Yonsei University · Medicine
Professor Jin Young Kwak's research lab specializes in thyroid nodule diagnostics and risk stratification, with a strong focus on ultrasound-based imaging techniques and molecular markers. The lab investigates the clinical utility of ultrasonography features, elastography, and genetic mutations—particularly BRAF(V600E)—to improve the detection and prognosis of papillary thyroid microcarcinoma (PTMC). Key research directions include optimizing thyroid imaging reporting systems (TIRADS), evaluating the predictive value of US features for extrathyroidal extension, and integrating cytologic and molecular data for personalized patient management.
Figures are computed from collected data and may differ slightly.
Risk 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.
The BRAF(V600E) mutation can be used as a potential prognostic factor in PTMC patients in a BRAF(V600E)-prevalent area. Future studies will be needed to determine how this information can be used to alter patient care.
Ultrasonography (US)-based elastography has been introduced as a noninvasive technique for evaluating thyroid nodules that encompasses a variety of approaches such as supersonic shear imaging and acoustic radiation force impulse imaging as well as real-time tissue elastography. However, the diagnostic performances for differentiating malignant thyroid nodules from benign ones with elastography as an adjunctive tool of gray-scale US is still under debate. In this review article, diagnostic perfor
Open papers in the app to read, cite, and organize with AI.
