Prediction of outcome in patients with colorectal cancer (CRC) is challenging as a result of
lack of a robust biomarker and heterogeneity between and within tumors. The aim of this …

Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have
become an increasingly significant health problem worldwide. Noninvasive imaging plays a …

The high incidence of rectal cancer in both sexes makes it one of the most common tumors,
with significant morbidity and mortality rates. To define the best treatment option and …

Purpose To investigate the value of T2-radiomics combined with anatomical MRI staging
criteria from pre-treatment rectal MRI in predicting complete response to neoadjuvant …

Purpose Distant metastases are currently the main cause of treatment failure in locally
advanced rectal cancer (LARC) patients. The aim of this research is to investigate a …

The main therapeutic options for colorectal cancer are surgical resection and adjuvant
chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant …

Purpose: The construction and validation of a radiomics nomogram based on machine
learning using magnetic resonance image (MRI) for predicting the efficacy of neoadjuvant …

Objective Different grades of meningiomas require different treatment strategies and have a
different prognosis; thus, the noninvasive classification of meningiomas before surgery is of …

Objectives To compare computed tomography (CT)–based radiomics for preoperatively
differentiating type I and II epithelial ovarian cancers (EOCs) using different machine …

Objectives To establish and validate a radiomics model based on multiparametric magnetic
resonance imaging (MRI), and to predict microsatellite instability (MSI) status in rectal cancer …