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Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital
Radiation pneumonitis (RP) remains a major toxicity in thoracic radiotherapy. While lung radiomics has shown promise for RP prediction, the optimal region for feature extraction remains unclear. This study investigated whether restricting the extraction regio...
Predicting radiation pneumonitis (RP) using machine learning is promising, particularly when functional lung heterogeneity is incorporated via dose-function histogram (DFH) and CT ventilation imaging (CTVI). However, traditional dose–function metrics often fa...
Grade ≥2 radiation pneumonitis (RP) occurs in approximately 30% of patients undergoing radiotherapy for lung cancer. Therefore, a predictive model to estimate RP risk before radiotherapy is required. Radiomics and dosiomics have shown potential for RP predict...