TU‐G‐108‐02: Left Atrium Dose‐Volume Parameters Predict for Clinically Significant Radiation Pneumonitis

E. Huang, M. Folkert, J. Bradley, A. Apte, J. Deasy

Research output: Contribution to journalArticle

Abstract

Purpose: To detect and quantify the association between cardiac substructure irradiation and the risk of developing radiation pneumonitis (RP) within a multivariate framework for patients treated with conventional external beam radiotherapy for non‐small‐cell lung cancer (NSCLC). Methods: All evaluable 3‐D conformal radiation therapy (3D‐CRT) treatment plans for patients with registered outcomes treated for NSCLC between 1991 and 2001 were eligible for this study (N=209). RP events occurred in 49 (23.4%) patients, with events defined as requiring steroid management or more intensive intervention (CTCAE v.4.0 Grade 2 or greater). Cardiac substructures including the left ventricle, right ventricle, left atrium, right atrium, ascending aorta, and descending aorta were contoured and individually reviewed by a single physician. Cross‐validation methods were used to build a multivariate model included clinical factors (age, gender, race, performance status, weight loss, smoking history, and histology); dosimetric parameters for cardiac substructures and normal lung [D5–D100, V10–V80, mean dose, maximum dose, and minimum dose ]; other treatment factors (chemotherapy, treatment time, fraction size); and the center of mass of the GTV within the lung, in the superior‐inferior dimension (GTV_COMSI). An optimal multivariate model was obtained by step‐wise variable selection and logistic regression. Results: Statistically significant variables (p less than 0.05) with the highest univariate Spearman rank correlations (Rs) included: Left atrium D5 (Rs,0.235), left atrium D10 (Rs,0.228), right ventricle Dmax (Rs,0.2), right atrium Dmax (Rs,0.197), and GTV_COMSI (Rs,0.22). The optimal logistic model used four variables, incorporating the left atrium D20 and V30, the lung D35, and the GTV_COMSI; (Rs=0.31) with an area under the receiver‐operator curve of 0.75. The best model using only whole‐heart variables had an Rs=0.26. Conclusion: Left atrium dose‐volume parameters had greater predictive power than other heart substructures and previously derived lung parameters to predict RP, and were incorporated into a robust prognostic multiparametric model.

Original languageEnglish (US)
Pages (from-to)453
Number of pages1
JournalMedical Physics
Volume40
Issue number6
DOIs
StatePublished - 2013

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Radiation Pneumonitis
Heart Atria
Heart Ventricles
Lung
Lung Neoplasms
Radiotherapy
Logistic Models
Age Factors
Thoracic Aorta
Area Under Curve
Aorta
Weight Loss
Histology
Therapeutics
Smoking
History
Steroids
Physicians
Drug Therapy

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

TU‐G‐108‐02 : Left Atrium Dose‐Volume Parameters Predict for Clinically Significant Radiation Pneumonitis. / Huang, E.; Folkert, M.; Bradley, J.; Apte, A.; Deasy, J.

In: Medical Physics, Vol. 40, No. 6, 2013, p. 453.

Research output: Contribution to journalArticle

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title = "TU‐G‐108‐02: Left Atrium Dose‐Volume Parameters Predict for Clinically Significant Radiation Pneumonitis",
abstract = "Purpose: To detect and quantify the association between cardiac substructure irradiation and the risk of developing radiation pneumonitis (RP) within a multivariate framework for patients treated with conventional external beam radiotherapy for non‐small‐cell lung cancer (NSCLC). Methods: All evaluable 3‐D conformal radiation therapy (3D‐CRT) treatment plans for patients with registered outcomes treated for NSCLC between 1991 and 2001 were eligible for this study (N=209). RP events occurred in 49 (23.4{\%}) patients, with events defined as requiring steroid management or more intensive intervention (CTCAE v.4.0 Grade 2 or greater). Cardiac substructures including the left ventricle, right ventricle, left atrium, right atrium, ascending aorta, and descending aorta were contoured and individually reviewed by a single physician. Cross‐validation methods were used to build a multivariate model included clinical factors (age, gender, race, performance status, weight loss, smoking history, and histology); dosimetric parameters for cardiac substructures and normal lung [D5–D100, V10–V80, mean dose, maximum dose, and minimum dose ]; other treatment factors (chemotherapy, treatment time, fraction size); and the center of mass of the GTV within the lung, in the superior‐inferior dimension (GTV_COMSI). An optimal multivariate model was obtained by step‐wise variable selection and logistic regression. Results: Statistically significant variables (p less than 0.05) with the highest univariate Spearman rank correlations (Rs) included: Left atrium D5 (Rs,0.235), left atrium D10 (Rs,0.228), right ventricle Dmax (Rs,0.2), right atrium Dmax (Rs,0.197), and GTV_COMSI (Rs,0.22). The optimal logistic model used four variables, incorporating the left atrium D20 and V30, the lung D35, and the GTV_COMSI; (Rs=0.31) with an area under the receiver‐operator curve of 0.75. The best model using only whole‐heart variables had an Rs=0.26. Conclusion: Left atrium dose‐volume parameters had greater predictive power than other heart substructures and previously derived lung parameters to predict RP, and were incorporated into a robust prognostic multiparametric model.",
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AB - Purpose: To detect and quantify the association between cardiac substructure irradiation and the risk of developing radiation pneumonitis (RP) within a multivariate framework for patients treated with conventional external beam radiotherapy for non‐small‐cell lung cancer (NSCLC). Methods: All evaluable 3‐D conformal radiation therapy (3D‐CRT) treatment plans for patients with registered outcomes treated for NSCLC between 1991 and 2001 were eligible for this study (N=209). RP events occurred in 49 (23.4%) patients, with events defined as requiring steroid management or more intensive intervention (CTCAE v.4.0 Grade 2 or greater). Cardiac substructures including the left ventricle, right ventricle, left atrium, right atrium, ascending aorta, and descending aorta were contoured and individually reviewed by a single physician. Cross‐validation methods were used to build a multivariate model included clinical factors (age, gender, race, performance status, weight loss, smoking history, and histology); dosimetric parameters for cardiac substructures and normal lung [D5–D100, V10–V80, mean dose, maximum dose, and minimum dose ]; other treatment factors (chemotherapy, treatment time, fraction size); and the center of mass of the GTV within the lung, in the superior‐inferior dimension (GTV_COMSI). An optimal multivariate model was obtained by step‐wise variable selection and logistic regression. Results: Statistically significant variables (p less than 0.05) with the highest univariate Spearman rank correlations (Rs) included: Left atrium D5 (Rs,0.235), left atrium D10 (Rs,0.228), right ventricle Dmax (Rs,0.2), right atrium Dmax (Rs,0.197), and GTV_COMSI (Rs,0.22). The optimal logistic model used four variables, incorporating the left atrium D20 and V30, the lung D35, and the GTV_COMSI; (Rs=0.31) with an area under the receiver‐operator curve of 0.75. The best model using only whole‐heart variables had an Rs=0.26. Conclusion: Left atrium dose‐volume parameters had greater predictive power than other heart substructures and previously derived lung parameters to predict RP, and were incorporated into a robust prognostic multiparametric model.

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