Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status.

Purpose: The detection of human epidermal growth factor receptor 2 (HER2) expression status is essential to determining the chemotherapy regimen for breast cancer patients and to improving their prognosis. We developed a deep learning radiomics (DLR) model combining time-frequency domain features of ultrasound (US) video of breast lesions with clinical parameters for predicting HER2 expression status.

Patients And Methods: Data for this research was obtained from 807 breast cancer patients who visited from February 2019 to July 2020.

Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer.

Background: Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinical and ultrasound features related with estrogen receptor, progesterone receptor, and human epidermal growth factor receptor2.

Methods: We collected clinical data and reviewed preoperative ultrasound images of enrolled breast cancers from September 2017 to August 2020.

Development and Validation of a Simple-to-Use Nomogram for Predicting the Upgrade of Atypical Ductal Hyperplasia on Core Needle Biopsy in Ultrasound-Detected Breast Lesions.

Background: The rate of carcinoma upgrade for atypical ductal hyperplasia (ADH) diagnosed on core needle biopsy (CNB) is variable on open excision. The purpose of the present study was to develop and validate a simple-to-use nomogram for predicting the upgrade of ADH diagnosed with ultrasound (US)-guided core needle biopsy in patients with US-detected breast lesions.

Methods: Two retrospective sets, the training set ( = 401) and the validation set ( = 186), from Fudan University Shanghai Cancer Center between January 2014 and December 2019 were retrospectively analyzed.

Sonographic Features of Triple-Negative Breast Carcinomas Are Correlated With mRNA-lncRNA Signatures and Risk of Tumor Recurrence.

Background: To determine a correlation between mRNA and lncRNA signatures, sonographic features, and risk of recurrence in triple-negative breast cancers (TNBC).

Methods: We retrospectively reviewed the data from 114 TNBC patients having undergone transcriptome analysis. The risk of tumor recurrence was determined based on the correlation between transcriptome profiles and recurrence-free survival.

An Ultrasound Radiomics Nomogram for Preoperative Prediction of Central Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma.

This study aimed to establish and validate an ultrasound radiomics nomogram for the preoperative prediction of central lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC). The prediction model was developed in 609 patients with clinicopathologically confirmed unifocal PTC who received ultrasonography between Jan 2018 and June 2018. Radiomic features were extracted after the ultrasonography of PTC.

The Role of Contrast-Enhanced Ultrasound in the Diagnosis and Pathologic Response Prediction in Breast Cancer: A Meta-analysis and Systematic Review.

Purpose: To determine the overall performance of contrast-enhanced ultrasound (CEUS) in differentiating between benign and malignant breast lesions and in predicting the pathologic response to neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC).

Materials And Methods: Articles published up to April 2019 were systematically searched in Medline, Web of Science, and China National Knowledge Infrastructure. The sensitivities and specificities across studies, the calculations of positive and negative likelihood ratios (LR and LR), diagnostic odds ratio (OR), and constructed summary receiver operating characteristic curves were determined.

Does Lesion Size Affect the Value of Shear Wave Elastography for Differentiating Between Benign and Malignant Thyroid Nodules?

Objectives: We aimed to investigate the diagnostic performance of shear wave elastography (SWE) combined with conventional ultrasonography (US) for differentiating between benign and malignant thyroid nodules of different sizes.

Methods: A total of 445 thyroid nodules from 445 patients were divided into 3 groups based on diameter (group 1, ≤ 10 mm; group 2, 10-20 mm; and group 3, > 20 mm). The mean elasticity index of the whole lesion was automatically calculated, and the threshold for differentiation between benign and malignant nodules was constructed by a receiver operating characteristic curve analysis.

Study on breast cancer animal model of tumor-micro vessel variation before and after the chemotherapy by contrast enhanced ultrasound quantitative analysis.

Aim to discuss whether the contrast enhanced ultrasound (CEUS) can effectively monitor the efficacy on neoadjuvant chemotherapy of breast cancer or not by analyzing the indicators on chemotherapy CEUS and breast cancer tumor biology, especially tumor microcirculation indicator on animal mode. Human breast cancer cell lines MCF-7 are planted under the skins of nude mice. By simulating clinical neoadjuvant chemotherapy regimen periodically inject CMF (cyclophosphamide, methotrexate and fluorouracil) into the experimental group, and normal saline into the control group.

Is Ultrasonography More Sensitive Than Computed Tomography for Identifying Calcifications in Thyroid Nodules?

Objectives: The primary objective of this study was to evaluate the difference and agreement between ultrasonography (US) and computed tomography (CT) for identifying calcifications in thyroid nodules.

Methods: Data from the medical records of 20,248 patients were reviewed for preoperative diagnostic investigations and postoperative pathologic diagnoses. In total, 5247 records were selected for analysis based on the presence of calcifications reported in any of the following 3 modes: US, CT, and pathologic analysis.