Innovative Quantitative Analysis for Disease Progression Assessment in
  Familial Cerebral Cavernous Malformations
Ruige Zong Tao Wang Chunwang Li Xinlin Zhang Yuanbin Chen Longxuan Zhao Qixuan Li Qinquan Gao Dezhi Kang Fuxin Lin Tong Tong
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, comprising 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
93.22\%. More importantly, we focus on quantitative statistics of lesions,
which is combined with image registration to realize the quantitative
comparison of lesions between different examinations of patients, and a
visualization framework has 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, assisting
clinical decision-making for FCCM and accelerating progress in FCCM clinical
research. This highlights the potential of practical application of the
framework in FCCM clinical research and clinical decision-making. The codes are
available at https://github.com/6zrg/Quantitative-Statistics-of-FCCM.