Support vector machine model based on gray matter volume for identifying amyotrophic lateral sclerosis and analysis of relevant brain regions
10.13929/j.issn.1003-3289.2025.07.005
- VernacularTitle:基于灰质体积支持向量机模型评估肌萎缩侧索硬化及分析相关脑区
- Author:
Shan WU
1
;
Haining LI
;
Qiuli ZHANG
;
Qianqian DUAN
;
Xinyi YU
;
Xing QIN
;
Fangfang HU
;
Jiaoting JIN
;
Jingxia DANG
;
Ming ZHANG
Author Information
1. 西安交通大学第一附属医院医学影像科,陕西西安 710061
- Publication Type:Journal Article
- Keywords:
amyotrophic lateral sclerosis;
magnetic resonance imaging;
gray matter;
machine learning
- From:
Chinese Journal of Medical Imaging Technology
2025;41(7):1051-1055
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10％was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40％GMV features had the highest classification accuracy(82.50％),with sensitivity,specificity and area under the curve(AUG)of 85.05％,80.40％and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.
