Beyond the margin recipe: the probability of correct target dosage and tumor control in the presence of a dose limiting structure

Abstract

In the past, hypothetical spherical target volumes and ideally conformal dose distributions were analyzed to establish the safety of planning target volume (PTV) margins. In this work we extended these models to estimate how alternative methods of shaping dose distributions could lead to clinical improvements. Based on a spherical clinical target volume (CTV) and Gaussian distributions of systematic and random geometrical uncertainties, idealized 3D dose distributions were optimized to exhibit specific stochastic properties. A nearby spherical organ at risk (OAR) was introduced to explore the benefit of non-spherical dose distributions. Optimizing for the same minimum dose safety criterion as implied by the generally accepted use of a PTV, the extent of the high dose region in one direction could be reduced by half provided that dose in other directions is sufficiently compensated. Further reduction of this unilateral dosimetric margin decreased the target dose confidence, however the actual minimum CTV dose at 90% confidence typically exceeded the minimum PTV dose by 20% of prescription. Incorporation of smooth dose-effect relations within the optimization led to more concentrated dose distributions compared to the use of a PTV, with an improved balance between the probability of tumor cell kill and the risk of geometrical miss, and lower dose to surrounding tissues. Tumor control rate improvements in excess of 20% were found to be common for equal integral dose, while at the same time evading a nearby OAR. These results were robust against uncertainties in dose-effect relations and target heterogeneity, and did not depend on ‘shoulders’ or ‘horns’ in the dose distributions.

The clinical target distribution: a probabilistic alternative to the clinical target volume

“…In the case of the CTD it is not obvious how to add the PTV margin. However, a more advanced recent approach to handle spatial uncertainties is through robust, probabilistic, and 4D optimization (Fredriksson, 2012, Chen et al, 2012, Trofimov et al, 2005, Witte et al, 2018, which can be applied in a straight-forward manner to the CTD-based plan.…”

Evaluation of OAR dose sparing and plan robustness of beam-specific PTV in lung cancer IMRT treatment

“…This allowed physicists and physicians to identify the most suitable trade-off between target coverage and sparing of surrounding normal tissues at the treatment planning stage, without having to modify or redraw a CTV. In addition, Witte et al [16] also tested the probabilistic planning margin volume concepts in the simulated phantom. Watkins et al [17] defined the definite target volume to deliver extremely high doses to sub-volumes of PTVs in multiple treatment sites.…”

Composite minimax robust optimization of VMAT improves target coverage and reduces non-target dose in head and neck cancer patients

“…PTV-less optimization approaches have been described in literature that provide a superior balance between tumor control rate and normal tissue toxicity. These optimization approaches are referred to as robust optimization [4][5][6][7][8][9][10].…”

“…The probabilistic approach consists of optimizing the expectation value of objectives based on an a priori probability density function of geometric errors. Recently, Witte et al investigated the potential clinical benefit of PTV-less probabilistic planning in a spherical phantom [10]. They demonstrated that an indentation of the 95% dose level by one third of the margin size at a strictly uniform dose distribution at prescription level is feasible without sacrificing tumor dose confidence.…”