Journal
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS
Volume 65, Issue 1, Pages 112-124Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijrobp.2005.11.046
Keywords
radiation pneumonitis; lung cancer; NTCP; radiotherapy; modeling
Funding
- NCI NIH HHS [R01 CA85181] Funding Source: Medline
Ask authors/readers for more resources
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 D-35 (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 V-20 (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. (c) 2006 Elsevier Inc.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available