Evaluation of a new method for calculation of cumulative doses in the rectum wall using repeat CT scans

Deformable image registration for radiation therapy: principle, methods, applications and evaluation

Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process. Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.

Evaluation of an application for intensity-based deformable image registration and dose accumulation in radiotherapy

BACKGROUND

Methods to accurately accumulate doses in radiotherapy (RT) are important for tumour and normal tissues being influenced by geometric uncertainties. The purpose of this study was to investigate a pre-release deformable image registration (DIR)-based dose accumulation application, in the setting of prostate RT.

MATERIAL AND METHODS

Initially accumulated bladder and prostate doses were assessed (based on 8-9 repeat CT scans/patient) for nine prostate cancer patients using an intensity-based DIR and dose accumulation algorithm as provided by the Dynamic Adaptive Radiation Therapy (DART) software. The accumulated bladder and prostate dose-volume histograms (DVHs) were compared on a range of parameters (paired Wilcoxon signed-rank test, 5% significance level) to DVHs derived using an in-house developed dose accumulation method based on biomechanical, contour-driven DIR (SurfaceRegistration). Finally, both these accumulated dose distributions were compared to the 'static' DVH, assessed from the planning CT.

RESULTS

Over the population, doses accumulated with DART were overall lower than those from SurfaceRegistration (p < 0.05: D2%, gEUD and NTCP (bladder); Dmin (prostate)). The magnitude of these differences peaked for the bladder gEUD with a population median of 47 Gy for DART versus 57 Gy for SurfaceRegistration. Across the ten bladder dose/volume parameters investigated, the most pronounced individual differences were observed between the 'accumulated' DVHs and the 'static' DVHs, with deviations in mean dose up to 22 Gy.

CONCLUSION

Substantial and significant differences were observed in the dose distributions between the two investigated DIR-based dose accumulation applications. The most pronounced individual differences were seen for the bladder and relative to the planned dose distribution, encouraging the use of repeat imaging data in RT planning and evaluation for this organ.

Prediction of rectum and bladder morbidity following radiotherapy of prostate cancer based on motion-inclusive dose distributions

BACKGROUND AND PURPOSE

In radiotherapy (RT) of prostate cancer the key organs at risk (ORs) - the rectum and the bladder - display considerable motion, which may influence the dose/volume parameters predicting for morbidity. In this study we compare motion-inclusive doses to planned doses for the rectum and bladder and explore their associations with prospectively recorded morbidity.

MATERIALS AND METHODS

The study included 38 prostate cancer patients treated with hypo-fractionated image-guided intensity-modulated RT that had an average of nine repeat CT scans acquired during treatment. These scans were registered to the respective treatment planning CT (pCT) followed by a new dose calculation from which motion-inclusive dose distributions were derived. The pCT volumes, the treatment course averaged volumes as well as the planned and motion-inclusive doses were associated with acute and late morbidity (morbidity cut-off: ≥ Grade 2).

RESULTS

Acute rectal morbidity (observed in 29% of cases) was significantly associated with both smaller treatment course averaged rectal volumes (population median: 75 vs. 94 cm(3)) and the motion-inclusive volume receiving doses close to the prescription dose (2 Gy-equivalent dose of 76 Gy).

CONCLUSION

Variation in rectum and bladder volumes leads to deviations between planned and delivered dose/volume parameters that should be accounted for to improve the ability to predict morbidity following RT.

Statistical simulations to estimate motion-inclusive dose-volume histograms for prediction of rectal morbidity following radiotherapy

BACKGROUND AND PURPOSE

Internal organ motion over a course of radiotherapy (RT) leads to uncertainties in the actual delivered dose distributions. In studies predicting RT morbidity, the single estimate of the delivered dose provided by the treatment planning computed tomography (pCT) is typically assumed to be representative of the dose distribution throughout the course of RT. In this paper, a simple model for describing organ motion is introduced, and is associated to late rectal morbidity data, with the aim of improving morbidity prediction.

MATERIAL AND METHODS

Organ motion was described by normally distributed translational motion, with its magnitude characterised by the standard deviation (SD) of this distribution. Simulations of both isotropic and anisotropic (anterior-posterior only) motion patterns were performed, as were random, systematic or combined random and systematic motion. The associations between late rectal morbidity and motion-inclusive delivered dose-volume histograms (dDVHs) were quantified using Spearman's rank correlation coefficient (Rs) in a series of 232 prostate cancer patients, and were compared to the associations obtained with the static/planned DVH (pDVH).

RESULTS

For both isotropic and anisotropic motion, different associations with rectal morbidity were seen with the dDVHs relative to the pDVHs. The differences were most pronounced in the mid-dose region (40-60 Gy). The associations were dependent on the applied motion patterns, with the strongest association with morbidity obtained by applying random motion with an SD in the range 0.2-0.8 cm.

CONCLUSION

In this study we have introduced a simple model for describing organ motion occurring during RT. Differing and, for some cases, stronger dose-volume dependencies were found between the motion-inclusive dose distributions and rectal morbidity as compared to the associations with the planned dose distributions. This indicates that rectal organ motion during RT influences the efforts to model the risk of morbidity using planning distributions alone.

A Monte Carlo study of the impact of the choice of rectum volume definition on estimates of equivalent uniform doses and the volume parameter

Calculations of normal tissue complication probability (NTCP) values for the rectum are difficult because it is a hollow, non-rigid, organ. Finding the true cumulative dose distribution for a number of treatment fractions requires a CT scan before each treatment fraction. This is labour intensive, and several surrogate distributions have therefore been suggested, such as dose wall histograms, dose surface histograms and histograms for the solid rectum, with and without margins. In this study, a Monte Carlo method is used to investigate the relationships between the cumulative dose distributions based on all treatment fractions and the above-mentioned histograms that are based on one CT scan only, in terms of equivalent uniform dose. Furthermore, the effect of a specific choice of histogram on estimates of the volume parameter of the probit NTCP model was investigated. It was found that the solid rectum and the rectum wall histograms (without margins) gave equivalent uniform doses with an expected value close to the values calculated from the cumulative dose distributions in the rectum wall. With the number of patients available in this study the standard deviations of the estimates of the volume parameter were large, and it was not possible to decide which volume gave the best estimates of the volume parameter, but there were distinct differences in the mean values of the values obtained.