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Left Atrium Dose-Volume Parameters Predict for Clinically Significant Radiation Pneumonitis


E Huang

E Huang1*, M Folkert1, J Bradley2, A Apte1, J Deasy1, (1) Memorial Sloan Kettering Cancer Center, New York, NY (2) Washington University School of Medicine, St. Louis, MO

TU-G-108-2 Tuesday 4:30PM - 6:00PM Room: 108

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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