Rectum motion and morbidity prediction: Improving correlation between late morbidity and DVH parameters through use of rectum planning organ at risk volumes

Computational analysis of interfractional anisotropic shape variations of the rectum in prostate cancer radiation therapy

PURPOSE

To analyze the uncertainties of the rectum due to anisotropic shape variations by using a statistical point distribution model (PDM).

MATERIALS AND METHODS

The PDM was applied to the rectum contours that were delineated on planning computed tomography (CT) and cone-beam CT (CBCT) at 80 fractions of 11 patients. The standard deviations (SDs) of systematic and random errors of the shape variations of the whole rectum and the region in which the rectum overlapped with the PTV (ROP regions) were derived from the PDMs at all fractions of each patient. The systematic error was derived by using the PDMs of planning and average rectum surface determined from rectum surfaces at all fractions, while the random error was derived by using a PDM-based covariance matrix at all fractions of each patient.

RESULTS

Regarding whole rectum, the population SDs were larger than 1.0 mm along all directions for random error, and along the anterior, superior, and inferior directions for systematic error. The deviation is largest along the superior and inferior directions for systematic and random errors, respectively. For ROP regions, the population SDs of systematic error were larger than 1.0 mm along the superior and inferior directions. The population SDs of random error for the ROP regions were larger than 1.0 mm except along the right and posterior directions.

CONCLUSIONS

The anisotropic shape variations of the rectum, especially in the ROP regions, should be considered when determining a planning risk volume (PRV) margins for the rectum associated with the acute toxicities.

Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy

In radiotherapy for prostate cancer irradiation of neighboring organs at risk may lead to undesirable side-effects. Given this setting, the bladder presents the largest inter-fraction shape variations hampering the computation of the actual delivered dose vs. planned dose. This paper proposes a population model, based on longitudinal data, able to estimate the probability of bladder presence during treatment, using only the planning computed tomography (CT) scan as input information. As in previously-proposed principal component analysis (PCA) population-based models, we have used the data to obtain the dominant eigenmodes that describe bladder geometric variations between fractions. However, we have used a longitudinal analysis along each mode in order to properly characterize patient's variance from the total population variance. We have proposed is a mixed-effects (ME) model in order to separate intra- and inter-patient variability, in an effort to control confounding cohort effects. Other than using PCA, bladder shapes are represented by using spherical harmonics (SPHARM) that additionally enables data compression without information lost. Based on training data from repeated CT scans, the ME model was thus implemented following dimensionality reduction by means of SPHARM and PCA. We have evaluated the model in a leave-one-out cross validation framework on the training data but also using independent data. Probability maps (PMs) were thus generated with several draws from the learnt model as predicted regions where the bladder will likely move and deform. These PMs were compared with the actual regions using metrics based on mutual information distance and misestimated voxels. The prediction was also compared with two previous population PCA-based models. The proposed model was able to reduce the uncertainties in the estimation of the probable region of bladder motion and deformation. This model can thus be used for tailoring radiotherapy treatments.

On voxel-by-voxel accumulated dose for prostate radiation therapy using deformable image registration

Since delivered dose is rarely the same with planned, we calculated the delivered total dose to ten prostate radiotherapy patients treated with rectal balloons using deformable dose accumulation (DDA) and compared it with the planned dose. The patients were treated with TomoTherapy using two rectal balloon designs: five patients had the Radiadyne balloon (balloon A), and five patients had the EZ-EM balloon (balloon B). Prostate and rectal wall contours were outlined on each pre-treatment MVCT for all patients. Delivered fractional doses were calculated using the MVCT taken immediately prior to delivery. Dose grids were accumulated to the last MVCT using DDA tools in Pinnacle3 TM (v9.100, Philips Radiation Oncology Systems, Fitchburg, USA). Delivered total doses were compared with planned doses using prostate and rectal wall DVHs. The rectal NTCP was calculated based on total delivered and planned doses for all patients using the Lyman model. For 8/10 patients, the rectal wall NTCP calculated using the delivered total dose was less than planned, with seven patients showing a decrease of more than 5% in NTCP. For 2/10 patients studied, the rectal wall NTCP calculated using total delivered dose was 2% higher than planned. This study indicates that for patients receiving hypofractionated radiotherapy for prostate cancer with a rectal balloon, total delivered doses to prostate is similar with planned while delivered dose to rectal walls may be significantly different from planned doses. 8/10 patients show significant correlation between rectal balloon anterior-posterior positions and some VD values.

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.

A study on planning organ at risk volume for the rectum using cone beam computed tomography in the treatment of prostate cancer

In this study, we analyzed planning organ at risk volume (PRV) for the rectum using a series of cone beam computed tomographies (CBCTs) acquired during the treatment of prostate cancer and evaluated the dosimetric effect of different PRV definitions. Overall, 21 patients with prostate cancer were treated radically with 78Gy in 39 fractions had in total 418 CBCTs, each acquired at the end of the first 5 fractions and then every alternate fraction. The PRV was generated from the Boolean sum volume of the rectum obtained from first 5 fractions (PRV-CBCT-5) and from all CBCTs (PRV-CBCT-All). The PRV margin was compared at the superior, middle, and inferior slices of the contoured rectum to compare PRV-CBCT-5 and PRV-CBCT-All. We also compared the dose received by the planned rectum (Rectum-computed tomography [CT]), PRV-CBCT-5, PRV-CBCT-All, and average rectum (CBCT-AV-dose-volume histogram [DVH]) at critical dose levels. The average measured rectal volume for all 21 patients for Rectum-CT, PRV-CBCT-5, and PRV-CBCT-All was 44.3 ± 15.0, 92.8 ± 40.40, and 121.5 ± 36.7cm(3), respectively. For PRV-CBCT-All, the mean ± standard deviation displacement in the anterior, posterior, right, and left lateral directions in centimeters was 2.1 ± 1.1, 0.9 ± 0.5, 0.9 ± 0.8, and 1.1 ± 0.7 for the superior rectum; 0.8 ± 0.5, 1.1 ± 0.5, 1.0 ± 0.5, and 1.0 ± 0.5 for the middle rectum; and 0.3 ± 0.3; 0.9 ± 0.5; 0.4 ± 0.2, and 0.5 ± 0.3 for the inferior rectum, respectively. The first 5 CBCTs did not predict the PRV for individual patients. Our study shows that the PRV margin is different for superior, middle, and the inferior parts of the rectum, it is wider superiorly and narrower inferiorly. A uniform PRV margin does not represent the actual rectal variations during treatment for all treatment fractions. The large variation in interpatient rectal size implies a potential role for adaptive radiotherapy for prostate cancer.

Dose/volume-response relations for rectal morbidity using planned and simulated motion-inclusive dose distributions

BACKGROUND AND PURPOSE

Many dose-limiting normal tissues in radiotherapy (RT) display considerable internal motion between fractions over a course of treatment, potentially reducing the appropriateness of using planned dose distributions to predict morbidity. Accounting explicitly for rectal motion could improve the predictive power of modelling rectal morbidity. To test this, we simulated the effect of motion in two cohorts.

MATERIALS AND METHODS

The included patients (232 and 159 cases) received RT for prostate cancer to 70 and 74 Gy. Motion-inclusive dose distributions were introduced as simulations of random or systematic motion to the planned dose distributions. Six rectal morbidity endpoints were analysed. A probit model using the QUANTEC recommended parameters was also applied to the cohorts.

RESULTS

The differences in associations using the planned over the motion-inclusive dose distributions were modest. Statistically significant associations were obtained with four of the endpoints, mainly at high doses (55-70 Gy), using both the planned and the motion-inclusive dose distributions, primarily when simulating random motion. The strongest associations were observed for GI toxicity and rectal bleeding (Rs=0.12-0.21; Rs=0.11-0.20). Applying the probit model, significant associations were found for tenesmus and rectal bleeding (Rs=0.13, p=0.02).

CONCLUSION

Equally strong associations with rectal morbidity were observed at high doses (>55 Gy), for the planned and the simulated dose distributions including in particular random rectal motion. Future studies should explore patient-specific descriptions of rectal motion to achieve improved predictive power.

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.

Deformable image registration for contour propagation from CT to cone-beam CT scans in radiotherapy of prostate cancer

BACKGROUND AND PURPOSE

Daily organ motion occurring during the course of radiotherapy in the pelvic region leads to uncertainties in the doses delivered to the tumour and the organs at risk. Motion patterns include both volume and shape changes, calling for deformable image registration (DIR), in approaches involving dose accumulation and adaptation. In this study, we tested the performance of a DIR application for contour propagation from the treatment planning computed tomography (pCT) to repeat cone-beam CTs (CBCTs) for a set of prostate cancer patients.

MATERIAL AND METHODS

The prostate, rectum and bladder were delineated in the pCT and in six to eight repeat CBCTs for each of five patients. The pCT contours were propagated onto the corresponding CBCT using the Multi-modality Image Registration and Segmentation application, resulting in 36 registrations. Prior to the DIR, a rigid registration was performed. The algorithm used for the DIR was based on a 'demons' algorithm and the performance of it was examined quantitatively using the Dice similarity coefficient (DSC) and qualitatively as visual slice-by-slice scoring by a radiation oncologist grading the deviations in shape and/or distance relative to the anatomy.

RESULTS

The average DSC (range) for the DIR over all scans and patients was 0.80 (0.65-0.87) for prostate, 0.77 (0.63-0.87) for rectum and 0.73 (0.34-0.91) for bladder, while the corresponding DSCs for the rigid registrations were 0.77 (0.65-0.86), 0.71 (0.55-0.82) and 0.64 (0.33-0.87). The percentage of propagated contours of good/acceptable quality was 45% for prostate; 20% for rectum and 33% for bladder. For the bladder, there was an association between the average DSC and the different scores of the qualitative evaluation.

CONCLUSIONS

DIR improved the performance of pelvic organ contour propagation from the pCT to CBCTs as compared to rigid registration only. Still, a large fraction of the propagated rectum and bladder contours were unacceptable. The image quality of the CBCTs was sub-optimal and the usability of CBCTs for dose accumulation and adaptation purposes is therefore likely to benefit from improved image quality and improvements of the DIR algorithm.