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

Zafer Kocak, Gerben R. Borst, Jing Zeng, Sumin Zhou, Donna R. Hollis, Junan Zhang, Elizabeth S. Evans, Rodney J. Folz, Terrence Wong, Daniel Kahn, Jose S.A. Belderbos, Joos V. Lebesque, Lawrence B. Marks

Research output: Contribution to journalArticle

48 Citations (Scopus)

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 The 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.

Original languageEnglish (US)
Pages (from-to)178-186
Number of pages9
JournalInternational Journal of Radiation Oncology Biology Physics
Volume67
Issue number1
DOIs
StatePublished - Jan 1 2007

Fingerprint

Radiation Pneumonitis
lungs
Radiation
Pneumonia
radiation
Lung
dosage
Lung Injury
Single-Photon Emission-Computed Tomography
Research Ethics Committees
Netherlands
Publications
Retrospective Studies
Perfusion
grade
cancer
Neoplasms

Keywords

  • Dose-volume histogram
  • Function
  • Lung cancer
  • Predictive models
  • Radiation pneumonitis

ASJC Scopus subject areas

  • Radiation
  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

Cite this

Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis. / Kocak, Zafer; 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.

In: International Journal of Radiation Oncology Biology Physics, Vol. 67, No. 1, 01.01.2007, p. 178-186.

Research output: Contribution to journalArticle

Kocak, Z, Borst, GR, Zeng, J, Zhou, S, Hollis, DR, Zhang, J, Evans, ES, Folz, RJ, Wong, T, Kahn, D, Belderbos, JSA, Lebesque, JV & Marks, LB 2007, 'Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis', International Journal of Radiation Oncology Biology Physics, vol. 67, no. 1, pp. 178-186. https://doi.org/10.1016/j.ijrobp.2006.09.031
Kocak, Zafer ; 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. In: International Journal of Radiation Oncology Biology Physics. 2007 ; Vol. 67, No. 1. pp. 178-186.
@article{ce64dab81e7440e8ac311b74252e52a1,
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 The 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.",
keywords = "Dose-volume histogram, Function, Lung cancer, Predictive models, Radiation pneumonitis",
author = "Zafer Kocak and Borst, {Gerben R.} and Jing Zeng and Sumin Zhou and Hollis, {Donna R.} and Junan Zhang and Evans, {Elizabeth S.} and Folz, {Rodney J.} and Terrence Wong and Daniel Kahn and Belderbos, {Jose S.A.} and Lebesque, {Joos V.} and Marks, {Lawrence B.}",
year = "2007",
month = "1",
day = "1",
doi = "10.1016/j.ijrobp.2006.09.031",
language = "English (US)",
volume = "67",
pages = "178--186",
journal = "International Journal of Radiation Oncology Biology Physics",
issn = "0360-3016",
publisher = "Elsevier Inc.",
number = "1",

}

TY - JOUR

T1 - Prospective assessment of dosimetric/physiologic-based models for predicting radiation pneumonitis

AU - Kocak, Zafer

AU - Borst, Gerben R.

AU - Zeng, Jing

AU - Zhou, Sumin

AU - Hollis, Donna R.

AU - Zhang, Junan

AU - Evans, Elizabeth S.

AU - Folz, Rodney J.

AU - Wong, Terrence

AU - Kahn, Daniel

AU - Belderbos, Jose S.A.

AU - Lebesque, Joos V.

AU - Marks, Lawrence B.

PY - 2007/1/1

Y1 - 2007/1/1

N2 - 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 The 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.

AB - 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 The 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.

KW - Dose-volume histogram

KW - Function

KW - Lung cancer

KW - Predictive models

KW - Radiation pneumonitis

UR - http://www.scopus.com/inward/record.url?scp=33845611897&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33845611897&partnerID=8YFLogxK

U2 - 10.1016/j.ijrobp.2006.09.031

DO - 10.1016/j.ijrobp.2006.09.031

M3 - Article

C2 - 17189069

AN - SCOPUS:33845611897

VL - 67

SP - 178

EP - 186

JO - International Journal of Radiation Oncology Biology Physics

JF - International Journal of Radiation Oncology Biology Physics

SN - 0360-3016

IS - 1

ER -