Abstract
Alzheimer's disease (AD) diagnosis faces challenges in precision and early detection due to the reliance on methods that lack quantitative accuracy. Researchers at Florida Atlantic University have developed a technology that directly addresses this challenge by transforming brain FDG-PET images into numerical data, enabling a definitive analytical approach to AD diagnosis. The numerical data conversion facilitates early and precise identification of Alzheimer's, significantly impacting patient outcomes.
This method stands apart in its avoidance of extraneous data, preserving the integrity of the original imaging. What is generated is an authentic, numerical representation of the brain's glucose metabolism, which is crucial for AD assessment. The technology surpasses existing diagnostic practices, offering a substantial leap forward in the accurate quantification of neurodegenerative changes, ultimately transforming the landscape of Alzheimer's diagnostics.
FAU seeks to advance this innovation into the marketplace through licensing or development partnerships.
Benefit
Accuracy - Ensures definitive diagnosticsEfficiency - Speeds up analysisReliability - Reduces diagnostic variabilityMarket Application
Neurology - Improves disease detectionResearch - Aids Alzheimer's studiesPharmaceutical - Supports therapy development
