A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.

Objective: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal growth factor receptor 2 (HER2) and to identify luminal histotype of the breast cancer.

Methods: From four Italian centers were recruited 180 malignant lesions and 68 benign lesions. However, only the malignant lesions were considered for the analysis.

Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome.

Objective: The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome.

Methods: A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer.

US-Elastography for Breast Lesion Characterization: Prospective Comparison of US BIRADS, Strain Elastography and Shear wave Elastography.

Purpose:  To evaluate the diagnostic performance of strain elastography (SE) and 2 D shear wave elastography (SWE) and SE/SWE combination in comparison with conventional multiparametric ultrasound (US) with respect to improving BI-RADS classification results and differentiating benign and malignant breast lesions using a qualitative and quantitative assessment.

Materials And Methods:  In this prospective study, 130 histologically proven breast masses were evaluated with baseline US, color Doppler ultrasound (CDUS), SE and SWE (Toshiba Aplio 500 with a 7-15 MHz wide-band linear transducer). Each lesion was classified according to the BIRADS lexicon by evaluating the size, the B-mode and color Doppler features, the SE qualitative (point color scale) and SE semi-quantitative (strain ratio) methods, and quantitative SWE.

Automated classification of focal breast lesions according to S-detect: validation and role as a clinical and teaching tool.

Purpose: To assess the diagnostic performance and the potential as a teaching tool of S-detect in the assessment of focal breast lesions.

Methods: 61 patients (age 21-84 years) with benign breast lesions in follow-up or candidate to pathological sampling or with suspicious lesions candidate to biopsy were enrolled. The study was based on a prospective and on a retrospective phase.

Diagnostic imaging and CEUS findings in a rare case of Desmoid-type fibromatosis. A case report.

Desmoid-type fibromatosis (DF), also known as aggressive fibromatosis, is a locally aggressive benign fibroblastic neoplasm that can infiltrate or recur but cannot metastasize. It is rare, with an estimated annual incidence of two to four new cases per million people. Most DFs occur sporadically, but it may also be associated with the hereditary syndrome familial adenomatous polyposis.