Publication date: Available online 8 April 2017
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Austin M. Faught, Tokihiro Yamamoto, Richard Castillo, Edward Castillo, Jingjing Zhang, Moyed Miften, Yevgeniy Vinogradskiy
Purpose4DCT-ventilation imaging is increasingly being used to calculate lung ventilation and implement functional-guided radiotherapy in clinical trials. There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation. The purpose of our study was to evaluate which dose-function metrics best predict for radiation pneumonitis (RP).Methods and MaterialsSeventy lung cancer patients with 4DCT imaging and pneumonitis grading were used. Pre-treatment 4DCTs of each patient were used to calculate ventilation images. We evaluated 3 types of dose function metrics that combined that patient's 4DCT-ventilation image and treatment planning dose distribution: 1) structure-based approaches 2) image-based approaches using the dose-function histogram (DFH) and 3) non-linear weighting schemes. Log-likelihood methods were used to generate normal tissue complication probability (NTCP) models predicting grade 3+ pneumonitis for all dose-function schemes. The area under the curve (AUC) was used to assess the predictive power of the models. All techniques were compared to NTCP models based on traditional, total lung dose metrics.ResultsThe most predictive models were structure-based approaches that focused on the volume of functional lung receiving ≥20Gy (AUC=0.70). Probability of grade 3+ RP of 20% and 10% correspond to V20Gy to the functional sub-volumes of 26.8% and 9.3%, respectively. Imaging-based analysis with the DFH and non-linear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when evaluating the percentage of functionality receiving ≥20Gy. All dose-function metrics outperformed the traditional dose metrics (mean lung dose, AUC=0.55).ConclusionA full range of dose-function metrics and functional thresholds were examined. The calculated AUC values for the most predictive functional models occupied a narrow range (0.66-0.70) and all demonstrated notable improvements over AUC from traditional lung dose metrics (0.55). Identifying the combinations most predictive of grade 3+ RP provides valuable data to inform the functional-guided radiotherapy process.
Teaser
We performed a retrospective analysis of 70 lung cancer patients with 4DCT images to assess which dose-function metrics are most predictive of clinical radiation pneumonitis and should be used in functional-guided radiotherapy. Normal tissue complication probability models were developed based on standard lung dose metrics and four additional functional schemes that considered lung function as determined from 4DCT ventilation imaging. Results provide valuable data in the guidance of prospective clinical trials in functional-guided radiotherapy.from #MedicinebyAlexandrosSfakianakis via xlomafota13 on Inoreader http://ift.tt/2nuj8Lb
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