Ultrasound features for prediction of long-term outcomes of women with primary breast cancer <20 mm.

Background: Some women die despite the favorable prognosis of small breast cancers. Breast ultrasound features may reflect pathological and biological characteristics of a breast tumor. This study aimed to explore whether ultrasound features could identify small breast cancers with poor outcomes.

Multi-parameter ultrasonography-based predictive model for breast cancer diagnosis.

Objectives: To develop, validate, and evaluate a predictive model for breast cancer diagnosis using conventional ultrasonography (US), shear wave elastography (SWE), and contrast-enhanced US (CEUS).

Materials And Methods: This retrospective study included 674 patients with 674 breast lesions. The data, a main and an independent datasets, were divided into three cohorts.

Deep learning radiomics of ultrasonography for differentiating sclerosing adenosis from breast cancer.

Objectives: The purpose of our study is to present a method combining radiomics with deep learning and clinical data for improved differential diagnosis of sclerosing adenosis (SA)and breast cancer (BC).

Methods: A total of 97 patients with SA and 100 patients with BC were included in this study. The best model for classification was selected from among four different convolutional neural network (CNN) models, including Vgg16, Resnet18, Resnet50, and Desenet121.

Preoperative Non-Invasive Prediction of Breast Cancer Molecular Subtypes With a Deep Convolutional Neural Network on Ultrasound Images.

Purpose: This study aimed to develop a deep convolutional neural network (DCNN) model to classify molecular subtypes of breast cancer from ultrasound (US) images together with clinical information.

Methods: A total of 1,012 breast cancer patients with 2,284 US images (center 1) were collected as the main cohort for training and internal testing. Another cohort of 117 breast cancer cases with 153 US images (center 2) was used as the external testing cohort.

A Convolutional Neural Network Based on Ultrasound Images of Primary Breast Masses: Prediction of Lymph-Node Metastasis in Collaboration With Classification of Benign and Malignant Tumors.

A convolutional neural network (CNN) can perform well in either of two independent tasks [classification and axillary lymph-node metastasis (ALNM) prediction] based on breast ultrasound (US) images. This study is aimed to investigate the feasibility of performing the two tasks simultaneously. We developed a multi-task CNN model based on a self-built dataset containing 5911 breast US images from 2131 patients.

Ultrasonic multimodality imaging features and the classification value of nonpuerperal mastitis.

Objective: To explore the value of ultrasonic multimodality imaging for characterizing nonpuerperal mastitis (NPM) lesions and feasibility of distinguishing different subtypes.

Methods: Thirty-eight NPM lesions were assessed using conventional ultrasonography (US), strain elastography (SE), and contrast-enhanced ultrasound (CEUS). The lesions were confirmed pathologically and classified as granulomatous lobular mastitis (GLM), plasma cell mastitis (PCM), or nonspecific mastitis (NSM).

The association between conventional ultrasound and contrast-enhanced ultrasound appearances and pathological features in small breast cancer.

Objective: To investigate the association between ultrasound appearances and pathological features in small breast cancer.

Materials And Methods: A total of 186 small breast cancers in 186 patients were analyzed in this retrospective study from January 2015 to December 2019 according to pathological results. Forty-seven cases of axillary lymph node metastasis were found.

LMO2 upregulation due to AR deactivation in cancer-associated fibroblasts induces non-cell-autonomous growth of prostate cancer after androgen deprivation.

The androgen receptor (AR) is expressed in prostate fibroblasts in addition to normal prostate epithelial cells and prostate cancer (PCa) cells. Moreover, AR activation in fibroblasts dramatically influences prostate cancer (PCa) cell behavior. Androgen deprivation leads to deregulation of AR downstream target genes in both fibroblasts and PCa cells.

Conventional and contrast-enhanced ultrasound features in sclerosing adenosis and correlation with pathology.

Objectives: To evaluate the efficacy of conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) in differential diagnosis of sclerosing adenosis (SA) from malignance and investigate the correlated features with pathology.

Methods: We retrospectively enrolled 103 pathologically confirmed SA. All lesions were evaluated with conventional US while 31 lesions with CEUS.

Qualitative analysis of contrast-enhanced ultrasound in the diagnosis of small, TR3-5 benign and malignant thyroid nodules measuring ≤1 cm.

Objective: To evaluate the performance of contrast-enhanced ultrasound in the diagnosis of small, solid, TR3-5 benign and malignant thyroid nodules (≤1 cm).

Methods: From January 2016 to March 2018, 185 thyroid nodules from 154 patients who underwent contrast enhanced ultrasound (CEUS) and fine-needle aspiration or thyroidectomy in Shanghai General Hospital were included. The χ test was used to compare the CEUS characteristics of benign and malignant thyroid nodules, and the CEUS features of malignant nodules assigned scores.

Diagnostic efficacy of contrast-enhanced ultrasound for breast lesions of different sizes: a comparative study with magnetic resonance imaging.

Objective: This study aimed to compare the diagnostic performance of contrast-enhanced ultrasound (CEUS), MRI, and the combined use of the two modalities for differentiating breast lesions of different sizes.

Methods: A total of 406 patients with 406 solid breast masses detected by conventional ultrasound underwent both CEUS and MRI scans. Histological results were used as reference standards.

Incorporation of contrast-enhanced ultrasound in the differential diagnosis for breast lesions with inconsistent results on mammography and conventional ultrasound.

Objective: To identify the efficacy of contrast-enhanced ultrasound (CEUS) in re-evaluating masses with inconsistent Breast Imaging Reporting and Data System (BI-RADS) on mammography (MG) and conventional ultrasound (US).

Materials And Methods: A total of 637 breast lesions were evaluated with MG, US, and CEUS within 6 months and assessed as BI-RADS MG and US. CEUS was used as an additional screening to rerate BI-RADS US according to a five-point system.

Deregulation of ATG9A by impaired AR signaling induces autophagy in prostate stromal fibroblasts and promotes BPH progression.

The activation of androgen receptor (AR) signaling plays an essential role in both prostate stromal cells and epithelial cells during the development of benign prostatic hyperplasia (BPH). Here we demonstrated that androgen ablation after 5α-reductase inhibitor (5-ARI) treatment induced autophagy in prostate stromal fibroblasts inhibiting cell apoptosis. In addition, we found that ATG9A expression was increased after androgen ablation, which facilitated autophagic flux development.