The role of FDG PET/CT radiomics in the prediction of pathological response to neoadjuvant treatment in patients with esophageal cancer.

Background: Attainment of a complete histopathological response following neoadjuvant therapy has been associated with favorable long-term survival outcomes in esophageal cancer patients. We investigated the ability of F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) radiomic features to predict the pathological response to neoadjuvant treatment in patients with esophageal cancer.

Materials And Methods: A retrospective review of medical records of patients with locally advanced resectable esophageal or esophagogastric junctional cancers.

Radiological artificial intelligence - predicting personalized immunotherapy outcomes in lung cancer.

Personalized medicine has revolutionized approaches to treatment in the field of lung cancer by enabling therapies to be specific to each patient. However, physicians encounter an immense number of challenges in providing the optimal treatment regimen for the individual given the sheer complexity of clinical aspects such as tumor molecular profile, tumor microenvironment, expected adverse events, acquired or inherent resistance mechanisms, the development of brain metastases, the limited availability of biomarkers and the choice of combination therapy. The integration of innovative next-generation technologies such as deep learning-a subset of machine learning-and radiomics has the potential to transform the field by supporting clinical decision making in cancer treatment and the delivery of precision therapies while integrating numerous clinical considerations.

Distribution of Aeration and Pulmonary Blood Volume in Healthy, ARDS and COVID-19 Lungs: A Dual-Energy Computed Tomography Retrospective Cohort Study.

Rationale And Objectives: Few reports have studied lung aeration and perfusion in normal lungs, COVID-19, and ARDS from other causes (NC-ARDS) using dual-energy computed tomography pulmonary angiograms (DE-CTPA). To describe lung aeration and blood-volume distribution using DE-CTPAs of patients with NC-ARDS, COVID-19, and controls with a normal DE-CTPA ("healthy lungs"). We hypothesized that each of these conditions has unique ranges of aeration and pulmonary blood volumes.