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This project is a multicenter observational study that establishes a longitudinal cohort of patients with Alzheimer's disease and other dementias based on neuroimaging, molecular imaging, biological and digital markers to explore new solutions such as dementia disease mechanism, diagnosis, condition evaluation, and prognosis assessment.
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This project will build a longitudinal database based on multimodal MRI imaging information of dementia subjects, various body fluid or digital markers, and a cohort. The convolutional neural network algorithm will be used to explore the imaging characteristics of healthy controls, AD, FTD, and DLB, develop an early prediction model for degenerative dementia, and achieve early differential diagnosis of different dementia subtypes. This study further performed GE180, ASEM, and exendin-4 radionuclide imaging on some subjects who completed conventional PET (AV45, Tauvir, and FDG) imaging to explore the diagnostic efficacy of these three probes as new diagnostic probes for early AD. In addition, through longitudinal follow-up of Aβ-positive MCI patients, multimodal MRI and PET image fusion technology were used to explore the changes in fused images during their conversion to AD in order to obtain early and accurate diagnostic markers.
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Jintao Wang
Data sourced from clinicaltrials.gov
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