Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to...

Area of Science:

• Neuroimaging
• Biomarkers
• Neurodegenerative Diseases

Background:

• Identifying reliable biomarkers for Alzheimer's Disease (AD) risk assessment is crucial.
• Mild cognitive impairment (MCI) is a prodromal stage for AD, necessitating early detection strategies.

Purpose of the Study:

• To investigate white matter integrity in MCI patients who converted to AD versus those who remained stable.
• To identify specific white matter tracts and diffusion measures predictive of MCI to AD conversion.

Main Methods:

• Diffusion tensor imaging (DTI) and automated fiber quantification were used on 34 MCI-to-AD converters and 53 stable MCI patients.
• Support vector machines (SVMs) analyzed diffusion properties of 20 major white matter tracts to classify conversion risk.

Main Results:

• Diffusivity measures from seven white matter tracts predicted AD conversion, with axial diffusivity being the most significant.
• Specific regions within the right cingulate hippocampal bundle, right inferior frontal occipital fasciculus, and left inferior longitudinal fasciculus were key predictors.
• An SVM model utilizing these regions achieved 75% accuracy in predicting MCI to AD conversion.

Conclusions:

• White matter integrity changes, particularly in specific tracts, serve as potential biomarkers for AD risk in MCI.
• These DTI-based findings offer a promising avenue for early AD detection and risk stratification.