Automated characterisation of cerebral microbleeds using their size and spatial distribution on brain MRI

Sundaresan, Vaanathi; Zamboni, Giovanna; Dineen, Robert A.; Auer, Dorothee P.; Sotiropoulos, Stamatios N.; Sprigg, Nikola; Jenkinson, Mark; Griffanti, Ludovica

Abstract

Cerebral microbleeds (CMBs) are small, hypointense hemosiderin deposits in the brain measuring 2–10 mm in diameter. As one of the important biomarkers of small vessel disease, they have been associated with various neurodegenerative and cerebrovascular diseases. Hence, automated detection, and subsequent extraction of clinically useful metrics (e.g., size and spatial distribution) from CMBs are essential for investigating their clinical impact, especially in large-scale studies. While some work has been done for CMB segmentation, extraction of clinically relevant information is not yet explored. Herein, we propose the first automated method to characterise CMBs using their size and spatial distribution, i.e., CMB count in three regions (and their substructures) used in Microbleed Anatomical Rating Scale (MARS): infratentorial, deep, and lobar. Our method uses structural atlases of the brain for determining individual regions. On an intracerebral haemorrhage study dataset, we achieved a mean absolute error of 2.5 mm for size estimation and an overall accuracy > 90% for automated rating. The code and the atlas of MARS regions in Montreal Neurological Institute—MNI space are publicly available. Relevance statement: Our method to automatically characterise cerebral microbleeds (size and location) showed a mean absolute error of 2.5 mm for size estimation and an over 90% accuracy for rating of infratentorial, deep and lobar regions. This is a promising approach to automatically provide clinically relevant cerebral microbleeds metrics. Key Points: We present a method to automatically characterise cerebral microbleeds according to size and location. The method achieved a mean absolute error of 2.5 mm for size estimation. Automated rating for infratentorial, deep, and lobar regions achieved an over 90% overall accuracy. We made the code and atlas of Microbleed Anatomical Rating Scale regions publicly available.

Citation

Sundaresan, V., Zamboni, G., Dineen, R. A., Auer, D. P., Sotiropoulos, S. N., Sprigg, N., Jenkinson, M., & Griffanti, L. (2025). Automated characterisation of cerebral microbleeds using their size and spatial distribution on brain MRI. European Radiology Experimental, 9(1), Article 5. https://doi.org/10.1186/s41747-024-00544-z

• Journal Article Type: Article
• Acceptance Date: Dec 13, 2024
• Online Publication Date: Jan 13, 2025
• Publication Date: Dec 1, 2025
• Deposit Date: Mar 3, 2025
• Publicly Available Date: Mar 19, 2025
• Journal: European Radiology Experimental
• Electronic ISSN: 2509-9280
• Publisher: SpringerOpen
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Issue: 1
• Article Number: 5
• DOI: https://doi.org/10.1186/s41747-024-00544-z
• Public URL: https://nottingham-repository.worktribe.com/output/45863342
• Publisher URL: https://eurradiolexp.springeropen.com/articles/10.1186/s41747-024-00544-z