Soft‐tissue sarcomas (STS) represent a group of rare and heterogeneous tumors associated
with several challenges, including incorrect or late diagnosis, the lack of clinical expertise …

This article proposes a summary of the current status of the research regarding the use of
radiomics and artificial intelligence to improve the radiological assessment of patients with …

Purpose In high-grade soft-tissue sarcomas (STS) the standard of care encompasses
multimodal therapy regimens. While there is a growing body of evidence for prognostic …

Simple Summary In soft-tissue sarcoma (STS) patients, the decision for the optimal treatment
modality largely depends on STS size, location, and a pathological measure that assesses …

Purpose To develop a CT-based radiomic signature to predict biochemical recurrence
(BCR) in prostate cancer patients after sRT guided by positron-emission tomography …

Simple Summary This review based on a literature search aims at showing the impact of
Texture Analysis in the prediction of response to neoadjuvant radiotherapy and/or …

Objectives To evaluate the performance of machine learning–augmented MRI-based
radiomics models for predicting response to neoadjuvant chemotherapy (NAC) in soft tissue …

Objectives Radiomics of soft tissue sarcomas (STS) is assumed to correlate with histologic
and molecular tumor features, but radiogenomics analyses are lacking. Our aim was to …

Objective To systematically review radiomic feature reproducibility and model validation
strategies in recent studies dealing with CT and MRI radiomics of bone and soft-tissue …

Simple Summary Differentiating atypical lipomatous tumors from lipomas on MR images is a
challenging task due to similar imaging characteristics. Given these challenges, it would be …