Your browser doesn't support javascript.
loading
Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study.
Xiao, Xin-Yun; Zeng, Jing-Yi; Cao, Yun-Bin; Tang, Ying; Zou, Zhang-Yu; Li, Jian-Qi; Chen, Hua-Jun.
Afiliação
  • Xiao XY; Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
  • Zeng JY; Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
  • Cao YB; Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
  • Tang Y; Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
  • Zou ZY; Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China.
  • Li JQ; Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
  • Chen HJ; Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
Quant Imaging Med Surg ; 14(8): 5774-5788, 2024 Aug 01.
Article em En | MEDLINE | ID: mdl-39144033
ABSTRACT

Background:

Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity.

Methods:

This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R.

Results:

In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05).

Conclusions:

The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Quant Imaging Med Surg Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Quant Imaging Med Surg Ano de publicação: 2024 Tipo de documento: Article