Journal Article DKFZ-2021-02230

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Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting.

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2021
IOP Publ. Bristol

Physics in medicine and biology 66(20), 205003 () [10.1088/1361-6560/ac287f]
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Abstract: Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models.Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate.Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ2 mm/2%≥ 99.01% (E[d]),γ2 mm/2%≥ 98.04% (σ(d))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[d])/ 93.70% (σ(d)) (range errors) and 99.86% (E[d])/ 96.64% (σ(d)) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude.Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

Keyword(s): Monte Carlo ; importance sampling ; intensity modulated particle therapy (IMPT) ; proton therapy ; range error ; setup error ; uncertainty

Classification:

Note: #EA:E040#LA:E040#

Contributing Institute(s):
  1. E040 Med. Physik in der Strahlentherapie (E040)
Research Program(s):
  1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2021
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Medline ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; National-Konsortium ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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 Record created 2021-10-13, last modified 2024-02-29



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