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MRI-Based Screening of Preclinical Alzheimer's Disease for Prevention Clinical Trials

Identifying healthy individuals with amyloid pathology is an important challenge for Alzheimer's prevention clinical trials. This paper reported on noninvasive, cost-efficient techniques to detect preclinical Alzheimer's to meet this need. Researchers applied machine learning to structural MRI of 96 cognitively normal subjects to identify amyloid-positive ones. Used for subject classification in a simulated clinical trial setting, the proposed method saved 60 percent on unneeded CSF/PET tests and reduced by 47 percent the cost of recruitment. This protocol could foster the development of secondary prevention strategies for Alzheimer's.

Casamitjana A, Petrone P, Tuckolka A, et al. MRI-based screening of preclinical Alzheimer's disease for prevention clinical trials. Journal of Alzheimer's Disease 2018;64(4):1099-1112.

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