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), nonadapted 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 &lt; 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.(c) 2021 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 159 (2021) 136-143 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).</p

Daily adaptive proton therapy: challenges and clinical potential

With proton therapy, highly conformal dose can be applied to the tumor while sparing the surrounding organs at risk. Protons are however sensitive to density changes in the beam path: If the patient anatomy is changing, the resulting dose is distorted. To restore the initial plan quality, the plan has to be adapted. In this thesis, the concept of daily adaptive proton therapy (DAPT) is investigated to react to daily anatomical changes and improve the overall treatment quality. With DAPT, a new plan is optimized based on a 3D image acquired directly (some minutes) before each fraction. The whole online workflow must be efficient, not exceeding 5 to 10 minutes, to not increase the occupancy time in the treatment room too much or decrease the patient comfort. DAPT has the potential to improve the treatment quality, but technical and workflow challenges have prevented its clinical integration so far. In this thesis, different aspects about the clinical benefit of DAPT and the sensitivity of DAPT to different uncertainties caused by simplifications in the DAPT workflow, such as analytical dose calculation or structure propagation, are investigated. Additionally, the uncertainties in the evaluation of the overall applied treatment dose and outcome are discussed and the dosimetric benefit of DAPT is shown in a phantom experiment. After a short introduction (chapter 1), more details about the clinical implementation of DAPT at the Paul Scherrer Institute (PSI) are discussed in chapter 2. The potential benefit of DAPT for patients treated in the paranasal sinuses is discussed in chapter 3. There it is shown how DAPT enables novel planning concepts and can reduce the integral dose to healthy tissue. Chapter 4 shows that DAPT brings a dosimetric benefit to the patients, even if the daily plan is optimized with analytical dose calculation algorithms in challenging anatomical sites such as the nose or the lung. Chapter 5 investigates how the use of propagated structures is affecting the dose distribution of the daily plan, because in the strict time span allowed for a DAPT treatment, there is no time for correcting the contours. For each fraction, there is only limited time to check the daily plan, which makes a careful offline dose review and monitoring of the treatment progress necessary. In chapter 6, the uncertainties of deformable image registration for the dose accumulation are investigated and in chapter 7 the effect of DAPT to the clinical outcome (e.g. tumor control, mortality or other side effects) is evaluated. Finally, the dosimetric benefit of the DAPT workflow implemented at PSI is shown in chapter 8 in an end-to-end test over multiple fractions with a newly developed anthropomorphic phantom with anatomical changes. The work described in this thesis puts the benefits of DAPT in relation to different uncertainties occurring during the DAPT workflow. In different planning studies and in an end-to-end experiment it was shown that the dosimetric benefits of DAPT are larger than the risks of the investigated uncertainties. It was also shown that the dosimetric benefit of DAPT can translate into an improved clinical outcome. The first patient treatment with the DAPT workflow tested in this project is planned for the beginning of next year, 2021

Correction of Geometrical Effects of a Knife-Edge Slit Camera for Prompt Gamma-Based Range Verification in Proton Therapy

Prompt gamma (PG) based range verification can potentially reduce the safety margins in proton therapy. A knife-edge slit camera has been developed in this context using analytical PG simulations as reference for absolute range verification during patient treatment. Geometrical deviations between measurement and simulation could be observed and have to be corrected for in order to improve the range retrieval of the system. A geometrical correction model is derived from Monte Carlo simulations in water. The influence of different parameters is tested and the model is validated in a dedicated benchmark experiment. We found that the geometrical correction improves the agreement between measured and simulated PG profiles resulting in an improved range retrieval and higher accuracy for absolute range verification. An intrinsic offset of 1.4 mm between measurement and simulation is observed in the experimental data and corrected in the PG simulation. In summary, the absolute range verification capabilities of a PG camera have been improved by applying a geometrical correction model

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

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

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

Intensity modulated proton therapy plan generation in under ten seconds.

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. 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. 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. 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

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.ISSN:0284-186XISSN:1651-226