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  • 1.
    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, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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.

  • 2.
    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.

  • 3.
    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.

  • 4.
    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.

  • 5.
    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
    Show others...
    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: 2018-09-10Bibliographically 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
    Show others...
    2018 (English)In: Brain Sciences, ISSN 2076-3425, E-ISSN 2076-3425, Vol. 8, no 2Article 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)
    Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-09-10
    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
    Show others...
    2016 (English)In: Frontiers in Human Neuroscience, ISSN 1662-5161, 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: 2018-09-10Bibliographically approved
  • 6.
    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.

  • 7.
    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.

  • 8.
    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.

  • 9.
    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, 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.

  • 10.
    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.

  • 11.
    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.

  • 12.
    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 surgery2017In: 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.

  • 13.
    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).
    MRI adipose tissue and muscle composition analysis: a review of automation techniques2018In: British Journal of Radiology, ISSN 0007-1285, E-ISSN 1748-880X, Vol. 91, no 1089, article id 20180252Article, review/survey (Refereed)
    Abstract [en]

    MRI is becoming more frequently used in studies involving measurements of adipose tissue and volume and composition of skeletal muscles. The large amount of data generated by MRI calls for automated analysis methods. This review article presents a summary of automated and semi-automated techniques published between 2013 and 2017. Technical aspects and clinical applications for MRI-based adipose tissue and muscle composition analysis are discussed based on recently published studies. The conclusion is that very few clinical studies have used highly automated analysis methods, despite the rapidly increasing use of MRI for body composition analysis. Possible reasons for this are that the availability of highly automated methods has been limited for non-imaging experts, and also that there is a limited number of studies investigating the reproducibility of automated methods for MRI-based body composition analysis.

    The full text will be freely available from 2019-07-24 00:01
  • 14.
    Borga, Magnus
    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).
    West, Janne
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bell, Jimmy
    Westminster University, London, UK.
    Harvey, Nicholas
    University of Southampton, IK.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Heymsfield, Steven
    Pennington Biomedical Research Center, Baton Rouge, LA, US.
    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.
    Advanced body composition assessment: From body mass index to body composition profiling2018In: Journal of Investigative Medicine, ISSN 1081-5589, E-ISSN 1708-8267, Vol. 66, p. 887-895Article, review/survey (Refereed)
    Abstract [en]

    This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative magnetic resonance imaging (MRI). Earlier published studies of this method are summarized, and a previously un-published validation study, based on 4.753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy x-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRI show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 % and 4.6 % for fat (computed from AT) and lean tissue respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of more than 20 %. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat in combination with rapid scanning protocols and efficient image analysis tools make quantitative MRI a powerful tool for advanced body composition assessment. 

  • 15.
    Brannmark, Cecilia
    et al.
    University of Gothenburg, Sweden.
    Lövfors, William
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Komai, Ali M.
    University of Gothenburg, Sweden.
    Axelsson, Tom
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    El Hachmane, Mickael F.
    University of Gothenburg, Sweden.
    Musovic, Saliha
    University of Gothenburg, Sweden.
    Paul, Alexandra
    Chalmers University of Technology, Sweden.
    Nyman, Elin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. AstraZeneca RandD, Sweden.
    Olofsson, Charlotta S.
    University of Gothenburg, Sweden.
    Mathematical modeling of white adipocyte exocytosis predicts adiponectin secretion and quantifies the rates of vesicle exo- and endocytosis2017In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 292, no 49, p. 20032-20043Article in journal (Refereed)
    Abstract [en]

    Adiponectin is a hormone secreted from white adipocytes and takes part in the regulation of several metabolic processes. Although the pathophysiological importance of adiponectin has been thoroughly investigated, the mechanisms controlling its release are only partly understood. We have recently shown that adiponectin is secreted via regulated exocytosis of adiponectin-containing vesicles, that adiponectin exocytosis is stimulated by cAMP-dependent mechanisms, and that Ca2+ and ATP augment the cAMP-triggered secretion. However, much remains to be discovered regarding the molecular and cellular regulation of adiponectin release. Here, we have used mathematical modeling to extract detailed information contained within our previously obtained high-resolution patch-clamp time-resolved capacitance recordings to produce the first model of adiponectin exocytosis/secretion that combines all mechanistic knowledge deduced from electrophysiological experimental series. This model demonstrates that our previous understanding of the role of intracellular ATP in the control of adiponectin exocytosis needs to be revised to include an additional ATP-dependent step. Validation of the model by introduction of data of secreted adiponectin yielded a very close resemblance between the simulations and experimental results. Moreover, we could show that Ca2+-dependent adiponectin endocytosis contributes to the measured capacitance signal, and we were able to predict the contribution of endocytosis to the measured exocytotic rate under different experimental conditions. In conclusion, using mathematical modeling of published and newly generated data, we have obtained estimates of adiponectin exo- and endocytosis rates, and we have predicted adiponectin secretion. We believe that our model should have multiple applications in the study of metabolic processes and hormonal control thereof.

  • 16.
    Campbell, Walter S.
    et al.
    Univ Nebraska Med Ctr, NE 68198 USA.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Vreeman, Daniel J.
    Indiana Univ Sch Med, IN 46202 USA.
    Lazenby, Audrey J.
    Univ Nebraska Med Ctr, NE 68198 USA.
    Talmon, Geoffrey A.
    Univ Nebraska Med Ctr, NE 68198 USA.
    Campbell, James R.
    Univ Nebraska Med Ctr, NE USA.
    A computable pathology report for precision medicine: extending an observables ontology unifying SNOMED CT and LOINC2018In: JAMIA Journal of the American Medical Informatics Association, ISSN 1067-5027, E-ISSN 1527-974X, Vol. 25, no 3, p. 259-266Article in journal (Refereed)
    Abstract [en]

    The College of American Pathologists (CAP) introduced the first cancer synoptic reporting protocols in 1998. However, the objective of a fully computable and machine-readable cancer synoptic report remains elusive due to insufficient definitional content in Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) and Logical Observation Identifiers Names and Codes (LOINC). To address this terminology gap, investigators at the University of Nebraska Medical Center (UNMC) are developing, authoring, and testing a SNOMED CT observable ontology to represent the data elements identified by the synoptic worksheets of CAP. Investigators along with collaborators from the US National Library of Medicine, CAP, the International Health Terminology Standards Development Organization, and the UK Health and Social Care Information Centre analyzed and assessed required data elements for colorectal cancer and invasive breast cancer synoptic reporting. SNOMED CT concept expressions were developed at UNMC in the Nebraska LexiconA (c) SNOMED CT namespace. LOINC codes for each SNOMED CT expression were issued by the Regenstrief Institute. SNOMED CT concepts represented observation answer value sets. UNMC investigators created a total of 194 SNOMED CT observable entity concept definitions to represent required data elements for CAP colorectal and breast cancer synoptic worksheets, including biomarkers. Concepts were bound to colorectal and invasive breast cancer reports in the UNMC pathology system and successfully used to populate a UNMC biobank. The absence of a robust observables ontology represents a barrier to data capture and reuse in clinical areas founded upon observational information. Terminology developed in this project establishes the model to characterize pathology data for information exchange, public health, and research analytics.

  • 17.
    Casas Garcia, Belén
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Frederica
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Bolger, Ann F.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. University of Calif San Francisco, CA USA.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bridging the gap between measurements and modelling: a cardiovascular functional avatar2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 6214Article in journal (Refereed)
    Abstract [en]

    Lumped parameter models of the cardiovascular system have the potential to assist researchers and clinicians to better understand cardiovascular function. The value of such models increases when they are subject specific. However, most approaches to personalize lumped parameter models have thus far required invasive measurements or fall short of being subject specific due to a lack of the necessary clinical data. Here, we propose an approach to personalize parameters in a model of the heart and the systemic circulation using exclusively non-invasive measurements. The personalized model is created using flow data from four-dimensional magnetic resonance imaging and cuff pressure measurements in the brachial artery. We term this personalized model the cardiovascular avatar. In our proof-of-concept study, we evaluated the capability of the avatar to reproduce pressures and flows in a group of eight healthy subjects. Both quantitatively and qualitatively, the model-based results agreed well with the pressure and flow measurements obtained in vivo for each subject. This non-invasive and personalized approach can synthesize medical data into clinically relevant indicators of cardiovascular function, and estimate hemodynamic variables that cannot be assessed directly from clinical measurements.

  • 18.
    Casas Garcia, Belén
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Frederica
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Bolger, Ann F
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Univ Calif San Francisco, CA USA.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach2018In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 1515Article in journal (Refereed)
    Abstract [en]

    Background: The possibility of non-invasively assessing load-independent parameters characterizing cardiac function is of high clinical value. Typically, these parameters are assessed during resting conditions. However, for diagnostic purposes, the parameter behavior across a physiologically relevant range of heart rate and loads is more relevant than the isolated measurements performed at rest. This study sought to evaluate changes in non-invasive estimations of load-independent parameters of left-ventricular contraction and relaxation patterns at rest and during dobutamine stress. Methods: We applied a previously developed approach that combines non-invasive measurements with a physiologically-based, reduced-order model of the cardiovascular system to provide subject-specific estimates of parameters characterizing left ventricular function. In this model, the contractile state of the heart at each time point along the cardiac cycle is modeled using a time-varying elastance curve. Non-invasive data, including four-dimensional magnetic resonance imaging (4D Flow MRI) measurements, were acquired in nine subjects without a known heart disease at rest and during dobutamine stress. For each of the study subjects, we constructed two personalized models corresponding to the resting and the stress state. Results: Applying the modeling framework, we identified significant increases in the left ventricular contraction rate constant [from 1.5 +/- 0.3 to 2 +/- 0.5 (p = 0.038)] and relaxation constant [from 37.2 +/- 6.9 to 46.1 +/- 12 (p = 0.028)]. In addition, we found a significant decrease in the elastance diastolic time constant from 0.4 +/- 0.04 s to 0.3 +/- 0.03 s = 0.008). Conclusions: The integrated image-modeling approach allows the assessment of cardiovascular function given as model-based parameters. The agreement between the estimated parameter values and previously reported effects of dobutamine demonstrates the potential of the approach to assess advanced metrics of pathophysiology that are otherwise difficult to obtain non-invasively in clinical practice.

  • 19.
    Chan, Yung-Kuan
    et al.
    Natl Chung Hsing Univ, Taiwan.
    Chen, Yung-Fu
    Cent Taiwan Univ Sci and Technol, Taiwan.
    Pham, Tuan
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Chang, Weide
    Calif State Univ Sacramento, CA 95819 USA.
    Hsieh, Ming-Yuan
    Natl Taichung Univ Educ, Taiwan.
    Editorial Material: Artificial Intelligence in Medical Applications in JOURNAL OF HEALTHCARE ENGINEERING, vol , issue , pp2018In: Journal of Healthcare Engineering, ISSN 2040-2295, E-ISSN 2040-2309, article id 4827875Article in journal (Other academic)
    Abstract [en]

    n/a

  • 20.
    Cornet, Ronald
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Univ Amsterdam, Netherlands.
    Infrastructure and Capacity Building for Semantic Interoperability in Healthcare in the Netherlands2017In: BUILDING CAPACITY FOR HEALTH INFORMATICS IN THE FUTURE, IOS PRESS , 2017, Vol. 234, p. 70-74Conference paper (Refereed)
    Abstract [en]

    Over 15 years, a broad spectrum of activities was undertaken to realize a health IT infrastructure in the Netherlands. In this paper we reflect on the history, challenges, accomplishments, changes, and the way forward. It shows that the infrastructure depends on technical, legal, and semantic aspects, which are frequently reciprocally related. It also highlights the fact that the role of health professionals and of patients is increasingly considered as a crucial element.

  • 21.
    Cornet, Ronald
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Univ Amsterdam, Netherlands.
    Hill, Carly
    Univ Amsterdam, Netherlands.
    de Keizer, Nicolette
    Univ Amsterdam, Netherlands.
    Comparison of Three English-to-Dutch Machine Translations of SNOMED CT Procedures2017In: MEDINFO 2017: PRECISION HEALTHCARE THROUGH INFORMATICS, IOS PRESS , 2017, Vol. 245, p. 848-852Conference paper (Refereed)
    Abstract [en]

    Dutch interface terminologies are needed to use SNOMED CT in the Netherlands. Machine translation may support in their creation. The aim of our study is to compare different machine translations of procedures in SNOMED CT. Procedures were translated using Google Translate, Matecat, and Thot. Google Translate and Matecat are tools with large but general translation memories. The translation memory of Thot was trained and tuned with various configurations of a Dutch translation of parts of SNOMED CT, a medical dictionary and parts of the UMLS Metathesaurus. The configuration with the highest BLEU score, representing closeness to human translation, was selected. Similarity was determined between Thot translations and those by Google and Matecat. The validity of translations was assessed through random samples. Google and Matecat translated similarly in 85.4% of the cases and generally better than Thot. Whereas the quality of translations was considered acceptable, machine translations alone are yet insufficient.

  • 22.
    Cros, Olivier
    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). Department of Otolaryngology, Head & Neck Surgery, Aalborg University Hospital, Denmark.
    Gaihede, Michael
    Department of Otolaryngology, Head & Neck Surgery, Aalborg University Hospital, Denmark; Department of Clinical Medicine, Aalborg University, Denmark.
    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. Linköping University, Faculty of Arts and Sciences.
    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).
    Surface and curve skeleton from a structure tensor analysis applied on mastoid air cells in human temporal bones2017In: IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 270-274Conference paper (Refereed)
    Abstract [en]

    The mastoid of human temporal bone contains numerous air cells connected to each others. In order to gain further knowledge about these air cells, a more compact representation is needed to obtain an estimate of the size distribution of these cells. Already existing skeletonization methods often fail in producing a faithful skeleton mostly due to noise hampering the binary representation of the data. This paper proposes a different approach by extracting geometrical information embedded in the Euclidean distance transform of a volume via a structure tensor analysis based on quadrature filters, from which a secondary structure tensor allows the extraction of surface skeleton along with a curve skeleton from its eigenvalues. Preliminary results obtained on a X-ray micro-CT scans of a human temporal bone show very promising results.

  • 23.
    Cubo, Ruben
    et al.
    Uppsala Univ, Sweden.
    Åström, Mattias
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Medvedev, Alexander
    Uppsala Univ, Sweden.
    Optimization-Based Contact Fault Alleviation in Deep Brain Stimulation Leads2018In: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 26, no 1, p. 69-76Article in journal (Refereed)
    Abstract [en]

    Deep brain stimulation (DBS) is a neurosurgical treatment in, e.g., Parkinsons Disease. Electrical stimulation in DBS is delivered to a certain target through electrodes implanted into the brain. Recent developments aiming at better stimulation target coverage and lesser side effects have led to an increase in the number of contacts in a DBS lead as well as higher hardware complexity. This paper proposes an optimization-based approach to alleviation of the fault impact on the resulting therapeutical effect in field steering DBS. Faulty contacts could be an issue given recent trends of increasing number of contacts in DBS leads. Hence, a fault detection/alleviation scheme, such as the one proposed in this paper, is necessary ensure resilience in the chronic stimulation. Two alternatives are considered and compared with the stimulation prior to the fault: one using higher amplitudes on the remaining contacts and another with alleviating contacts in the neighborhood of the faulty one. Satisfactory compensation for a faulty contact can be achieved in both ways. However, to designate alleviating contacts, a model-based optimization procedure is necessary. Results suggest that stimulating with more contacts yields configurations that are more robust to contact faults, though with reduced selectivity.

  • 24.
    Durrieu, Lucía
    et al.
    IFIByNE, DFBMC, FCEN, UBA, Buenos Aires, Argentine.
    Johansson, Rikard
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Bush, Alan
    IFIByNE, DFBMC, FCEN, UBA, Buenos Aires, Argentine.
    Janzén, David
    Linköping University, Department of Clinical and Experimental Medicine, Division of Cell Biology. Linköping University, Faculty of Medicine and Health Sciences.
    Gollvik, Martin
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Cedersund, Gunnar
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Colman-Lerner, Alejandro
    IFIByNE, DFBMC, FCEN, UBA, Buenos Aires, Argentine.
    Quantification of nuclear transport in single cells2014Other (Other academic)
    Abstract [en]

    Regulation of nuclear transport is a key cellular function involved in many central processes, such as gene expression regulation and signal transduction. Rates of protein movement between cellular compartments can be measured by FRAP. However, no standard and reliable methods to calculate transport rates exist. Here we introduce a method to extract import and export rates, suitable for noisy single cell data. This method consists of microscope procedures, routines for data processing, an ODE model to fit to the data, and algorithms for parameter optimization and error estimation. Using this method, we successfully measured import and export rates in individual yeast. For YFP, average transport rates were 0.15 sec-1. We estimated confidence intervals for these parameters through likelihood profile analysis. We found large cell-to-cell variation (CV = 0.79) in these rates, suggesting a hitherto unknown source of cellular heterogeneity. Given the passive nature of YFP diffusion, we attribute this variation to large differences among cells in the number or quality of nuclear pores. Owing to its broad applicability and sensitivity, this method will allow deeper mechanistic insight into nuclear transport processes and into the largely unstudied cell-to-cell variation in kinetic rates.

  • 25.
    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).
    Repliker. ”Öppen vetenskap behöver inte kosta en enda krona”2016In: Dagens Nyheter, ISSN 1101-2447Article in journal (Other (popular science, discussion, etc.))
  • 26.
    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).
    Öppen vetenskap behöver inte kosta en krona2017In: Svenska Dagbladet, ISSN 1101-2412Article in journal (Other (popular science, discussion, etc.))
  • 27.
    Eklund, Anders
    et al.
    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).
    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).
    Reply to Chen et al.: Parametric methods for cluster inference perform worse for two‐sided t‐tests2018In: Human Brain Mapping, ISSN 1065-9471, E-ISSN 1097-0193Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    One‐sided t‐tests are commonly used in the neuroimaging field, but two‐sided tests should be the default unless a researcher has a strong reason for using a one‐sided test. Here we extend our previous work on cluster false positive rates, which used one‐sided tests, to two‐sided tests. Briefly, we found that parametric methods perform worse for two‐sided t‐tests, and that nonparametric methods perform equally well for one‐sided and two‐sided tests.

  • 28.
    Eklund, Anders
    et al.
    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).
    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).
    Nichols, Thomas E
    Big Data Institute, University of Oxford, Oxford, United Kingdom, Department of Statistics, University of Warwick, Coventry, United KingdomWellcome Trust Centre for Integrative Neuroimaging (WIN-FMRIB), University of Oxford, Oxford, United Kingdom, .
    Cluster failure revisited: Impact of first level design and physiological noise on cluster false positive rates2018In: Human Brain Mapping, ISSN 1065-9471, E-ISSN 1097-0193Article in journal (Refereed)
    Abstract [en]

    Methodological research rarely generates a broad interest, yet our work on the validity of cluster inference methods for functional magnetic resonance imaging (fMRI) created intense discussion on both the minutia of our approach and its implications for the discipline. In the present work, we take on various critiques of our work and further explore the limitations of our original work. We address issues about the particular event‐related designs we used, considering multiple event types and randomization of events between subjects. We consider the lack of validity found with one‐sample permutation (sign flipping) tests, investigating a number of approaches to improve the false positive control of this widely used procedure. We found that the combination of a two‐sided test and cleaning the data using ICA FIX resulted in nominal false positive rates for all data sets, meaning that data cleaning is not only important for resting state fMRI, but also for task fMRI. Finally, we discuss the implications of our work on the fMRI literature as a whole, estimating that at least 10% of the fMRI studies have used the most problematic cluster inference method (p = .01 cluster defining threshold), and how individual studies can be interpreted in light of our findings. These additional results underscore our original conclusions, on the importance of data sharing and thorough evaluation of statistical methods on realistic null data.

  • 29.
    Eklund, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. 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. Linköping University, Faculty of Arts and Sciences.
    Lindqvist, Martin A
    Department of Biostatistics, Johns Hopkins University, Baltimore, USA.
    Villani, Mattias
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes2017In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 155, p. 354-369Article in journal (Refereed)
    Abstract [en]

    We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data. The model is analyzed from a Bayesian perspective and has the benefit of automatically down-weighting time points close to motion spikes in a data-driven manner. We develop a highly efficient Markov Chain Monte Carlo (MCMC) algorithm that allows for Bayesian variable selection among the regressors to model both the mean (i.e., the design matrix) and variance. This makes it possible to include a broad range of explanatory variables in both the mean and variance (e.g., time trends, activation stimuli, head motion parameters and their temporal derivatives), and to compute the posterior probability of inclusion from the MCMC output. Variable selection is also applied to the lags in the autoregressive noise process, making it possible to infer the lag order from the data simultaneously with all other model parameters. We use both simulated data and real fMRI data from OpenfMRI to illustrate the importance of proper modeling of heteroscedasticity in fMRI data analysis. Our results show that the GLMH tends to detect more brain activity, compared to its homoscedastic counterpart, by allowing the variance to change over time depending on the degree of head motion.

  • 30.
    Eklund, Anders
    et al.
    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).
    Nichols, Thomas
    University of Warwick, England.
    How open science revealed false positives in brain imaging2017In: Significance, ISSN 1740-9705, E-ISSN 1740-9713Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    A team set out to validate software used in fMRI analysis, but ended up invalidating one of neuroscience's most common testing procedures.

  • 31.
    Eklund, Anders
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Nichols, Thomas
    Department of Statistics, University of Warwick, UK / WMG, University of Warwick, UK.
    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).
    Reply to BROWN AND BEHRMANN, COX ET AL., AND KESSLER ET AL.: Data and code sharing is the way forward for fMRI2017In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, p. 1-2Article in journal (Other academic)
    Abstract [en]

    We are glad that our paper (1) has generated intense discussions in the fMRI field (2⇓–4), on how to analyze fMRI data, and how to correct for multiple comparisons. The goal of the paper was not to disparage any specific fMRI software, but to point out that parametric statistical methods are based on a number of assumptions that are not always valid for fMRI data, and that nonparametric statistical methods (5) are a good alternative. Through AFNI’s introduction of nonparametric statistics in the function 3dttest++ (3, 6), the three most common fMRI softwares now all support nonparametric group inference [SPM through the toolbox SnPM (www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/nichols/software/snpm), and FSL through the function randomise].

    Cox et al. (3) correctly point out that the bug in the AFNI function 3dClustSim only had a minor impact on the false-positive rate (FPR). This was also covered in our original paper (1): “We note that FWE [familywise error] rates are lower with the bug-fixed 3dClustSim function. As an example, the updated function reduces the degree of false …

  • 32.
    Ewerlöf, Maria
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Larsson, Marcus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Salerud, Göran
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera2017In: IMAGING, MANIPULATION, AND ANALYSIS OF BIOMOLECULES, CELLS, AND TISSUES XV, SPIE-INT SOC OPTICAL ENGINEERING , 2017, Vol. 10068, article id UNSP 1006814Conference paper (Refereed)
    Abstract [en]

    Hyperspectral imaging (HSI) can estimate the spatial distribution of skin blood oxygenation, using visible to near-infrared light. HSI oximeters often use a liquid-crystal tunable filter, an acousto-optic tunable filter or mechanically adjustable filter wheels, which has too long response/switching times to monitor tissue hemodynamics. This work aims to evaluate a multispectral snapshot imaging system to estimate skin blood volume and oxygen saturation with high temporal and spatial resolution. We use a snapshot imager, the xiSpec camera (MQ022HG-IM-SM4X4-VIS, XIMEA (R)), having 16 wavelength-specific Fabry-Perot filters overlaid on the custom CMOS-chip. The spectral distribution of the bands is however substantially overlapping, which needs to be taken into account for an accurate analysis. An inverse Monte Carlo analysis is performed using a two-layered skin tissue model, defined by epidermal thickness, haemoglobin concentration and oxygen saturation, melanin concentration and spectrally dependent reduced-scattering coefficient, all parameters relevant for human skin. The analysis takes into account the spectral detector response of the xiSpec camera. At each spatial location in the field-of-view, we compare the simulated output to the detected diffusively backscattered spectra to find the best fit. The imager is evaluated for spatial and temporal variations during arterial and venous occlusion protocols applied to the forearm. Estimated blood volume changes and oxygenation maps at 512x272 pixels show values that are comparable to reference measurements performed in contact with the skin tissue. We conclude that the snapshot xiSpec camera, paired with an inverse Monte Carlo algorithm, permits us to use this sensor for spatial and temporal measurement of varying physiological parameters, such as skin tissue blood volume and oxygenation.

  • 33.
    Farzam, Parisa
    et al.
    Barcelona Institute Science and Technology, Spain; Harvard Medical Sch, MA 02129 USA.
    Johansson, Johannes
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Barcelona Institute Science and Technology, Spain.
    Mireles, Miguel
    Barcelona Institute Science and Technology, Spain.
    Jimenez-Valerio, Gabriela
    Bellvitge Biomed Research Institute IDIBELL, Spain.
    Martinez-Lozano, Mar
    Bellvitge Biomed Research Institute IDIBELL, Spain.
    Choe, Regine
    University of Rochester, NY 14627 USA; University of Rochester, NY 14627 USA.
    Casanovas, Oriol
    Bellvitge Biomed Research Institute IDIBELL, Spain.
    Durduran, Turgut
    Barcelona Institute Science and Technology, Spain; ICREA, Spain.
    Pre-clinical longitudinal monitoring of hemodynamic response to anti-vascular chemotherapy by hybrid diffuse optics2017In: Biomedical Optics Express, ISSN 2156-7085, E-ISSN 2156-7085, Vol. 8, no 5, p. 2563-2582Article in journal (Refereed)
    Abstract [en]

    The longitudinal effect of an anti-vascular endothelial growth factor receptor 2 (VEGFR-2) antibody (DC 101) therapy on a xenografted renal cell carcinoma (RCC) mouse model was monitored using hybrid diffuse optics. Two groups of immunosuppressed male nude mice (seven treated, seven controls) were measured. Tumor microvascular blood flow, total hemoglobin concentration and blood oxygenation were investigated as potential biomarkers for the monitoring of the effect of therapy twice a week and were related to the final treatment outcome. These hemodynamic biomarkers have shown a clear differentiation between two groups by day four. Moreover, we have observed that pre-treatment values and early changes in hemodynamics are highly correlated with the therapeutic outcome demonstrating the potential of diffuse optics to predict the therapy response at an early time point. (C) 2017 Optical Society of America

  • 34.
    Felter, Pierre-Loïc
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Creating hemodynamic atlas of aorta2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Turbulent blood flow is involved in the pathogenesis of several cardiovascular diseases. While it is known that turbulence is present in patients with obstructive disease in the major vessels, the magnitude and impact of turbulence in the normal heart and aorta is still relatively unexplored. Besides, existing analysis method of the blood flow is a labour intensive process and requires excessive amount of time.

    A method to automatically create hemodynamic atlases has been developed, using 4D Flow magnetic resonance imaging (MRI), a powerful tool to measure blood flow characteristics. The resulting atlases show the expected blood flow characteristics in the aorta for a group of similar subjects.

    Application of the method in healthy young and healthy old has shown significant differences in kinetic energy and turbulent kinetic energy in the aortic flow. 

  • 35.
    Fredriksson, Ingemar
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Perimed AB, Sweden.
    Larsson, Marcus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Vessel packaging effect in laser speckle contrast imaging and laser Doppler imaging2017In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 22, no 10, article id 106005Article in journal (Refereed)
    Abstract [en]

    Laser speckle-based techniques are frequently used to assess microcirculatory blood flow. Perfusion estimates are calculated either by analyzing the speckle fluctuations over time as in laser Doppler flowmetry (LDF), or by analyzing the speckle contrast as in laser speckle contrast imaging (LSCI). The perfusion estimates depend on the amount of blood and its speed distribution. However, the perfusion estimates are commonly given in arbitrary units as they are nonlinear and depend on the magnitude and the spatial distribution of the optical properties in the tissue under investigation. We describe how the spatial confinement of blood to vessels, called the vessel packaging effect, can be modeled in LDF and LSCI, which affect the Doppler power spectra and speckle contrast, and the underlying bio-optical mechanisms for these effects. As an example, the perfusion estimate is reduced by 25% for LDF and often more than 50% for LSCI when blood is located in vessels with an average diameter of 40 aem, instead of being homogeneously distributed within the tissue. This significant effect can be compensated for only with knowledge of the average diameter of the vessels in the tissue. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.

  • 36.
    Fredriksson, Ingemar
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Perimed AB, Sweden.
    Saager, Rolf B.
    University of Calif Irvine, CA USA; University of Calif Irvine, CA USA.
    Durkin, Anthony J.
    University of Calif Irvine, CA USA.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. University of Calif Irvine, CA USA; University of Calif Irvine, CA USA.
    Evaluation of a multi-layer diffuse reflectance spectroscopy system using optical phantoms2017In: DESIGN AND QUALITY FOR BIOMEDICAL TECHNOLOGIES X, SPIE-INT SOC OPTICAL ENGINEERING , 2017, Vol. 10056, article id UNSP 100560GConference paper (Refereed)
    Abstract [en]

    A fiber probe-based device for assessing microcirculatory parameters, especially red blood cell (RBC) tissue fraction, their oxygen saturation and speed resolved perfusion, has been evaluated using state-of-the-art multi-layer tissue simulating phantoms. The device comprises both diffuse reflectance spectroscopy (DRS) at two source-detector separations (0.4 and 1.2 mm) and laser Doppler flowmetry (LDF) and use an inverse Monte Carlo method for identifying the parameters of a multi-layered tissue model. First, model parameters affecting scattering, absorption and geometrical parameters are fitted to measured DRS spectra, then speed parameters are fitted to LDF spectra. In this paper, the accuracy of the spectral parameters is evaluated. The measured spectral shapes at the two source-detector separations were in good agreement with forward calculated spectral shapes. In conclusion, the multi-layer skin model based on spectral features of the included chromophores, can reliably estimate the tissue fraction of RBC, its oxygen saturation and the reduced scattering coefficient spectrum of the tissue. Furthermore, it was concluded that some freedom in the relative intensity difference between the two DRS channels is necessary in order to compensate for non-modeled surface structure effects.

  • 37.
    Fredriksson, Ingemar
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Perimed AB, Sweden.
    Saager, Rolf B.
    University of Calif Irvine, CA 92715 USA.
    Durkin, Anthony J.
    University of Calif Irvine, CA USA.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. University of Calif Irvine, CA 92715 USA.
    Evaluation of a pointwise microcirculation assessment method using liquid and multilayered tissue simulating phantoms2017In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 22, no 11, article id 115004Article in journal (Refereed)
    Abstract [en]

    A fiber-optic probe-based instrument, designed for assessment of parameters related to microcirculation, red blood cell tissue fraction (f(RBC)), oxygen saturation (S-O2), and speed resolved perfusion, has been evaluated using state-of-the-art tissue phantoms. The probe integrates diffuse reflectance spectroscopy (DRS) at two source-detector separations and laser Doppler flowmetry, using an inverse Monte Carlo method for identifying the parameters of a multilayered tissue model. Here, we characterize the accuracy of the DRS aspect of the instrument using (1) liquid blood phantoms containing yeast and (2) epidermis-dermis mimicking solid-layered phantoms fabricated from polydimethylsiloxane, titanium oxide, hemoglobin, and coffee. The rootmean-square (RMS) deviations for f(RBC) for the two liquid phantoms were 11% and 5.3%, respectively, and 11% for the solid phantoms with highest hemoglobin signatures. The RMS deviation for SO2 was 5.2% and 2.9%, respectively, for the liquid phantoms, and 2.9% for the solid phantoms. RMS deviation for the reduced scattering coefficient (mus), for the solid phantoms was 15% (475 to 850 nm). For the liquid phantoms, the RMS deviation in average vessel diameter (D) was 1 mu m. In conclusion, the skin microcirculation parameters fRBC and SO2, as well as, mu(s) and D are estimated with reasonable accuracy. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.

  • 38.
    Gesicho, Milka B.
    et al.
    Department of Information Science and Media Studies, University of Bergen, Norway.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Were, Martin C.
    Institute of Biomedical Informatics, Moi University, Kenya.
    Critical Issues in Evaluating National-Level Health Data Warehouses in LMICs: Kenya Case Study2017In: Informatics Empowers Healthcare Transformation / [ed] Househ M.S.,Mantas J.,Hasman A.,Gallos P., 2017, Vol. 238, p. 201-204Conference paper (Refereed)
    Abstract [en]

    Low-Middle-Income-Countries (LMICs) are beginning to adopt national health data warehousing (NHDWs) for making strategic decisions and for improving health outcomes. Given the numerous challenges likely to be faced in establishment of NHDWs by LMICs, it is prudent that evaluations are done in relation to the data warehouses (DWs), in order to identify and mitigate critical issues that arise. When critic issues are not identified, DWs are prone to suboptimal implementation with compromised outcomes. Despite the fact that several publications exist on evaluating DWs, evaluations specific to health data warehouses are scanty, with almost none evaluating NHDWs more so in LMICs. This paper uses a systematic approach guided by an evaluation framework to identify critical issues to be considered in evaluating Kenyas NHDW.

  • 39.
    Gharehbaghi, A.
    et al.
    Malardalen Univ, Sweden.
    Sepehri, Amir A.
    CAPIS Biomed Res and Dept Ctr, Belgium.
    Linden, Maria
    Malardalen Univ, Sweden.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    A Hybrid Machine Learning Method for Detecting Cardiac Ejection Murmurs2018In: EMBEC and NBC 2017, SPRINGER-VERLAG SINGAPORE PTE LTD , 2018, Vol. 65, p. 787-790Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel method for detecting cardiac ejection murmurs from other pathological and physiological heart murmurs in children. The proposed method combines a hybrid model and a time growing neural network for an improved detection even in mild condition. Children with aortic stenosis and pulmonary stenosis comprised the patient category against the reference category containing mitral regurgitation, ventricular septal defect, innocent murmur and normal (no murmur) conditions. In total, 120 referrals to a children University hospital participated to the study after giving their informed consent. Confidence interval of the accuracy, sensitivity and specificity is estimated to be 87.2%-88.8%, 83.4%-86.9% and 88.3%-90.0%, respectively.

  • 40.
    Gharehbaghi, Arash
    et al.
    Malardalen Univ, Sweden.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Univ Bergen, Norway.
    Sepehri, Amir A.
    CAPIS Biomed Res and Dev Ctr, Belgium.
    Extraction of Diagnostic Information from Phonocardiographic Signal Using Time-Growing Neural Network2019In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 3, SPRINGER , 2019, Vol. 68, no 3, p. 849-853Conference paper (Refereed)
    Abstract [en]

    This paper presents an original method for extracting medical information from a heart sound recording, so called Phonocardiographic (PCG) signal. The extracted information is employed by a binary classifier to distinguish between stenosis and regurgitation murmurs. The method is based on using our original neural network, the Time-Growing Neural Network (TGNN), in an innovative way. Children with an obstruction on their semilunar valve are considered as the patient group (PG) against a reference group (RG) of children with a regurgitation in their atrioventricular valve. PCG signals were collected from 55 children, 25/30 from the PG/RG, who referred to the Children Medical Center of Tehran University. The study was conducted according to the guidelines of Good Clinical Practices and the Declaration of Helsinki. Informed consents were obtained for all the patients prior to the data acquisition. The accuracy and sensitivity of the method was estimated to be 85% and 80% respectively, exhibiting a very good performance to be used as a part of decision support system. Such a decision support system can improve the screening accuracy in primary healthcare centers, thanks to the innovative use of TGNN.

  • 41.
    Gharehbaghi, Arash
    et al.
    Department of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
    Sepehri, Amir A.
    CAPIS Biomedical Research and Development Center, Mon, Belgium.
    Lindén, Maria
    Department of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Department of Information Science and Media Studies, University of Bergen, Norway.
    Intelligent Phonocardiography for Screening Ventricular Septal Defect Using Time Growing Neural Network2017In: Informatics Empowers Healthcare Transformation / [ed] Househ M.S.,Mantas J.,Hasman A.,Gallos P., IOS Press, 2017, Vol. 238, p. 108-111Conference paper (Refereed)
    Abstract [en]

    This paper presents results of a study on the applicability of the intelligent phonocardiography in discriminating between Ventricular Spetal Defect (VSD) and regurgitation of the atrioventricular valves. An original machine learning method, based on the Time Growing Neural Network (TGNN), is employed for classifying the phonocardiographic recordings collected from the pediatric referrals to a children hospital. 90 individuals, 30 VSD, 30 with the valvular regurgitation, and 30 healthy subjects, participated in the study after obtaining the informed consents. The accuracy and sensitivity of the approach is estimated to be 86.7% and 83.3%, respectively, showing a good performance to be used as a decision support system.

  • 42.
    Giambini, Hugo
    et al.
    Mayo Clin, MN 55905 USA.
    Hatta, Taku
    Mayo Clin, MN USA.
    Gorny, Krzysztof R.
    Mayo Clin, MN USA.
    Widholm, Per
    Linköping University, Department of Medical and Health Sciences. 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.
    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).
    Adkins, Mark C.
    Mayo Clin, MN USA.
    Zhao, Chunfeng
    Mayo Clin, MN 55905 USA; Mayo Clin, MN USA.
    An, Kai-Nan
    Mayo Clin, MN 55905 USA; Mayo Clin, MN USA.
    INTRAMUSCULAR FAT INFILTRATION EVALUATED BY MAGNETIC RESONANCE IMAGING PREDICTS THE EXTENSIBILITY OF THE SUPRASPINATUS MUSCLE2018In: Muscle and Nerve, ISSN 0148-639X, E-ISSN 1097-4598, Vol. 57, no 1, p. 129-135Article in journal (Refereed)
    Abstract [en]

    Introduction: Rotator cuff (RC) tears result in muscle atrophy and fat infiltration within the RC muscles. An estimation of muscle quality and deformation, or extensibility, is useful in selecting the most appropriate surgical procedure. We determined if noninvasive quantitative assessment of intramuscular fat using MRI could be used to predict extensibility of the supraspinatus muscle. Methods: Seventeen cadaveric shoulders were imaged to assess intramuscular fat infiltration. Extensibility and histological evaluations were then performed. Results: Quantitative fat infiltration positively correlated with histological findings and presented a positive correlation with muscle extensibility (r=0.69; P=0.002). Extensibility was not significantly different between shoulders graded with a higher fat content versus those with low fat when implementing qualitative methods. Discussion: A noninvasive prediction of whole-muscle extensibility may directly guide pre-operative planning to determine if the torn edge could efficiently cover the original footprint while aiding in postoperative evaluation of RC repair.

  • 43.
    Gorgolewski, Krzysztof J.
    et al.
    Department of Psychology, Stanford University, Stanford, California, United States of America.
    Alfaro-Almagro, Fidel
    Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, Oxford, United Kingdom.
    Auer, Tibor
    Department of Psychology, Royal Holloway University of London, Egham, United Kingdom.
    Bellec, Pierre
    Centre de Recherche de l’Institut Universitaire Gériatrique de Montréal, Montreal, Canada, Department of computer science and operations research, Université de Montréal, Montreal, Canada.
    Capotă, Michel
    Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, Oregon, United States of America.
    Chakravarty, M. Mallar
    Douglas Mental Health University Institute, McGill University, Montreal, Canada, Department of Psychiatry McGill University, Montreal, Canada.
    Churchill, Nathan W.
    Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Ontario, Canada.
    Li Cohen, Alexander
    Department of Neurology, Boston Children’s Hospital, Boston, Massachusetts, United States of America.
    Craddock, R. Cameron
    Computational Neuroimaging Lab, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, United States of America, Center for the Developing Brain, Child Mind Institute, New York, New York, United States of America.
    Devenyi, Gabriel A.
    Douglas Mental Health University Institute, McGill University, Montreal, Canada, Department of Psychiatry McGill University, Montreal, Canada.
    Eklund, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Science & Engineering.
    Esteban, Oscar
    Department of Psychology, Stanford University, Stanford, California, United States of America.
    Flandin, Guillaume
    Wellcome Trust Centre for Neuroimaging, London, United Kingdom.
    Ghosh, Satrajit S.
    McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Department of Otolaryngology, Harvard Medical School, Boston, Massachusetts, United States of America.
    Guntupalli, J. Swaroop
    Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.
    Jenkinson, Mark
    Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, Oxford, United Kingdom.
    Keshavan, Anisha
    UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, United States of America.
    Kiar, Gregory
    Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland, United States of America, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
    Liem, Franziskus
    University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
    Reddy Raamana, Pradeep
    Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada, Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
    Raffelt, David
    Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
    Steele, Cristopher J.
    Douglas Mental Health University Institute, McGill University, Montreal, Canada, Department of Psychiatry McGill University, Montreal, Canada.
    Quirion, Pierre-Olivier
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smith, Robert E.
    Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
    Strother, Stephen C.
    Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada, Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
    Varoquaux, Gaël
    Parietal team, INRIA Saclay Ile-de-France, Palaiseau, France.
    Wang, Yida
    Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, Oregon, United States of America.
    Yarkoni, Tal
    Department of Psychology, University of Texas at Austin, Austin, Texas, United States of America.
    Poldrack, Russel A.
    Department of Psychology, Stanford University, Stanford, California, United States of America.
    BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods2017In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 13, no 3, article id e1005209Article in journal (Refereed)
    Abstract [en]

    The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

  • 44.
    Gu, Xuan
    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).
    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).
    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).
    Repeated Tractography of a Single Subject: How High Is the Variance?2017In: Modeling, Analysis, and Visualization of Anisotropy / [ed] Thomas Schultz, Evren Özarslan, Ingrid Hotz, Springer, 2017, p. 331-354Chapter in book (Other academic)
    Abstract [en]

    We have investigated the test-retest reliability of diffusion tractography, using 32 diffusion datasets from a single healthy subject. Preprocessing was carried out using functions in FSL (FMRIB Software Library), and tractography was carried out using FSL and Dipy. The tractography was performed in diffusion space, using two seed masks (corticospinal and cingulum gyrus tracts) created from the JHU White-Matter Tractography atlas. The tractography results were then warped into MNI standard space by a linear transformation. The reproducibility of tract metrics was examined using the standard deviation, the coefficient of variation (CV) and the Dice similarity coefficient (DSC), which all indicated a high reproducibility. Our results show that the multi-fiber model in FSL is able to reveal more connections between brain areas, compared to the single fiber model, and that distortion correction increases the reproducibility.

  • 45.
    Gu, Xuan
    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).
    Sidén, Per
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering.
    Wegmann, Bertil
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. 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).
    Villani, Mattias
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering.
    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).
    Bayesian Diffusion Tensor Estimation with Spatial Priors2017In: CAIP 2017: Computer Analysis of Images and Patterns, 2017, Vol. 10424, p. 372-383Conference paper (Refereed)
    Abstract [en]

    Spatial regularization is a technique that exploits the dependence between nearby regions to locally pool data, with the effect of reducing noise and implicitly smoothing the data. Most of the currently proposed methods are focused on minimizing a cost function, during which the regularization parameter must be tuned in order to find the optimal solution. We propose a fast Markov chain Monte Carlo (MCMC) method for diffusion tensor estimation, for both 2D and 3D priors data. The regularization parameter is jointly with the tensor using MCMC. We compare FA (fractional anisotropy) maps for various b-values using three diffusion tensor estimation methods: least-squares and MCMC with and without spatial priors. Coefficient of variation (CV) is calculated to measure the uncertainty of the FA maps calculated from the MCMC samples, and our results show that the MCMC algorithm with spatial priors provides a denoising effect and reduces the uncertainty of the MCMC samples.

  • 46.
    Göransson, Nathanael
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Johansson, Johannes
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Alonso, Fabiola
    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.
    Zsigmond, Peter
    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.
    Postoperative lead movement after deep brain stimulation surgery and changes of stimulation area2017Conference paper (Other academic)
    Abstract [en]

    Introduction

    Lead movement after deep brain stimulation (DBS) may occur and influence the area of stimulation. The cause of the displacement is not fully understood. The aim of the study was to investigate differences in lead position between the day after surgery and approximately one month postoperatively and also simulate the electric field (EF) around the active contacts.

    Methods

    23 patients with movement disorders underwent DBS surgery (37 leads). CT at the two time points were co-fused respectively with the stereotactic images in Surgiplan. The coordinates (x, y, z) of the lead tips were compared between the two dates (paired t-test). 8 of these patients were selected for the EF simulation in Comsol Multiphysics.

    Results

    There was a significant discrepancy (mean ± s.d.) on the left lead: x (0.44 ± 0.72, p < 0.01), y (0.64 ± 0.54, p < 0.001), z (0.62 ± 0.71, p < 0.001).  On the right lead, corresponding values were: x (-0.11 ± 0.61, n.s.), y (0.71 ± 0.54, p < 0.001), z (0.49 ± 0.81, p < 0.05).  No correlation was found between bilateral (n =14) vs. unilateral DBS, gender (n = 17 male) and age < 60 years (n = 8).  The lead movement affected the EF spread (Fig. 1).

    Conclusion

    The left lead tip displayed a tendency to move lateral, anterior and inferior and the right a tendency to move anterior and inferior. Lead movement after DBS can be a factor to consider before starting the stimulation. The differences in the area of stimulation might affect clinical outcome.

  • 47.
    Haj Hosseini, Neda
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Richter, Johan
    Östergötlands Läns Landsting, Reconstruction Centre, Department of Neurosurgery UHL. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Medicine and Health Sciences.
    Milos, Peter
    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. Neurokirurgi.
    Hallbeck, Martin
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Pathology and Clinical Genetics.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Optical Guidance for Brain Tumor Stereotactic Biopsy2017Conference paper (Refereed)
  • 48.
    Haj-Hosseini, Neda
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Gimm, Oliver
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping.
    Höög, Anders
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Pathology and Clinical Genetics.
    Johansson, Kenth
    Landstinget i Kalmar län och Sahlgrenska universitetssjukhus, Västra Götalandsregion.
    Optiska metoder för identifiering av bisköldkörtel och sköldkörtel2017Conference paper (Refereed)
    Abstract [sv]

    Identifiering av bisköldkörtlar är viktigt vid sköldkörtel- och bisköldkörtelkirurgi och kan vara svårt då de liknar omgivande vävnad såsom fett och lymfkörtlar. Peroperativ detektering av dessa vävnader kan förbättra möjligheten att bota patienter med hyperparathyroidism och minska risken för bisköldkörtelskador vid thyroideakirurgi. Optiska metoder är potentiella tekniker för att möjliggöra detta. Optiska tekniker utvärderades på vävnadsprover från patienter vid bisköldkörtel- och sköldkörteloperation. Teknikerna bestod av nära infraröd fluorescens (NIR) spektroskopi och optisk koherenstomografi (OCT) som ger en bild av vävnadens mikrostruktur liknande till ultraljud med högre upplösning (10 μm).

  • 49.
    Haj-Hosseini, Neda
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Richter, Johan
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Kobayashi Frisk, Lisa
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Milos, Peter
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Hallbeck, Martin
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Fluorescence Guidance for Brain Tumor Biopsies2018Conference paper (Refereed)
    Abstract [en]

    To provide guidance during stereotactic biopsy in brain tumors, fluorescence spectroscopy was used in ten patients. It was shown that the fiber optical probe could provide real-time guidance with clear fluorescence in all patients.

  • 50.
    Haj-Hosseini, Neda
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Richter, Johan
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Milos, Peter
    Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery. Neurokirurgi.
    Hallbeck, Martin
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    5-ALA fluorescence and laser Doppler flowmetry for guidance in a stereotactic brain tumor biopsy2018In: Biomedical Optics Express, E-ISSN 2156-7085, Vol. 9, no 5, p. 2284-2296Article in journal (Refereed)
    Abstract [en]

    A fiber optic probe was developed for guidance during stereotactic brain biopsy procedures to target tumor tissue and reduce the risk of hemorrhage. The probe was connected to a setup for the measurement of 5-aminolevulinic acid (5-ALA) induced fluorescence and microvascular blood flow. Along three stereotactic trajectories, fluorescence (n = 109) and laser Doppler flowmetry (LDF) (n = 144) measurements were done in millimeter increments. The recorded signals were compared to histopathology and radiology images. The median ratio of protoporphyrin IX (PpIX) fluorescence and autofluorescence (AF) in the tumor was considerably higher than the marginal zone (17.3 vs 0.9). The blood flow showed two high spots (3%) in total. The proposed setup allows simultaneous and real-time detection of tumor tissue and microvascular blood flow for tracking the vessels.

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