Comparison of 1.5 T and 3 T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software.
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 Pharmaceutic...
| Publicado en: | Neuroradiology Vol. 65; no. 10; pp. 1473 - 1483 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=171898852&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 171898852 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Oct2023 vid: 65 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 171898852 171100623 171898852 171898852 10.1007/s00234-023-03216-8 171898852 ppf: 1473 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Comparison of 1.5 T and 3 T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software. aug: au: Tajima, Taku Akai, Hiroyuki Yasaka, Koichiro Kunimatsu, Akira Yoshioka, Naoki Akahane, Masaaki Ohtomo, Kuni Abe, Osamu Kiryu, Shigeru affil: Department of Radiology, International University of Health and Welfare Mita Hospital, 1-4-3 Mita, Minato-Ku, 108-8329, Tokyo, Japan sug: subj: Magnetic Resonance Angiography Equipment and Supplies Cerebral Aneurysm Diagnosis Deep Learning False Positive Results Human Retrospective Design Pearson's Correlation Coefficient Fisher's Exact Test Mann-Whitney U Test Male Female Descriptive Statistics Middle Age Aged Aged, 80 and Over Funding Source Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: 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 χ2 test, Fisher's exact test, and the Mann‒Whitney U test were used for the statistical analyses as appropriate. 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. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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