Jun-kyung Sung
Korea University
About the Lab
Professor Jun-kyung Sung's research lab specializes in neuroimaging and biomedical diagnostics, focusing on the early detection and differential diagnosis of Alzheimer’s disease and mild cognitive impairment using advanced neuroimaging techniques such as PET with tau and amyloid tracers, MRI, and functional brain imaging. The lab investigates the topographic and functional brain network changes associated with different subtypes of cognitive decline, particularly distinguishing early-onset and late-onset Alzheimer’s disease. It also pioneers mobile and portable neurodiagnostic solutions, integrating machine learning with neuroanatomical features like cortical thickness and hippocampal morphology for real-time, point-of-care diagnosis.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
6Background and Purpose Mild cognitive impairment (MCI) is a condition with diverse clinical outcomes and subgroups. Here we investigated the topographic distribution of tau in vivo using the positron emission tomography (PET) tracer [18F]THK5351 in MCI subgroups. Methods This study included 96 participants comprising 38 with amnestic MCI (aMCI), 21 with nonamnestic MCI (naMCI), and 37 with normal cognition (NC) who underwent 3.0-T MRI, [18F]THK5351 PET, and detailed neuropsychological tests. [18
Purpose Because the brain can divide into many separateregions structurally and these regions don’t exist independentlyin terms of their function, there are some tendencies betweenthese regions. Methods This functional connectivity has been analyzedusing functional magnetic resonance imaging (fMRI), but inrecent, diffuse optical tomography (DOT) has started toanalyze these connectivity. In our experiment, we measuredthe coactivation in brain regions in response to sensorystimulation using CW-DOT
Objectives: Mobile healthcare applications are becoming a growing trend. Also, the prevalence of dementia in modern society is showing a steady growing trend. Among degenerative brain diseases that cause dementia, Alzheimer disease (AD) is the most common. The purpose of this study was to identify AD patients using magnetic resonance imaging in the mobile environment. Methods: We propose an incremental classification for mobile healthcare systems. Our classification method is based on incrementa
Purpose: Alzheimer’s disease (AD) dementia may not be a single disease entity. Early-onset AD (EOAD) and late-onset AD (LOAD) have been united under the same eponym of AD until now, but disentangling the heterogeneity according to the age of sonset has been a major tenet in the field of AD research. Materials and Methods: Ninety-nine patients with AD (EOAD, n=54; LOAD, n=45) and 66 cognitively normal controls completed both [18F]THK5351 and [18F]flutemetamol (FLUTE) positron emission tomography
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