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Title: Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters

Abstract

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{sub 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{sub 2} (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,more » including both high- and low-dose regions (D{sub 35}, International Commission on Radiation Units and Measurements maximum dose), risk-stratify patients more accurately than any single dosimetric or clinical parameter.« less

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [2]
  1. Department of Radiation Oncology, Washington University School of Medicine, Siteman Cancer Center, St. Louis, Missouri (United States)
  2. Department of Radiation Oncology, Washington University School of Medicine, Siteman Cancer Center, St. Louis, Missouri (United States). E-mail: jdeasy@radonc.wustl.edu
Publication Date:
OSTI Identifier:
20793464
Resource Type:
Journal Article
Resource Relation:
Journal Name: International Journal of Radiation Oncology, Biology and Physics; Journal Volume: 65; Journal Issue: 1; Other Information: DOI: 10.1016/j.ijrobp.2005.11.046; PII: S0360-3016(05)03075-0; Copyright (c) 2006 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; CARCINOMAS; HEALTH HAZARDS; INFORMATION; LUNGS; METRICS; PATIENTS; PLANNING; PNEUMONITIS; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOTHERAPY; SIMULATION

Citation Formats

Hope, Andrew J., Lindsay, Patricia E., El Naqa, Issam, Alaly, James R., Vicic, Milos, Bradley, Jeffrey D., and Deasy, Joseph O. Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters. United States: N. p., 2006. Web. doi:10.1016/J.IJROBP.2005.1.
Hope, Andrew J., Lindsay, Patricia E., El Naqa, Issam, Alaly, James R., Vicic, Milos, Bradley, Jeffrey D., & Deasy, Joseph O. Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters. United States. doi:10.1016/J.IJROBP.2005.1.
Hope, Andrew J., Lindsay, Patricia E., El Naqa, Issam, Alaly, James R., Vicic, Milos, Bradley, Jeffrey D., and Deasy, Joseph O. Mon . "Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters". United States. doi:10.1016/J.IJROBP.2005.1.
@article{osti_20793464,
title = {Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parameters},
author = {Hope, Andrew J. and Lindsay, Patricia E. and El Naqa, Issam and Alaly, James R. and Vicic, Milos and Bradley, Jeffrey D. and Deasy, Joseph O.},
abstractNote = {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{sub 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{sub 2} (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{sub 35}, International Commission on Radiation Units and Measurements maximum dose), risk-stratify patients more accurately than any single dosimetric or clinical parameter.},
doi = {10.1016/J.IJROBP.2005.1},
journal = {International Journal of Radiation Oncology, Biology and Physics},
number = 1,
volume = 65,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2006},
month = {Mon May 01 00:00:00 EDT 2006}
}
  • Purpose: Single dose-volume metrics are of limited value for the prediction of radiation pneumonitis (RP) in day-to-day clinical practice. We investigated whether multiparametric models that incorporate clinical and physiologic factors might have improved accuracy. Methods and Materials: The records of 160 patients who received radiation therapy for non-small-cell lung cancer were reviewed. All patients were treated to the same dose and with an identical technique. Dosimetric, pulmonary function, and clinical parameters were analyzed to determine their ability to predict for the subsequent development of RP. Results: Twenty-seven patients (17%) developed RP. On univariate analysis, the following factors were significantly correlatedmore » with the risk of pneumonitis: fractional volume of lung receiving >5-20 Gy, absolute volume of lung spared from receiving >5-15 Gy, mean lung dose, craniocaudal position of the isocenter, transfer coefficient for carbon monoxide (KCOc), total lung capacity, coadministration of angiotensin converting enzyme inhibitors, and coadministration of angiotensin receptor antagonists. By combining the absolute volume of lung spared from receiving >5 Gy with the KCOc, we defined a new parameter termed Transfer Factor Spared from receiving >5 Gy (TFS{sub 5}). The area under the receiver operator characteristic curve for TFS{sub 5} was 0.778, increasing to 0.846 if patients receiving modulators of the renin-angiotensin system were excluded from the analysis. Patients with a TFS{sub 5} <2.17 mmol/min/kPa had a risk of RP of 30% compared with 5% for the group with a TFS{sub 5} {>=}2.17. Conclusions: TFS{sub 5} represents a simple parameter that can be used in routine clinical practice to more accurately segregate patients into high- and low-risk groups for developing RP.« less
  • Purpose: To report clinical and dosimetric factors predictive of radiation pneumonitis (RP) in patients receiving lung stereotactic body radiation therapy (SBRT) from a series of 240 patients. Methods and Materials: Of the 297 isocenters treating 263 patients, 240 patients (n=263 isocenters) had evaluable information regarding RP. Age, gender, current smoking status and pack-years, O{sub 2} use, Charlson Comorbidity Index, prior lung radiation therapy (yes/no), dose/fractionation, V{sub 5}, V{sub 13}, V{sub 20}, V{sub prescription}, mean lung dose, planning target volume (PTV), total lung volume, and PTV/lung volume ratio were recorded. Results: Twenty-nine patients (11.0%) developed symptomatic pneumonitis (26 grade 2, 3more » grade 3). The mean V{sub 20} was 6.5% (range, 0.4%-20.2%), and the average mean lung dose was 5.03 Gy (0.547-12.2 Gy). In univariable analysis female gender (P=.0257) and Charlson Comorbidity index (P=.0366) were significantly predictive of RP. Among dosimetric parameters, V{sub 5} (P=.0186), V{sub 13} (P=.0438), and V{sub prescription} (where dose = 60 Gy) (P=.0128) were significant. There was only a trend toward significance for V{sub 20} (P=.0610). Planning target volume/normal lung volume ratio was highly significant (P=.0024). In multivariable analysis the clinical factors of female gender, pack-years smoking, and larger gross internal tumor volume and PTV were predictive (P=.0094, .0312, .0364, and .052, respectively), but no dosimetric factors were significant. Conclusions: Rate of symptomatic RP was 11%. Our mean lung dose was <600 cGy in most cases and V20 <10%. In univariable analysis, dosimetric factors were predictive, while tumor size (or tumor/lung volume ratio) played a role in multivariable and univariable and analysis, respectively.« less
  • Purpose: The purpose of this study was to prospectively investigate clinical correlations between dosimetric parameters associated with radiation pneumonitis (RP) and functional lung imaging. Methods and Materials: Functional lung imaging was performed using four-dimensional computed tomography (4D-CT) for ventilation imaging, single-photon emission computed tomography (SPECT) for perfusion imaging, or both (V/Q-matched region). Using 4D-CT, ventilation imaging was derived from a low attenuation area according to CT numbers below different thresholds (vent-860 and -910). Perfusion imaging at the 10th, 30th, 50th, and 70th percentile perfusion levels (F10-F70) were defined as the top 10%, 30%, 50%, and 70% hyperperfused normal lung, respectively.more » All imaging data were incorporated into a 3D planning system to evaluate correlations between RP dosimetric parameters (where fV20 is the percentage of functional lung volume irradiated with >20 Gy, or fMLD, the mean dose administered to functional lung) and the percentage of functional lung volume. Radiation pneumonitis was evaluated using Common Terminology Criteria for Adverse Events version 4.0. Statistical significance was defined as a P value of <.05. Results: Sixty patients who underwent curative radiation therapy were enrolled (48 patients for non-small cell lung cancer, and 12 patients for small cell lung cancer). Grades 1, 2, and ≥3 RP were observed in 16, 44, and 6 patients, respectively. Significant correlations were observed between the percentage of functional lung volume and fV20 (r=0.4475 in vent-860 and 0.3508 in F30) or fMLD (r=0.4701 in vent-860 and 0.3128 in F30) in patients with grade ≥2 RP. F30∩vent-860 results exhibited stronger correlations with fV20 and fMLD in patients with grade ≥2 (r=0.5509 in fV20 and 0.5320 in fMLD) and grade ≥3 RP (r=0.8770 in fV20 and 0.8518 in fMLD). Conclusions: RP dosimetric parameters correlated significantly with functional lung imaging.« less
  • Purpose: To determine if heterogeneity correction significantly affects commonly measured dosimetric parameters predicting pulmonary toxicity in patients receiving radiation for lung cancer. Methods and Materials: Sixty-eight patients treated for lung cancer were evaluated. The conformal treatment technique mostly employed anteroposterior/posterior-anterior fields and off-cord obliques. The percent total lung volume receiving 20 Gy or higher (V{sub 2}) and mean lung dose (MLD) were correlated with the incidence of radiation pneumonitis. Parameters from both heterogeneity-corrected and heterogeneity-uncorrected plans were used to assess this risk. Results: Univariate analysis revealed a significant correlation between the development of radiation pneumonitis and both V{sub 2} andmore » MLD. A best-fit line to a plot of V{sub 2} from the homogeneous plan against the corresponding V{sub 2} heterogeneous value produced a slope of 1.00 and zero offset, indicating no difference between the two parameters. For MLD, a similarly significant correlation is seen between the heterogeneous and homogeneous parameters, indicating a 4% difference when correcting for heterogeneity. A significant correlation was also observed between the MLD and V{sub 2} parameters (p < 0.0001). Conclusions: A high degree of correlation exists between heterogeneity-corrected and heterogeneity-uncorrected dosimetric parameters for lung and the risk of developing pneumonitis. Either V{sub 2} or MLD predicts the pneumonitis risk with similar effect.« less
  • Purpose: Studies have proposed that patients who receive radiation therapy to the base of the lung are more susceptible to radiation pneumonitis than patients who receive therapy to the apex of the lung. The primary purpose of the present study was to develop a novel method to incorporate the lung dose spatial information into a predictive radiation pneumonitis model. A secondary goal was to apply the method to a 547 lung cancer patient database to determine whether including the spatial information could improve the fit of our model. Methods and Materials: The three-dimensional dose distribution of each patient was mappedmore » onto one common coordinate system. The boundaries of the coordinate system were defined by the extreme points of each individual patient lung. Once all dose distributions were mapped onto the common coordinate system, the spatial information was incorporated into a Lyman-Kutcher-Burman predictive radiation pneumonitis model. Specifically, the lung dose voxels were weighted using a user-defined spatial weighting matrix. We investigated spatial weighting matrices that linearly scaled each dose voxel according to the following orientations: superior-inferior, anterior-posterior, medial-lateral, left-right, and radial. The model parameters were fit to our patient cohort with the endpoint of severe radiation pneumonitis. The spatial dose model was compared against a conventional dose-volume model to determine whether adding a spatial component improved the fit of the model. Results: Of the 547 patients analyzed, 111 (20.3%) experienced severe radiation pneumonitis. Adding in a spatial parameter did not significantly increase the accuracy of the model for any of the weighting schemes. Conclusions: A novel method was developed to investigate the relationship between the location of the deposited lung dose and pneumonitis rate. The method was applied to a patient database, and we found that for our patient cohort, the spatial location does not influence the risk of pneumonitis.« less