An automated toolbox for microcalcification cluster modeling for mammographic imaging.

Background: Mammographic imaging is essential for breast cancer detection and diagnosis. In addition to masses, calcifications are of concern and the early detection of breast cancer also heavily relies on the correct interpretation of suspicious microcalcification clusters. Even with advances in imaging and the introduction of novel techniques such as digital breast tomosynthesis and contrast-enhanced mammography, a correct interpretation can still be challenging given the subtle nature and large variety of calcifications.

Integrating Clinical Variables, Radiomics, and Tumor-derived Cell-Free DNA for Enhanced Prediction of Resectable Esophageal Adenocarcinoma Outcomes.

Purpose: The value of integrating clinical variables, radiomics, and tumor-derived cell-free DNA (cfDNA) for the prediction of survival and response to chemoradiation of patients with resectable esophageal adenocarcinoma is not yet known. Our aim was to investigate if radiomics and cfDNA metrics combined with clinical variables can improve personalized predictions.

Methods And Materials: A cohort of 111 patients with resectable esophageal adenocarcinoma from 2 centers treated with neoadjuvant chemoradiation therapy was used for exploratory retrospective analyses.

Radiomic feature robustness in CT scans affected by fiducial marker induced streak artifacts for patients with hepatocellular carcinoma.

Background: Stereotactic body radiation therapy for hepatocellular carcinoma necessitates the implantation of gold fiducial markers in the liver, resulting in artifacts on computed tomography (CT) scans, which affect radiomic feature values.

Purpose: This report aims to assess the effect of these artifacts on radiomic features and how removing CT slices affects radiomic features extracted from 3D regions of interest (ROI).

Methods: First, the range variation in 38 tumor contours unaffected by artifacts was assessed after sequentially and randomly removing 25%, 50%, 75% of slices.

Prognostic models for colorectal cancer recurrence using carcinoembryonic antigen measurements.

Objective: Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. A considerable percentage of patients who undergo surgery with curative intent will experience cancer recurrence. Early identification of individuals with a higher risk of recurrence is crucial for healthcare professionals to intervene promptly and devise appropriate treatment strategies.