곽진영 교수
Jin-Young Kwox
연세대학교 영상의학과 · 의학
연구실 소개
곽진영 교수의 연구실은 갑상선 질환, 특히 갑상선 결절의 영상학적 특징과 분자생물학적 특성 간의 연관성을 중심으로 한 진단 및 위험도 분류 체계 개발에 주력하고 있습니다. 초음파 영상 소견을 기반으로 한 TIRADS 시스템의 실용적 적용과 함께, BRAF(V600E) 돌연변이와의 연관성을 분석함으로써 개인화된 진료 전략 수립에 기여하고 있습니다. 특히 갑상선 미소암(Papillary Thyroid Microcarcinoma, PTMC)의 병행 소견 및 외성 확산 여부 예측에 초점을 맞춘 임상적 유용성 연구가 두드러집니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Risk stratification of thyroid malignancy by using the number of suspicious US features allows for a practical and convenient TIRADS.
The predictor model using suspicious malignant US features may be helpful in risk stratification of thyroid nodules.
Repeat FNAB should be performed for thyroid nodules that have suspicious US features, even if the initial cytologic results indicate that it is a benign lesion.
This study suggests that the presence and degree of contact between a PTMC and the adjacent capsule as found on preoperative US can provide an useful predictive information about an extrathyroidal extension.
PURPOSE: To evaluate the association of known prognostic factors with the BRAF(V600E) mutation and its association with ultrasonographic (US) features in Korean patients with papillary thyroid microcarcinoma (PTMC). MATERIALS AND METHODS: This retrospective study was institutional review board approved; informed consent was not required from patients. From July 2008 to November 2008, 339 consecutive patients underwent surgery for PTMC. US-guided fine-needle aspiration biopsy was performed to eva
BACKGROUND: Pulmonary actinomycosis is a chronic pulmonary infection caused by Actinomyces. Both improving oral hygiene and early application of antibiotics to the case of suspicious pulmonary infections result in changes in incidences and presentations of pulmonary actinomycosis. However, there are little reports dealt with the recent clinical characteristics of pulmonary actinomycosis. This study aimed to review the characteristics of pulmonary actinomycosis occurred during the first decade of
Ultrasonography (renamed from the Journal of Korean Society of Ultrasound in Medicine in January 2014), the official English-language journal of the Korean Society of Ultrasound in Medicine (KSUM), is an international peer-reviewed academic journal dedicated to practice, research, technology, and education dealing with medical ultrasound, Aims and Scope:Ultrasonography (renamed from the Journal of Korean Society of Ultrasound in Medicine in January 2014), the official English-language journal of
BACKGROUND: The purpose of the present study was to evaluate the clinicopathologic factors and ultrasound (US) features predictive of central lymph node metastasis (LNM) in patients diagnosed with papillary thyroid microcarcinoma (PTMC). METHODS: From March 2008 to August 2008, the clinicopathologic features and preoperative US features of 483 patients who were diagnosed with conventional PTMC were included. Medical records, US features, and pathology reports of all patients were retrospectively
PURPOSE: The aim of this study was to evaluate the overall ultrasonographic features and clinical factors that contribute to inadequate sampling in ultrasound-guided fine-needle aspiration biopsy (US-FNAB) of thyroid nodules. MATERIALS AND METHODS: From April 2008 to December 2008, 4077 US-FNABs in 3767 consecutive patients were reviewed. We evaluated the clinical, ultrasound and pathological features of patients and analysed the association between these features and inadequate samples. We also
BACKGROUND: We designed a deep convolutional neural network (CNN) to diagnose thyroid malignancy on ultrasound (US) and compared the diagnostic performance of CNN with that of experienced radiologists. METHODS: Between May 2012 and February 2015, 589 thyroid nodules in 519 patients were diagnosed as benign or malignant by surgical excision. Experienced radiologists retrospectively reviewed the US of the thyroid nodules in a test set. CNNs were trained and tested using retrospective data of 439 a
Computer-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
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