Simple Summary Worldwide gastrointestinal (GI) malignancies account for about 25% of the
global cancer incidence. For some malignancies, screening programs, such as routine colon …

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 …

Rectal cancer is a relatively common malignancy in the United States. Magnetic resonance
imaging (MRI) of rectal cancer has evolved tremendously in recent years, and has become a …

While colorectal cancers (CRC) are paradigmatic tumors invaded by effector memory
lymphocytes, the mechanisms accounting for the relative resistance of MSI negative CRC to …

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in
disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and …

Objectives To investigate the feasibility and efficacy of a deep-learning (DL)-based three-
dimensional (3D) super-resolution (SR) MRI radiomics model for preoperative T-staging …

Radiomics analyses commonly apply imaging features of different complexity for the
prediction of the endpoint of interest. However, the prognostic value of each feature class is …

Background To develop and validate a survival model with clinico-biological features and
18F-FDG PET/CT radiomic features via machine learning, and for predicting the prognosis …

While cross-sectional imaging has seen continuous progress and plays an undiscussed
pivotal role in the diagnostic management and treatment planning of patients with rectal …

Purpose To establish and validate two predictive radiomics models for preoperative
prediction of lymph node metastases (LNMs) and tumor deposits (TDs) respectively in rectal …