CT-Based Radiomics Analysis of Different Machine Learning Models for Discriminating the Risk Stratification of Pheochromocytoma and Paraganglioma: A Multicenter Study.

Rationale And Objectives: Using different machine learning models CT-based radiomics to integrate clinical radiological features to discriminating the risk stratification of pheochromocytoma/paragangliomas (PPGLs).

Materials And Methods: The present study included 201 patients with PPGLs from three hospitals (training set: n = 125; external validation set: n = 45; external test set: n = 31). Patients were divided into low-risk and high-risk groups using a staging system for adrenal pheochromocytoma and paraganglioma (GAPP).

Radiomics Based on DCE-MRI for Predicting Response to Neoadjuvant Therapy in Breast Cancer.

Rationale And Objectives: To compare the value of radiomics and diameter% based on pre- and early-treatment dynamic enhanced MR (DCE-MRI) of the breast in predicting response to neoadjuvant therapy (NAT) in breast cancer and to construct a tool for early noninvasive prediction of NAT outcomes.

Materials And Methods: Retrospective analysis of clinical and imaging data of 142 patients with primary invasive breast cancer who underwent DCE-MRI before and after two cycles of NAT at our institution. Enroled patients were randomly assigned in a 7:3 ratio to the training group and the test group.

Radiomics Based on Dynamic Contrast-Enhanced MRI to Early Predict Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Therapy.

Rationale And Objectives: To investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-based radiomics at baseline and after two cycles of neoadjuvant therapy (NAT) and associated longitudinal changes for early prediction of the NAT response in patients with breast cancer.

Materials And Methods: One hundred seventeen patients with breast cancer who underwent DCE-MRI before NAT and after two cycles of NAT from April 2019 to November 2021 were enrolled retrospectively. Patients were randomly divided into a training set (n = 81) and a test set (n = 36) at a ratio of 7:3.

Imaging features of granular cell tumor in the breast: Case report.

Rationale: Granular cell tumor of the breast (GCTB) is a benign rare tumor. There are limited reports on its imaging manifestations. GCTB is often misdiagnosed as breast cancer, which results in unnecessary radical mastectomy and excessive treatment.