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Quantifying the Effects of Radiation Therapy Fractionation Scheme On Dose Response Modeling

E.M. Wallat1*, A.E. Wuschner1, M.J. Flakus1, W. Shao2, J.M. Reinhardt2, G.E. Christensen2, J.E. Bayouth1, (1)University of Wisconsin-Madison, Madison, WI (2) University of Iowa, Iowa City, IA

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: To quantify the effects of radiation therapy (RT) fractionation scheme on modeling post-RT ventilation changes due to radiation damage.


Methods: Three dose response models were created using 4DCT-dervied ventilation maps from 30 standard fractionation subjects and 23 hypofractionated stereotactic body radiation therapy (SBRT) subjects. One model consisted of 18 subjects from each fractionation scheme, another only used 18 SBRT subjects, and the last model only used 23 standard fractionation subjects. Gamma analysis was performed on each of the models for validation using the remaining subjects in each group. Gamma pass rates and accuracy were compared across each model for each validation subject.


Results: When comparing regions within the lung that received a dose of 20 Gy or more, accuracy and gamma pass rates for the validation SBRT subjects and standard fractionation subjects were not significantly different from each other across all three models. Additionally, the model created using only SBRT subjects was significantly worse at predicting damage, yielding a true positive rate ten times lower than the other two models. This could be due to the SBRT treatment volumes being much smaller on average than standard fractionation, thus inhibiting its ability to predict damage across a larger volume.


Conclusion: It was shown that there were no significant differences between predictive dose response models built using subjects from different fractionation schemes. While there is no difference across models, there may be different mechanisms of damage that are occurring in each fractionation scheme that are not fully described in a model that is only based on pre-RT lung ventilation and dose.

Funding Support, Disclosures, and Conflict of Interest: Funded by NCI Grant NCT02843568

Keywords

Dose Response, Lung, Ventilation/perfusion

Taxonomy

TH- Response Assessment: Imaging-based: CT

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