Beam model development and clinical experience with RadCalc for treatment plan quality assurance in online adaptive workflow with an MR-linac.

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Tác giả: Jack D Aylward, Michael G Jameson, Urszula Jelen, Zoë Moutrie

Ngôn ngữ: eng

Ký hiệu phân loại: 006.31 Machine learning

Thông tin xuất bản: United States : Journal of applied clinical medical physics , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 749333

 PURPOSE: The aim of this work was to report on the optimization, commissioning, and validation of a beam model using a commercial independent dose verification software RadCalc version 7.2 (Lifeline Software Inc, Tyler, TX, USA), along with 4 years of experience employing RadCalc for offline and online monitor unit (MU) verification on the Elekta Unity MR-linac (MRL) for a range of clinical sites. METHODS: Calculation settings and model parameters, including the Clarkson integration settings and radiation/light field offset, have been systematically examined and optimized, and pitfalls in the use of density inhomogeneity corrections and in off-axis calculations were investigated and addressed. The resulting model was commissioned by comparing RadCalc calculations to measurements for a variety of cases, selected following relevant recommendations, ranging from simple fields in a water tank to end-to-end point dose measurements in an anthropomorphic phantom. RESULTS: For simple geometries, the agreement was within 2%, and for complex geometries, within 5%. When validating against the Monaco (Elekta AB, Stockholm, Sweden) treatment planning system (TPS), for 39 clinical commissioning plans, the mean total point dose difference was -0.3 ± 0.8% (-2.0%-1.1%). Finally, when applied retrospectively to 4085 clinical plan calculations, the agreement with the TPS was 0.3 ± 1.1% (-4.8%-4.2%), with fail rates of 0.1% for total point dose (discrepancy >
  4%) and 0.3% for individual fields (discrepancy >
  10%). CONCLUSIONS: Improved calculation agreement with the TPS and therefore increased confidence in the online QA, opened the way for an automated and physics-light independent MU verification workflow within our MRL program.
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