Abstract
BACKGROUND
Deformable image registration (DIR)-based dose accumulation (DDA) is regularly used in adaptive radiotherapy research. However, the applicability and reliability of DDA for direct clinical usage are still being debated. One primary concern is the validity of DDA, particularly for scenarios with substantial anatomical changes, for which energy-conservation problems were observed in conceptual studies.
PURPOSE
We present and validate an energy-conservation (EC)-based DDA validation workflow and further investigate its usefulness for actual patient data, specifically for lung cancer cases.
METHODS
For five non-small cell lung cancer (NSCLC) patients, DDA based on five selective DIR methods were calculated for five different treatment plans, which include one intensity-modulated photon therapy (IMRT), two intensity-modulated proton therapy (IMPT), and two combined proton-photon therapy (CPPT) plans. All plans were optimized on the planning CT (planCT) acquired in deep inspiration breath-hold (DIBH) and were re-optimized on the repeated DIBH CTs of three later fractions. The resulting fractional doses were warped back to the planCT using each DIR. An EC-based validation of the accumulation process was implemented and applied to all DDA results. Correlations between relative organ mass/volume variations and the extent of EC violation were then studied using Bayesian linear regression (BLR).
RESULTS
For most OARs, EC violation within 10% is observed. However, for the PTVs and GTVs with substantial regression, severe overestimation of the fractional energy was found regardless of treatment type and applied DIR method. BLR results show that EC violation is linearly correlated to the relative mass variation (R^2 > 0.95) and volume variation (R^2 > 0.60).
CONCLUSION
DDA results should be used with caution in regions with high mass/volume variation for intensity-based DIRs. EC-based validation is a useful approach to provide patient-specific quality assurance of the validity of DDA in radiotherapy.
Wu, Xin