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Comparing Different NTCP Models That Predict the Incidence of Radiation Pneumonitis. Normal Tissue Complication Probability

Overview
Specialties Oncology
Radiology
Date 2003 Feb 8
PMID 12573760
Citations 125
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Abstract

Purpose: To compare different normal tissue complication probability (NTCP) models to predict the incidence of radiation pneumonitis on the basis of the dose distribution in the lung.

Methods And Materials: The data from 382 breast cancer, malignant lymphoma, and inoperable non-small-cell lung cancer patients from two centers were studied. Radiation pneumonitis was scored using the Southwestern Oncology Group criteria. Dose-volume histograms of the lungs were calculated from the dose distributions that were corrected for dose per fraction effects. The dose-volume histogram of each patient was reduced to a single parameter using different local dose-effect relationships. Examples of single parameters were the mean lung dose (MLD) and the volume of lung receiving more than a threshold dose (V(Dth)). The parameters for the different NTCP models were fit to patient data using a maximum likelihood analysis.

Results: The best fit resulted in a linear local dose-effect relationship, with the MLD as the resulting single parameter. The relationship between the MLD and NTCP could be described with a median toxic dose (TD(50)) of 30.8 Gy and a steepness parameter m of 0.37. The best fit for the relationship between the V(Dth) and the NTCP was obtained with a D(th) of 13 Gy. The MLD model was found to be significantly better than the V(Dth) model (p <0.03). However, for 85% of the studied patients, the difference in NTCP calculated with both models was <10%, because of the high correlation between the two parameters. For dose distributions outside the range of the studied dose-volume histograms, the difference in NTCP, using the two models could be >35%. For arbitrary dose distributions, an estimate of the uncertainty in the NTCP could be determined using the probability distribution of the parameter values of the Lyman-Kutcher-Burman model.

Conclusion: The maximum likelihood method revealed that the underlying local dose-effect relation for radiation pneumonitis was linear (the MLD model), rather than a step function (the V(Dth) model). Thus, for the studied patient population, the MLD was the most accurate predictor for the incidence of radiation pneumonitis.

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