Comparison of 1.5T and 3T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software.

Abstract

To compare the diagnostic performance of 1.5T versus 3T magnetic resonance angiography (MRA) for detecting cerebral aneurysms with clinically available deep learning-based computer-assisted detection software (EIRL aneurysm® [EIRL_an]), which has been approved by the Japanese Pharmaceuticals and Medical Devices Agency. We also sought to analyze the causes of potential false positives. In this single-center, retrospective study, we evaluated the MRA scans of 90 patients who underwent head MRA (1.5T and 3T in 45 patients each) in clinical practice. Overall, 51 patients had 70 aneurysms. We used MRI from a vendor not included in the dataset used to create the EIRL_an algorithm. Two radiologists determined the ground truth, the accuracy of the candidates noted by EIRL_an, and the causes of false positives. The sensitivity, number of false positives per case (FPs/case), and the causes of false positives were compared between 1.5T and 3T MRA. Pearson's χ2 test, Fisher's exact test, and the Mann‒Whitney U test were used for the statistical analyses as appropriate. The sensitivity was high for 1.5T and 3T MRA (0.875‒1), but the number of FPs/case was significantly higher with 3T MRA (1.511 vs. 2.578, p < 0.001). The most common causes of false positives (descending order) were the origin/bifurcation of vessels/branches, flow-related artifacts, and atherosclerosis and were similar between 1.5T and 3T MRA. EIRL_an detected significantly more false-positive lesions with 3T than with 1.5T MRA in this external validation study. Our data may help physicians with limited experience with MRA to correctly diagnose aneurysms using EIRL_an.