TY - JOUR T1 - Computer-Aided Diagnosis Improves Detection of Small Intracranial Aneurysms on MRA in a Clinical Setting JF - American Journal of Neuroradiology JO - Am. J. Neuroradiol. DO - 10.3174/ajnr.A3996 AU - I.L. Štep̌án-Buksakowska AU - J.M. Accurso AU - F.E. Diehn AU - J. Huston AU - T.J. Kaufmann AU - P.H. Luetmer AU - C.P. Wood AU - X. Yang AU - D.J. Blezek AU - R. Carter AU - C. Hagen AU - D. Hořínek AU - A. Hejčl AU - M. Roček AU - B.J. Erickson Y1 - 2014/06/12 UR - http://www.ajnr.org/content/early/2014/06/12/ajnr.A3996.abstract N2 - BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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 (F1,47 = 7.00, P = .011). Five of the 6 radiologists had improved performance with computer-aided diagnosis, primarily due to increased sensitivity. CONCLUSIONS: In conditions similar to clinical practice, using computer-aided diagnosis significantly improved radiologists' detection of intracranial DSA-confirmed aneurysms of ≤6 mm. Abbreviations CADcomputer-aided diagnosisFOMfigure of merit ER -