skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis

Abstract

Purpose: Clinical and 3D dosimetric parameters are associated with symptomatic radiation pneumonitis rates in retrospective studies. Such parameters include: mean lung dose (MLD), radiation (RT) dose to perfused lung (via SPECT), and pre-RT lung function. Based on prior publications, we defined pre-RT criteria hypothesized to be predictive for later development of pneumonitis. We herein prospectively test the predictive abilities of these dosimetric/functional parameters on 2 cohorts of patients from Duke and Netherlands Cancer Institute (NKI). Methods and Materials: For the Duke cohort, 55 eligible patients treated between 1999 and 2005 on a prospective IRB-approved study to monitor RT-induced lung injury were analyzed. A similar group of patients treated at the NKI between 1996 and 2002 were identified. Patients believed to be at high and low risk for pneumonitis were defined based on: (1) MLD; (2) OpRP (sum of predicted perfusion reduction based on regional dose-response curve); and (3) pre-RT DLCO. All doses reflected tissue density heterogeneity. The rates of grade {>=}2 pneumonitis in the 'presumed' high and low risk groups were compared using Fisher's exact test. Results: In the Duke group, pneumonitis rates in patients prospectively deemed to be at 'high' vs. 'low' risk are 7 of 20 and 9more » of 35, respectively; p = 0.33 one-tailed Fisher's. Similarly, comparable rates for the NKI group are 4 of 21 and 6 of 44, respectively, p = 0.41 one-tailed Fisher's. Conclusion: The prospective model appears unable to accurately segregate patients into high vs. low risk groups. However, considered retrospectively, these data are consistent with prior studies suggesting that dosimetric (e.g., MLD) and functional (e.g., PFTs or SPECT) parameters are predictive for RT-induced pneumonitis. Additional work is needed to better identify, and prospectively assess, predictors of RT-induced lung injury.« less

Authors:
 [1];  [2];  [3];  [1];  [1];  [4];  [1];  [1];  [5];  [6];  [1];  [3];  [3];  [7]
  1. Department of Radiation Oncology, Duke University Medical Center, Durham, NC (United States)
  2. (Turkey)
  3. Department of Radiation Oncology, Netherlands Cancer Institute-Antoni van Leewenhoek Hospital, Amsterdam (Netherlands)
  4. Cancer Center Biostatistics, Duke University Medical Center, Durham, NC (United States)
  5. Pulmonary Medicine, Duke University Medical Center, Durham, NC (United States)
  6. Radiology-Nuclear Medicine Division, Duke University Medical Center, Durham, NC (United States)
  7. Department of Radiation Oncology, Duke University Medical Center, Durham, NC (United States). E-mail: marks@radonc.duke.edu
Publication Date:
OSTI Identifier:
20850312
Resource Type:
Journal Article
Resource Relation:
Journal Name: International Journal of Radiation Oncology, Biology and Physics; Journal Volume: 67; Journal Issue: 1; Other Information: DOI: 10.1016/j.ijrobp.2006.09.031; PII: S0360-3016(06)03121-X; Copyright (c) 2007 Elsevier Science B.V., Amsterdam, 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; HEALTH HAZARDS; INJURIES; LUNGS; NEOPLASMS; PATIENTS; PNEUMONITIS; RADIATION DOSES; SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY

Citation Formats

Kocak, Zafer, Department of Radiation Oncology, Trakya University Hospital, Edirne, Borst, Gerben R., Zeng Jing, Zhou Sumin, Hollis, Donna R., Zhang Junan, Evans, Elizabeth S., Folz, Rodney J., Wong, Terrence, Kahn, Daniel, Belderbos, Jose S.A., Lebesque, Joos V., and Marks, Lawrence B. Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis. United States: N. p., 2007. Web. doi:10.1016/j.ijrobp.2006.09.031.
Kocak, Zafer, Department of Radiation Oncology, Trakya University Hospital, Edirne, Borst, Gerben R., Zeng Jing, Zhou Sumin, Hollis, Donna R., Zhang Junan, Evans, Elizabeth S., Folz, Rodney J., Wong, Terrence, Kahn, Daniel, Belderbos, Jose S.A., Lebesque, Joos V., & Marks, Lawrence B. Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis. United States. doi:10.1016/j.ijrobp.2006.09.031.
Kocak, Zafer, Department of Radiation Oncology, Trakya University Hospital, Edirne, Borst, Gerben R., Zeng Jing, Zhou Sumin, Hollis, Donna R., Zhang Junan, Evans, Elizabeth S., Folz, Rodney J., Wong, Terrence, Kahn, Daniel, Belderbos, Jose S.A., Lebesque, Joos V., and Marks, Lawrence B. Mon . "Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis". United States. doi:10.1016/j.ijrobp.2006.09.031.
@article{osti_20850312,
title = {Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis},
author = {Kocak, Zafer and Department of Radiation Oncology, Trakya University Hospital, Edirne and Borst, Gerben R. and Zeng Jing and Zhou Sumin and Hollis, Donna R. and Zhang Junan and Evans, Elizabeth S. and Folz, Rodney J. and Wong, Terrence and Kahn, Daniel and Belderbos, Jose S.A. and Lebesque, Joos V. and Marks, Lawrence B.},
abstractNote = {Purpose: Clinical and 3D dosimetric parameters are associated with symptomatic radiation pneumonitis rates in retrospective studies. Such parameters include: mean lung dose (MLD), radiation (RT) dose to perfused lung (via SPECT), and pre-RT lung function. Based on prior publications, we defined pre-RT criteria hypothesized to be predictive for later development of pneumonitis. We herein prospectively test the predictive abilities of these dosimetric/functional parameters on 2 cohorts of patients from Duke and Netherlands Cancer Institute (NKI). Methods and Materials: For the Duke cohort, 55 eligible patients treated between 1999 and 2005 on a prospective IRB-approved study to monitor RT-induced lung injury were analyzed. A similar group of patients treated at the NKI between 1996 and 2002 were identified. Patients believed to be at high and low risk for pneumonitis were defined based on: (1) MLD; (2) OpRP (sum of predicted perfusion reduction based on regional dose-response curve); and (3) pre-RT DLCO. All doses reflected tissue density heterogeneity. The rates of grade {>=}2 pneumonitis in the 'presumed' high and low risk groups were compared using Fisher's exact test. Results: In the Duke group, pneumonitis rates in patients prospectively deemed to be at 'high' vs. 'low' risk are 7 of 20 and 9 of 35, respectively; p = 0.33 one-tailed Fisher's. Similarly, comparable rates for the NKI group are 4 of 21 and 6 of 44, respectively, p = 0.41 one-tailed Fisher's. Conclusion: The prospective model appears unable to accurately segregate patients into high vs. low risk groups. However, considered retrospectively, these data are consistent with prior studies suggesting that dosimetric (e.g., MLD) and functional (e.g., PFTs or SPECT) parameters are predictive for RT-induced pneumonitis. Additional work is needed to better identify, and prospectively assess, predictors of RT-induced lung injury.},
doi = {10.1016/j.ijrobp.2006.09.031},
journal = {International Journal of Radiation Oncology, Biology and Physics},
number = 1,
volume = 67,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}
  • 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 demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination. Methods and Materials: Patients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD wasmore » calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate {>=}20% were plotted. Results: The 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD. Conclusions: The atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.« less
  • Purpose: High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Methods and Materials: Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF)more » images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose–response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. Results: The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=−0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). Conclusions: 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage.« less
  • Purpose: To determine whether the association between mean lung dose (MLD) and risk of severe (grade {>=}3) radiation pneumonitis (RP) depends on the dose distribution pattern to normal lung among patients receiving 3-dimensional conformal radiation therapy for non-small-cell lung cancer. Methods and Materials: Three cohorts treated with different beam arrangements were identified. One cohort (2-field boost [2FB]) received 2 parallel-opposed (anteroposterior-posteroanterior) fields per fraction initially, followed by a sequential boost delivered using 2 oblique beams. The other 2 cohorts received 3 or 4 straight fields (3FS and 4FS, respectively), ie, all fields were irradiated every day. The incidence of severemore » RP was plotted against MLD in each cohort, and data were analyzed using the Lyman-Kutcher-Burman (LKB) model. Results: The incidence of grade {>=}3 RP rose more steeply as a function of MLD in the 2FB cohort (N=120) than in the 4FS cohort (N=138), with an intermediate slope for the 3FS group (N=99). The estimated volume parameter from the LKB model was n=0.41 (95% confidence interval, 0.15-1.0) and led to a significant improvement in fit (P=.05) compared to a fit with volume parameter fixed at n=1 (the MLD model). Unlike the MLD model, the LKB model with n=0.41 provided a consistent description of the risk of severe RP in all three cohorts (2FB, 3FS, 4FS) simultaneously. Conclusions: When predicting risk of grade {>=}3 RP, the mean lung dose does not adequately take into account the effects of high doses. Instead, the effective dose, computed from the LKB model using volume parameter n=0.41, may provide a better dosimetric parameter for predicting RP risk. If confirmed, these findings support the conclusion that for the same MLD, high doses to small lung volumes ('a lot to a little') are worse than low doses to large volumes ('a little to a lot').« 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