Review and recommendations on deformable image registration uncertainties for radiotherapy applications.

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

Comparing Predicted Toxicities between Hypofractionated Proton and Photon Radiotherapy of Liver Cancer Patients with Different Adaptive Schemes.

With the availability of MRI linacs, online adaptive intensity modulated radiotherapy (IMRT) has become a treatment option for liver cancer patients, often combined with hypofractionation. Intensity modulated proton therapy (IMPT) has the potential to reduce the dose to healthy tissue, but it is particularly sensitive to changes in the beam path and might therefore benefit from online adaptation. This study compares the normal tissue complication probabilities (NTCPs) for liver and duodenal toxicity for adaptive and non-adaptive IMRT and IMPT treatments of liver cancer patients. Adaptive and non-adaptive IMRT and IMPT plans were optimized to 50 Gy (RBE = 1.1 for IMPT) in five fractions for 10 liver cancer patients, using the original MRI linac images and physician-drawn structures. Three liver NTCP models were used to predict radiation-induced liver disease, an increase in albumin-bilirubin level, and a Child-Pugh score increase of more than 2. Additionally, three duodenal NTCP models were used to predict gastric bleeding, gastrointestinal (GI) toxicity with grades >3, and duodenal toxicity grades 2-4. NTCPs were calculated for adaptive and non-adaptive IMRT and IMPT treatments. In general, IMRT showed higher NTCP values than IMPT and the differences were often significant. However, the differences between adaptive and non-adaptive treatment schemes were not significant, indicating that the NTCP benefit of adaptive treatment regimens is expected to be smaller than the expected difference between IMRT and IMPT.

Large anatomical changes in head-and-neck cancers - A dosimetric comparison of online and offline adaptive proton therapy.

Purpose: This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods: IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results: Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion: Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers.

PURPOSE: To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. METHODS: We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. RESULTS: The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. CONCLUSION: The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.

Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans.

Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1-5 repeated images during treatment: 'reference adaptation', with structures drawn by a physician; 'single-DIR adaptation', using a single set of deformably propagated structures; 'multi-DIR adaptation', using robust planning with multiple deformed structure sets; 'conservative adaptation', using the intersection and union of all deformed structures; 'probabilistic adaptation', using the probability of a voxel belonging to the structure in the optimization weight; and 'no adaptation'. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast 'plausibility check', and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.

Experimental validation of daily adaptive proton therapy.

Anatomical changes during proton therapy require rapid treatment plan adaption to mitigate the associated dosimetric impact. This in turn requires a highly efficient workflow that minimizes the time between imaging and delivery. At the Paul Scherrer Institute, we have developed an online adaptive workflow, which is specifically designed for treatments in the skull-base/cranium, with the focus set on simplicity and minimizing changes to the conventional workflow. The dosimetric and timing performance of this daily adaptive proton therapy (DAPT) workflow has been experimentally investigated using an in-house developed DAPT software and specifically developed anthropomorphic phantom. After a standard treatment preparation, which includes the generation of a template plan, the treatment can then be adapted each day, based on daily imaging acquired on an in-room CT. The template structures are then rigidly propagated to this CT and the daily plan is fully re-optimized using the same field arrangement, DVH constraints and optimization settings of the template plan. After a dedicated plan QA, the daily plan is delivered. To minimize the time between imaging and delivery, clinically integrated software for efficient execution of all online adaption steps, as well as tools for comprehensive and automated QA checks, have been developed. Film measurements of an end-to-end validation of a multi-fraction DAPT treatment showed high agreement to the calculated doses. Gamma pass rates with a 3%/3 mm criteria were >92% when comparing the measured dose to the template plan. Additionally, a gamma pass rate >99% was found comparing measurements to the Monte Carlo dose of the daily plans reconstructed from the logfile, accumulated over the delivered fractions. With this, we experimentally demonstrate that the described adaptive workflow can be delivered accurately in a timescale similar to a standard delivery.

An approach for estimating dosimetric uncertainties in deformable dose accumulation in pencil beam scanning proton therapy for lung cancer.

Deformable image registration (DIR) is an important component for dose accumulation and associated clinical outcome evaluation in radiotherapy. However, the resulting deformation vector field (DVF) is subject to unavoidable discrepancies when different algorithms are applied, leading to dosimetric uncertainties of the accumulated dose. We propose here an approach for proton therapy to estimate dosimetric uncertainties as a consequence of modeled or estimated DVF uncertainties. A patient-specific DVF uncertainty model was built on the first treatment fraction, by correlating the magnitude differences of five DIR results at each voxel to the magnitude of any single reference DIR. In the following fractions, only the reference DIR needs to be applied, and DVF geometric uncertainties were estimated by this model. The associated dosimetric uncertainties were then derived by considering the estimated geometric DVF uncertainty, the dose gradient of fractional recalculated dose distribution and the direction factor from the applied reference DIR of this fraction. This estimated dose uncertainty was respectively compared to the reference dose uncertainty when different DIRs were applied individually for each dose warping. This approach was validated on seven NSCLC patients, each with nine repeated CTs. The proposed model-based method is able to achieve dose uncertainty distribution on a conservative voxel-to-voxel comparison within ±5% of the prescribed dose to the 'reference' dosimetric uncertainty, for 77% of the voxels in the body and 66%-98% of voxels in investigated structures. We propose a method to estimate DIR induced uncertainties in dose accumulation for proton therapy of lung tumor treatments.

Dosimetric influence of deformable image registration uncertainties on propagated structures for online daily adaptive proton therapy of lung cancer patients.

PURPOSE: A major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow. MATERIAL AND METHODS: For five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs. RESULTS: Due to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach. CONCLUSION: For the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption.

Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy.

BACKGROUND AND PURPOSE: Non-small cell lung cancer (NSCLC) patients show typically large anatomical changes during treatment, making recalculation or adaption necessary. For report and review, the applied treatment dose can be accumulated on the reference planning CT using deformable image registration (DIR). We investigated the dosimetric impact of using six different clinically available DIR algorithms for dose accumulation in presence of inter-fractional anatomy variations. MATERIALS AND METHODS: For seven NSCLC patients, proton treatment plans with 66 Gy-RBE to the planning target volume (PTV) were optimised. Nine repeated CTs were registered to the planning CT using six DIR algorithms each. All CTs were acquired in visually guided deep-inspiration breath-hold. The plans were recalculated on the repeated CTs and warped back to the planning CT using the corresponding DIRs. Fraction doses warped with the same DIR were summed up to six different accumulated dose distributions per patient, and compared to the initial dose. RESULTS: The PTV-V95 of accumulated doses decreased by 16% on average over all patients, with variations due to DIR selection of 8.7%. A separation of the dose effects caused by anatomical changes and DIR uncertainty showed a good agreement between the dose degradation caused by anatomical changes and the dose predicted from the average of all DIRs (differences of only 1.6%). CONCLUSION: The dose degradation caused by anatomical changes was more pronounced than the uncertainty of employing different DIRs for dose accumulation, with averaged results from several DIRs providing a good representation of dose degradation caused by anatomy. However, accumulated dose variations between DIRs can be substantial, leading to an additional dose uncertainty.

Daily Adaptive Proton Therapy: Is it Appropriate to Use Analytical Dose Calculations for Plan Adaption?

PURPOSE: The accuracy of analytical dose calculations (ADC) and dose uncertainties resulting from anatomical changes are both limiting factors in proton therapy. For the latter, rapid plan adaption is necessary; for the former, Monte Carlo (MC) approaches are increasingly recommended. These, however, are inherently slower than analytical approaches, potentially limiting the ability to rapidly adapt plans. Here, we compare the clinical relevance of uncertainties resulting from both. METHODS AND MATERIALS: Five patients with non-small cell lung cancer with up to 9 computed tomography (CT) scans acquired during treatment and five paranasal (head and neck) patients with 10 simulated anatomical changes (sinus filling) were analyzed. On the initial planning CT scans, treatment plans were optimized and calculated using an ADC and then recalculated with MC. Additionally, all plans were recalculated (non-adapted) and reoptimized (adapted) on each repeated CT using the same ADC as for the initial plan, and the resulting dose distributions were compared. RESULTS: When comparing analytical and MC calculations in the initial treatment plan and averaged over all patients, 94.2% (non-small cell lung cancer) and 98.5% (head and neck) of voxels had differences <±5%, and only minor differences in clinical target volume (CTV) V95 (average <2%) were observed. In contrast, when recalculating nominal plans on the repeat (anatomically changed) CT scans, CTV V95 degraded by up to 34%. Plan adaption, however, restored CTV V95 differences between adapted and nominal plans to <0.5%. Adapted organ-at-risk doses remained the same or improved. CONCLUSIONS: Dose degradations caused by anatomic changes are substantially larger than uncertainties introduced by the use of analytical instead of MC dose calculations. Thus, if the use of analytical calculations can enable more rapid and efficient plan adaption than MC approaches, they can and should be used for plan adaption for these patient groups.

Online daily adaptive proton therapy.

It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an online adaptive strategy.

The influence of errors in small field dosimetry on the dosimetric accuracy of treatment plans.

Background: Dosimetric effects of inaccuracies of output factors (OFs) implemented in treatment planning systems (TPSs) were investigated.Materials and methods: Modified beam models (MBM) for which the OFs of small fields (down to 1 × 1 cm2) were increased by up to 12% compared to the original beam models (OBM) were created for two TPSs. These beam models were used to recalculate treatment plans of different complexity. Treatment plans using stereotactic 3D-conformal (s3D-CRT) for brain metastasis as well as VMAT plans for head and neck and prostate cancer patients were generated. Dose distributions calculated with the MBM and the OBM were compared to measured dose distributions acquired using film dosimetry and a 2D-detector-array. For the s3D-CRT plans the calculated and measured dose at the isocenter was evaluated. For VMAT, gamma pass rates (GPRs) were calculated using global gamma index with 3%/3 mm, 2%/3 mm, 1%/3 mm and 2%/2 mm with a 20% threshold. Contribution of small fields to the total fluence was expressed as the ratio (F) of fluence trough leaf openings smaller than 2 cm to the total fluence.Results: Using film dosimetry for the s3D-CRT plans, the average of the ratio of calculated dose to measured dose at the isocenter was 1.01 and 1.06 for the OBM and MBM model, respectively. A significantly lower GPR of the MBM compared to the OBM was only found for the localized prostate cases (F = 12.4%) measured with the 2D-detector-array and an acceptance criterion of 1%/3 mm.Conclusion: The effects of uncertainties in small field OFs implemented in TPSs are most pronounced for s3D-CRT cases and can be clearly identified using patient specific quality assurance. For VMAT these effects mainly remain undetected using standard patient specific quality assurance. Using tighter acceptance criteria combined with an analysis of the fluence generated by small fields can help identifying inaccuracies of OFs implemented in TPSs.

Daily adaptive proton therapy - the key to innovative planning approaches for paranasal cancer treatments.

Background: For proton therapy of paranasal tumors, field directions avoiding volumes that might change during therapy are typically used. If the plan is optimized on the daily anatomy using daily adapted proton therapy (DAPT) however, field directions crossing the nasal cavities might be feasible. In this study, we investigated the effectiveness of DAPT for enabling narrow-field treatment approaches. Material and methods: For five paranasal tumor patients, representing a wide patient spectrum, anatomically robust 4-field-star and narrow-field plans were calculated and their robustness to anatomical and setup uncertainties was compared with and without DAPT. Based on the nominal planning CTs, per patient up to 125 simulated CTs (simCTs) with different nasal cavity fillings were created and random translations and rotations due to patient setup uncertainties were further simulated. Plans were recalculated or re-optimized on all error scenarios, representing non-adapted and DAPT fractions, respectively. From these, 100 possible treatments (60 GyRBE, 30 fx) were simulated and changes in integral dose, target and organs at risk (OARs) doses evaluated. Results: In comparison to the 4-field-star approach, the use of narrow-fields reduced integral dose between 29% and 56%. If OARs did not overlap with the target, OAR doses were also reduced. Finally, the significantly reduced target coverage in non-adapted treatments (mean V95 reductions of up to 34%) could be almost fully restored with DAPT in all cases (differences <1%). Conclusions: DAPT was found to be not only an effective way to increase plan robustness to anatomical and positional uncertainties, but also opened the possibility to use improved and more conformal field arrangements.

Intensity modulated proton therapy plan generation in under ten seconds.

Background: Treatment planning for intensity modulated proton therapy (IMPT) can be significantly improved by reducing the time for plan calculation, facilitating efficient sampling of the large solution space characteristic of IMPT treatments. Additionally, fast plan generation is a key for online adaptive treatments, where the adapted plan needs to be ideally available in a few seconds. However, plan generation is a computationally demanding task and, although dose restoration methods for adaptive therapy have been proposed, computation times remain problematic. Material and methods: IMPT plan generation times were reduced by the development of dedicated graphical processing unit (GPU) kernels for our in-house, clinically validated, dose and optimization algorithms. The kernels were implemented into a coherent system, which performed all steps required for a complete treatment plan generation. Results: Using a single GPU, our fast implementation was able to generate a complete new treatment plan in 5-10 sec for typical IMPT cases, and in under 25 sec for plans to very large volumes such as for cranio-spinal axis irradiations. Although these times did not include the manual input of optimization parameters or a final clinical dose calculation, they included all required computational steps, including reading of CT and beam data. In addition, no compromise was made on plan quality. Target coverage and homogeneity for four patient plans improved (by up to 6%) or remained the same (changes <1%). No worsening of dose-volume parameters of the relevant organs at risk by more than 0.5% was observed. Conclusions: Fast plan generation with a clinically validated dose calculation and optimizer is a promising approach for daily adaptive proton therapy, as well as for automated or highly interactive planning.

Sensitivity of a prompt-gamma slit-camera to detect range shifts for proton treatment verification.

BACKGROUND AND PURPOSE: A prompt-gamma imaging (PGI) slit-camera was recently applied successfully in clinical proton treatments using pencil beam scanning (PBS) and double scattering (DS). However, its full capability under clinical conditions has still to be systematically evaluated. Here, the performance of the slit-camera is systematically assessed in well-defined error scenarios using realistic treatment deliveries to an anthropomorphic head phantom. MATERIALS AND METHODS: The sensitivity and accuracy to detect introduced global and local range shifts with the slit-camera was investigated in PBS and DS irradiations. For PBS, measured PGI information of shifted geometries were compared spot-wise with un-shifted PGI information derived from either a reference measurement or a treatment-plan-based simulation. Furthermore, for DS and PBS the integral PGI signal of the whole field was evaluated. RESULTS: Deviations from the treatment plan were detected with an accuracy better than 2 mm in PBS. The PGI simulation accuracy was well below 1 mm. Interfractional comparisons are more affected by measurement noise. The field-integral PGI sum signal allows the detection of global shifts in DS. CONCLUSIONS: Detection of global and local range shifts under close-to-clinical conditions is possible with the PGI slit-camera. Especially for PBS, high sensitivity and high accuracy in shift detection were found.