Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach.

Background: The modern approach to treating rectal cancer, which involves total mesorectal excision directed by imaging assessments, has significantly enhanced patient outcomes. However, locally recurrent rectal cancer (LRRC) continues to be a significant clinical issue. Identifying LRRC through imaging is complex, due to the mismatch between fibrosis and inflammatory pelvic tissue.

Symptomatic Myeloma: PET, Whole-Body MR Imaging with Diffusion-Weighted Imaging or Both.

According to international guidelines, patients with suspected myeloma should primarily undergo low-dose whole-body computed tomography (CT) for diagnostic purposes. To optimize sensitivity and specificity and enable treatment response assessment, whole-body MR (WB-MR) imaging should include diffusion-weighted imaging with apparent diffusion coefficient maps and T1-weighted Dixon sequences with bone marrow Fat Fraction Quantification. At baseline WB-MR imaging shows greater sensitivity for the detecting focal lesions and diffuse bone marrow infiltration pattern than 18F-fluorodeoxyglucose PET-CT, which is considered of choice for evaluating response to treatment and minimal residual disease and imaging of extramedullary disease.

An Apparent Diffusion Coefficient-Based Machine Learning Model Can Improve Prostate Cancer Detection in the Grey Area of the Prostate Imaging Reporting and Data System Category 3: A Single-Centre Experience.

The Prostate Imaging and Reporting Data System (PI-RADS) has a key role in the management of prostate cancer (PCa). However, the clinical interpretation of PI-RADS 3 score lesions may be challenging and misleading, thus postponing PCa diagnosis to biopsy outcome. Multiparametric magnetic resonance imaging (mpMRI) radiomic analysis may represent a stand-alone noninvasive tool for PCa diagnosis.