TG-219 Compliant Monte Carlo solutions are here.
2022 saw many radiation oncology software vendors introduce 3D second check solutions, with Monte Carlo dose calculation emerging as a clear gold standard. This comes in the wake of the report by AAPM Task Group 219, which recommends a shift to Monte Carlo dose calculation for independent dose verification of complex treatment plans.
In the past, a simple 2D point check was sufficient to ensure the accuracy of our dose delivery. With the advent of treatment modalities like IMRT, VMAT, and SRS – allowing for much greater precision in our treatment plans – these simple checks lack the rigor to identify all the plan calculation errors that might occur. Even ostensibly 3D dose calculation algorithms like finite-sized pencil beam or collapsed cone convolution/superposition significantly overestimate dose when compared to measurement, according to TG-219’s findings. Therefore, when making the long-overdue move to 3D plan second check, we are compromising the integrity of our treatment plans by not using the most robust class of independent dose calculation algorithm – Monte Carlo.
One leading approach to Monte Carlo dose recalculation comes from ScientificRT and their SciMoCa algorithm. Compared to an average of several other Monte Carlo algorithms, SciMoCa performs 120 times faster, while keeping deviations under 2%. SciMoCa runs on a CPU server, using variance reduction techniques that eliminate the need for costly and hard-to-acquire GPU servers. Through a robust beam modeling process, SciMoCa is able to minimize systematic errors that affect plan calculation for all patients. With support for a wide variety of plan types (including SRS-cone, electron, CyberKnife, Tomotherapy, and Zap-X), SciMoCa has long been and remains at the forefront of Monte Carlo dose calculation in radiation oncology QA.
MIM SureCalc® MonteCarlo leverages SciMoCa for plan second check and dose-guided adaptive assessment. MIM can perform these robust checks with minimal user input utilizing our industry-leading approach to flexible automation – giving you as much or as little control over your clinical processes as you prefer, while ensuring standardization when needed.
Reach out at the link below to schedule a demonstration on our sample cases or anonymized data of your own.
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Additional Reading:
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Kerns JR, Stingo F, Followill DS, Howell RM, Melancon A, Kry SF. Treatment Planning System Calculation Errors Are Present in Most Imaging and Radiation Oncology Core-Houston Phantom Failures. Int J Radiat Oncol Biol Phys. 2017 Aug 1;98(5):1197-1203. doi: 10.1016/j.ijrobp.2017.03.049. Epub 2017 Apr 4. PMID: 28721904; PMCID: PMC5567850.
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Kry SF, Glenn MC, Peterson CB, Branco D, Mehrens H, Steinmann A, Followill DS. Independent recalculation outperforms traditional measurement-based IMRT QA methods in detecting unacceptable plans. Med Phys. 2019 Aug;46(8):3700-3708. doi: 10.1002/mp.13638. Epub 2019 Jun 23. PMID: 31152568; PMCID: PMC6692191.
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Zhu TC, Stathakis S, Clark JR, Feng W, Georg D, Holmes SM, Kry SF, Charlie Ma CM, Miften M, Mihailidis D, Moran JM, Papanikolaou N, Poppe B, Xiao Y. Erratum: "Report of AAPM Task Group 219 on independent calculation-based dose/MU verification for IMRT". Med Phys. 2022 Aug;49(8):5713. doi: 10.1002/mp.15772. Epub 2022 Jul 14. Erratum for: Med Phys. 2021 Oct;48(10):e808-e829. PMID: 35833598.
1FAQs for the Practical Use of MIM SureCalc Monte Carlo
