Bi-O Ju
Yonsei University · Medicine
About the Lab
Professor Bi-O Ju's research lab specializes in advanced neuroimaging and artificial intelligence applications for neurological disorders, with a focus on improving diagnostic accuracy and understanding disease mechanisms. The lab develops and validates deep learning models for automated detection of intracranial aneurysms and brain metastases, leveraging MRI techniques such as TOF MRA and DCE-MRI. Key research directions include assessing tumor vascularity and permeability, characterizing meningeal lymphatic function in aging and disease, and exploring the clinical significance of necrosis in brain metastases. The lab integrates quantitative imaging biomarkers with machine learning to enhance early diagnosis and personalized treatment planning in neuro-oncology and neurodegenerative diseases.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15MRgFUS was demonstrated to be effective palliative treatment within 2 weeks in selected patients with painful bone metastases.
Software-aided reading showed significant incremental value in the sensitivity of clinicians in the detection of aneurysms on MRA without a significant increase in false-positive findings, especially for the neurosurgeon and neurologist. Software-aided reading showed equivocal value for the radiologist.
The present deep learning model for automated detection of unruptured intracranial aneurysms on TOF MRA achieved the target diagnostic performance comparable to that of human radiologists. With high standalone performance, this model may be useful for accurate and efficient diagnosis of intracranial aneurysm.
Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive imaging technique used to evaluate tissue vascularity/permeability features through consecutive imaging acquisitions after gadolinium-based contrast agent administration.Over the past several decades, techniques and protocols for DCE-MRI have evolved, leading to growing applications of DCE-MRI for different neurological disorders.Although most established applications of DCE-MRI are for studying tumors, an increasing number of studies have
Although necrosis is common in brain metastasis (BM), its biological and clinical significances remain unknown. We evaluated necrosis extent differences by primary cancer subtype and correlated BM necrosis to overall survival post-craniotomy. We analyzed 145 BMs of patients receiving craniotomy. Necrosis to tumor ratio (NTR) was measured. Patients were divided into two groups by NTR: BMs with sparse necrosis and with abundant necrosis. Clinical features were compared. To investigate factor relev
This study shows that the dynamic changes of meningeal lymphatic vessels in PSD can be assessed with DCE-MRI, and the results are different from those of the venous structures. Our finding that delayed wash-out was more pronounced in the PSD of older participants suggests that aging may disturb the meningeal lymphatic drainage.
DCE-MRI parameters and CAFs are pharmacodynamic biomarkers of bevacizumab for CRCLM. In our study, change in K<sup>trans</sup> at 3 days after bevacizumab monotherapy was a favorable prognostic factor; however, the value of CAFs as a prognostic biomarker was not found.
Purpose: Breast cancer brain metastases (BCBM) may involve subtypes that differ from the primary breast cancer lesion.This study aimed to develop a radiomics-based model that utilizes preoperative brain MRI for multiclass classification of BCBM subtypes and to investigate whether the model offers better prediction accuracy than the assumption that primary lesions and their BCBMs would be of the same subtype (non-conversion model) in an external validation set. Materials and Methods:The training
Background: Hemorrhage in brain metastases (BMs) from lung cancer is common and associated with a poor prognosis. Research on associated factors of spontaneous hemorrhage in patients with BMs is limited. This study aimed to investigate the predictive risk factors for BM hemorrhage and assess whether hemorrhage affects patient survival. Methods: We retrospectively evaluated 159 BMs from 80 patients with lung adenocarcinoma from January 2017 to May 2022. Patients were classified into hemorrhagic a
Background Delirium is characterized by acute brain dysfunction. Although delirium significantly affects the quality of life of patients with brain metastases, little is known about delirium in patients who undergo craniotomy for brain metastases. This study aimed to identify the factors influencing the occurrence of delirium following craniotomy for brain metastases and determine its impact on patient prognosis. Method A total of 153 patients who underwent craniotomy for brain metastases betwee
Research Areas
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