Objective The main aim of the present systematic review was a comprehensive overview of
the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues …

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of
diagnosis and staging, refined surveillance strategies, and introduced specific and …

Simple Summary The integration of artificial intelligence (AI) into radiomic models has
become increasingly popular due to advances in computer-aided diagnosis tools. These …

Prostate cancer is the second most common cause of malignancy among men, with bone
metastasis being a significant source of morbidity and mortality in advanced cases …

Objective This study aimed to develop a predictive model to detect osteoporosis using
radiomic features from lumbar spine computed tomography (CT) images. Methods A total of …

Simple Summary Existing research on predicting biochemical recurrence after prostate
surgery has been insufficient. Here, we aimed to predict biochemical recurrence after radical …

Purpose This study aimed to develop and assess an automated segmentation framework
based on deep learning for metastatic prostate cancer (mPCa) lesions in whole-body [68Ga] …

Automatic segmentation of the prostate of and the prostatic zones on MRI remains one of the
most compelling research areas. While different image enhancement techniques are …

Introduction In the last decade, two new radionuclide-based therapies, 223Radichloride and
radioligand therapy (RLT) targeting prostate-specific membrane antigen (PSMA), have been …

Introduction This study was conducted to evaluate the predictive values of volumetric
parameters and radiomic features (RFs) extracted from pretreatment 68Ga-PSMA PET and …