Sensitivity and specificity of Monte Carlo based independent secondary dose computation for detecting modulation-related dose errors in intensity modulated radiotherapy

Background - The recent availability of Monte Carlo based independent secondary dose calculation (ISDC) for patient-specific quality assurance (QA) of modulated radiotherapy requires the definition of appropriate, more sensitive action levels, since contemporary recommendations were defined for less...

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Hauptverfasser: Kowatsch, Matthias (VerfasserIn) , Szeverinski, Philipp (VerfasserIn) , Clemens, Patrick (VerfasserIn) , Künzler, Thomas (VerfasserIn) , Söhn, Matthias (VerfasserIn) , Alber, Markus (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: August 2025
In: Zeitschrift für medizinische Physik
Year: 2025, Jahrgang: 35, Heft: 3, Pages: 259-269
ISSN:1876-4436
DOI:10.1016/j.zemedi.2023.10.001
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.zemedi.2023.10.001
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S0939388923001174
Volltext
Verfasserangaben:Matthias Kowatsch, Philipp Szeverinski, Patrick Clemens, Thomas Künzler, Matthias Söhn, Markus Alber

MARC

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520 |a Background - The recent availability of Monte Carlo based independent secondary dose calculation (ISDC) for patient-specific quality assurance (QA) of modulated radiotherapy requires the definition of appropriate, more sensitive action levels, since contemporary recommendations were defined for less accurate ISDC dose algorithms. - Purpose - The objective is to establish an optimum action level and measure the efficacy of a Monte Carlo ISDC software for pre-treatment QA of intensity modulated radiotherapy treatments. - Methods - The treatment planning system and the ISDC were commissioned by their vendors from independent base data sets, replicating a typical real-world scenario. In order to apply Receiver-Operator-Characteristics (ROC), a set of treatment plans for various case classes was created that consisted of 190 clinical treatment plans and 190 manipulated treatment plans with dose errors in the range of 1.5-2.5%. All 380 treatment plans were evaluated with ISDC in the patient geometry. ROC analysis was performed for a number of Gamma (dose-difference/distance-to-agreement) criteria. QA methods were ranked according to Area under the ROC curve (AUC) and optimum action levels were derived via Youden’s J statistics. - Results - Overall, for original treatment plans, the mean Gamma pass rate (GPR) for Gamma(1%, 1mm) was close to 90%, although with some variation across case classes. The best QA criterion was Gamma(2%, 1mm) with GPR>90% and an AUC of 0.928. Gamma criteria with small distance-to-agreement had consistently higher AUC. GPR of original treatment plans depended on their modulation degree. An action level in terms of Gamma(1%, 1mm) GPR that decreases with modulation degree was the most efficient criterion with sensitivity=0.91 and specificity=0.95, compared with Gamma(3%, 3mm) GPR>99%, sensitivity=0.73 and specificity=0.91 as a commonly used action level. - Conclusions - ISDC with Monte Carlo proves highly efficient to catch errors in the treatment planning process. For a Monte Carlo based TPS, dose-difference criteria of 2% or less, and distance-to-agreement criteria of 1mm, achieve the largest AUC in ROC analysis. 
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