How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?a)

Abstract

The purpose of this study was to investigate the number of intermediate states required to adequately approximate the clinically relevant cumulative dose to deforming/moving thoracic anatomy in four-dimensional (4D) conformal radiotherapy that uses 6 MV photons to target tumors. Four patients were involved in this study. For the first three patients, computed tomography images acquired at exhale and inhale were available; they were registered using B-spline deformation model and the computed transformation was further used to simulate intermediate states between exhale and inhale. For the fourth patient, 4D-acquired, phase-sorted datasets were available and each dataset was registered with the exhale dataset. The exhale-inhale transformation was also used to simulate intermediate states in order to compare the cumulative doses computed using the actual and the simulated datasets. Doses to each state were calculated using the Dose Planning Method (DPM) Monte Carlo code and dose was accumulated for scoring on the exhale anatomy via the transformation matrices for each state and time weighting factors. Cumulative doses were estimated using increasing numbers of intermediate states and compared to simpler scenarios such as a "2-state" model which used only the exhale and inhale datasets or the dose received during the average phase of the breathing cycle. Dose distributions for each modeled state as well as the cumulative doses were assessed using dose volume histograms and several treatment evaluation metrics such as mean lung dose, normal tissue complication probability, and generalized uniform dose. Although significant "point dose" differences can exist between each breathing state, the differences decrease when cumulative doses are considered, and can become less significant yet in terms of evaluation metrics depending upon the clinical end point. This study suggests that for certain "clinical" end points of importance for lung cancer, satisfactory predictions of accumulated total dose to be received by the distorting anatomy can be achieved by calculating the dose to but a few (or even simply the average) phases of the breathing cycle.

A simplified method of four‐dimensional dose accumulation using the mean patient density representation

“…4,5,10 Furthermore, recalculation of the dose on daily 4DCT images would result in hundreds of required dose calculations, which is not feasible in the clinic today. Therefore, efforts to simplify 4D dose calculation and planning using 4DCT datasets have been proposed by including fewer breathing phases 9 or using the midventilation phase. 14,15 Some groups have also averaged the CT density over the entire breathing cycle to create an average 4DCT ͑AVG-CT͒ and utilized that image set for dose calculation.…”

“…[4][5][6][7][8][9][10] Briefly, these methods rely on dose calculation to patient datasets representing multiple instances of the patient anatomy ͑both intraand interfraction͒, and an algorithm to then accumulate these multiple dose instances to a reference geometry of the patient. Both 4DCT and 4D dose accumulation are integral components of image-guided adaptive radiation therapy ͑IG-ART͒, which uses patient-specific dynamic or temporal information for treatment planning and potential modifications during treatment.…”

Analysis of deformable image registration accuracy using computational modeling

“…[6][7][8] An important aspect of DIR is the validation process, which is necessary in the development of 4D or adaptive radiotherapy techniques, which deliver nonuniform dose distributions to different parts of the target volume and organs at risk. A clinical workflow recently described by Yan 2 for adaptive radiotherapy highlighted the need for quality assurance of DIR.…”

Evaluation of dosimetric misrepresentations from 3D conventional planning of liver SBRT using 4D deformable dose integration

“…Clinical application of dose‐warping techniques is a contentious topic as reflected by, for instance, a recent point‐counterpoint article and correspondences published by Medical Physics which raised the question, ‘Is it appropriate to “deform” dose along with deformable image registration in adaptive radiotherapy?’ (33) Although the answer is not likely to be without complexity, a number of published studies have shown the applicability of dose‐warping techniques 9 , 10 , 11 , 14 , 15 , 16 , 17 . We have previously corresponded to the point‐counterpoint article 34 , 35 following earlier work in which we demonstrated an experimental validation of the dose‐warping technique, as well as accurate performance of deformable registration algorithms (13) .…”

“…Previous studies have focused primarily on the case of pulmonary lesions 14 , 15 , 16 , 17 . However, like the lung, the liver is an organ that undergoes significant deformation due to respiration 5 , 18 .…”