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Serial contrast-enhanced axial images of the forearm in a patient with recurrent myxofibrosarcoma (MFS). Arrows indicate slowly enlarging, ...

indianjurol.com

indian journal of urology-iju is the official publication of the urological society of india (usi).

carenewengland.org

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radiology.wisc.edu

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ajnr.org

BACKGROUND AND PURPOSE: ASPECTS quantifies early ischemic changes in anterior circulation stroke on NCCT but has interrater variability. We examined the agreement of conventional and automated ASPECTS and studied the value of computer-aided detection. MATERIALS AND METHODS: We retrospectively collected imaging data from consecutive patients with acute ischemic stroke with large-vessel occlusion undergoing thrombectomy. Five raters scored conventional ASPECTS on baseline NCCTs, which were also processed by RAPID software. Conventional and automated ASPECTS were compared with a consensus criterion standard. We determined the agreement over the full ASPECTS range as well as dichotomized, reflecting thrombectomy eligibility according to the guidelines (ASPECTS 0–5 versus 6–10). Raters subsequently scored ASPECTS on the same NCCTs with assistance of the automated ASPECTS outputs, and agreement was obtained. RESULTS: For the total of 175 cases, agreement among raters individually and the criterion standard varied from fair to good (weighted κ = between 0.38 and 0.76) and was moderate (weighted κ = 0.59) for the automated ASPECTS. The agreement of all raters individually versus the criterion standard improved with software assistance, as did the interrater agreement (overall Fleiss κ = 0.15–0.23; P < .001 and .39 to .55; P = .01 for the dichotomized ASPECTS). CONCLUSIONS: Automated ASPECTS had agreement with the criterion standard similar to that of conventional ASPECTS. However, including automated ASPECTS during the evaluation of NCCT in acute stroke improved the agreement with the criterion standard and improved interrater agreement, which could, therefore, result in more uniform scoring in clinical practice. CAD : computer-aided detection and diagnosis

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a non-profit foundation dedicated to the research, improved diagnosis and development of successful treatments and outcomes for symptomatic tarlov cysts.