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DOI 10.1109/tbme.2025.3539498

Медицинская библиотека · IEEE transactions on bio-medical engineering · 2025

Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations.

Zong Ruige, Wang Tao, Li Chunwang, Zhang Xinlin, Chen Yuanbin, Zhao Longxuan, Li Qixuan, Gao Qinquan, Kang Dezhi, Lin Fuxin, Tong Tong

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Familial cerebral cavernous malformation (FCCM) is a hereditary disorder characterized by abnormal vascular structures within the central nervous system. The FCCM lesions are often numerous and intricate, making quantitative analysis of the lesions a labor-intensive task. Consequently, clinicians face challenges in quantitatively assessing the severity of lesions and determining whether lesions have progressed. To alleviate this problem, we propose a quantitative statistical framework for FCCM, which comprises an efficient annotation module, an FCCM lesion segmentation module, and an FCCM lesion quantitative statistics module. Our framework demonstrates precise segmentation of the FCCM lesion based on efficient data annotation, achieving a Dice coefficient of 91.09%. More importantly, we focus on 3D quantitative statistics of lesions, which is combined with image registration to realize the quantitative comparison of lesions between different examinations of patients. A visualization framework has also been established for doctors to comprehensively compare and analyze lesions. The experimental results have demonstrated that our proposed framework not only obtains objective, accurate, and comprehensive quantitative statistical information, which provides a quantitative assessment method for disease progression and drug efficacy study, but also considerably reduces the manual measurement and statistical workload of lesions. This highlights the potential of practical application of the framework in FCCM clinical research and clinical decision-making.

Для цитирования: Zong Ruige, Wang Tao, Li Chunwang, Zhang Xinlin, Chen Yuanbin, Zhao Longxuan, Li Qixuan, Gao Qinquan, Kang Dezhi, Lin Fuxin, Tong Tong. Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations.. IEEE transactions on bio-medical engineering. 2025. DOI: 10.1109/tbme.2025.3539498.

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