Evaluation of proton and photon dose distributions recalculated on 2D and 3D Unet-generated pseudoCTs from T1-weighted MR head scans.

Introduction: The recent developments of magnetic resonance (MR) based adaptive strategies for photon and, potentially for proton therapy, require a fast and reliable conversion of MR images to X-ray computed tomography (CT) values. CT values are needed for photon and proton dose calculation. The improvement of conversion results employing a 3D deep learning approach is evaluated. Material and methods: A database of 89 T1-weighted MR head scans with about 100 slices each, including rigidly registered CTs, was created. Twenty-eight validation patients were randomly sampled, and four patients were selected for application. The remaining patients were used to train a 2D and a 3D U-shaped convolutional neural network (Unet). A stack size of 32 slices was used for 3D training. For all application cases, volumetric modulated arc therapy photon and single-field uniform dose pencil-beam scanning proton plans at four different gantry angles were optimized for a generic target on the CT and recalculated on 2D and 3D Unet-based pseudoCTs. Mean (absolute) error (MAE/ME) and a gradient sharpness estimate were used to quantify the image quality. Three-dimensional gamma and dose difference analyses were performed for photon (gamma criteria: 1%, 1 mm) and proton dose distributions (gamma criteria: 2%, 2 mm). Range (80% fall off) differences for beam's eye view profiles were evaluated for protons. Results: Training 36 h for 1000 epochs in 3D (6 h for 200 epochs in 2D) yielded a maximum MAE of 147 HU (135 HU) for the application patients. Except for one patient gamma pass rates for photon and proton dose distributions were above 96% for both Unets. Slice discontinuities were reduced for 3D training at the cost of sharpness. Conclusions: Image analysis revealed a slight advantage of 2D Unets compared to 3D Unets. Similar dose calculation performance was reached for the 2D and 3D network.

Scatter correction of 4D cone beam computed tomography to detect dosimetric effects due to anatomical changes in proton therapy for lung cancer.

BACKGROUND: The treatment of moving tumor entities is expected to have superior clinical outcomes, using image-guided adaptive intensity-modulated proton therapy (IMPT). PURPOSE: For 21 lung cancer patients, IMPT dose calculations were performed on scatter-corrected 4D cone beam CTs (4DCBCTcor ) to evaluate their potential for triggering treatment adaptation. Additional dose calculations were performed on corresponding planning 4DCTs and day-of-treatment 4D virtual CTs (4DvCTs). METHODS: A 4DCBCT correction workflow, previously validated on a phantom, generates 4DvCT (CT-to-CBCT deformable registration) and 4DCBCTcor images (projection-based correction using 4DvCT as a prior) with 10 phase bins, using day-of-treatment free-breathing CBCT projections and planning 4DCT images as input. Using a research planning system, robust IMPT plans administering eight fractions of 7.5 Gy were created on a free-breathing planning CT (pCT) contoured by a physician. The internal target volume (ITV) was overridden with muscle tissue. Robustness settings for range and setup uncertainties were 3% and 6 mm, and a Monte Carlo dose engine was used. On every phase of planning 4DCT, day-of-treatment 4DvCT, and 4DCBCTcor , the dose was recalculated. For evaluation, image analysis as well as dose analysis were performed using mean error (ME) and mean absolute error (MAE) analysis, dose-volume histogram (DVH) parameters, and 2%/2-mm gamma pass rate analysis. Action levels (1.6% ITV D98 and 90% gamma pass rate) based on our previous phantom validation study were set to determine which patients had a loss of dosimetric coverage. RESULTS: Quality enhancements of 4DvCT and 4DCBCTcor over 4DCBCT were observed. ITV D98% and bronchi D2% had its largest agreement for 4DCBCTcor -4DvCT, and the largest gamma pass rates (>94%, median 98%) were found for 4DCBCTcor -4DvCT. Deviations were larger and gamma pass rates were smaller for 4DvCT-4DCT and 4DCBCTcor -4DCT. For five patients, deviations were larger than the action levels, suggesting substantial anatomical changes between pCT and CBCT projections acquisition. CONCLUSIONS: This retrospective study shows the feasibility of daily proton dose calculation on 4DCBCTcor for lung tumor patients. The applied method is of clinical interest as it generates up-to-date in-room images, accounting for breathing motion and anatomical changes. This information could be used to trigger replanning.

ScatterNet for projection-based 4D cone-beam computed tomography intensity correction of lung cancer patients.

Background and purpose: In radiotherapy, dose calculations based on 4D cone beam CTs (4DCBCTs) require image intensity corrections. This retrospective study compared the dose calculation accuracy of a deep learning, projection-based scatter correction workflow (ScatterNet), to slower workflows: conventional 4D projection-based scatter correction (CBCTcor) and a deformable image registration (DIR)-based method (4DvCT). Materials and methods: For 26 lung cancer patients, planning CTs (pCTs), 4DCTs and CBCT projections were available. ScatterNet was trained with pairs of raw and corrected CBCT projections. Corrected projections from ScatterNet and the conventional workflow were reconstructed using MA-ROOSTER, yielding 4DCBCTSN and 4DCBCTcor. The 4DvCT was generated by 4DCT to 4DCBCT DIR, as part of the 4DCBCTcor workflow. Robust intensity modulated proton therapy treatment plans were created on free-breathing pCTs. 4DCBCTSN was compared to 4DCBCTcor and the 4DvCT in terms of image quality and dose calculation accuracy (dose-volume-histogram parameters and 3%/3mm gamma analysis). Results: 4DCBCTSN resulted in an average mean absolute error of 87HU and 102HU when compared to 4DCBCTcor and 4DvCT respectively. High agreement was observed in targets with median dose differences of 0.4Gy (4DCBCTSN-4DCBCTcor) and 0.3Gy (4DCBCTSN-4DvCT). The gamma analysis showed high average 3%/3mm pass rates of 96% for both 4DCBCTSN vs. 4DCBCTcor and 4DCBCTSN vs. 4DvCT. Conclusions: Accurate 4D dose calculations are feasible for lung cancer patients using ScatterNet for 4DCBCT correction. Average scatter correction times could be reduced from 10min (4DCBCTcor) to 3.9s, showing the clinical suitability of the proposed deep learning-based method.

Continuous time-resolved estimated synthetic 4D-CTs for dose reconstruction of lung tumor treatments at a 0.35 T MR-linac.

Objective.To experimentally validate a method to create continuous time-resolved estimated synthetic 4D-computed tomography datasets (tresCTs) based on orthogonal cine MRI data for lung cancer treatments at a magnetic resonance imaging (MRI) guided linear accelerator (MR-linac).Approach.A breathing porcine lung phantom was scanned at a CT scanner and 0.35 T MR-linac. Orthogonal cine MRI series (sagittal/coronal orientation) at 7.3 Hz, intersecting tumor-mimicking gelatin nodules, were deformably registered to mid-exhale 3D-CT and 3D-MRI datasets. The time-resolved deformation vector fields were extrapolated to 3D and applied to a reference synthetic 3D-CT image (sCTref), while accounting for breathing phase-dependent lung density variations, to create 82 s long tresCTs at 3.65 Hz. Ten tresCTs were created for ten tracked nodules with different motion patterns in two lungs. For each dataset, a treatment plan was created on the mid-exhale phase of a measured ground truth (GT) respiratory-correlated 4D-CT dataset with the tracked nodule as gross tumor volume (GTV). Each plan was recalculated on the GT 4D-CT, randomly sampled tresCT, and static sCTrefimages. Dose distributions for corresponding breathing phases were compared in gamma (2%/2 mm) and dose-volume histogram (DVH) parameter analyses.Main results.The mean gamma pass rate between all tresCT and GT 4D-CT dose distributions was 98.6%. The mean absolute relative deviations of the tresCT with respect to GT DVH parameters were 1.9%, 1.0%, and 1.4% for the GTVD98%,D50%, andD2%, respectively, 1.0% for the remaining nodulesD50%, and 1.5% for the lungV20Gy. The gamma pass rate for the tresCTs was significantly larger (p< 0.01), and the GTVD50%deviations with respect to the GT were significantly smaller (p< 0.01) than for the sCTref.Significance.The results suggest that tresCTs could be valuable for time-resolved reconstruction and intrafractional accumulation of the dose to the GTV for lung cancer patients treated at MR-linacs in the future.

X-ray CT adaptation based on a 2D-3D deformable image registration framework using simulated in-room proton radiographies.

The aim of this work is to investigate in-room proton radiographies to compensate realistic rigid and non-rigid transformations in clinical-like scenarios based on 2D-3D deformable image registration (DIR) framework towards future clinical implementation of adaptive radiation therapy (ART). Monte Carlo simulations of proton radiographies (pRads) based on clinical x-ray CT of a head and neck, and a brain tumor patients are simulated for two different detector configurations (i.e. integration-mode and list-mode detectors) including high and low proton statistics. A realistic deformation, derived from cone beam CT of the patient, is applied to the treatment planning CT. Rigid inaccuracies in patient positioning are also applied and the effect of small, medium and large fields of view (FOVs) is investigated. A stopping criterion, as desirable in realistic scenarios devoid of ground truth proton CT (pCT), is proposed and investigated. Results show that rigid and non-rigid transformations can be compensated based on a limited number of low dose pRads. The root mean square error with respect to the pCT shows that the 2D-3D DIR of the treatment planning CT based on 10 pRads from integration-mode data and 2 pRads from list-mode data is capable of achieving comparable accuracy (∼90% and >90%, respectively) to conventional 3D-3D DIR. The dice similarity coefficient over the segmented regions of interest also verifies the improvement in accuracy prior to and after 2D-3D DIR. No relevant changes in accuracy are found between high and low proton statistics except for 2 pRads from integration-mode data. The impact of FOV size is negligible. The convergence of the metric adopted for the stopping criterion indicates the optimal convergence of the 2D-3D DIR. This work represents a further step towards the potential implementation of ART in proton therapy. Further computational optimization is however required to enable extensive clinical validation.

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body.

Objective. As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical computed tomography (CT) scans.Approach. A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code.Main results. The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively.Significance. The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.

Evaluation of an anthropomorphic ion chamber and 3D gel dosimetry head phantom at a 0.35 T MR-linac using separate 1.5 T MR-scanners for gel readout.

PURPOSE: To date, no universally accepted technique for the evaluation of the overall dosimetric performance of hybrid integrated magnetic resonance imaging (MR) - linear accelerators (linacs) is available. We report on the suitability and reliability of a novel phantom with modular inserts for combined polymer gel (PG) and ionisation chamber (IC) measurements at a 0.35 T MR-linac. METHODS: Three 3D-printed, modular head phantoms, based on real patient anatomy, were used for repeated (2 times) PG irradiations of cranial treatment plans on a 0.35 T MR-linac. The PG readout was performed on two 1.5 T diagnostic MR-scanners to reduce scanning time. The PG dose volumes were normalised to the IC dose (normalised dose N1) and to the median planning target volume dose (normalised dose N2). Linearity of the PG dose response was validated and dose profiles, centres of mass (COM) of the 95% isodoses and dose volume histograms (DVH) were compared between planned and measured dose distributions and a 3D gamma analysis was performed. RESULTS: Dose linearity of the PG was good (R2> 0.99 for all linear fit functions). High agreement was found between planned and measured dose volumes in the dose profiles and DVHs. The largest dose deviation was found in the intermediate dose region (mean dose deviation 0.2Gy; 5.6%). A mean COM offset of 1.2mm indicated high spatial accuracy. Mean 3D gamma passing rates (2%, 2mm) of 83.3% for N1 and 91.6% for N2 dose distributions were determined. When comparing repeated PG measurements to each other, a mean gamma passing rate of 95.7% was found. CONCLUSION: The new modular phantom was found practical for use at a 0.35 T MR-linac. In contrast to the high dose region, larger mean deviations were found in the mid dose range. The PG measurements showed high reproducibility. The MR-linac performed well in a non-adaptive setting in terms of spatial and dosimetric accuracy.

Dosimetric impact of geometric distortions in an MRI-only proton therapy workflow for lung, liver and pancreas.

In a radiation therapy workflow based on Magnetic Resonance Imaging (MRI), dosimetric errors may arise due to geometric distortions introduced by MRI. The aim of this study was to quantify the dosimetric effect of system-dependent geometric distortions in an MRI-only workflow for proton therapy applied at extra-cranial sites. An approach was developed, in which computed tomography (CT) images were distorted using an MRI displacement map, which represented the MR distortions in a spoiled gradient-echo sequence due to gradient nonlinearities and static magnetic field inhomogeneities. A retrospective study was conducted on 4DCT/MRI digital phantoms and 18 4DCT clinical datasets of the thoraco-abdominal site. The treatment plans were designed and separately optimized for each beam in a beam specific Planning Target Volume on the distorted CT, and the final dose distribution was obtained as the average. The dose was then recalculated in undistorted CT using the same beam geometry and beam weights. The analysis was performed in terms of Dose Volume Histogram (DVH) parameters. No clinically relevant dosimetric impact was observed on organs at risk, whereas in the target structure, geometric distortions caused statistically significant variations in the planned dose DVH parameters and dose homogeneity index (DHI). The dosimetric variations in the target structure were smaller in abdominal cases (ΔD2%, ΔD98%, and ΔDmean all below 0.1% and ΔDHI below 0.003) compared to the lung cases. Indeed, lung patients with tumors isolated inside lung parenchyma exhibited higher dosimetric variations (ΔD2%≥0.3%, ΔD98%≥15.9%, ΔDmean≥3.3% and ΔDHI≥0.102) than lung patients with tumor close to soft tissue (ΔD2%≤0.4%, ΔD98%≤5.6%, ΔDmean≤0.9% and ΔDHI≤0.027) potentially due to higher density variations along the beam path. Results suggest the potential applicability of MRI-only proton therapy, provided that specific analysis is applied for isolated lung tumors.

Applications of a patient-specific whole-body CT-mesh hybrid computational phantom in second cancer risk prediction.

Objective.CT-mesh hybrid phantoms (or 'hybrid(s)') made from integrated patient CT data and mesh-type reference computational phantoms (MRCPs) can be beneficial for patient-specific whole-body dose evaluation, but this benefit has yet to be evaluated for second cancer risk prediction. The purpose of this study is to compare the hybrid's ability to predict risk throughout the body with a patient-scaled MRCP against ground truth whole-body CTs (WBCTs).Approach.Head and neck active scanning proton treatment plans were created for and simulated on seven hybrids and the corresponding scaled MRCPs and WBCTs. Equivalent dose throughout the body was calculated and input into five second cancer risk models for both excess absolute and excess relative risk (EAR and ERR). The hybrid phantom was evaluated by comparing equivalent dose and risk predictions against the WBCT.Main results.The hybrid most frequently provides whole-body second cancer risk predictions which are closer to the ground truth when compared to a scaled MRCP alone. The performance of the hybrid relative to the scaled MRCP was consistent across ERR, EAR, and all risk models. For all in-field organs, where the hybrid shares the WBCT anatomy, the hybrid was better than or equal to the scaled MRCP for both equivalent dose and risk prediction. For out-of-field organs across all patients, the hybrid's equivalent dose prediction was superior than the scaled MRCP in 48% of all comparisons, equivalent for 34%, and inferior for 18%. For risk assessment in the same organs, the hybrid's prediction was superior than the scaled MRCP in 51.8% of all comparisons, equivalent in 28.6%, and inferior in 19.6%.Significance.Whole-body risk predictions from the CT-mesh hybrid have shown to be more accurate than those from a reference phantom alone. These hybrids could aid in risk-optimized treatment planning and individual risk assessment to minimize second cancer incidence.

Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation.

PURPOSE: Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy. METHODS: Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (Dmean, D2%, D98%, D95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds). RESULTS: Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV Dmean, D2%, D95% and D98% for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated Dmean over the lungs was 2.3% and Dmean for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%. CONCLUSIONS: Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.

Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework.

PURPOSE: The interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects. METHODS: We implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D5%, D50% and D95%. RESULTS: Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σD95% up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible (σ<0.1%). The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ< 0.1 %) and can be used as substitutes for interplay assessment. CONCLUSION: It is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.

Deformable image registration of the treatment planning CT with proton radiographies in perspective of adaptive proton therapy.

The purpose of this work is to investigate the potentiality of using a limited number of in-room proton radiographies to compensate anatomical changes in adaptive proton therapy. The treatment planning CT is adapted to the treatment delivery scenario relying on 2D-3D deformable image registration (DIR). The proton radiographies, expressed in water equivalent thickness (WET) are simulated for both list-mode and integration-mode detector configurations in pencil beam scanning. Geometrical and analytical simulations of an anthropomorphic phantom in the presence of anatomical changes due to breathing are adopted. A Monte Carlo simulation of proton radiographies based on a clinical CT image in the presence of artificial anatomical changes is also considered. The accuracy of the 2D-3D DIR, calculated as root mean square error, strongly depends on the considered anatomical changes and is considered adequate for promising adaptive proton therapy when comparable to the accuracy of conventional 3D-3D DIR. In geometrical simulation, this is achieved with a minimum of eight/nine radiographies (more than 90% accuracy). Negligible improvement (sim1%) is obtained with the use of 180 radiographies. Comparing different detector configurations, superior accuracy is obtained with list-mode than integration-mode max (WET with maximum occurrence) and mean (average WET weighted by occurrences). Moreover, integration-mode max performs better than integration-mode mean. Results are minimally affected by proton statistics. In analytical simulation, the anatomical changes are approximately compensated (about 60%-70% accuracy) with two proton radiographies and minor improvement is observed with nine proton radiographies. In clinical data, two proton radiographies from list-mode have demonstrated better performance than nine from integration-mode (more than 100% and about 50%-70% accuracy, respectively), even avoiding the finer grid spacing of the last numerical optimization stage. In conclusion, the choice of detector configuration as well as the amount and complexity of the considered anatomical changes determine the minimum number of radiographies to be used.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions.

PURPOSE: Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA). MATERIAL AND METHODS: The variance-based SA requires a large number (104 -105 ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S = 0: noninfluential input, S = 1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps. RESULTS AND CONCLUSIONS: The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including ∼ 3 × 10 4 RWD calculations took 39, 11, and 55 min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D98 for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

Dosimetric comparison of MR-linac-based IMRT and conventional VMAT treatment plans for prostate cancer.

BACKGROUND: The aim of this study was to evaluate and compare the performance of intensity modulated radiation therapy (IMRT) plans, planned for low-field strength magnetic resonance (MR) guided linear accelerator (linac) delivery (labelled IMRT MRL plans), and clinical conventional volumetric modulated arc therapy (VMAT) plans, for the treatment of prostate cancer (PCa). Both plans used the original planning target volume (PTV) margins. Additionally, the potential dosimetric benefits of MR-guidance were estimated, by creating IMRT MRL plans using smaller PTV margins. MATERIALS AND METHODS: 20 PCa patients previously treated with conventional VMAT were considered. For each patient, two different IMRT MRL plans using the low-field MR-linac treatment planning system were created: one with original (orig.) PTV margins and the other with reduced (red.) PTV margins. Dose indices related to target coverage, as well as dose-volume histogram (DVH) parameters for the target and organs at risk (OAR) were compared. Additionally, the estimated treatment delivery times and the number of monitor units (MU) of each plan were evaluated. RESULTS: The dose distribution in the high dose region and the target volume DVH parameters (D98%, D50%, D2% and V95%) were similar for all three types of treatment plans, with deviations below 1% in most cases. Both IMRT MRL plans (orig. and red. PTV margins) showed similar homogeneity indices (HI), however worse values for the conformity index (CI) were also found when compared to VMAT. The IMRT MRL plans showed similar OAR sparing when the orig. PTV margins were used but a significantly better sparing was feasible when red. PTV margins were applied. Higher number of MU and longer predicted treatment delivery times were seen for both IMRT MRL plans. CONCLUSIONS: A comparable plan quality between VMAT and IMRT MRL plans was achieved, when applying the same PTV margin. However, online MR-guided adaptive radiotherapy allows for a reduction of PTV margins. With a red. PTV margin, better sparing of the surrounding tissues can be achieved, while maintaining adequate target coverage. Nonetheless, longer treatment delivery times, characteristic for the IMRT technique, have to be expected.

Validation of proton dose calculation on scatter corrected 4D cone beam computed tomography using a porcine lung phantom.

Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCTcor), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCTcorwas then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCTcorand the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCTcorcase. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCTcor), respectively. The 4DCBCTcortechnique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.

Combining inter-observer variability, range and setup uncertainty in a variance-based sensitivity analysis for proton therapy.

Margin concepts in proton therapy aim to ensure full dose coverage of the clinical target volume (CTV) in presence of setup and range uncertainty. Due to inter-observer variability (IOV), the CTV itself is uncertain. We present a framework to evaluate the combined impact of IOV, setup and range uncertainty in a variance-based sensitivity analysis (SA). For ten patients with skull base meningioma, the mean calculation time to perform the SA including 1.6 × 104 dose recalculations was 59 min. For two patients in this dataset, IOV had a relevant impact on the estimated CTV D95% uncertainty.

Accounting for prompt gamma emission and detection for range verification in proton therapy treatment planning.

Prompt gamma (PG) imaging is widely investigated as one of the most promising methods for proton range verification in proton therapy. The performance of this technique is affected by several factors like tissue heterogeneity, number of protons in the considered pencil beam and the detection device. Our previous work proposed a new treatment planning concept which boosts the number of protons of a few PG monitoring-friendly pencil beams (PBs), selected on the basis of two proposed indicators quantifying the conformity between the dose and PG at the emission level, above the desired detectability threshold. To further explore this method at the detection level, in this work we investigated the response of a knife-edge slit PG camera which was deployed in the first clinical application of PG to proton therapy monitoring. The REGistration Graphical User Interface (REGGUI) is employed to simulate the PG emission, PG detection as well as the corresponding dose distribution. As the PG signal detected by this kind of PG camera is sensitive to the relative position of the camera and PG signal falloff, we optimized our PB selection method for this camera by introducing a new camera position indicator identifying whether the expected falloff of the PG signal is centered in the field of view of the camera or not. Our camera-adapted PB selection method is investigated using computed tomography (CT) scans at two different treatment time points of a head and neck, and a prostate cancer patient under scenarios considering different statistics level. The results show that a precision of 0.8 mm for PG falloff identification can be achieved when a PB has more than 2 × 108 primary protons. Except for one case due to unpredictable and comparably large anatomical changes, the PG signals of most of the PBs recommended by all our indicators are observed to be reliable for proton range verification with deviations between the inter-fractional shift of proton range (as deduced from the PB dose distribution) and the detected PG signal within 2.0 mm. In contrast, a shift difference up to 9.6 mm has been observed for the rejected PBs. The magnitude of the proton range shift due to the inter-fractional anatomical changes is observed to be up to 23 mm. The proposed indicators are shown to be valuable for identifying and recommending reliable PBs to create new PG monitoring-friendly TPs. Comparison between our PB boosting method and the alternative PB aggregation, which combines the signal of nearby PBs to reach the desired counting statistics, is also discussed.

Measurement-based range evaluation for quality assurance of CBCT-based dose calculations in adaptive proton therapy.

PURPOSE: The implementation of volumetric in-room imaging for online adaptive radiotherapy makes extensive testing of this image data for treatment planning necessary. Especially for proton beams the higher sensitivity to stopping power properties of the tissue results in more stringent requirements. Current approaches mainly focus on recalculation of the plans on the new image data, lacking experimental verification, and ignoring the impact on the plan re-optimization process. The aim of this study was to use gel and film dosimetry coupled with a three-dimensional (3D) printed head phantom (based on the planning CT of the patient) for 3D range verification of intensity-corrected cone beam computed tomography (CBCT) image data for adaptive proton therapy. METHODS: Single field uniform dose pencil beam scanning proton plans were optimized for three different patients on the patients' planning CT (planCT) and the patients' intensity-corrected CBCT (scCBCT) for the same target volume using the same optimization constraints. The CBCTs were corrected on projection level using the planCT as a prior. The dose optimized on planCT and recalculated on scCBCT was compared in terms of proton range differences (80% distal fall-off, recalculation). Moreover, the dose distribution resulting from recalculation of the scCBCT-optimized plan on the planCT and the original planCT dose distribution were compared (simulation). Finally, the two plans of each patient were irradiated on the corresponding patient-specific 3D printed head phantom using gel dosimetry inserts for one patient and film dosimetry for all three patients. Range differences were extracted from the measured dose distributions. The measured and the simulated range differences were corrected for range differences originating from the initial plans and evaluated. RESULTS: The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1 mm and the interquartile ranges (IQRs) within 0.3 mm for all three patients. The range differences of the film measurement were accurately matching with the simulation approach in the film plane. The median values of these range differences deviated less than 0.1 mm and the IQRs less than 0.4 mm. For the full 3D evaluation of the gel range differences, the median value and IQR matched those of the simulation approach within 0.7 and 0.5 mm, respectively. scCBCT- and planCT-based dose distributions were found to have a range agreement better than 3 mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement). CONCLUSIONS: The results of this initial study indicate that an online adaptive proton workflow based on scatter-corrected CBCT image data for head irradiations is feasible. The novel presented measurement- and simulation-based method was shown to be equivalent to the standard literature recalculation approach. Additionally, it has the capability to catch effects of image differences on the treatment plan optimization. This makes the measurement-based approach particularly interesting for quality assurance of CBCT-based online adaptive proton therapy. The observed uncertainties could be kept within those of the registration and positioning. The proposed validation could also be applied for other alternative in-room images, e.g. for MR-based pseudoCTs.

Porcine lung phantom-based validation of estimated 4D-MRI using orthogonal cine imaging for low-field MR-Linacs.

Real-time motion monitoring of lung tumors with low-field magnetic resonance imaging-guided linear accelerators (MR-Linacs) is currently limited to sagittal 2D cine magnetic resonance imaging (MRI). To provide input data for improved intrafractional and interfractional adaptive radiotherapy, the 4D anatomy has to be inferred from data with lower dimensionality. The purpose of this study was to experimentally validate a previously proposed propagation method that provides continuous time-resolved estimated 4D-MRI based on orthogonal cine MRI for a low-field MR-Linac. Ex vivo porcine lungs were injected with artificial nodules and mounted in a dedicated phantom that allows for the simulation of periodic and reproducible breathing motion. The phantom was scanned with a research version of a commercial 0.35 T MR-Linac. Respiratory-correlated 4D-MRI were reconstructed and served as ground truth images. Series of interleaved orthogonal slices in sagittal and coronal orientation, intersecting the injected targets, were acquired at 7.3 Hz. Estimated 4D-MRI at 3.65 Hz were created in post-processing using the propagation method and compared to the ground truth 4D-MRI. Eight datasets at different breathing frequencies and motion amplitudes were acquired for three porcine lungs. The overall median (95[Formula: see text] percentile) deviation between ground truth and estimated deformation vector fields was 2.3 mm (5.7 mm), corresponding to 0.7 (1.6) times the in-plane imaging resolution (3.5 × 3.5 mm2). Median (95[Formula: see text] percentile) estimated nodule position errors were 1.5 mm (3.8 mm) for nodules intersected by orthogonal slices and 2.1 mm (7.1 mm) for nodules located more than 2 cm away from either of the orthogonal slices. The estimation error depended on the breathing phase, the motion amplitude and the location of the estimated position with respect to the orthogonal slices. By using the propagation method, the 4D motion within the porcine lung phantom could be accurately and robustly estimated. The method could provide valuable information for treatment planning, real-time motion monitoring, treatment adaptation, and post-treatment evaluation of MR-guided radiotherapy treatments.

CyberKnife radiation therapy as a platform for translational mouse studies.

PURPOSE: Radiation therapy (RT) is a common nonsurgical treatment in the management of patients with cancer. While genetically engineered mouse models (GEMM) recapitulate human disease, conventional linear particle accelerator systems are not suited for state-of-the-art, imageguided targeted RT (IGRT) of these murine tumors. We employed the CyberKnife (CK; Accuray) platform for IGRT of GEMM-derived non-small cell lung cancer (NSCLC) lesions. MATERIAL AND METHODS: GEMM-derived KrasLSL-G12D/+/Trp53fl/fl -driven NSCLC flank tumors were irradiated using the CK RT platform. We applied IGRT of 2, 4, 6, and 8 Gy using field sizes of 5-12.5 mm to average gross tumor volumes (GTV) of 0.9 cm3 using Xsight Spine Tracking (Accuray). RESULTS: We found that 0 mm planning target volume (PTV) margin is sufficient for IGRT of murine tumors using the CK. We observed that higher RT doses (6-8 Gy) decreased absolute cell numbers of tumor infiltrating leukocytes (TIL) by approximately half compared to low doses (2-4 Gy) within 1 h, but even with low dose RT (2 Gy) TIL were found to be reduced after 8-24 h. CONCLUSION: We here demonstrate that the CK RT system allows for targeted IGRT of murine tumors with high precision and constitutes a novel promising platform for translational mouse RT studies.