Biomarkers.

Area of Science:

• Neuroimaging
• Neurodegenerative Diseases
• Biomarker Discovery

Background:

• Frontotemporal Dementia (FTD) is a group of neurodegenerative disorders affecting frontal and temporal lobes.
• Key subtypes include behavioral variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA), and non-fluent variant primary progressive aphasia (nfvPPA).
• Accurate diagnosis and progression monitoring are crucial for developing effective therapies.

Purpose of the Study:

• To identify sensitive imaging biomarkers for differentiating FTD subtypes.
• To optimize clinical trial design by estimating required sample sizes.
• To leverage advanced automated processing for enhanced reliability.

Main Methods:

• Utilized the PIANO™ automated pipeline for volumetric and diffusion MRI (dMRI) analysis on 238 participants (52 bvFTD, 32 nfvPPA, 35 svPPA, 117 controls).
• Assessed gray matter density, mean diffusivity (MD), and free water (FW).
• Performed sample size calculations for detecting a 60% reduction in metrics over 6-24 months, incorporating deep learning segmentation.

Main Results:

• Distinct atrophy patterns observed: svPPA showed rapid progression (up to 15% volume loss in 24 months) in the hippocampus and temporal cortex.
• bvFTD exhibited frontal and cingulate changes; nfvPPA showed less localized changes.
• Sample size needs were lowest for svPPA (<35 participants per arm for 6-12 month trials), with PIANO™ analyses showing higher sensitivity and reduced needs.

Conclusions:

• Advanced imaging biomarkers effectively differentiate FTD subtypes and monitor progression.
• Integration of volumetric, dMRI, and deep learning enhances early detection and reduces clinical trial sample sizes.
• This approach facilitates cost-effective trials and personalized intervention strategies based on subtype-specific progression patterns.