Direct aperture optimization for online adaptive radiation therapy

Abstract

This paper is the first investigation of using direct aperture optimization (DAO) for online adaptive radiation therapy (ART). A geometrical model representing the anatomy of a typical prostate case was created. To simulate interfractional deformations, four different anatomical deformations were created by systematically deforming the original anatomy by various amounts (0.25, 0.50, 0.75, and 1.00 cm). We describe a series of techniques where the original treatment plan was adapted in order to correct for the deterioration of dose distribution quality caused by the anatomical deformations. We found that the average time needed to adapt the original plan to arrive at a clinically acceptable plan is roughly half of the time needed for a complete plan regeneration, for all four anatomical deformations. Furthermore, through modification of the DAO algorithm the optimization search space was reduced and the plan adaptation was significantly accelerated. For the first anatomical deformation (0.25 cm), the plan adaptation was six times more efficient than the complete plan regeneration. For the 0.50 and 0.75 cm deformations, the optimization efficiency was increased by a factor of roughly 3 compared to the complete plan regeneration. However, for the anatomical deformation of 1.00 cm, the reduction of the optimization search space during plan adaptation did not result in any efficiency improvement over the original (nonmodified) plan adaptation. The anatomical deformation of 1.00 cm demonstrates the limit of this approach. We propose an innovative approach to online ART in which the plan adaptation and radiation delivery are merged together and performed concurrently-adaptive radiation delivery (ARD). A fundamental advantage of ARD is the fact that radiation delivery can start almost immediately after image acquisition and evaluation. Most of the original plan adaptation is done during the radiation delivery, so the time spent adapting the original plan does not increase the overall time the patient has to spend on the treatment couch. As a consequence, the effective time allotted for plan adaptation is drastically reduced. For the 0.25, 0.5, and 0.75 cm anatomical deformations, the treatment time was increased by only 2, 4, and 6 s, respectively, as compared to no plan adaptation. For the anatomical deformation of 1.0 cm the time increase was substantially larger. The anatomical deformation of 1.0 cm represents an extreme case, which is rarely observed for the prostate, and again demonstrates the limit of this approach. ARD shows great potential for an online adaptive method with minimal extension of treatment time.

Search for IMRT inverse plans with piecewise constant fluence maps using compressed sensing techniques

“…15,16 Segment-based optimization algorithms achieve small numbers of segments by imposing the physical constraints of beam apertures in the optimization. [7][8][9][10][11][12][13][14]28 In a sense, this is similar to what many investigators have done in the context of 3D conformal therapy plan optimization, where the machine related parameters such as the beam weights and wedge angles are optimized. These algorithms eventually search in a space of all possible segments for a sparse optimal solution.…”

“…Segment-based methods tackle the problem from the delivery aspect typically by enforcing a prechosen ͑often unjustified͒ number of segments for each incident beam and then optimizing the shapes and weights of the apertures. [7][8][9][10][11][12][13][14] However, searching for an optimal solution by using segmentbased optimization is inherently complicated because of the highly nonconvex dependence of the objective function on the multi-leaf collimator ͑MLC͒ coordinates and the optimality of the final solution is not always guaranteed when an iterative algorithm is used.…”

Dosimetric assessment of rigid setup error by CBCT for HN‐IMRT

“…This is an important finding because of the growing interest in adaptive radiotherapy, ( 27 – 28 ) where the average fractional dose, which is easier to calculate, is often used to estimate the actual dose received by the patient. The main reason for the differences is due to the fact that the random setup error is larger than the systematic.…”

Stochastic programming for off-line adaptive radiotherapy

“…Based on these measurements, treatment is then adjusted for future fractions. Online ART, on the other hand, attempts to adapt the treatment to variations during the delivery of a fraction (Mestrovic et al 2007;Thongphiew et al 2008). Unlike online ART, in off-line ART, a more thorough and careful analysis of measurement data can be performed after the delivery.…”