Dose mapping sensitivity to deformable registration uncertainties in fractionated radiotherapy – applied to prostate proton treatments

Abstract

BackgroundCalculation of accumulated dose in fractionated radiotherapy based on spatial mapping of the dose points generally requires deformable image registration (DIR). The accuracy of the accumulated dose thus depends heavily on the DIR quality. This motivates investigations of how the registration uncertainty influences dose planning objectives and treatment outcome predictions.A framework was developed where the dose mapping can be associated with a variable known uncertainty to simulate the DIR uncertainties in a clinical workflow. The framework enabled us to study the dependence of dose planning metrics, and the predicted treatment outcome, on the DIR uncertainty. The additional planning margin needed to compensate for the dose mapping uncertainties can also be determined. We applied the simulation framework to a hypofractionated proton treatment of the prostate using two different scanning beam spot sizes to also study the dose mapping sensitivity to penumbra widths.ResultsThe planning parameter most sensitive to the DIR uncertainty was found to be the target D95. We found that the registration mean absolute error needs to be ≤0.20 cm to obtain an uncertainty better than 3% of the calculated D95 for intermediate sized penumbras. Use of larger margins in constructing PTV from CTV relaxed the registration uncertainty requirements to the cost of increased dose burdens to the surrounding organs at risk.ConclusionsThe DIR uncertainty requirements should be considered in an adaptive radiotherapy workflow since this uncertainty can have significant impact on the accumulated dose. The simulation framework enabled quantification of the accuracy requirement for DIR algorithms to provide satisfactory clinical accuracy in the accumulated dose.

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

“…Unfortunately, DIR is a high dimensional nonconvex problem, whose performance depends on numerous parameters such as type of algorithm, its implementation and image modality and quality . If used to calculate dose accumulation, small registration errors can cause significant dose errors in high gradient regions as shown by Tilly and Saleh‐Sayah …”

“…Hence, some groups proposed methods based on inverse consistency metrics or related to the Jacobian of the deformation fields to assure the plausibility of the physical characteristic of DVFs for clinical implementation of dose warping. Others investigated mathematical models relating the dose‐warping uncertainties to DIR errors, while experimental evaluation of both DIR and dose‐warping have been carried out using deformable dosimetric gels . Even though some studies showed promising results, the problem of the management of dose‐warping uncertainties in clinical settings remains an open area of research and a matter of debate, and is outside the aim of this paper.…”

Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm

“…Validation of DIR is a key aspect, therefore some authors have been evaluating the accuracy of DIR and dose warping using manually annotated points and structures, 5,6,12,13 physical plausibility of the transformations, 14,15 and by developing deformable and virtual phantoms with known deformations. [16][17][18][19] Others focused on estimating the accuracy requirements for dose warping 20,21 or estimating its precision. [22][23][24][25] Monte Carlo methods have also been proposed to recalculate doses using a deformed grid (with deformed and irregular voxels), which still uses DIR but minimizes the errors associated with dose interpolation.…”

“Patient‐specific validation of deformable image registration in radiation therapy: Overview and caveats”

“…57 The variance of these dose distributions revealed the pattern of dose mapping uncertainty arising from DVF uncertainties. Tilly et al 140 created a different model, by sampling DIR errors at a sparse grid of control points which was then applied to the denser dose grid by means of 3-D cubic interpolation. They studied the impact of the dose mapping uncertainties on the radiobiological outcome metrics for spot scanned proton therapy of the prostate, concluding that an uncertainty of the dose to the 95% of the tumor volume (D 95% ) less than 3% and a tumor control probability uncertainty less than 2% would require a mean absolute DIR error better than 2.5 and 3.5 mm, respectively.…”