Lung Cancer Research Today is a free monthly online journal that collates and summarizes the latest research about Lung Cancer, including details on symptoms, smoking, genetics, treatment, causes. | ||||||||
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Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters.Hope AJ, Lindsay PE, El Naqa I, Alaly JR, Vicic M, Bradley JD, Deasy JO Department of Radiation Oncology, Washington University School of Medicine, Siteman Cancer Center, St. Louis, Missouri 63110-1032, USA. PURPOSE: To determine the clinical, dosimetric, and spatial parameters that correlate with radiation pneumonitis. METHODS AND MATERIALS: Patients treated with high-dose radiation for non-small-cell lung cancer with three-dimensional treatment planning were reviewed for clinical information and radiation pneumonitis (RP) events. Three-dimensional treatment plans for 219 eligible patients were recovered. Treatment plan information, including parameters defining tumor position and dose-volume parameters, was extracted from non-heterogeneity-corrected dose distributions. Correlation to RP events was assessed by Spearman's rank correlation coefficient (R). Mathematical models were generated that correlate with RP. RESULTS: Of 219 patients, 52 required treatment for RP (median interval, 142 days). Tumor location was the most highly correlated parameter on univariate analysis (R = 0.24). Multiple dose-volume parameters were correlated with RP. Models most frequently selected by bootstrap resampling included tumor position, maximum dose, and D35 (minimum dose to the 35% volume receiving the highest doses) (R = 0.28). The most frequently selected two- or three-parameter models outperformed commonly used metrics, including V20 (fractional volume of normal lung receiving >20 Gy) and mean lung dose (R = 0.18). CONCLUSIONS: Inferior tumor position was highly correlated with pneumonitis events within our population. Models that account for inferior tumor position and dosimetric information, including both high- and low-dose regions (D(35), International Commission on Radiation Units and Measurements maximum dose), risk-stratify patients more accurately than any single dosimetric or clinical parameter. Published 18 April 2006 in Int J Radiat Oncol Biol Phys, 65(1): 112-24.
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