Augustine, Kurt E.

PurposeTo commission an open source Monte Carlo (MC) dose engine, “MCsquare” for a synchrotron‐based proton machine, integrate it into our in‐house C++‐based I/O user interface and our web‐based software platform, expand its functionalities, and improve calculation efficiency for intensity‐modulated proton therapy (IMPT).MethodsWe commissioned MCsquare using a double Gaussian beam model based on in‐air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread‐out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++‐based dose calculation code and web‐based second check platform “DOSeCHECK.” We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well‐benchmarked GPU‐accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)‐related model‐dependent biological dose calculation.ResultsDifferences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients’ geometries using an inexpensive CPU workstation (Intel Xeon E5‐2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.ConclusionsMCsquare was successfully commissioned for a synchrotron‐based proton beam therapy delivery system and integrated into our web‐based second check platform. After adopting CT resampling and implementing LET model‐dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo‐based and LET‐guided robust optimization in IMPT, which will be done in the future studies.

PurposeAt our institution, all proton patient plans undergo patient‐specific quality assurance (PSQA) prior to treatment delivery. For intensity‐modulated proton beam therapy, quality assurance is complex and time consuming, and it may involve multiple measurements per field. We reviewed our PSQA workflow and identified the steps that could be automated and developed solutions to improve efficiency.MethodsWe used the treatment planning system's (TPS) capability to support C# scripts to develop an Eclipse scripting application programming interface (ESAPI) script and automate the preparation of the verification phantom plan for measurements. A local area network (LAN) connection between our measurement equipment and shared database was established to facilitate equipment control, measurement data transfer, and storage. To improve the analysis of the measurement data, a Python script was developed to automatically perform a 2D–3D γ‐index analysis comparing measurements in the plane of a two‐dimensional detector array with TPS predictions in a water phantom for each acquired measurement.ResultsDevice connection via LAN granted immediate access to the plan and measurement information for downstream analysis using an online software suite. Automated scripts applied to verification plans reduced time from preparation steps by at least 50%; time reduction from automating γ‐index analysis was even more pronounced, dropping by a factor of 10. On average, we observed an overall time savings of 55% in completion of the PSQA per patient plan.ConclusionsThe automation of the routine tasks in the PSQA workflow significantly reduced the time required per patient, reduced user fatigue, and frees up system users from routine and repetitive workflow steps allowing increased focus on evaluating key quality metrics.