Young‐Jin Park
Yonsei University · 医学
研究室紹介
Professor Young-Jin Park's research lab specializes in medical imaging and radiomics, focusing on leveraging advanced imaging techniques—such as ultrasound, MRI, and radiomic analysis—to improve diagnostic accuracy and prognostic prediction in oncology. The lab develops and validates deep learning and machine learning models for thyroid and breast cancer, with particular emphasis on risk stratification, disease-free survival prediction, and image-pathology correlation. Key research directions include computer-aided diagnosis (CAD), radiomic feature extraction from medical images, and the integration of imaging with clinical outcomes to support personalized treatment planning.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learning-based US CAD system (dCAD) for the diagnosis of thyroid nodules and compare its performance with those of a support vector machine (SVM)-based US CAD system (sCAD) and radiologists. dCAD was developed by using US images of 4919 thyroid nodules from three institutions. Its diagnostic performance was prospectively evaluated between June 2016 and F
The present study showed that US radiomic features of the primary tumor were associated with lateral cervical lymph node status. Although their discriminatory performance was slightly lower in the validation cohort, our study shows that US radiomic features of the primary tumor alone have the potential to predict lateral LNM.
Breast magnetic resonance (MR) imaging has high sensitivity in breast cancer diagnosis. The probability of malignancy for additional detected lesions is higher in patients with breast cancer than in the population without malignancy, which is why biopsy or further study should be considered for additional detected lesions. Because of the shortcomings of MR imaging-guided biopsy, second-look ultrasonography (US) may be the preferred next step. Detecting target lesions at second-look US and correl
Patients with papillary thyroid carcinoma (PTC) would benefit from risk stratification tools that can aid in planning personalized treatment and follow-up. The aim of this study was to develop a conventional ultrasound (US)-based radiomics signature to estimate disease-free survival (DFS) in patients with conventional PTC. Imaging features were extracted from the pretreatment US images of 768 patients with conventional PTC who were treated between January 2004 and February 2006. The median follo
Ultrasound (US)-guided breast biopsy has become the main method for diagnosing breast pathology, and it has a high diagnostic accuracy, approaching that of open surgical biopsy. However, methods for confirming adequate lesion retrieval after US-guided biopsy are relatively limited and false-negative results are unavoidable. Determining imaging-pathology concordance after US-guided biopsy is essential for validating the biopsy result and providing appropriate management. In this review article, w
Radiomic features hold potential to improve prediction of disease-free survival (DFS) in triple-negative breast cancer (TNBC) and may show better performance if developed from TNBC patients. We aimed to develop a radiomics score based on MRI features to estimate DFS in patients with TNBC. A total of 228 TNBC patients who underwent preoperative MRI and surgery between April 2012 and December 2016 were included. Patients were temporally divided into the training (n = 169) and validation (n = 59) s
BACKGROUND & AIMS: The dynamic enhancement pattern of HCCs smaller than 3 cm in diameter on gadoxetic acid-enhanced magnetic resonance imaging (MRI) have not been extensively investigated. We aimed to evaluate the dynamic enhancement patterns of small HCCs (≤3 cm) on gadoxetic acid-enhanced magnetic resonance imaging (MRI) and compare enhancement patterns with multiphasic multidetector computed tomography (MDCT) based on tumour cellular differentiation and size. METHODS: We retrospectively inclu
Women with a personal history of breast cancer are at increased risk of future breast cancer events, and may benefit from supplemental screening methods that could enhance early detection of subclinical disease. However, current literature on breast magnetic resonance (MR) imaging surveillance is limited. We investigated outcomes of surveillance breast magnetic resonance (MR) imaging in women with a personal history of breast cancer. We reviewed 1053 consecutive breast MR examinations that were
BACKGROUND: Background parenchymal enhancement (BPE) on dynamic contrast-enhanced (DCE)-MRI has been associated with breast cancer risk, both based on qualitative and quantitative assessments. PURPOSE: To investigate whether BPE of the contralateral breast on preoperative DCE-MRI is associated with therapy outcome in ER-positive, HER2-negative, node-negative invasive breast cancer. STUDY TYPE: Retrospective. POPULATION: In all, 289 patients with unilateral ER-positive, HER2-negative, node-negati
High-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy data may serve as a biomarker for breast cancer, with only a small volume of tissue sample required for assessment. However, previous studies utilized only a single tissue sample from each patient. The aim of this study was to investigate whether intratumoral location and biospecimen type affected the metabolic characterization of breast cancer assessed by HR-MAS MR spectroscopy. This prospective study was approve