Radiology
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Randomized Controlled Trial Multicenter Study
Prevalence of Carotid Web in Patients with Acute Intracranial Stroke Due to Intracranial Large Vessel Occlusion.
Purpose To investigate the prevalence of symptomatic carotid web in patients with acute ischemic stroke due to intracranial large vessel occlusion, to determine the clinical and imaging profile of patients with carotid web as well as their association with ischemic stroke, and to determine the interobserver agreement in the assessment of carotid webs. Materials and Methods All patients (n = 500) of the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) in whom the carotid bifurcation could be assessed (n = 443) were included. The presence of a carotid web at the carotid bifurcations was evaluated at computed tomographic (CT) angiography. ⋯ Fair to good interobserver agreement (κ, 0.72) was observed for diagnosing carotid webs at CT angiography. Conclusion Carotid webs at the symptomatic carotid bifurcation were observed in 2.5% of the patients with acute ischemic stroke due to large vessel occlusion and were mostly diagnosed in female patients with a fair to good interobserver agreement. © RSNA, 2017 Clinical trial registration nos. NTR1804 and ISRCTN10888758 Online supplemental material is available for this article.
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Purpose To evaluate whether arterial input functions (AIFs) derived from dynamic susceptibility-contrast (DSC) magnetic resonance (MR) imaging, or AIFDSC values, improve diagnostic accuracy and reliability of the pharmacokinetic (PK) parameters of dynamic contrast material-enhanced (DCE) MR imaging for differentiating high-grade from low-grade astrocytomas, compared with AIFs obtained from DCE MR imaging (AIFDCE). Materials and Methods This retrospective study included 226 patients (138 men, 88 women; mean age, 52.27 years ± 15.17; range, 24-84 years) with pathologically confirmed astrocytomas (World Health Organization grade II = 21, III = 53, IV = 152; isocitrate dehydrogenase mutant, 11.95% [27 of 226]; 1p19q codeletion 0% [0 of 226]). All patients underwent both DSC and DCE MR imaging before surgery, and AIFDSC and AIFDCE were obtained from each image. ⋯ All three parameters had better ICCs with AIFDSC than with AIFDCE (Ktrans, 0.737 vs 0.095; vp, 0.848 vs 0.728; ve, 0.875 vs 0.581, respectively). In AIF analysis, maximal signal intensity (0.837 vs 0.524) and wash-in slope (0.800 vs 0.432) demonstrated better ICCs with AIFDSC than AIFDCE. Conclusion AIFDSC-driven DCE MR imaging PK parameters showed better diagnostic accuracy and reliability for differentiating high-grade from low-grade astrocytoma than those derived from AIFDCE. © RSNA, 2017 Online supplemental material is available for this article.
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Purpose To compare the diagnostic yield and complication rates of electromagnetic navigational bronchoscopic (ENB)-guided and computed tomography (CT)-guided percutaneous tissue sampling of lung nodules. Materials and Methods Retrospectively identified were 149 patients sampled percutaneously with CT guidance and 146 patients who underwent ENB with transbronchial biopsy of a lung lesion between 2013 and 2015. Clinical data, incidence of complications, and nodule pathologic analyses were assessed through electronic medical record review. ⋯ Similar yield for molecular analyses was noted with the two approaches (ENB-guided sampling, 88.9% [32 of 36]; CT-guided sampling, 82.0% [41 of 50]). The two groups had similar rates of major complications (symptomatic hemorrhage, P > .999; pneumothorax requiring chest tube and/or admission, P = .417). Conclusion CT-guided transthoracic biopsy provided higher diagnostic yield in the assessment of peripheral pulmonary nodules than navigational bronchoscopy with a similar rate of clinically relevant complications. © RSNA, 2017 Online supplemental material is available for this article.
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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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The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. ⋯ Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.