Different patterns of structural network impairments in two amyotrophic lateral sclerosis subtypes driven by 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging

Author:

Feng Feng12,Feng Guozheng345,Liu Jiajin6,Hao Weijun7,Huang Weijie345ORCID,Bi Xiao6,Li Mao1,Wang Hongfen1,Yang Fei1,He Zhengqing1,Bai Jiongming1,Wang Haoran1,Ma Guolin8,Xu Baixuan6,Shu Ni345,Huang Xusheng1

Affiliation:

1. Department of Neurology, First Medical Center, Chinese PLA General Hospital , Beijing 100853 , China

2. Department of Neurology, PLA Rocket Force Characteristic Medical Center , Beijing 100088 , China

3. State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing 100875 , China

4. Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University , Beijing 100875 , China

5. Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University , Beijing 100875 , China

6. Department of Nuclear Medicine, First Medical Center, Chinese PLA General Hospital , Beijing 100853 , China

7. Health Service Department of the Guard Bureau, The Joint Staff Department , Beijing 100017 , China

8. Department of Radiology, China-Japan Friendship Hospital , Beijing 100029 , China

Abstract

Abstract The structural network damages in amyotrophic lateral sclerosis patients are evident but contradictory due to the high heterogeneity of the disease. We hypothesized that patterns of structural network impairments would be different in amyotrophic lateral sclerosis subtypes by a data-driven method using 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging. The data of positron emission tomography, structural MRI and diffusion tensor imaging in fifty patients with amyotrophic lateral sclerosis and 23 healthy controls were collected by a 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid. Two amyotrophic lateral sclerosis subtypes were identified as the optimal cluster based on grey matter volume and standardized uptake value ratio. Network metrics at the global, local and connection levels were compared to explore the impaired patterns of structural networks in the identified subtypes. Compared with healthy controls, the two amyotrophic lateral sclerosis subtypes displayed a pattern of a locally impaired structural network centralized in the sensorimotor network and a pattern of an extensively impaired structural network in the whole brain. When comparing the two amyotrophic lateral sclerosis subgroups by a support vector machine classifier based on the decreases in nodal efficiency of structural network, the individualized network scores were obtained in every amyotrophic lateral sclerosis patient and demonstrated a positive correlation with disease severity. We clustered two amyotrophic lateral sclerosis subtypes by a data-driven method, which encompassed different patterns of structural network impairments. Our results imply that amyotrophic lateral sclerosis may possess the intrinsic damaged pattern of white matter network and thus provide a latent direction for stratification in clinical research.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

State Key Laboratory of Cognitive Neuroscience and Learning

Publisher

Oxford University Press (OUP)

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