| Sumario: | Purpose While the total number of people with dementia is rapidly growing, the treatment or clinical interventions are limited yet. Neuroimaging (brain MRI and PET) is currently essential to interpret the state of an individual's brain health. An accurate and efficient interpretation of neuroimaging is thus needed for health care providers and researchers. Our research team aims to support all the relevant personnel to make better decisions by providing quantified analysis results using AI-based neuroimaging technologies. This talk will discuss recent advancements in AI-powered technologies for diagnostic, prognostic, clinical intervention, and treatment planning. Method We have utilized both the South Korea neuroimaging dataset (CABI, Catholic Aging Brain Imaging database) and open-source neuroimaging dataset for the technology development. We have developed MRI(T1w, FLAIR) and PET(amyloid, tau, FDG) analysis technology to quantify brain properties using AI. Those AI-based technologies include 1) T1w multilabel segmentation algorithm, 2) FLAIR white matter hyperintensity segmentation algorithm, and 3) amyloid/tau/glucose uptake measurement tool from PET. These neuroimaging techniques are used to quantify the level of atrophy, vascular burden, or substance deposition in the brain to provide dementia biomarkers for accurate diagnosis or prognosis based on objective measurements. Results and Discussion Each technology was highly robust and much faster than a legacy algorithm in the neuroimaging field. A large-scale T1w MRI data could be analyzed for their visual atrophy scales automatically in a short time. Quantitative PET analysis provides helpful information to support clinical decisions faster and more reliable. Finally, all those AI-based technologies together could be used to build a prognosis prediction tool for dementia converter in a couple of years. The AI technology for neuroimaging analysis is needed to better understand the status and prognosis in the near future for middle to later adulthood.
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