RT Journal Article SR Electronic T1 Deep Learning–Based Software Improves Clinicians' Detection Sensitivity of Aneurysms on Brain TOF-MRA JF American Journal of Neuroradiology JO Am. J. Neuroradiol. FD American Society of Neuroradiology SP 1769 OP 1775 DO 10.3174/ajnr.A7242 VO 42 IS 10 A1 B. Sohn A1 K.-Y. Park A1 J. Choi A1 J.H. Koo A1 K. Han A1 B. Joo A1 S.Y. Won A1 J. Cha A1 H.S. Choi A1 S.-K. Lee YR 2021 UL http://www.ajnr.org/content/42/10/1769.abstract AB BACKGROUND AND PURPOSE: The detection of cerebral aneurysms on MRA is a challenging task. Recent studies have used deep learning–based software for automated detection of aneurysms on MRA and have reported high performance. The purpose of this study was to evaluate the incremental value of using deep learning–based software for the detection of aneurysms on MRA by 2 radiologists, a neurosurgeon, and a neurologist.MATERIALS AND METHODS: TOF-MRA examinations of intracranial aneurysms were retrospectively extracted. Four physicians interpreted the MRA blindly. After a washout period, they interpreted MRA again using the software. Sensitivity and specificity per patient, sensitivity per lesion, and the number of false-positives per case were measured. Diagnostic performances, including subgroup analysis of lesions, were compared. Logistic regression with a generalized estimating equation was used.RESULTS: A total of 332 patients were evaluated; 135 patients had positive findings with 169 lesions. With software assistance, patient-based sensitivity was statistically improved after the washout period (73.5% versus 86.5%, P < .001). The neurosurgeon and neurologist showed a significant increase in patient-based sensitivity with software assistance (74.8% versus 85.2%, P = .03, and 56.3% versus 84.4%, P < .001, respectively), while the number of false-positive cases did not increase significantly (23 versus 30, P = .20, and 22 versus 24, P = .75, respectively).CONCLUSIONS: Software-aided reading showed significant incremental value in the sensitivity of clinicians in the detection of aneurysms on MRA without a significant increase in false-positive findings, especially for the neurosurgeon and neurologist. Software-aided reading showed equivocal value for the radiologist.ACAanterior cerebral arteryCADcomputer-assisted detection