An energy transfer method for 4D Monte Carlo dose calculation

Monte Carlo dose calculation for photon and electron radiotherapy on dynamically deforming anatomy

BACKGROUND

Dose calculation in radiotherapy aims to accurately estimate and assess the dose distribution of a treatment plan. Monte Carlo (MC) dose calculation is considered the gold standard owing to its ability to accurately simulate particle transport in inhomogeneous media. However, uncertainties such as the patient's dynamically deforming anatomy can still lead to differences between the delivered and planned dose distribution.

PURPOSE

Development and validation of a deformable voxel geometry for MC dose calculations (DefVoxMC) to account for dynamic deformation in the dose calculation process of photon- and electron-based radiotherapy treatment plans for clinically motivated cases.

METHODS

DefVoxMC relies on the subdivision of a regular voxel geometry into dodecahedrons. It allows shifting the dodecahedrons' corner points according to the deformation in the patient's anatomy using deformation vector fields (DVF). DefVoxMC is integrated into the Swiss Monte Carlo Plan (SMCP) to allow the MC dose calculation of photon- and electron-based treatment plans on the deformable voxel geometry. DefVoxMC is validated in two steps. A compression test and a Fano test are performed in silico. Delta4 (for photon beams) and EBT4 film measurements in a cubic PMMA phantom (for electron beams) are performed on a TrueBeam in Developer Mode for clinically motivated treatment plans. During these measurements, table motion is used to mimic rigid dynamic patient motion. The measured and calculated dose distributions are compared using gamma passing rate (GPR) (3% / 2 mm (global), 10% threshold). DefVoxMC is used to study the impact of patient-recorded breathing motion on the dose distribution for clinically motivated lung and breast cases, each prescribed 50 Gy to 50% of the target volume. A volumetric modulated arc therapy (VMAT) and an arc mixed-beam radiotherapy (Arc-MBRT) plan are created for the lung and breast case, respectively. For the dose calculation, the dynamic deformation of the patient's anatomy is described by DVFs obtained from deformable image registration of the different phases of 4DCTs. The resulting dose distributions are compared to the ones of the static situation using dose-volume histograms and dose differences.

RESULTS

DefVoxMC is successfully integrated into the SMCP to enable the MC dose calculation of photon- and electron-based treatments on a dynamically deforming patient anatomy. The compression and the Fano test agree within 1.0% and 0.1% with the expected result, respectively. Delta4 and EBT4 film measurements agree with the calculated dose by a GPR >95%. For the clinically motivated cases, breathing motion resulted in areas with a dose increase of up to 26.9 Gy (lung) and up to 7.6 Gy (breast) compared to the static situation. The largest dose differences are observed in high-dose-gradient regions perpendicular to the beam plane, consequently decreasing the planning target volume coverage (V95%) by 4.2% for the lung case and 2.0% for the breast case.

CONCLUSIONS

A novel method for MC dose calculation for photon- and electron-based treatments on dynamically deforming anatomy is successfully developed and validated. Applying DefVoxMC to clinically motivated cases, we found that breathing motion has non-negligible impact on the dosimetric plan quality.

A multi-institutional comparison of retrospective deformable dose accumulation for online adaptive magnetic resonance-guided radiotherapy

Background and Purpose

Application of different deformable dose accumulation (DDA) solutions makes institutional comparisons after online-adaptive magnetic resonance-guided radiotherapy (OA-MRgRT) challenging. The aim of this multi-institutional study was to analyze accuracy and agreement of DDA-implementations in OA-MRgRT.

Material and Methods

One gold standard (GS) case deformed with a biomechanical-model and five clinical cases consisting of prostate (2x), cervix, liver, and lymph node cancer, treated with OA-MRgRT, were analyzed. Six centers conducted DDA using institutional implementations. Deformable image registration (DIR) and DDA results were compared using the contour metrics Dice Similarity Coefficient (DSC), surface-DSC, Hausdorff-distance (HD95%), and accumulated dose-volume histograms (DVHs) analyzed via intraclass correlation coefficient (ICC) and clinical dosimetric criteria (CDC).

Results

For the GS, median DDA errors ranged from 0.0 to 2.8 Gy across contours and implementations. DIR of clinical cases resulted in DSC > 0.8 for up to 81.3% of contours and a variability of surface-DSC values depending on the implementation. Maximum HD95%=73.3 mm was found for duodenum in the liver case. Although DVH ICC > 0.90 was found after DDA for all but two contours, relevant absolute CDC differences were observed in clinical cases: Prostate I/II showed maximum differences in bladder V28Gy (10.2/7.6%), while for cervix, liver, and lymph node the highest differences were found for rectum D2cm3 (2.8 Gy), duodenum Dmax (7.1 Gy), and rectum D0.5cm3 (4.6 Gy).

Conclusion

Overall, high agreement was found between the different DIR and DDA implementations. Case- and algorithm-dependent differences were observed, leading to potentially clinically relevant results. Larger studies are needed to define future DDA-guidelines.

Radiation therapy margin reduction for patients with localized prostate cancer: A prospective study of the dosimetric impact and quality of life

OBJECTIVES

To investigate the impact of reducing Clinical Target Volume (CTV) to Planning Target Volume (PTV) margins on delivered radiation therapy (RT) dose and patient reported quality-of-life (QOL) for patients with localized prostate cancer.

METHODS

Twenty patients were included in a single institution IRB-approved prospective study. Nine were planned with reduced margins (4 mm at prostate/rectum interface, 5 mm elsewhere), and 11 with standard margins (6/10 mm). Cumulative delivered dose was calculated using deformable dose accumulation. Each daily CBCT dataset was deformed to the planning CT (pCT), dose was computed, and accumulated on the resampled pCT using a parameter-optimized, B-spline algorithm (Elastix, ITK/VTK). EPIC-26 patient reported QOL was prospectively collected pre-treatment, post-treatment, and at 2-, 6-, 12-, 18-, 24-, 36-, 48-, and 60-month follow-ups. Post -RT QOL scores were baseline corrected and standardized to a [0-100] scale using EPIC-26 methodology. Correlations between QOL scores and dosimetric parameters were investigated, and the overall QOL differences between the two groups (QOLMargin-reduced -QOLcontrol ) were calculated.

RESULTS

The median QOL follow-up length for the 20 patients was 48 months. Difference between delivered dose and planned dose did not reach statistical significance (p > 0.1) for both targets and organs at risk between the two groups. At 4 years post-RT, standardized mean QOLMargin-reduced -QOLcontrol were improved for Urinary Incontinence, Urinary Irritative/Obstructive, Bowel, and Sexual EPIC domains by 3.5, 14.8, 10.2, and 16.1, respectively (higher values better). The control group showed larger PTV/rectum and PTV/bladder intersection volumes (7.2 ± 5.8, 18.2 ± 8.1 cc) than the margin-reduced group (2.6 ± 1.8, 12.5 ± 8.3 cc), though the dose to these intersection volumes did not reach statistical significance (p > 0.1) between the groups. PTV/rectum intersection volume showed a moderate correlation (r = -0.56, p < 0.05) to Bowel EPIC domain.

CONCLUSIONS

Results of this prospective study showed that margin-reduced group exhibited clinically meaningful improvement of QOL without compromising the target dose coverage.

4D Monte Carlo dose reconstructions using surface motion measurements

PURPOSE

To investigate the feasibility of a 4D Monte Carlo based dose reconstruction method to study the dosimetric impact of respiratory motion using surface motion measurements for patients undergoing VMAT treatments for Non-Small Cell Lung Cancer.

METHODS

The 4Ddefdosxyznrc/EGSnrc algorithm was used to reconstruct VMAT doses delivered to the patients using machine log files and respiratory traces measured with the RADPOS 4D dosimetry system. The RADPOS sensor was adhered to the patient's abdomen prior to each treatment fraction and its position was used as a surrogate for tumour motion. Treatment log files were synchronized with the patient respiratory traces. Patient specific respiratory models were generated from deformable registration of the inhale and exhale 4DCT images and the respiratory traces. The reconstructed doses were compared to planned doses calculated with DOSXYZnrc/EGSnrc on the average-intensity and the exhale phase CT images.

RESULTS

Respiratory motion measurements and log files were acquired for 2 patients over 5 treatment fractions each. The motion was predominantly along the anterior/posterior direction (A/P). The average respiratory amplitudes were 8.7 ± 2.7 mm and 10.0 ± 1.2 mm for Patient 1 and 2, respectively. Both patients displayed inter- and intra-fractional variations in the baseline position. Small inter-fractional differences were observed in the reconstructed doses for each patient. Differences between the reconstructed and planned doses were attributed to differences in organ volumes.

CONCLUSION

The 4D reconstruction method was successfully implemented for the two patients studied. Small differences between the planned and reconstructed doses were observed due to the small tumour motion of these patients.

Development of a multi-layer quality assurance program to evaluate the uncertainty of deformable dose accumulation in adaptive radiotherapy

PURPOSE

Deformable dose accumulation (DDA) has uncertainties which impede the implementation of DDA-based adaptive radiotherapy (ART) in clinic. The purpose of this study is to develop a multi-layer quality assurance (MLQA) program to evaluate uncertainties in DDA.

METHODS

A computer program is developed to generate a pseudo-inverse displacement vector field (DVF) for each deformable image registration (DIR) performed in Accuray's PreciseART. The pseudo-inverse DVF is first used to calculate a pseudo-inverse consistency error (PICE) and then implemented in an energy and mass congruent mapping (EMCM) method to reconstruct a deformed dose. The PICE is taken as a metric to estimate DIR uncertainties. A pseudo-inverse dose agreement rate (PIDAR) is used to evaluate the consequence of the DIR uncertainties in DDA and the principle of energy conservation is used to validate the integrity of dose mappings. The developed MLQA program was tested using the data collected from five representative cancer patients treated with tomotherapy.

RESULTS

DIRs were performed in PreciseART to generate primary DVFs for the five patients. The fidelity index and PICE of these DVFs on average are equal to 0.028 mm and 0.169 mm, respectively. With the criteria of 3 mm/3% and 5 mm/5%, the PIDARs of the PreciseART-reconstructed doses are 73.9 ± 4.4% and 87.2 ± 3.3%, respectively. The PreciseART and EMCM-based dose reconstructions have their deposited energy changed by 5.6 ± 3.9% and 2.6 ± 1.5% in five GTVs, and by 9.2 ± 7.8% and 4.7 ± 3.6% in 30 OARs, respectively.

CONCLUSIONS

A pseudo-inverse map-based EMCM program has been developed to evaluate DIR and dose mapping uncertainties. This program could also be used as a sanity check tool for DDA-based ART.

Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies-which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation-can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.

Detailed dosimetric evaluation of inter-fraction and respiratory motion in lung stereotactic body radiation therapy based on daily 4D cone beam CT images

Objective. Periodic respiratory motion and inter-fraction variations are sources of geometric uncertainty in stereotactic body radiation therapy (SBRT) of pulmonary lesions. This study extensively evaluates and validates the separate and combined dosimetric effect of both factors using 4D-CT and daily 4D-cone beam CT (CBCT) dose accumulation scenarios.Approach. A first cohort of twenty early stage or metastatic disease lung cancer patients were retrospectively selected to evaluate each scenario. The planned-dose (3D_Ref) was optimized on a 3D mid-position CT. To estimate the dosimetric impact of respiratory motion (4D_Ref), inter-fractional variations (3D_Acc) and the combined effect of both factors (4D_Acc), three dose accumulation scenarios based on 4D-CT, daily mid-cone beam CT (CBCT) position and 4D-CBCT were implemented via CT-CT/CT-CBCT deformable image registration (DIR) techniques. Each scenario was compared to 3D_Ref.A separate cohort of ten lung SBRT patients was selected to validate DIR techniques. The distance discordance metric (DDM) was implemented per voxel and per patient for tumor and organs at risk (OARs), and the dosimetric impact for CT-CBCT DIR geometric errors was calculated.Main results.Median and interquartile range (IQR) of the dose difference per voxel were 0.05/2.69 Gy and -0.12/2.68 Gy for3DAcc-3DRefand4DAcc-3DRef.For4DRef-3DRefthe IQR was considerably smaller -0.15/0.78 Gy. These findings were confirmed by dose volume histogram parameters calculated in tumor and OARs. For CT-CT/CT-CBCT DIR validation, DDM (95th percentile) was highest for heart (6.26 mm)/spinal cord (8.00 mm), and below 3 mm for tumor and the rest of OARs. The dosimetric impact of CT-CBCT DIR errors was below 2 Gy for tumor and OARs.Significance. The dosimetric impact of inter-fraction variations were shown to dominate those of periodic respiration in SBRT for pulmonary lesions. Therefore, treatment evaluation and dose-effect studies would benefit more from dose accumulation focusing on day-to-day changes then those that focus on respiratory motion.

Quantitative investigation of dose accumulation errors from intra-fraction motion in MRgRT for prostate cancer

Accurate spatial dose delivery in radiotherapy is frequently complicated due to changes in the patient's internal anatomy during and in-between therapy segments. The recent introduction of hybrid MRI radiotherapy systems allows unequaled soft-tissue visualization during radiation delivery and can be used for dose reconstruction to quantify the impact of motion. To this end, knowledge of anatomical deformations obtained from continuous monitoring during treatment has to be combined with information on the spatio-temporal dose delivery to perform motion-compensated dose accumulation (MCDA). Here, the influence of the choice of deformable image registration algorithm, dose warping strategy, and magnetic resonance image resolution and signal-to-noise-ratio on the resulting MCDA is investigated. For a quantitative investigation, four 4D MRI-datasets representing typical patient observed motion patterns are generated using finite element modeling and serve as a gold standard. Energy delivery is simulated intra-fractionally in the deformed image space and, subsequently, MCDA-processed. Finally, the results are substantiated by comparing MCDA strategies on clinically acquired patient data. It is shown that MCDA is needed for correct quantitative dose reconstruction. For prostate treatments, using the energy per mass transfer dose warping strategy has the largest influence on decreasing dose estimation errors.

Validation of 4D Monte Carlo dose calculations using a programmable deformable lung phantom

PURPOSE

To validate the accuracy of 4D Monte Carlo (4DMC) simulations to calculate dose deliveries to a deforming anatomy in the presence of realistic respiratory motion traces. A previously developed deformable lung phantom comprising an elastic tumor was modified to enable programming of arbitrary motion profiles. 4D simulations of the dose delivered to the phantom were compared with the measurements.

METHODS

The deformable lung phantom moving with irregular breathing patterns was irradiated using static and VMAT beam deliveries. Using the RADPOS 4D dosimetry system, point doses were measured inside and outside the tumor. Dose profiles were acquired using films along the motion path of the tumor (S-I). In addition to dose measurements, RADPOS was used to record the motion of the tumor during dose deliveries. Dose measurements were then compared against 4DMC simulations with EGSnrc/4DdefDOSXYZnrc using the recorded tumor motion.

RESULTS

The agreements between dose profiles from measurements and simulations were determined to be within 2%/2 mm. Point dose agreements were within 2σ of experimental and/or positional/dose reading uncertainties. 4DMC simulations were shown to accurately predict the sensitivity of delivered dose to the starting phase of breathing motions. We have demonstrated that our 4DMC method, combined with RADPOS, can accurately simulate realistic dose deliveries to a deforming anatomy moving with realistic breathing traces. This 4DMC tool has the potential to be used as a quality assurance tool to verify treatments involving respiratory motion. Adaptive treatment delivery is another area that may benefit from the potential of this 4DMC tool.

Comparison of planned dose on different CT image sets to four-dimensional Monte Carlo dose recalculation using the patient's actual breathing trace for lung stereotactic body radiation therapy

PURPOSE

The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning.

METHODS

We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration.

RESULTS

Δ D 98 % and Δ D 2 % between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort.

CONCLUSIONS

We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.

Deformable Registration for Dose Accumulation

As deformable image registration makes its way into the clinical routine, the summation of doses from fractionated treatment regimens to evaluate cumulative doses to targets and healthy tissues is also becoming a frequently utilized tool in the context of image-guided adaptive radiotherapy. Accounting for daily geometric changes using deformable image registration and dose accumulation potentially enables a better understanding of dose-volume-effect relationships, with the goal of translation of this knowledge to personalization of treatment, to further enhance treatment outcomes. Treatment adaptation involving image deformation requires patient-specific quality assurance of the image registration and dose accumulation processes, to ensure that uncertainties in the 3D dose distributions are identified and appreciated from a clinical relevance perspective. While much research has been devoted to identifying and managing the uncertainties associated with deformable image registration and dose accumulation approaches, there are still many unanswered questions. Here, we provide a review of current deformable image registration and dose accumulation techniques, and related clinical application. We also discuss salient issues that need to be deliberated when applying deformable algorithms for dose mapping and accumulation in the context of adaptive radiotherapy and response assessment.

A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system

PURPOSE

The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings.

METHODS

To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique.

RESULTS

Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator.

CONCLUSIONS

A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.

Real-time energy/mass transfer mapping for online 4D dose reconstruction

In this work we describe an ultra-fast, low-latency implementation of the energy/mass transfer (EMT) mapping method to accumulate dose on deforming geometries such as lung using the central processing unit (CPU). It enables the computation of the actually delivered dose for intensity-modulated radiation therapy on 4D image data in real-time at 25 Hz. In order to accumulate the delivered dose onto a reference phase a pre-calculated deformable vector field is used. The aim of this study is to present an online dose accumulation technique that can be carried out in less than 40 ms to accommodate the machine log update rate of our research linac. Three speed optimisation strategies for the CPU are discussed: single-core optimisation, parallelisation for multiple cores and vectorisation. The single-core implementation accumulates dose in about 1.1 s on a typical high resolution grid for a lung stereotactic body radiation therapy case. Adding parallelisation decreased the runtime to about 50 ms while adding vectorisation satisfied our real-time constraint by further reducing the dose accumulation time to 15 ms without compromising on resolution or accuracy. The presented method allows real-time dose accumulation on deforming patient geometries and has the potential to enable online dose evaluation and re-planning scenarios.

An automated dose tracking system for adaptive radiation therapy

BACKGROUND AND OBJECTIVE

The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART.

METHODS

Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools.

RESULTS

The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement.

CONCLUSIONS

An efficient and convenient dose tracking system for ART in the clinical setting is presented. The software and automated processes were rigorously evaluated and validated using patient image datasets. Automation of the various procedures has improved efficiency significantly, allowing for the routine clinical application of ART for improving radiation therapy effectiveness.

Adaptive radiotherapy for NSCLC patients: utilizing the principle of energy conservation to evaluate dose mapping operations

Tumor regression during the course of fractionated radiotherapy confounds the ability to accurately estimate the total dose delivered to tumor targets. Here we present a new criterion to improve the accuracy of image intensity-based dose mapping operations for adaptive radiotherapy for patients with non-small cell lung cancer (NSCLC). Six NSCLC patients were retrospectively investigated in this study. An image intensity-based B-spline registration algorithm was used for deformable image registration (DIR) of weekly CBCT images to a reference image. The resultant displacement vector fields were employed to map the doses calculated on weekly images to the reference image. The concept of energy conservation was introduced as a criterion to evaluate the accuracy of the dose mapping operations. A finite element method (FEM)-based mechanical model was implemented to improve the performance of the B-Spline-based registration algorithm in regions involving tumor regression. For the six patients, deformed tumor volumes changed by 21.2  ±  15.0% and 4.1  ±  3.7% on average for the B-Spline and the FEM-based registrations performed from fraction 1 to fraction 21, respectively. The energy deposited in the gross tumor volume (GTV) was 0.66 Joules (J) per fraction on average. The energy derived from the fractional dose reconstructed by the B-spline and FEM-based DIR algorithms in the deformed GTV's was 0.51 J and 0.64 J, respectively. Based on landmark comparisons for the 6 patients, mean error for the FEM-based DIR algorithm was 2.5  ±  1.9 mm. The cross-correlation coefficient between the landmark-measured displacement error and the loss of radiation energy was  -0.16 for the FEM-based algorithm. To avoid uncertainties in measuring distorted landmarks, the B-Spline-based registrations were compared to the FEM registrations, and their displacement differences equal 4.2  ±  4.7 mm on average. The displacement differences were correlated to their relative loss of radiation energy with a cross-correlation coefficient equal to 0.68. Based on the principle of energy conservation, the FEM-based mechanical model has a better performance than the B-Spline-based DIR algorithm. It is recommended that the principle of energy conservation be incorporated into a comprehensive QA protocol for adaptive radiotherapy.

Development of a deformable dosimetric phantom to verify dose accumulation algorithms for adaptive radiotherapy

Adaptive radiotherapy may improve treatment outcomes for lung cancer patients. Because of the lack of an effective tool for quality assurance, this therapeutic modality is not yet accepted in clinic. The purpose of this study is to develop a deformable physical phantom for validation of dose accumulation algorithms in regions with heterogeneous mass. A three-dimensional (3D) deformable phantom was developed containing a tissue-equivalent tumor and heterogeneous sponge inserts. Thermoluminescent dosimeters (TLDs) were placed at multiple locations in the phantom each time before dose measurement. Doses were measured with the phantom in both the static and deformed cases. The deformation of the phantom was actuated by a motor driven piston. 4D computed tomography images were acquired to calculate 3D doses at each phase using Pinnacle and EGSnrc/DOSXYZnrc. These images were registered using two registration software packages: VelocityAI and Elastix. With the resultant displacement vector fields (DVFs), the calculated 3D doses were accumulated using a mass-and energy congruent mapping method and compared to those measured by the TLDs at four typical locations. In the static case, TLD measurements agreed with all the algorithms by 1.8% at the center of the tumor volume and by 4.0% in the penumbra. In the deformable case, the phantom's deformation was reproduced within 1.1 mm. For the 3D dose calculated by Pinnacle, the total dose accumulated with the Elastix DVF agreed well to the TLD measurements with their differences <2.5% at four measured locations. When the VelocityAI DVF was used, their difference increased up to 11.8%. For the 3D dose calculated by EGSnrc/DOSXYZnrc, the total doses accumulated with the two DVFs were within 5.7% of the TLD measurements which are slightly over the rate of 5% for clinical acceptance. The detector-embedded deformable phantom allows radiation dose to be measured in a dynamic environment, similar to deforming lung tissues, supporting the validation of dose mapping and accumulation operations in regions with heterogeneous mass, and dose distributions.

Evaluation of deformable image registration methods for dose monitoring in head and neck radiotherapy

In the context of head and neck cancer (HNC) adaptive radiation therapy (ART), the two purposes of the study were to compare the performance of multiple deformable image registration (DIR) methods and to quantify their impact for dose accumulation, in healthy structures. Fifteen HNC patients had a planning computed tomography (CT0) and weekly CTs during the 7 weeks of intensity-modulated radiation therapy (IMRT). Ten DIR approaches using different registration methods (demons or B-spline free form deformation (FFD)), preprocessing, and similarity metrics were tested. Two observers identified 14 landmarks (LM) on each CT-scan to compute LM registration error. The cumulated doses estimated by each method were compared. The two most effective DIR methods were the demons and the FFD, with both the mutual information (MI) metric and the filtered CTs. The corresponding LM registration accuracy (precision) was 2.44 mm (1.30 mm) and 2.54 mm (1.33 mm), respectively. The corresponding LM estimated cumulated dose accuracy (dose precision) was 0.85 Gy (0.93 Gy) and 0.88 Gy (0.95 Gy), respectively. The mean uncertainty (difference between maximal and minimal dose considering all the 10 methods) to estimate the cumulated mean dose to the parotid gland (PG) was 4.03 Gy (SD = 2.27 Gy, range: 1.06-8.91 Gy).

Direct dose mapping versus energy/mass transfer mapping for 4D dose accumulation: fundamental differences and dosimetric consequences

The direct dose mapping (DDM) and energy/mass transfer (EMT) mapping are two essential algorithms for accumulating the dose from different anatomic phases to the reference phase when there is organ motion or tumor/tissue deformation during the delivery of radiation therapy. DDM is based on interpolation of the dose values from one dose grid to another and thus lacks rigor in defining the dose when there are multiple dose values mapped to one dose voxel in the reference phase due to tissue/tumor deformation. On the other hand, EMT counts the total energy and mass transferred to each voxel in the reference phase and calculates the dose by dividing the energy by mass. Therefore it is based on fundamentally sound physics principles. In this study, we implemented the two algorithms and integrated them within the Eclipse treatment planning system. We then compared the clinical dosimetric difference between the two algorithms for ten lung cancer patients receiving stereotactic radiosurgery treatment, by accumulating the delivered dose to the end-of-exhale (EE) phase. Specifically, the respiratory period was divided into ten phases and the dose to each phase was calculated and mapped to the EE phase and then accumulated. The displacement vector field generated by Demons-based registration of the source and reference images was used to transfer the dose and energy. The DDM and EMT algorithms produced noticeably different cumulative dose in the regions with sharp mass density variations and/or high dose gradients. For the planning target volume (PTV) and internal target volume (ITV) minimum dose, the difference was up to 11% and 4% respectively. This suggests that DDM might not be adequate for obtaining an accurate dose distribution of the cumulative plan, instead, EMT should be considered.

Advances in 4D radiation therapy for managing respiration: part II - 4D treatment planning

The development of 4D CT imaging technology made possible the creation of patient models that are reflective of respiration-induced anatomical changes by adding a temporal dimension to the conventional 3D, spatial-only, patient description. This had opened a new venue for treatment planning and radiation delivery, aimed at creating a comprehensive 4D radiation therapy process for moving targets. Unlike other breathing motion compensation strategies (e.g. breath-hold and gating techniques), 4D radiotherapy assumes treatment delivery over the entire respiratory cycle - an added bonus for both patient comfort and treatment time efficiency. The time-dependent positional and volumetric information holds the promise for optimal, highly conformal, radiotherapy for targets experiencing movements caused by respiration, with potentially elevated dose prescriptions and therefore higher cure rates, while avoiding the uninvolved nearby structures. In this paper, the current state of the 4D treatment planning is reviewed, from theory to the established practical routine. While the fundamental principles of 4D radiotherapy are well defined, the development of a complete, robust and clinically feasible process still remains a challenge, imposed by limitations in the available treatment planning and radiation delivery systems.

Accuracy and sensitivity of four-dimensional dose calculation to systematic motion variability in stereotatic body radiotherapy (SBRT) for lung cancer

The dynamic movement of radiation beam in real-time tumor tracking may cause overdosing to critical organs surrounding the target. The primary objective of this study was to verify the accuracy of the 4D planning module incorporated in CyberKnife treatment planning system. The secondary objective was to evaluate the error that may occur in the case of a systematic change of motion pattern. Measurements were made using a rigid thorax phantom. Target motion was simulated with two waveforms (sin and cos4) of different amplitude and frequency. Inversely optimized dose distributions were calculated in the CyberKnife treatment planning system using the 4D Monte Carlo dose calculation algorithm. Each plan was delivered to the phantom assuming (1) reproducible target motion,and (2) systematic change of target motion pattern. The accuracy of 4D dose calculation algorithm was assessed using GAFCHROMIC EBT2 films based on 5%/3 mm γ criteria. Treatment plans were considered acceptable if the percentage of pixels passing the 5%/3 mm γ criteria was greater than 90%. The mean percentages of pixels passing were 95% for the target and 91% for the static off-target structure, respectively, with reproducible target motion. When systematic changes of the motion pattern were introduced during treatment delivery, the mean percentages of pixels passing decreased significantly in the off-target films (48%; p &lt; 0.05), but did not change significantly in the target films (92%; p = 0.324) compared to results of reproducible target motion. These results suggest that the accuracy of 4D dose calculation, particularly in off-target stationary structure, is strongly tied to the reproducibility of target motion and that the solutions of 4D planning do not reflect the clinical nature of nonreproducible target motion generally.

[Image-guided and adaptive radiotherapy]

Image-guided radiotherapy (IGRT) aims to take into account anatomical variations occurring during irradiation by visualization of anatomical structures. It may consist of a rigid registration of the tumour by moving the patient, in case of prostatic irradiation for example. IGRT associated with intensity-modulated radiotherapy (IMRT) is strongly recommended when high-dose is delivered in the prostate, where it seems to reduce rectal and bladder toxicity. In case of significant anatomical deformations, as in head and neck tumours (tumour shrinking and decrease in volume of the salivary glands), replanning appears to be necessary, corresponding to the adaptive radiotherapy. This should ideally be "monitored" and possibly triggered based on a calculation of cumulative dose, session after session, compared to the initial planning dose, corresponding to the concept of dose-guided adaptive radiotherapy. The creation of "planning libraries" based on predictable organ positions (as in cervical cancer) is another way of adaptive radiotherapy. All of these strategies still appear very complex and expensive and therefore require stringent validation before being routinely applied.

A method to evaluate dose errors introduced by dose mapping processes for mass conserving deformations

PURPOSE

To present a method to evaluate the dose mapping error introduced by the dose mapping process. In addition, apply the method to evaluate the dose mapping error introduced by the 4D dose calculation process implemented in a research version of commercial treatment planning system for a patient case.

METHODS

The average dose accumulated in a finite volume should be unchanged when the dose delivered to one anatomic instance of that volume is mapped to a different anatomic instance-provided that the tissue deformation between the anatomic instances is mass conserving. The average dose to a finite volume on image S is defined as d(S)=e(s)/m(S), where e(S) is the energy deposited in the mass m(S) contained in the volume. Since mass and energy should be conserved, when d(S) is mapped to an image R(d(S→R)=d(R)), the mean dose mapping error is defined as Δd(m)=|d(R)-d(S)|=|e(R)/m(R)-e(S)/m(S)|, where the e(R) and e(S) are integral doses (energy deposited), and m(R) and m(S) are the masses within the region of interest (ROI) on image R and the corresponding ROI on image S, where R and S are the two anatomic instances from the same patient. Alternatively, application of simple differential propagation yields the differential dose mapping error, Δd(d)=|∂d∂e*Δe+∂d∂m*Δm|=|(e(S)-e(R))m(R)-(m(S)-m(R))m(R) (2)*e(R)|=α|d(R)-d(S)| with α=m(S)/m(R). A 4D treatment plan on a ten-phase 4D-CT lung patient is used to demonstrate the dose mapping error evaluations for a patient case, in which the accumulated dose, D(R)=∑(S=0) (9)d(S→R), and associated error values (ΔD(m) and ΔD(d)) are calculated for a uniformly spaced set of ROIs.

RESULTS

For the single sample patient dose distribution, the average accumulated differential dose mapping error is 4.3%, the average absolute differential dose mapping error is 10.8%, and the average accumulated mean dose mapping error is 5.0%. Accumulated differential dose mapping errors within the gross tumor volume (GTV) and planning target volume (PTV) are lower, 0.73% and 2.33%, respectively.

CONCLUSIONS

A method has been presented to evaluate the dose mapping error introduced by the dose mapping process. This method has been applied to evaluate the 4D dose calculation process implemented in a commercial treatment planning system. The method could potentially be developed as a fully-automatic QA method in image guided adaptive radiation therapy (IGART).

[From image-guided radiotherapy to dose-guided radiotherapy]

PURPOSE

In case of tumour displacement, image-guided radiotherapy (IGRT) based on the use of cone beam CT (tomographie conique) allows replacing the tumour under the accelerator by rigid registration. Anatomical deformations require however replanning, involving an estimation of the cumulative dose, session after session. This is the objective of this study.

PATIENTS AND METHODS

Two examples of arc-intensity modulated radiotherapy are presented: a case of prostate cancer (total dose=80 Gy) with tomographie conique (daily prostate registration) and one head and neck cancer (70 Gy). For the head and neck cancer, the patient had a weekly scanner allowing a dose distribution calculation. The cumulative dose was calculated per voxel on the planning CT after deformation of the dose distribution (with trilinear interpolation) following the transformation given by a non-rigid registration step (Demons registration method) from: either the tomographie conique (prostate), or the weekly CT. The cumulative dose was eventually compared with the planned dose.

RESULTS

In cases of prostate irradiation, the "cumulative" dose corresponded to the planned dose to the prostate. At the last week of irradiation, it was above the planned dose for the rectum and bladder. The volume of rectal wall receiving more than 50 Gy (V50) was 20% at the planning and 26% at the end of treatment, increasing the risk of rectal toxicity (NTCP) of 14%. For the bladder wall, V50 were 73% and 82%, respectively. In head and neck, the "cumulative" dose to the parotid exceeded the planned dose (mean dose increasing from 46 Gy to 54 Gy) from the 5th week of irradiation on, suggesting the need for replanning within the first 5 weeks of radiotherapy.

CONCLUSION

The deformable registration estimates the cumulative dose delivered in the different anatomical structures. Validation on digital and physical phantoms is however required before clinical evaluation.

A distance to dose difference tool for estimating the required spatial accuracy of a displacement vector field

PURPOSE

To introduce a tool, termed distance to dose difference (DTD), which estimates the required spatial accuracy of displacement vector fields (DVFs) used for mapping four dimensional dose values.

METHODS

Dose mapping maps dose values from an irradiated geometry to a reference geometry. DVF errors result in dose being mapped from the wrong spatial location in the irradiated geometry, with a dose error equal to the dose difference between the error-free and sampled spatial locations. The DTD, defined as the distance to observe a given dose difference in the irradiated geometry, quantifies the permitted DVF error to ensure a prespecified desired dose mapping accuracy is achieved. To demonstrate the DTD, a treatment plan is generated with a 5 mm internal target volume-to-planning target volume margin for an intensity modulated radiation therapy lung patient. The DTD is evaluated for mapping dose from the end of inhale image with a dose error tolerance of 3.30 Gy, which equals 5% of the 66 Gy prescription dose. The DTD is loaded into the treatment planning system to visualize positional dependencies of permissible DVF errors overlaid on the patient's anatomy and DTD-volume-histograms are generated.

RESULTS

DTD values vary with location in the patient anatomy. For the test case, DTD analysis indicates that accurate DVFs (approximately 1 mm) are required in high dose gradient regions while large DVF errors (>20 mm) are acceptable in low dose gradient regions. Within the clinical target volume (CTV), tolerated DVF uncertainties range from 1 to 12 mm, depending on location. Ninety percent of the CTV volume had DTD values less than 4 mm.

CONCLUSIONS

The DVF spatial accuracy required to meet a dose mapping accuracy tolerance depends on the spatial location within the dose distribution. For dose mapping, DVFs accuracy must be highest in dose gradient regions, while less accurate DVFs can be tolerated in uniform dose regions. The DTD tool provides a useful first estimate of DVF required spatial accuracy.

Investigation of voxel warping and energy mapping approaches for fast 4D Monte Carlo dose calculations in deformed geometries using VMC++

A new deformable geometry class for the VMC++ Monte Carlo code was implemented based on the voxel warping method. Alternative geometries which use tetrahedral sub-elements were implemented and efficiency improvements investigated. A new energy mapping method, based on calculating the volume overlap between deformed reference dose grid and the target dose grid, was also developed. Dose calculations using both the voxel warping and energy mapping methods were compared in simple phantoms as well as a patient geometry. The new deformed geometry implementation in VMC++ increased calculation times by approximately a factor of 6 compared to standard VMC++ calculations in rectilinear geometries. However, the tetrahedron-based geometries were found to improve computational efficiency, relative to the dodecahedron-based geometry, by a factor of 2. When an exact transformation between the reference and target geometries was provided, the voxel and energy warping methods produced identical results. However, when the transformation is not exact, there were discrepancies in the energy deposited on the target geometry which lead to significant differences in the dose calculated by the two methods. Preliminary investigations indicate that these energy differences may correlate with registration errors; however, further work is needed to determine the usefulness of this metric for quantifying registration accuracy.

Monte Carlo dose calculation on deforming anatomy

This article presents the implementation and validation of a dose calculation approach for deforming anatomical objects. Deformation is represented by deformation vector fields leading to deformed voxel grids representing the different deformation scenarios. Particle transport in the resulting deformed voxels is handled through the approximation of voxel surfaces by triangles in the geometry implementation of the Swiss Monte Carlo Plan framework. The focus lies on the validation methodology which uses computational phantoms representing the same physical object through regular and irregular voxel grids. These phantoms are chosen such that the new implementation for a deformed voxel grid can be compared directly with an established dose calculation algorithm for regular grids. Furthermore, separate validation of the aspects voxel geometry and the density changes resulting from deformation is achieved through suitable design of the validation phantom. We show that equivalent results are obtained with the proposed method and that no statistically significant errors are introduced through the implementation for irregular voxel geometries. This enables the use of the presented and validated implementation for further investigations of dose calculation on deforming anatomy.

A pseudoinverse deformation vector field generator and its applications

PURPOSE

To present, implement, and test a self-consistent pseudoinverse displacement vector field (PIDVF) generator, which preserves the location of information mapped back-and-forth between image sets.

METHODS

The algorithm is an iterative scheme based on nearest neighbor interpolation and a subsequent iterative search. Performance of the algorithm is benchmarked using a lung 4DCT data set with six CT images from different breathing phases and eight CT images for a single prostrate patient acquired on different days. A diffeomorphic deformable image registration is used to validate our PIDVFs. Additionally, the PIDVF is used to measure the self-consistency of two nondiffeomorphic algorithms which do not use a self-consistency constraint: The ITK Demons algorithm for the lung patient images and an in-house B-Spline algorithm for the prostate patient images. Both Demons and B-Spline have been QAed through contour comparison. Self-consistency is determined by using a DIR to generate a displacement vector field (DVF) between reference image R and study image S (DVF(R-S)). The same DIR is used to generate DVF(S-R). Additionally, our PIDVF generator is used to create PIDVF(S-R). Back-and-forth mapping of a set of points (used as surrogates of contours) using DVF(R-S) and DVF(S-R) is compared to back-and-forth mapping performed with DVF(R-S) and PIDVF(S-R). The Euclidean distances between the original unmapped points and the mapped points are used as a self-consistency measure.

RESULTS

Test results demonstrate that the consistency error observed in back-and-forth mappings can be reduced two to nine times in point mapping and 1.5 to three times in dose mapping when the PIDVF is used in place of the B-Spline algorithm. These self-consistency improvements are not affected by the exchanging of R and S. It is also demonstrated that differences between DVF(S-R) and PIDVF(S-R) can be used as a criteria to check the quality of the DVF.

CONCLUSIONS

Use of DVF and its PIDVF will improve the self-consistency of points, contour, and dose mappings in image guided adaptive therapy.

Monte Carlo dose mapping on deforming anatomy

This paper proposes a Monte Carlo-based energy and mass congruent mapping (EMCM) method to calculate the dose on deforming anatomy. Different from dose interpolation methods, EMCM separately maps each voxel's deposited energy and mass from a source image to a reference image with a displacement vector field (DVF) generated by deformable image registration (DIR). EMCM was compared with other dose mapping methods: energy-based dose interpolation (EBDI) and trilinear dose interpolation (TDI). These methods were implemented in EGSnrc/DOSXYZnrc, validated using a numerical deformable phantom and compared for clinical CT images. On the numerical phantom with an analytically invertible deformation map, EMCM mapped the dose exactly the same as its analytic solution, while EBDI and TDI had average dose errors of 2.5% and 6.0%. For a lung patient's IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patient's entire dose region, respectively. As a 4D Monte Carlo dose calculation technique, EMCM is accurate and its speed is comparable to 3D Monte Carlo simulation. This method may serve as a valuable tool for accurate dose accumulation as well as for 4D dosimetry QA.