Abstract
Objectives
Time of flight magnetic resonance angiography (TOF-MRA) is the primary non-invasive screening method for cerebral aneurysms. We aimed to develop a computer-aided aneurysm detection method to improve the diagnostic efficiency and accuracy, especially decrease the false positive rate.
Methods
This is a retrospective multicenter study. The dataset contained 1160 TOF-MRA examinations composed of unruptured aneurysms (n = 1096) and normal controls (n = 166) from six hospitals. A total of 1037 examinations acquired from 2013 to 2019 were used as training set; 123 examinations acquired from 2020 to 2021 were used as external test set. We proposed an equalized augmentation strategy based on aneurysm location and constructed a detection model based on dual channel SE-3D UNet. The model was trained with a 5-fold cross-validation in the training set, then tested on the external test set.
Results
The proposed method achieved 82.46% sensitivity on patient-level, 73.85% sensitivity on lesion-level, and 0.88 false positives per case in the external test set. The performance did not show significant differences in subgroups according to the aneurysm site (except ACA), aneurysm size (except smaller than 3 mm), or MRI scanners. The performance preceded the basic SE-3D UNet by increasing 15.79% patient-level sensitivity and decreasing 4.19 FPs/case.
Conclusions
The proposed automated aneurysm detection method achieved acceptable sensitivity while controlling fairly low false positives per case. It might provide a useful auxiliary tool of cerebral aneurysms MRA screening.
Key Points
• The need for automated cerebral aneurysms detecting is growing.
• The strategy of equalized augmentation based on aneurysm location and dual-channel input could improve the model performance.
• The retrospective multi-center study showed that the proposed automated cerebral aneurysms detection using dual-channel SE-3D UNet could achieve acceptable sensitivity while controlling a low false positive rate.
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Abbreviations
- ACA:
-
Anterior cerebral artery
- AchA:
-
Anterior choroidal artery
- Acom:
-
Anterior communicating artery
- BA:
-
Basilar artery
- DSA:
-
Digital subtraction angiography
- FP:
-
False positive
- FROC:
-
Free-response receiver operating characteristics
- GPU:
-
Graphic processing unit
- ICA:
-
Internal carotid artery
- MCA:
-
Middle cerebral artery
- PCA:
-
Posterior cerebral artery
- Pcom:
-
Posterior communicating artery
- TOF-MRA:
-
Time-of-flight magnetic resonance angiography
- VA:
-
Vertebral artery
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Funding
This work was supported by National Natural Science Foundation of China [81971685], Jiangsu Natural Science Foundation [BK20180221], Science and Technology Commission of Shanghai Municipality [19411951200], Suzhou Science and Technology Development Project [SS202054, SS202072], Suzhou Health Science & Technology Project [GWZX201904], Youth Innovation Promotion Association CAS [2021324], and Shandong Natural Science Foundation [ZR2022QF093].
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The scientific guarantor of this publication is Yuxin Li.
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The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Informed consent
The informed consents were waived since all of TOF-MRA images were acquired from routine clinical work.
Ethical approval
The ethics board of our institution comprehensively reviewed and approved the protocol of this retrospective study.
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• retrospective
• diagnostic or prognostic study
• multicenter study
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Chen, G., Yifang, B., Jiajun, Z. et al. Automated unruptured cerebral aneurysms detection in TOF MR angiography images using dual-channel SE-3D UNet: a multi-center research. Eur Radiol 33, 3532–3543 (2023). https://doi.org/10.1007/s00330-022-09385-z
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DOI: https://doi.org/10.1007/s00330-022-09385-z