Automated Deep Learning-Based Detection and Segmentation of Lung Tumors at CT.

Background Detection and segmentation of lung tumors on CT scans are critical for monitoring cancer progression, evaluating treatment responses, and planning radiation therapy; however, manual delineation is labor-intensive and subject to physician variability. Purpose To develop and evaluate an ensemble deep learning model for automating identification and segmentation of lung tumors on CT scans. Materials and Methods A retrospective study was conducted between July 2019 and November 2024 using a large dataset of CT simulation scans and clinical lung tumor segmentations from radiotherapy plans.

Drug repurposing using artificial intelligence, molecular docking, and hybrid approaches: A comprehensive review in general diseases vs Alzheimer's disease.

Background: Alzheimer's disease (AD), the most prevalent form of dementia, remains enigmatic in its origins despite the widely accepted "amyloid hypothesis," which implicates amyloid-beta peptide aggregates in its pathogenesis and progression. Despite advancements in technology and healthcare, the incidence of AD continues to rise. The traditional drug development process remains time-consuming, often taking years to bring an AD treatment to market.

Etiology and Phenotypes of Cardiomyopathy in Southern Africa: The IMHOTEP Multicenter Pilot Study.

Background: Cardiomyopathies are an important cause of heart failure in Africa yet there are limited data on etiology and clinical phenotypes.

Objectives: The IMHOTEP (African Cardiomyopathy and Myocarditis Registry Program) was designed to systematically collect data on individuals diagnosed with cardiomyopathy living in Africa.

Methods: In this multicenter pilot study, patients (age ≥13 years) were eligible for inclusion if they had a diagnosis of cardiomyopathy or myocarditis.

Evolutionary Pressures Shape Undifferentiated Pleomorphic Sarcoma Development and Radiotherapy Response.

Radiotherapy is an integral component in the treatment of many types of cancer, with approximately half of cancer patients receiving radiotherapy. Systemic therapy applies pressure that can select for resistant tumor subpopulations, underscoring the importance of understanding how radiation impacts tumor evolution to improve treatment outcomes. We integrated temporal genomic profiling of 120 spatially distinct tumor regions from 20 patients with undifferentiated pleomorphic sarcomas (UPS), longitudinal circulating tumor DNA (ctDNA) analysis, and evolutionary biology computational pipelines to study UPS evolution during tumorigenesis and in response to radiotherapy.

Predictors of Atrial Fibrillation After Thoracic Radiotherapy.

Background: Atrial fibrillation (AF) has been associated with thoracic radiotherapy, but the specific risk with irradiating different cardiac substructures remains unknown.

Objectives: This study sought to examine the relationship between irradiation of cardiac substructures and the risk of clinically significant (grade ≥3) AF.

Methods: We analyzed data from patients who underwent definitive radiotherapy for localized cancers (non-small cell lung, breast, Hodgkin lymphoma, or esophageal) at our institution between 2004 and 2022.