GPU-accelerated Monte Carlo-based online adaptive proton therapy: A feasibility study

Hongying Feng, Samir H Patel, William W Wong, James E. Younkin, Gregory P. Penoncello, Danairis Hernandez Morales, Joshua B. Stoker, Daniel G. Robertson, Mirek Fatyga, Martin Bues, Steven Eric Schild, Robert Foote, Wei Liu

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To develop an online graphic processing unit (GPU)-accelerated Monte Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS. Methods and Materials: A four-step workflow was developed using our in-house developed GPU-accelerated Monte Carlo-based treatment planning system to implement online Monte Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient-specific quality assurance (PSQA) of the reoptimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS. Results: For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833–0.983) and DSC (0.909–0.992)] but suboptimal boundary coincidence [HD (2.37–20.76 mm)] for organs-at-risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention. Conclusion: The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.

Original languageEnglish (US)
Pages (from-to)3550-3563
Number of pages14
JournalMedical physics
Volume49
Issue number6
DOIs
StatePublished - Jun 2022

Keywords

  • deformable image registration
  • online adaptive radiation therapy
  • pencil beam scanning proton therapy
  • robust optimization

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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