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• W2152035880 abstract "<h3>BACKGROUND AND PURPOSE:</h3> MRA is widely accepted as a noninvasive diagnostic tool for the detection of intracranial aneurysms, but detection is still a challenging task with rather low detection rates. Our aim was to examine the performance of a computer-aided diagnosis algorithm for detecting intracranial aneurysms on MRA in a clinical setting. <h3>MATERIALS AND METHODS:</h3> Aneurysm detectability was evaluated retrospectively in 48 subjects with and without computer-aided diagnosis by 6 readers using a clinical 3D viewing system. Aneurysms ranged from 1.1 to 6.0 mm (mean = 3.12 mm, median = 2.50 mm). We conducted a multireader, multicase, double-crossover design, free-response, observer-performance study on sets of images from different MRA scanners by using DSA as the reference standard. Jackknife alternative free-response operating characteristic curve analysis with the figure of merit was used. <h3>RESULTS:</h3> For all readers combined, the mean figure of merit improved from 0.655 to 0.759, indicating a change in the figure of merit attributable to computer-aided diagnosis of 0.10 (95% CI, 0.03–0.18), which was statistically significant (<i>F</i>_1,47 = 7.00, <i>P</i> = .011). Five of the 6 radiologists had improved performance with computer-aided diagnosis, primarily due to increased sensitivity. <h3>CONCLUSIONS:</h3> In conditions similar to clinical practice, using computer-aided diagnosis significantly improved radiologists9 detection of intracranial DSA-confirmed aneurysms of ≤6 mm." @default.
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• W2152035880 date "2014-06-12" @default.
• W2152035880 modified "2023-10-17" @default.
• W2152035880 title "Computer-Aided Diagnosis Improves Detection of Small Intracranial Aneurysms on MRA in a Clinical Setting" @default.
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• W2152035880 doi "https://doi.org/10.3174/ajnr.a3996" @default.
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