Predicting radiation pneumonitis in lung cancer: a EUD-based machine learning approach for volumetric modulated arc therapy patients.

Purpose: This study aims to develop an optimal machine learning model that uses lung equivalent uniform dose (lung EUD to predict radiation pneumonitis (RP) occurrence in lung cancer patients treated with volumetric modulated arc therapy (VMAT).

Methods: We analyzed a cohort of 77 patients diagnosed with locally advanced squamous cell lung cancer (LASCLC) receiving concurrent chemoradiotherapy with VMAT. Patients were categorized based on the onset of grade II or higher radiation pneumonitis (RP 2+).

Prediction of radiation-induced acute skin toxicity in breast cancer patients using data encapsulation screening and dose-gradient-based multi-region radiomics technique: A multicenter study.

Purpose: Radiation-induced dermatitis is one of the most common side effects for breast cancer patients treated with radiation therapy (RT). Acute complications can have a considerable impact on tumor control and quality of life for breast cancer patients. In this study, we aimed to develop a novel quantitative high-accuracy machine learning tool for prediction of radiation-induced dermatitis (grade ≥ 2) (RD 2+) before RT by using data encapsulation screening and multi-region dose-gradient-based radiomics techniques, based on the pre-treatment planning computed tomography (CT) images, clinical and dosimetric information of breast cancer patients.

Radiation Enhances the Epithelial- Mesenchymal Transition of A549 Cells via miR3591-5p/USP33/PPM1A.

Background/aims: Radiotherapy plays a critical role in lung cancer treatment. Radiation can activate transforming growth factor-β (TGF-β) signaling and induce the epithelial-mesenchymal transition (EMT), which may lead to distant metastases. MicroRNAs (miRNAs) have been suggested to affect radiotherapy in lung cancer.

Delineation of Neck Clinical Target Volume Specific to Nasopharyngeal Carcinoma Based on Lymph Node Distribution and the International Consensus Guidelines.

Purpose: To establish the regional lymph node (LN) distribution probability map and draw the neck clinical target volume specific to nasopharyngeal carcinoma (NPC).

Methods And Materials: One thousand patients with pathologically proven NPC were enrolled from January 2010 to December 2011. The center point of the LNs with a minimal axial diameter of ≥4 mm was marked on a single treatment planning computed tomography scan.

Baicalin alleviates radiation-induced epithelial-mesenchymal transition of primary type II alveolar epithelial cells via TGF-β and ERK/GSK3β signaling pathways.

Background: Radiation therapy is commonly used to treat thoracic malignancies. However, it may lead to severe lung pneumonitis and ultimately fibrosis. Irradiation has been reported to increase epithelial-mesenchymal transition (EMT) of type II alveolar epithelial cells (AEC), which play an important role in pulmonary fibrosis.