Radiogenomic analysis for predicting lymph node metastasis and molecular annotation of radiomic features in pancreatic cancer.

Background: To provide a preoperative prediction model for lymph node metastasis in pancreatic cancer patients and provide molecular information of key radiomic features.

Methods: Two cohorts comprising 151 and 54 pancreatic cancer patients were included in the analysis. Radiomic features from the tumor region of interests were extracted by using PyRadiomics software.

Application of ultrasonography in predicting the biological risk of gastrointestinal stromal tumors.

Objectives: To explore and establish a reliable and noninvasive ultrasound model for predicting the biological risk of gastrointestinal stromal tumors (GISTs).

Materials And Methods: We retrospectively reviewed 266 patients with pathologically-confirmed GISTs and 191 patients were included. Data on patient sex, age, tumor location, biological risk classification, internal echo, echo homogeneity, boundary, shape, blood flow signals, presence of necrotic cystic degeneration, long diameter, and short/long (S/L) diameter ratio were collected.

A six-gene-based signature for breast cancer radiotherapy sensitivity estimation.

Breast cancer (BRCA) represents the most common malignancy among women worldwide with high mortality. Radiotherapy is a prevalent therapeutic for BRCA that with heterogeneous effectiveness among patients. Here, we proposed to develop a gene expression-based signature for BRCA radiotherapy sensitivity estimation.