PlanJury: probabilistic plan evaluation revisited

Purpose: Over a decade ago, the 'Van Herk margin recipe paper' introduced plan evaluation through DVH statistics based on population distributions of systematic and random errors. We extended this work for structures with correlated uncertainties (e.g. lymph nodes or parotid glands), and considered treatment plans containing multiple (overlapping) dose distributions (e.g. conventional lymph node and hypo-fractionated tumor doses) for which different image guidance protocols may lead to correlated errors.

Methods: A command-line software tool 'PlanJury' was developed which reads 3D dose and structure data exported from a treatment planning system. Uncertainties are specified by standard deviations and correlation coefficients. Parameters control the DVH statistics to be computed: e.g. the probability of reaching a DVH constraint, or the dose absorbed at given confidence in a (combined) volume. Code was written in C++ and parallelized using OpenMP. Testing geometries were constructed using idealized spherical volumes and dose distributions.

Results: Negligible stochastic noise could be attained within two minutes computation time for a single target. The confidence to properly cover both of two targets was 90% for two synchronously moving targets, but decreased by 7% if the targets moved independently. For two partially covered organs at risk the confidence of at least one organ below the mean dose threshold was 40% for synchronous motion, 36% for uncorrelated motion, but only 20% for either of the organs separately. Two abutting dose distributions ensuring 91% confidence of proper target dose for correlated motions led to 28% lower confidence for uncorrelated motions as relative displacements between the doses resulted in cold spots near the target.

Conclusions: Probabilistic plan evaluation can efficiently be performed for complicated treatment planning situations, thus providing important plan quality information unavailable in conventional PTV based evaluations.