Alzheimer's Imaging Consortium.

Area of Science:

• Neuroimaging
• Biomarker Discovery
• Alzheimer's Disease Research

Background:

• Amyloid-beta (Aβ) plaque deposition is an early hallmark of Alzheimer's disease (AD), preceding cognitive decline.
• Positron Emission Tomography (PET) is crucial for in vivo Aβ detection, enabling early AD intervention.
• A need exists for accurate, efficient, and automated PET-based pipelines for brain Aβ detection.

Purpose of the Study:

• To develop the Q Amyloid platform, an automated, tracer- and site-agnostic pipeline for Aβ detection and quantification.
• To address the current gap in automated PET-based analysis for brain Aβ accumulation.
• To provide a tool for early AD diagnosis and research.

Main Methods:

• Assembling a comprehensive dataset of structural MRI and Aβ-PET scans from diverse sources.
• Including Aβ-PET scans from multiple radiotracers (e.g., ¹¹C-Pittsburgh compound B, ¹⁸F-florbetaben) for broad applicability.
• Implementing data harmonization, pre-processing, quality control, and Aβ quantification using the Centiloid scale.

Main Results:

• The Q Amyloid platform generates subject-specific reports with Centiloid values and Aβ pathology status from PET and MRI scans.
• The platform is web-based, open-access, dynamic, and flexible, incorporating new quantification methods including AI.
• Automated identification and quantification of Aβ burden through PET.

Conclusions:

• Q Amyloid will serve as a valuable tool for medical research in early AD identification and tracking.
• It will provide pharmacodynamic biomarkers for anti-amyloid therapy development.
• The platform facilitates international data analysis, methodology sharing, and reusability.