Radiology
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Purpose To evaluate the diagnostic accuracy and reliability of computed tomographic (CT) angiography to distinguish true cervical internal carotid artery (ICA) occlusion from pseudo-occlusion (defined as an isolated intracranial thrombus that impedes ascending blood flow) in the context of acute stroke. Materials and Methods This was a retrospective study of patients who underwent thrombectomy with preprocedural CT angiography that helps to demonstrate a lack of attenuation in the cervical ICA on the symptomatic side (24 men and 13 women; mean age, 63 years; age range, 30-86 years). Seven readers, including five neuroradiologists and two interventional neuroradiology fellows, independently reviewed the CT angiography images to assess whether there was true cervical ICA occlusion. ⋯ Interobserver agreement coefficients did not reach the substantial value of 0.61 for either pairs or groups of readers. The cohort's average sensitivity and specificity was 68% (95% confidence interval [CI]: 59%, 76%) and 75% (95% CI: 71%, 80%), respectively, with a diagnostic odds ratio of 8 (95% CI: 3, 18) and only fair interobserver agreement (κ = 0.32; 95% CI: 0.16, 0.47). Conclusion In the context of acute ischemic stroke with ipsilateral ICA nonattenuation at single-phase CT angiography, even specialized radiologists may not reliably distinguish true cervical occlusion from pseudo-occlusion. © RSNA, 2017 Online supplemental material is available for this article.
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Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic resonance (MR) imaging-based attenuation correction (AC) (termed deep MRAC) in brain positron emission tomography (PET)/MR imaging. Materials and Methods A PET/MR imaging AC pipeline was built by using a deep learning approach to generate pseudo computed tomographic (CT) scans from MR images. A deep convolutional auto-encoder network was trained to identify air, bone, and soft tissue in volumetric head MR images coregistered to CT data for training. ⋯ Significantly lower PET reconstruction errors were realized with deep MRAC (-0.7% ± 1.1) compared with Dixon-based soft-tissue and air segmentation (-5.8% ± 3.1) and anatomic CT-based template registration (-4.8% ± 2.2). Conclusion The authors developed an automated approach that allows generation of discrete-valued pseudo CT scans (soft tissue, bone, and air) from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging. This deep learning approach for MR imaging-based AC provided reduced PET reconstruction error relative to a CT-based standard within the brain compared with current MR imaging-based AC approaches. © RSNA, 2017 Online supplemental material is available for this article.
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Purpose To assess the incidence of costal cartilage (CC) fractures in whole-body computed tomographic (CT) examinations for blunt trauma and to evaluate distribution of CC fractures, concomitant injuries, mechanism of injury, accuracy of reporting, and the effect on 30-day mortality. Materials and Methods Institutional review board approval was obtained for this retrospective study. All whole-body CT examinations for blunt trauma over 36 months were reviewed retrospectively and chest trauma CT studies were evaluated by a second reader. ⋯ The 30-day mortality of patients with CC fractures was 7.02% (eight of 114) versus 4.78% (22 of 460) of other patients with chest trauma (OR, 1.50; 95% CI: 0.65, 3.47; P = .3371). Conclusion CC fractures are common in high-energy blunt chest trauma and often occur with multiple consecutive rib fractures. Aortic and hepatic injuries were more common in patients with CC fractures than in patients without CC fractures. © RSNA, 2017.
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Purpose To determine the diagnostic performance of dual-energy computed tomography (CT) for detection of bone marrow (BM) infiltration in patients with multiple myeloma by using a virtual noncalcium (VNCa) technique. Materials and Methods In this prospective study, 34 consecutive patients with multiple myeloma or monoclonal gammopathy of unknown significance sequentially underwent dual-energy CT and magnetic resonance (MR) imaging of the axial skeleton. Two independent readers visually evaluated standard CT and color-coded VNCa images for the presence of BM involvement. ⋯ Receiver operating characteristic analysis revealed an area under the curve of 0.978. A cutoff of -44.9 HU provided a sensitivity of 93.3% (70 of 75), specificity of 92.4% (157 of 170), accuracy of 92.7% (227 of 245), positive predictive value of 84.3% (70 of 83), and negative predictive value of 96.9% (157 of 162) for the detection of BM infiltration. Conclusion Visual and ROI-based analyses of dual-energy VNCa images had excellent diagnostic performance for assessing BM infiltration in patients with multiple myeloma with precision comparable to that of MR imaging. © RSNA, 2017 Online supplemental material is available for this article.
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Purpose To determine which computed tomography (CT) findings or combinations of findings can help to accurately identify strangulation in adhesive small bowel obstruction (SBO). Materials and Methods Contrast agent-enhanced CT findings in a cohort of 256 patients consecutively admitted for adhesive SBO, with a delay of less than 24 hours between CT and surgery for the operated patients, were reviewed independently by two radiologists, with consensus by a third, to assess CT findings commonly associated with strangulation. The reference standard for strangulation was surgery. ⋯ Positive likelihood ratios were high when two or three of these CT findings were combined (positive likelihood ratios, 14.7 [95% CI: 7.1, 30.4] and 43.8 (95% CI: 14.2, 135.2], respectively). Among the strangulated cases, reduced bowel wall enhancement (odds ratio, 3.9; 95% CI: 1.3, 12) and mesenteric fluid (odds ratio, 3.6; 95% CI: 1.0, 12.8) were predictive of resection. Conclusion A score that combines three CT findings (reduced bowel wall enhancement, a closed-loop mechanism, and diffuse mesenteric haziness) can accurately predict strangulation in adhesive SBO. © RSNA, 2017 Online supplemental material is available for this article.