Integrated cerebellar radiomic‐network model for predicting mild cognitive impairment in Alzheimer's disease

Altered cerebellar radiomic features and topological networks were identified in the subjects with mild cognitive impairment (MCI). The cerebellar radiomic-network integrated models outperformed hippocampal models in distinguishing MCI from normal cognition. The cerebellar radiomic model effectively predicts MCI risk and can stratify individuals into distinct risk categories. Specific cerebellar radiomic features are associated with cognitive impairment across various stages of amyloid beta and tau pathology.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2024-11-13
DOI
https://doi.org/10.1002/alz.14361
Citations
18
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
7.28

Funders

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article

Integrated cerebellar radiomic‐network model for predicting mild cognitive impairment in Alzheimer's disease

Weidong Le, Tao Qiu, Tianbai Li, Qiqi Jia et al.
18 citations
Alzheimer s & Dementia
Radiomics and Machine Learning in Medical Imaging
7.28
article

Integrated cerebellar radiomic‐network model for predicting mild cognitive impairment in Alzheimer's disease

Weidong Le, Tao Qiu, Tianbai Li, Qiqi Jia, Yini Chen, Yiying Hu, Cong Liu, Song Li, Meichen Liu, Xinhui Qiu, Yiwei Qi, Bo Sun
article en
18 citations

Abstract

Altered cerebellar radiomic features and topological networks were identified in the subjects with mild cognitive impairment (MCI). The cerebellar radiomic-network integrated models outperformed hippocampal models in distinguishing MCI from normal cognition. The cerebellar radiomic model effectively predicts MCI risk and can stratify individuals into distinct risk categories. Specific cerebellar radiomic features are associated with cognitive impairment across various stages of amyloid beta and tau pathology.

Alzheimer s & DementiaVol. 21(1)
Dalian Medical University (CN), Chinese Academy of Sciences (CN), Shanghai Institute of Organic Chemistry (CN), Shanghai University of Medicine and Health Sciences (CN), First Affiliated Hospital of Dalian Medical University (CN)
U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Alzheimer's Drug Discovery Foundation, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, AbbVie, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Takeda Pharmaceutical Company, Northern California Institute for Research and Education, National Natural Science Foundation of China, Fudan University, Eisai, Natural Science Foundation of Liaoning Province, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, GE Healthcare, Canadian Institutes of Health Research, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering
Quality Education
Openalex Percentile: Top 2%
Radiomics and Machine Learning in Medical Imaging
7.28
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