Seoul National University · Medicine
Professor Hongyoon Choi's research lab specializes in translational biomedical imaging and molecular neuroscience, focusing on the development of advanced imaging technologies and computational models to understand neurodegenerative diseases, particularly Alzheimer’s disease. The lab integrates molecular imaging, deep learning, and systems biology to explore disease mechanisms, including amyloid pathology, microglial metabolism, and extracellular vesicle dynamics. A key focus is on creating non-invasive imaging biomarkers—such as those derived from PET and MRI—for early detection, disease progression monitoring, and therapeutic evaluation.
Figures are computed from collected data and may differ slightly.
Structural MR images concomitantly acquired with PET images can provide crucial anatomic information for precise quantitative analysis. However, in the clinical setting, not all the subjects have corresponding MR images. Here, we developed a model to generate structural MR images from amyloid PET using deep generative networks. We applied our model to quantification of cortical amyloid load without structural MR. <b>Methods:</b> We used florbetapir PET and structural MR data from the Alzheimer D
Extracellular vesicles play a crucial role in intercellular communication by transmitting biological materials from donor cells to recipient cells. They have pathophysiologic roles in cancer metastasis, neurodegenerative diseases, and inflammation. Extracellular vesicles also show promise as emerging therapeutics, with understanding of their physiology including targeting, distribution, and clearance therefore becoming an important issue. Here, we review recent advances in methods for tracking a
ApoE, ApoE receptors and APP cooperate in the pathogenesis of Alzheimer's disease. Intriguingly, the ApoE receptor LRP4 and APP are also required for normal formation and function of the neuromuscular junction (NMJ). In this study, we show that APP interacts with LRP4, an obligate co-receptor for muscle-specific tyrosine kinase (MuSK). Agrin, a ligand for LRP4, also binds to APP and co-operatively enhances the interaction of APP with LRP4. In cultured myotubes, APP synergistically increases agri
We suggest that deep learning model trained only by normal data was applicable for identifying wide-range of abnormalities in brain diseases, even uncommon ones, proposing its possible use for interpreting real-world clinical data.
Although metabolic modulation in the tumor microenvironment (TME) is one of the key mechanisms of cancer immune escape, there is a lack of understanding of the comprehensive immune landscape of the TME and its association with tumor metabolism based on clinical evidence. We aimed to investigate the relationship between the immune landscape in the TME and tumor glucose metabolism in lung adenocarcinoma. <b>Methods:</b> Using RNA sequencing and image data, we developed a transcriptome-based tumor
We identified the reconfiguration of microglial glucose metabolism in the hippocampus of AD, which could be evaluated by FDG PET as a feasible surrogate imaging biomarker for microglia-mediated inflammation.
Neuroimaging has been used to examine developmental changes of the brain. While PET studies revealed maturation-related changes, maturation of metabolic connectivity of the brain is not yet understood. Here, we show that rat brain metabolism is reconfigured to achieve long-distance connections with higher energy efficiency during maturation. Metabolism increased in anterior cerebrum and decreased in thalamus and cerebellum during maturation. When functional covariance patterns of PET images were
Although metabolic alterations are one of the hallmarks of cancer, there is a lack of understanding of how metabolic landscape is reconstituted according to cancer progression and which genetic alterations underlie its heterogeneity within cancer cells. Here, the configuration of the metabolic landscape according to genetic alteration is examined across 7648 subjects representing 29 cancers. The metabolic landscape and its reconfiguration according to the accumulated mutation maintained characte
Abstract Dopaminergic degeneration is a hallmark of Parkinson's disease (PD), which causes various symptoms affected by corticostriatal circuits. So far, the relationship between cortical changes and dopamine loss in the striatum is unclear. Here, we evaluate the gray matter (GM) changes in accordance with striatal dopaminergic degeneration in PD using hybrid PET/MR. Sixteen patients with idiopathic PD underwent 18 F‐FP‐CIT PET/MR. To measure dopaminergic degeneration in PD, binding ratio (BR) o
Our data demonstrate spatial bias of the DAT BR on (18)F-FP-CIT PET/MR. Voxelwise analysis and comparison to non-AC images identified the misclassification of ventricle as air to be the cause of bias. To obtain reliable quantification for brain PET/MR studies including (18)F-FP-CIT PET, alternative and more reliable segmentation strategies are required.
Enhanced expression of integrin αvβ3 is commonly used as a biomarker for angiogenesis, which is one of the key pathophysiologic processes in cerebral infarct. Integrin αvβ3 can be imaged with arginine-glycine-aspartic acid (RGD) peptide agents. In this study, characteristics of positron emission tomography (PET) using a 68Ga-labeled RGD were investigated in pediatric cerebral infarct. Pediatric patients with moyamoya disease underwent 68Ga-RGD PET in a research protocol for neovascularization ev
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