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  • 1.
    Kalra, Mannudeep K.
    et al.
    Department of Radiology, Massachusetts General Hospital, Boston, USA .
    Woisetschläger, Mischa
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Dahlström, Nils
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Sing, Sarabjeet
    Department of Radiology, Massachusetts General Hospital, Boston, USA .
    Lindblom, Maria
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Choy, Garry
    Department of Radiology, Massachusetts General Hospital, Boston, USA .
    Quick, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Schmidt, Bernhard
    Siemens Healthcare, Forchheim, Germany.
    Sedlmair, Martin
    Siemens Healthcare, Forchheim, Germany.
    Blake, Michail A.
    Radiology, Massachusetts General Hospital, Boston, USA.
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Radiation Dose Reduction with Sinogram Affirmed Iterative Reconstruction Technique for abdominal Computer Tomography2012In: Journal of Computer Assisted Tomography, ISSN 0363-8715, Vol. 36, no 3, p. 339-346Article in journal (Refereed)
    Abstract [en]

    Purpose: The objective of this study was to assess the effect of Sinogram Affirmed Iterative Reconstruction (SAFIRE) and filtered back-projection (FBP) techniques on abdominal computed tomography (CT) performed with 50% and 75% radiation dose reductions.

    Methods: Twenty-four patients (mean age, 64 ± 14 years; male-female ratio, 10:14) gave informed consent for an institutional review board–approved prospective study involving acquisition of additional research images through the abdomen on 128-slice multi–detector-row CT (SOMATOM Definition Flash) at quality reference mAs of 100 (50% lower dose) and 50 (75% lower dose) over a scan length of 10 cm using combined modulation (CARE Dose 4D). Standard-of-care abdominal CT was performed at 200 quality reference mAs, with remaining parameters held constant. The 50- and 100-mAs data sets were reconstructed with FBP and at 4 SAFIRE settings (S1, S2, S3, S4). Higher number of SAFIRE settings denotes increased strength of the algorithm resulting in lower image noise. Two abdominal radiologists independently compared the FBP and SAFIRE images for lesion number, location, size and conspicuity, and visibility of small structures, image noise, and diagnostic confidence. Objective noise and Hounsfield units (HU) were measured in the liver and the descending aorta.

    Results: All 43 lesions were detected on both FBP and SAFIRE images. Minor blocky, pixelated appearance of 50% and 75% reduced dose images was noted at S3 and S4 SAFIRE but not at S1 and S2 settings. Subjective noise was suboptimal in both 50% and 75% lower-dose FBP images but was deemed acceptable on all SAFIRE settings. Sinogram Affirmed Iterative Reconstruction images were deemed acceptable in all patients at 50% lower dose and in 22 of 24 patients at 75% lower dose. As compared with 75% reduced dose FBP, objective noise was lower by 22.8% (22.9/29.7), 35% (19.3/29.7), 44.3% (16.7/29.3), and 54.8% (13.4/29.7) on S1 to S4 settings, respectively (P < 0.001).

    Conclusions: Sinogram Affirmed Iterative Reconstruction–enabled reconstruction provides abdominal CT images without loss in diagnostic value at 50% reduced dose and in some patients also at 75% reduced dose.

  • 2.
    Persson, Anders
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Lindblom, Maria
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Jackowski, Christian
    Institute of Legal Medicine, University of Zürich, Schweiz.
    A state-of-the-art pipeline for postmortem CT and MRI visualization: from data acquisition to interactive image interpretation at autopsy2011In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 52, no 5, p. 522-536Article, review/survey (Refereed)
    Abstract [en]

    The importance of autopsy procedures leading to the establishment of the cause of death is well-known. A recent addition to the autopsy work flow is the possibility of conducting postmortem imaging, in its 3D version also called virtual autopsy (VA), using multidetector computed tomography (MDCT) or magnetic resonance imagining (MRI) data from scans of cadavers displayed with direct volume rendering (DVR) 3D techniques. The use of the data and their workflow are presented. Data acquisition was performed and high quality data-sets with submillimeter precision were acquired. New data acquisition techniques such as dualenergy CT (DECT) and quantitative MRI, then were implemented and provided additional information. Particular findings hardly visualized in conventional autopsy can rather easy be seen at the full body CT, such as air distribution, e.g. pneumothorax, pneumopericardium, air embolism, and wound channels. MRI shows natural deaths such as myocardial infarctions. Interactive visualization of these 3D data-sets can provide valuable insight into the corpses and enables non-invasive diagnostic procedures. In postmortem CT imaging, not being limited by a patient depending radiation dose limit the data-sets can, however, be generated with such a high resolution that they become difficult to handle in today’s archive retrieval and interactive visualization systems, specifically in the case of full body scans. To take full advantage of these new technologies the postmortem workflow needs to be tailored to the demands and opportunities that the new technologies allow.

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