Eun Ju Son
Yonsei University · Medicine
About the Lab
Professor Eun Ju Son's research lab specializes in diagnostic radiology and breast imaging, with a focus on improving the accuracy of breast cancer detection and axillary lymph node staging. The lab investigates advanced medical imaging techniques such as ultrasound, diffusion-weighted MRI, and FDG-PET to differentiate benign from malignant lesions and predict metastatic spread. A key emphasis is placed on optimizing non-invasive and minimally invasive diagnostic strategies during pregnancy and in patients with complex breast pathologies. The lab also explores the radiological features of rare breast tumors and thyroid nodules with high-risk US characteristics.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15In this paper, we evaluate the radiological features of pregnancy-associated breast lesions and discuss the difficulties in diagnosis by imaging. We selected patients who were diagnosed with pregnancy-associated breast lesions during the previous 5 years. All patients complained of palpable lesions in the breast and underwent ultrasonographic (US) examination, the first choice for examination of pregnancy-related breast lesions. Any suspicious lesions found by the US were recommended for a US-gu
BACKGROUND: Ultrasound (US) is probably the standard imaging procedure in most centers, and US-guided fine needle aspiration can be added if suspicious lymph nodes are found. However, US-guided fine needle aspiration is an invasive method to diagnose a metastasis and has showed relatively low sensitivity. In general, diffusion-weighted (DW) magnetic resonance imaging (MRI) has become an emerging technique for discriminating benign from malignant breast lesions in a short imaging acquisition time
BACKGROUND: The presence of axillary lymph node metastasis is the most important prognostic factor and an essential part of staging and prognosis of breast cancer. PURPOSE: To elucidate the usefulness and accuracy of ultrasonography (US), fluorodeoxyglucose positron emission tomography (FDG-PET) scan, and combined analysis for axillary lymph node staging in breast cancer. MATERIAL AND METHODS: A total of 250 consecutive breast cancer patients who had undergone US, FDG-PET, and sentinel lymph nod
Leiomyoma of the breast in a 50-year-old woman receiving tamoxifen.E J Son, K K Oh, E K Kim, H J Son, W H Jung and H D LeeAudio Available | Share
Follicular cell-derived well-differentiated thyroid cancer, papillary (PTC) and follicular thyroid carcinomas comprise 95% of all thyroid malignancies. Familial follicular cell-derived well-differentiated thyroid cancers contribute 5% of cases. Such familial follicular cell-derived carcinomas or non-medullary thyroid carcinomas (NMTC) are divided into two clinical-pathological groups. The syndromic-associated group is composed of predominately non-thyroidal tumors and includes Pendred syndrome,
Thyroid nodules with repeated Bethesda category III classification and irregular/microlobulated margins on US are at increased risk of malignancy, and operative management should be considered as opposed to repeat FNA.
The BRAF(V600E)mutation was significantly associated with several poor clinicopathologic characteristics, but was not associated with sonographic features, regardless of tumor size. We recommend that patients with a thyroid nodule with any suspicious sonographic feature undergo preoperative BRAF(V600E) testing for risk stratification and to guide the initial surgical approach in PTC.
PURPOSE: To evaluate the value of breast MRI in analysis of papillomas of the breast. MATERIALS AND METHODS: From 1996 to 2004, 94 patients underwent surgery due to papillomas of the breast. Among them, 21 patients underwent 3D fast low angle shot (FLASH) dynamic breast MRI. Eight masses were palpable and 11 of 21 patients had nipple discharge. Two radiologists indifferently analyzed the location, size of the lesions and shape, margin of the masses, multiplicity and ductal relation. The MRI find
This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients exhibiting suspicious microcalcification in screening mammograms between July 2007 and December 2019. Five pre-trained DCNN models and an ensemble model were used to classify the microcalcifications as either malignant or benign. Approximately one mil
BACKGROUND: Ultrasound (US)-guided fine needle aspiration cytology (FNAC) is an accurate, reliable, and simple method to identify a thyroid nodule as benign or malignant. However, non-diagnostic cytology results for thyroid nodules are a major limitation of US-guided FNAC. PURPOSE: To investigate the incidence of thyroid cancer among cases with non-diagnostic results on FNAC and to provide suggestions for the management of thyroid nodules that are initially non-diagnostic by FNAC according to ul
BACKGROUND: Clinical examination is not entirely sufficient for evaluation of the postoperative site for follow-up of patients with mastectomy. A few studies have reported that postoperative follow-up US evaluation allows early detection and proper management of local tumor recurrence. PURPOSE: To evaluate the diagnostic performance of the American College of Radiology (ACR) ultrasonographic (US) Breast Imaging Reporting and Data System (BI-RADS) categories 4 and 5 breast lesions at the mastecto
Research Areas
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