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Ji-Seok Jang

Yonsei University · Medicine

About the Lab

Professor Ji-Seok Jang's research lab specializes in radiation oncology and medical physics, focusing on improving treatment accuracy and outcomes in cancer patients through advanced imaging, treatment planning, and artificial intelligence. The lab investigates risk factors for treatment-related complications such as lymphedema and explores the integration of deep learning for automated contouring in radiotherapy. A key focus is on optimizing radiotherapy for rare and aggressive cancers, including mucosal melanoma and rectal cancer, particularly through combined modality approaches involving immunotherapy and stereotactic radiotherapy.

radiotherapylymphedemadeep learningauto-contouringimmunotherapy

Research Overview

Papers
284
Total Citations
3,400
Papers (5y)
90
Primary Field
Medicine

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
90total
2022
2023
2024
2025
2026
Citations per year (5y)
578total
20222023202420252026

Selected Papers

15
1
Article|114 citations·2019
Risk of Lymphedema Following Contemporary Treatment for Breast Cancer
Hwa Kyung Byun, Jee Suk Chang, Sang Hee Im, Youlia Kirova, A. Arsène-Henry, Seo Hee Choi, Young Up Cho, Hyung Seok Park, Jee Ye Kim, Chang‐Ok Suh, Ki Chang Keum, Joohyuk Sohn
SJR Q1Annals of SurgeryOA

OBJECTIVE: The aim of this study was to identify the comprehensive risk factors for lymphedema, thereby enabling a more informed multidisciplinary treatment decision-making. SUMMARY BACKGROUND DATA: Lymphedema is a serious long-term complication in breast cancer patients post-surgery; however, the influence of multimodal therapy on its occurrence remains unclear. METHODS: We retrospectively collected treatment-related data from 5549 breast cancer patients who underwent surgery between 2007 and 2

OncologyMedicine
2
Article|105 citations·2020
Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer
Min Seo Choi, Byeong Su Choi, Seung Yeun Chung, Nalee Kim, Jaehee Chun, Yong Bae Kim, Jee Suk Chang, Jin Sung Kim
SJR Q1Radiotherapy and OncologyOA
RadiationPhysics and Astronomy
3
Article|75 citations·2021
Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery
Seung Yeun Chung, Jee Suk Chang, Min Seo Choi, Yongjin Chang, Byong Su Choi, Jaehee Chun, Ki Chang Keum, Jin Sung Kim, Yong Bae Kim
SJR Q1Radiation OncologyOA

BACKGROUND: In breast cancer patients receiving radiotherapy (RT), accurate target delineation and reduction of radiation doses to the nearby normal organs is important. However, manual clinical target volume (CTV) and organs-at-risk (OARs) segmentation for treatment planning increases physicians' workload and inter-physician variability considerably. In this study, we evaluated the potential benefits of deep learning-based auto-segmented contours by comparing them to manually delineated contour

RadiationPhysics and Astronomy
4
Article|65 citations·2013
Long-term Survival Outcomes Following Internal Mammary Node Irradiation in Stage II-III Breast Cancer: Results of a Large Retrospective Study With 12-Year Follow-up
Jee Suk Chang, Won Park, Yong Bae Kim, Ik Jae Lee, Ki Chang Keum, Chang Geol Lee, Doo Ho Choi, Chang‐Ok Suh, Seung Jae Huh
SJR Q1International Journal of Radiation Oncology*Biology*PhysicsOA
Cancer ResearchBiochemistry, Genetics and Molecular Biology
5
Article|59 citations·2016
Three-dimensional analysis of patterns of locoregional recurrence after treatment in breast cancer patients: Validation of the ESTRO consensus guideline on target volume
Jee Suk Chang, Hwa Kyung Byun, Jun Won Kim, Kyung Hwan Kim, Jeongshim Lee, Yeona Cho, Ik Jae Lee, Ki Chang Keum, Chang‐Ok Suh, Yong Bae Kim
SJR Q1Radiotherapy and OncologyOA
Cancer ResearchBiochemistry, Genetics and Molecular Biology
6
Article|59 citations·2021
Risk of Cardiac Disease in Patients With Breast Cancer: Impact of Patient-Specific Factors and Individual Heart Dose From Three-Dimensional Radiation Therapy Planning
Seung Yeun Chung, Jaewon Oh, Jee Suk Chang, Jaeyong Shin, Kyung Hwan Kim, Kyeong‐Hyeon Chun, Ki Chang Keum, Chang‐Ok Suh, Seok‐Min Kang, Yong Bae Kim
SJR Q1International Journal of Radiation Oncology*Biology*PhysicsOA
Cardiology and Cardiovascular MedicineMedicine
7
letter|57 citations·2000
All‐Trans Retinoic Acid (Atra) and Tranexamic Acid: A Potentially Fatal Combination In Acute Promyelocytic Leukaemia
J. E. Brown, Adebayo Olujohungbe, Jee Suk Chang, W. David J. Ryder, G. R. Morganstern, Rahul Chopra, J H Scarffe
SJR Q1British Journal of HaematologyOA

Until recently, chemotherapy with a combination of anthracycline and cytosine arabinoside was the most effective treatment for acute promyelocytic leukaemia (APL) ( Fenaux & Degos, 1996). This can be safely combined with anti-fibrinolytic drugs such as tranexamic acid for the attempted prophylaxis of haemorrhage without the occurrence of thrombolytic complications. However, several studies have now demonstrated that all-trans retinoic acid (ATRA) can induce complete remission of APL with progres

Molecular BiologyBiochemistry, Genetics and Molecular Biology
8
Article|55 citations·2019
Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region
Hyothaek Lee, Eungman Lee, Nalee Kim, Joo Ho Kim, Joo ho Kim, Kwangwoo Park, Ho Lee, Jaehee Chun, Jae-ik Shin, Jee Suk Chang, Jin Sung Kim, Jin Sung Kim
SJR Q2Frontiers in OncologyOA

While atlas segmentation (AS) has proven to be a time-saving and promising method for radiation therapy contouring, optimal methods for its use have not been well-established. Therefore, we investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance. A total of 110 patients’ head planning CT images were selected. The mandible and thyroid were selected for this study. The mandibles and thyroids of the patient populatio

Biomedical EngineeringEngineering
9
Article|53 citations·2012
Patterns of regional recurrence after curative D2 resection for stage III (N3) gastric cancer: Implications for postoperative radiotherapy
Jee Suk Chang, Joon Seok Lim, Sung Hoon Noh, Woo Jin Hyung, Ji Yeong An, Yong Chan Lee, Sun Young Rha, Chang Geol Lee, Woong Sub Koom
SJR Q1Radiotherapy and OncologyOA
Pulmonary and Respiratory MedicineMedicine
10
Article|52 citations·2013
Preoperative Chemoradiotherapy Effects on Anastomotic Leakage After Rectal Cancer Resection
Jee Suk Chang, Ki Chang Keum, Nam Kyu Kim, Seung Hyuk Baik, Byung So Min, Hyuk Huh, Chang Geol Lee, Woong Sub Koom
SJR Q1Annals of SurgeryOA

We did not observe that preoperative CRT increased the risk of postoperative AL after LAR in patients with rectal cancer, using propensity score matching analysis.

OncologyMedicine
11
Article|52 citations·2017
Mapping patterns of locoregional recurrence following contemporary treatment with radiation therapy for breast cancer: A multi-institutional validation study of the ESTRO consensus guideline on clinical target volume
Jee Suk Chang, Jeongshim Lee, Mison Chun, Kyung Hwan Shin, Won Park, Jong Hoon Lee, Jin Hee Kim, Won Sup Yoon, Ik Jae Lee, Juree Kim, Hye Li Park, Yong Bae Kim
SJR Q1Radiotherapy and OncologyOA
Cancer ResearchBiochemistry, Genetics and Molecular Biology
12
Article|45 citations·2019
Effect of Radiotherapy Combined With Pembrolizumab on Local Tumor Control in Mucosal Melanoma Patients
Hyun Ju Kim, Jee Suk Chang, Mi Ryung Roh, Byung Ho Oh, Kee Yang Chung, Sang Joon Shin, Woong Sub Koom
SJR Q2Frontiers in OncologyOA

<b>Objective:</b> Mucosal melanoma is an aggressive malignancy with a poor response to conventional therapies. The efficacy of radiotherapy (RT), especially combined with immune checkpoint inhibitors (ICIs), for this rare melanoma subtype remains unknown. We investigated the reciprocal effect of RT and ICI on mucosal melanoma patients. <b>Materials and Methods:</b> We identified 23 patients with 31 tumors who were treated with RT between July 2008 and February 2017. All patients received RT for

OncologyMedicine
13
Article|45 citations·2014
Clinical Usefulness of 18F-Fluorodeoxyglucose-Positron Emission Tomography in Patients With Locally Advanced Pancreatic Cancer Planned to Undergo Concurrent Chemoradiation Therapy
Jee Suk Chang, Seo Hee Choi, Young In Lee, Kyung Hwan Kim, Jeong Youp Park, Si Young Song, Arthur Cho, Mijin Yun, Jong Doo Lee, Jinsil Seong
SJR Q1International Journal of Radiation Oncology*Biology*PhysicsOA
OncologyMedicine
14
Article|43 citations·2018
Radiotherapy is a safe and effective salvage treatment for recurrent cervical cancer
Hyun Ju Kim, Jee Suk Chang, Woong Sub Koom, Kyu Chan Lee, Gwi Eon Kim, Yong Bae Kim
SJR Q1Gynecologic OncologyOA
Obstetrics and GynecologyMedicine
15
Article|40 citations·2021
Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy
Hwa Kyung Byun, Jee Suk Chang, Min Seo Choi, Jaehee Chun, Jinhong Jung, C. Jeong, Jin Sung Kim, Yongjin Chang, Seung Yeun Chung, Seung-Ryul Lee, Yong Bae Kim
SJR Q1Radiation OncologyOA

PURPOSE: To study the performance of a proposed deep learning-based autocontouring system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts. METHODS: Eleven experts from two institutions delineated nine OARs in 10 cases of adjuvant radiotherapy after breast-conserving surgery. Autocontours were then provided to the experts for correction. Overall, 110 manual contours, 110 corrected autocontours, and 10 autocontours of each type of OAR were analyzed. The Dice sim

RadiationPhysics and Astronomy

Research Areas

OncologyCancer ResearchPulmonary and Respiratory MedicineSurgeryRadiationRadiology, Nuclear Medicine and Imaging

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