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Jeong Whun Kim

Seoul National University · Medicine

About the Lab

Professor Jeong Whun Kim's research lab specializes in diagnostic radiology and medical imaging, focusing on improving the accuracy of non-invasive imaging techniques for early detection and characterization of gastrointestinal and abdominal malignancies. The lab investigates advanced cross-sectional imaging modalities—such as CT, MRI, and ultrasound—combined with quantitative imaging biomarkers like diffusion-weighted imaging and radiomics to enhance tumor grading, staging, and tissue characterization. Key research directions include optimizing multi-modal imaging protocols for pancreatic neuroendocrine tumors, gallbladder carcinoma, and salivary gland lesions, with an emphasis on predicting histopathological features and guiding clinical decision-making.

medical imagingtumor gradingradiomicsabdominal cancerdiffusion-weighted imaging

Research Overview

Papers
458
Total Citations
6,990
Papers (5y)
72
Primary Field
Medicine

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
72total
2022
2023
2024
2025
2026
Citations per year (5y)
354total
20222023202420252026

Selected Papers

15
1
Article|204 citations·2018
Characteristics, incidence, and risk factors of immune checkpoint inhibitor-related pneumonitis in patients with non-small cell lung cancer
Jun Yeun Cho, Junghoon Kim, Jong Seok Lee, Yu Jung Kim, Se Hyun Kim, Yeon Joo Lee, Young‐Jae Cho, Ho Il Yoon, Jae Ho Lee, Choon‐Taek Lee, Jong Sun Park
SJR Q1Lung Cancer
OncologyMedicine
2
Article|115 citations·2016
Prediction of the therapeutic response after FOLFOX and FOLFIRI treatment for patients with liver metastasis from colorectal cancer using computerized CT texture analysis
Su Joa Ahn, Jung Hoon Kim, Sang Joon Park, Joon Koo Han
SJR Q1European Journal of Radiology
Radiology, Nuclear Medicine and ImagingMedicine
3
Article|112 citations·2017
Pancreatic neuroendocrine tumor: prediction of the tumor grade using CT findings and computerized texture analysis
Tae Won Choi, Jung Hoon Kim, Mi Hye Yu, Sang Joon Park, Joon Koo Han
SJR Q3Acta RadiologicaOA

Background Pancreatic neuroendocrine tumors (PNET) include heterogeneous tumors with a variable degree of inherent biologic aggressiveness represented by the histopathologic grade. Although several studies investigated the computed tomography (CT) characteristics which can predict the histopathologic grade of PNET, accurate prediction of the PNET grade by CT examination alone is still limited. Purpose To investigate the important CT findings and CT texture variables for prediction of grade of PN

EpidemiologyMedicine
4
Article|95 citations·2015
Pancreatic neuroendocrine tumour (PNET): Staging accuracy of MDCT and its diagnostic performance for the differentiation of PNET with uncommon CT findings from pancreatic adenocarcinoma
Jung Hoon Kim, Hyo Won Eun, Young Jae Kim, Jeong Min Lee, Joon Koo Han, Byung‐Ihn Choi
SJR Q1European Radiology
EpidemiologyMedicine
5
Article|94 citations·2018
Hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MR imaging can predict early recurrence after curative resection using image features and texture analysis
Su Joa Ahn, Jung Hoon Kim, Sang Joon Park, Seung Tack Kim, Joon Koo Han
SJR Q1Abdominal Radiology
HepatologyMedicine
6
Article|90 citations·2002
Preoperative evaluation of gallbladder carcinoma: Efficacy of combined use of MR imaging, MR cholangiography, and contrast‐enhanced dual‐phase three‐dimensional MR angiography
Jung Hoon Kim, Tae Kyoung Kim, Hyo Won Eun, Bong Soo Kim, M.-G. Lee, Pyo Nyun Kim, Hyun Kwon Ha
SJR Q1Journal of Magnetic Resonance ImagingOA

PURPOSE: To determine the efficacy of the combined use of magnetic resonance (MR) imaging, MR cholangiography (MRC), and MR angiography (MRA) in the preoperative evaluation of gallbladder carcinoma. MATERIALS AND METHODS: During a 20-month period, 41 patients with proven gallbladder carcinomas were referred for MR examination, including MR imaging, MRC, and gadolinium-enhanced dual-phase MRA to determine the operability of their gallbladder carcinoma. Eighteen patients who underwent surgery with

SurgeryMedicine
7
Article|77 citations·2015
High-Resolution Sonography for Distinguishing Neoplastic Gallbladder Polyps and Staging Gallbladder Cancer
Jung Hoon Kim, Jae Young Lee, Jee Hyun Baek, Hyo Won Eun, Young Jae Kim, Joon Koo Han, Byung Ihn Choi
SJR Q1American Journal of Roentgenology

OBJECTIVE. The purposes of this study were to compare staging accuracy of high-resolution sonography (HRUS) with combined low- and high-MHz transducers with that of conventional sonography for gallbladder cancer and to investigate the differences in the imaging findings of neoplastic and nonneoplastic gallbladder polyps. MATERIALS AND METHODS. Our study included 37 surgically proven gallbladder cancer (T1a = 7, T1b = 2, T2 = 22, T3 = 6), including 15 malignant neoplastic polyps and 73 surgically

SurgeryMedicine
8
Article|62 citations·2012
Diagnostic performance of MRI and EUS in the differentiation of benign from malignant pancreatic cyst and cyst communication with the main duct
Jung Hoon Kim, Hyo Won Eun, Hyun‐Jeong Park, Seong Sook Hong, Young Jae Kim
SJR Q1European Journal of Radiology
OncologyMedicine
9
Article|62 citations·2018
CT prediction of resectability and prognosis in patients with pancreatic ductal adenocarcinoma after neoadjuvant treatment using image findings and texture analysis
Bo Ram Kim, Jung Hoon Kim, Su Joa Ahn, Ijin Joo, Seo-Youn Choi, Sang Joon Park, Joon Koo Han
SJR Q1European Radiology
OncologyMedicine
10
Article|61 citations·2006
Imaging of Various Gastric Lesions with 2D MPR and CT Gastrography Performed with Multidetector CT
Jung Hoon Kim, Hyo Won Eun, Dong Erk Goo, Chan Sup Shim, Yong Ho Auh
SJR Q1Radiographics

Recent advances in computed tomographic (CT) technology, three-dimensional imaging software, and cheaper data storage capacity have made faster, simpler, and more accurate gastric imaging available. Two-dimensional multiplanar reformation and CT gastrography including virtual gastroscopy and transparency rendering allow multiplanar cross-sectional imaging, gastroscopic viewing, and upper gastrointestinal series imaging in the same data acquisition. Multi-detector row CT allows noninvasive assess

Pulmonary and Respiratory MedicineMedicine
11
Article|54 citations·2017
Diagnostic performance and imaging features for predicting the malignant potential of intraductal papillary mucinous neoplasm of the pancreas: a comparison of EUS, contrast-enhanced CT and MRI
Seo-Youn Choi, Jung Hoon Kim, Mi Hye Yu, Hyo Won Eun, Hae Kyung Lee, Joon Koo Han
SJR Q1Abdominal Radiology
OncologyMedicine
12
Article|53 citations·2013
Staging accuracy of MR for pancreatic neuroendocrine tumor and imaging findings according to the tumor grade
Jung Hoon Kim, Hyo Won Eun, Young Jae Kim, Joon Koo Han, Byung Ihn Choi
Abdominal Imaging
EpidemiologyMedicine
13
Review|51 citations·2020
Comparison of core needle biopsy and fine‐needle aspiration in diagnosis of ma lignant salivary gland neoplasm: Systematic review and meta‐analysis
Jungheum Cho, Junghoon Kim, Ji Sung Lee, Choong Guen Chee, Youngjune Kim, Sang Il Choi
SJR Q1Head & Neck

BACKGROUND: In this meta-analysis, we compared the risk of obtaining nondiagnostic results and the diagnostic accuracy for detection of salivary gland malignancy between core needle biopsy (CNB) and fine-needle aspiration (FNA). METHODS: All published English-language studies comparing CNB and FNA diagnostic accuracy for salivary gland masses through December 2019 were searched. Pooled risk ratios (RRs) of nondiagnostic results, sensitivities, and specificities of CNB and FNA for salivary gland

SurgeryMedicine
14
Article|51 citations·2014
Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Pancreatic Neuroendocrine Tumors
Eui Jin Hwang, Jeong Min Lee, Jeong Hee Yoon, Jung Hoon Kim, Joon Koo Han, Byung Ihn Choi, Kyoung Bun Lee, Jin‐Young Jang, Sun‐Whe Kim, Dominik Nickel, Berthold Kiefer
SJR Q1Investigative Radiology

Pure diffusion coefficient (D) is possibly a better marker than ADC(total) is for differentiating grade 1 from grade 2 or 3 PNET and, combined with tumor size, can predict grade 1 PNET with a high specificity.

EpidemiologyMedicine
15
Article|50 citations·2020
Deep learning-based decision support system for the diagnosis of neoplastic gallbladder polyps on ultrasonography: Preliminary results
Younbeom Jeong, Jung Hoon Kim, Hee‐Dong Chae, Sae‐Jin Park, Jae Seok Bae, Ijin Joo, Joon Koo Han
SJR Q1Scientific ReportsOA

Ultrasonography (US) has been considered image of choice for gallbladder (GB) polyp, however, it had limitations in differentiating between nonneoplastic polyps and neoplastic polyps. We developed and investigated the usefulness of a deep learning-based decision support system (DL-DSS) for the differential diagnosis of GB polyps on US. We retrospectively collected 535 patients, and they were divided into the development dataset (n = 437) and test dataset (n = 98). The binary classification convo

SurgeryMedicine

Research Areas

Pulmonary and Respiratory MedicineSurgeryOncologyHepatologyRadiology, Nuclear Medicine and ImagingEpidemiology

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