TY  - JOUR
AU  - Wahl, Niklas
AU  - Hennig, P.
AU  - Wieser, H. P.
AU  - Bangert, Mark
TI  - Efficiency of analytical and sampling-based uncertainty propagation in intensity-modulated proton therapy.
JO  - Physics in medicine and biology
VL  - 62
IS  - 14
SN  - 1361-6560
CY  - Bristol
PB  - IOP Publ.
M1  - DKFZ-2017-01369
SP  - 5790 - 5807
PY  - 2017
AB  - The sensitivity of intensity-modulated proton therapy (IMPT) treatment plans to uncertainties can be quantified and mitigated with robust/min-max and stochastic/probabilistic treatment analysis and optimization techniques. Those methods usually rely on sparse random, importance, or worst-case sampling. Inevitably, this imposes a trade-off between computational speed and accuracy of the uncertainty propagation. Here, we investigate analytical probabilistic modeling (APM) as an alternative for uncertainty propagation and minimization in IMPT that does not rely on scenario sampling. APM propagates probability distributions over range and setup uncertainties via a Gaussian pencil-beam approximation into moments of the probability distributions over the resulting dose in closed form. It supports arbitrary correlation models and allows for efficient incorporation of fractionation effects regarding random and systematic errors. We evaluate the trade-off between run-time and accuracy of APM uncertainty computations on three patient datasets. Results are compared against reference computations facilitating importance and random sampling. Two approximation techniques to accelerate uncertainty propagation and minimization based on probabilistic treatment plan optimization are presented. Runtimes are measured on CPU and GPU platforms, dosimetric accuracy is quantified in comparison to a sampling-based benchmark (5000 random samples). APM accurately propagates range and setup uncertainties into dose uncertainties at competitive run-times (GPU [Formula: see text] min). The resulting standard deviation (expectation value) of dose show average global [Formula: see text] pass rates between 94.2
LB  - PUB:(DE-HGF)16
C6  - pmid:28649976
DO  - DOI:10.1088/1361-6560/aa6ec5
UR  - https://inrepo02.dkfz.de/record/125214
ER  -