Chih‐Wei Chang, Rasmus Nilsson, Sebastian Andersson, Duncan Bohannon, Sagar A. Patel, Pretesh R. Patel, Tian Liu, Xiaofeng Yang, Jun Zhou

An optimized framework for cone‐beam computed tomography‐based online evaluation for proton therapy

  • General Medicine
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AbstractBackgroundClinical evidence has demonstrated that proton therapy can achieve comparable tumor control probabilities compared to conventional photon therapy but with the added benefit of sparing healthy tissues. However, proton therapy is sensitive to inter‐fractional anatomy changes. Online pre‐fraction evaluation can effectively verify proton dose before delivery to patients, but there is a lack of guidelines for implementing this workflow.PurposeThe purpose of this study is to develop a cone‐beam CT‐based (CBCT) online evaluation framework for proton therapy that enables knowledge transparency and evaluates the efficiency and accuracy of each essential component.MethodsTwenty‐three patients with various lesion sites were included to conduct a retrospective study of implementing the proposed CBCT evaluation framework for the clinic. The framework was implemented on the RayStation 11B Research platform. Two synthetic CT (sCT) methods, corrected CBCT (cCBCT), and virtual CT (vCT), were used, and the ground truth images were acquired from the same‐day deformed quality assurance CT (dQACT) for the comparisons. The evaluation metrics for the framework include time efficiency, dose‐difference distributions (gamma passing rates), and water equivalent thickness (WET) distributions.ResultsThe mean online CBCT evaluation times were 1.6 ± 0.3 min and 1.9 ± 0.4 min using cCBCT and vCT, respectively. The dose calculation and deformable image registration dominated the evaluation efficiency, and accounted for 33% and 30% of the total evaluation time, respectively. The sCT generation took another 19% of the total time. Gamma passing rates were greater than 91% and 97% using 1%/1 mm and 2%/2 mm criteria, respectively. When the appropriate sCT was chosen, the target mean WET difference from the reference were less than 0.5 mm. The appropriate sCT method choice determined the uncertainty for the framework, with the cCBCT being superior for head‐and‐neck patient evaluation and vCT being better for lung patient evaluation.ConclusionsAn online CBCT evaluation framework was proposed to identify the use of the optimal sCT algorithm regarding efficiency and dosimetry accuracy. The framework is extendable to adopt advanced imaging methods and has the potential to support online adaptive radiotherapy to enhance patient benefits. It could be implemented into clinical use in the future.

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