDA), a Medtech4Health initiative; ITEA/ VINNOVA (The Swedish Innovation Agency) project ASSIST (Automation, Surgery Support and Intuitive 3D visualization to optimize workflow in IGT SysTems) [2021-01954]; Wallenberg Center for Molecular Medicine

    Available from: 2023-11-19 Created: 2023-11-19 Last updated: 2024-01-03Bibliographically approved
    4. Multidimensional Diffusion MRI Methods With Confined Subdomains
    Open this publication in new window or tab >>Multidimensional Diffusion MRI Methods With Confined Subdomains
    2022 (English)In: Frontiers in Physics, E-ISSN 2296-424X, Vol. 10, article id 830274Article in journal (Refereed) Published
    Abstract [en]

    Diffusion Magnetic Resonance Imaging (dMRI) is an imaging technique with exquisite sensitivity to the microstructural properties of heterogeneous media. The conventionally adopted acquisition schemes involving single pulsed field gradients encode the random motion of water molecules into the NMR signal, however typically conflating the effects of different sources contributing to the water motion. Time-varying magnetic field gradients have recently been considered for disentangling such effects during the data encoding phase, opening to the possibility of adding specificity to the recovered information about the mediums microstructure. Such data is typically represented via a diffusion tensor distribution (DTD) model, thus assuming the existence of several non-exchanging compartments in each of which diffusion is unrestricted. In this work, we consider a model that takes confinement into account and possesses a diffusion time-dependence closer to that of restricted diffusion, to replace the free diffusion assumption in multidimensional diffusion MRI methods. We first demonstrate how the confinement tensor model captures the relevant signal modulations impressed by water diffusing in both free and closed spaces, for data simulated with a clinically feasible protocol involving time-varying magnetic field gradients. Then, we provide the basis for incorporating this model into two multidimensional dMRI methods, and attempt to recover a confinement tensor distribution (CTD) on a human brain dataset.

    Place, publisher, year, edition, pages
    Frontiers Media SA, 2022
    Keywords
    confinement; anisotropy; microstructure; restricted; tensor; distribution
    National Category
    Radiology, Nuclear Medicine and Medical Imaging
    Identifiers
    urn:nbn:se:liu:diva-184540 (URN)10.3389/fphy.2022.830274 (DOI)000780312100001 ()
    Available from: 2022-04-29 Created: 2022-04-29 Last updated: 2024-01-10
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  • 50.
    Boito, Deneb
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Tisell, Anders
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Levi, Richard
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Rehabilitation Medicine. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Özarslan, Evren
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Blystad, Ida
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up2023In: Brain Communications, E-ISSN 2632-1297, Vol. 5, no 6, article id fcad284Article in journal (Refereed)
    Abstract [en]

    There is mounting evidence of the long-term effects of COVID-19 on the central nervous system, with patients experiencing diverse symptoms, often suggesting brain involvement. Conventional brain MRI of these patients shows unspecific patterns, with no clear connection of the symptomatology to brain tissue abnormalities, whereas diffusion tensor studies and volumetric analyses detect measurable changes in the brain after COVID-19. Diffusion MRI exploits the random motion of water molecules to achieve unique sensitivity to structures at the microscopic level, and new sequences employing generalized diffusion encoding provide structural information which are sensitive to intravoxel features. In this observational study, a total of 32 persons were investigated: 16 patients previously hospitalized for COVID-19 with persisting symptoms of post-COVID condition (mean age 60 years: range 41–79, all male) at 7-month follow-up and 16 matched controls, not previously hospitalized for COVID-19, with no post-COVID symptoms (mean age 58 years, range 46–69, 11 males). Standard MRI and generalized diffusion encoding MRI were employed to examine the brain white matter of the subjects. To detect possible group differences, several tissue microstructure descriptors obtainable with the employed diffusion sequence, the fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, microscopic anisotropy, orientational coherence (Cc) and variance in compartment’s size (CMD) were analysed using the tract-based spatial statistics framework. The tract-based spatial statistics analysis showed widespread statistically significant differences (P < 0.05, corrected for multiple comparisons using the familywise error rate) in all the considered metrics in the white matter of the patients compared to the controls. Fractional anisotropy, microscopic anisotropy and Cc were lower in the patient group, while axial diffusivity, radial diffusivity, mean diffusivity and CMD were higher. Significant changes in fractional anisotropy, microscopic anisotropy and CMD affected approximately half of the analysed white matter voxels located across all brain lobes, while changes in Cc were mainly found in the occipital parts of the brain. Given the predominant alteration in microscopic anisotropy compared to Cc, the observed changes in diffusion anisotropy are mostly due to loss of local anisotropy, possibly connected to axonal damage, rather than white matter fibre coherence disruption. The increase in radial diffusivity is indicative of demyelination, while the changes in mean diffusivity and CMD are compatible with vasogenic oedema. In summary, these widespread alterations of white matter microstructure are indicative of vasogenic oedema, demyelination and axonal damage. These changes might be a contributing factor to the diversity of central nervous system symptoms that many patients experience after COVID-19.

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