Article ; Online: Comparison of 1.5 T and 3 T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software.
2023 Volume 65, Issue 10, Page(s) 1473–1482
Abstract: Purpose: To compare the diagnostic performance of 1.5 T versus 3 T magnetic resonance angiography ... T and 3 T in 45 patients each) in clinical practice. Overall, 51 patients had 70 aneurysms. We used ... were compared between 1.5 T and 3 T MRA. Pearson's χ: Results: The sensitivity was high for 1.5 T ...
Abstract | Purpose: To compare the diagnostic performance of 1.5 T versus 3 T 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. Methods: In this single-center, retrospective study, we evaluated the MRA scans of 90 patients who underwent head MRA (1.5 T and 3 T 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 1.5 T and 3 T MRA. Pearson's χ Results: The sensitivity was high for 1.5 T and 3 T MRA (0.875‒1), but the number of FPs/case was significantly higher with 3 T 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 1.5 T and 3 T MRA. Conclusion: EIRL_an detected significantly more false-positive lesions with 3 T than with 1.5 T MRA in this external validation study. Our data may help physicians with limited experience with MRA to correctly diagnose aneurysms using EIRL_an. |
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MeSH term(s) | Humans ; Intracranial Aneurysm/diagnostic imaging ; Magnetic Resonance Angiography ; Deep Learning ; Retrospective Studies ; Software ; Computers |
Language | English |
Publishing date | 2023-08-30 |
Publishing country | Germany |
Document type | Journal Article |
ZDB-ID | 123305-1 |
ISSN | 1432-1920 ; 0028-3940 |
ISSN (online) | 1432-1920 |
ISSN | 0028-3940 |
DOI | 10.1007/s00234-023-03216-8 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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