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BACKGROUND: The use of magnetic resonance (MR) imaging for proton therapy treatment planning is gaining attention as a highly effective method for guidance. At the core of this approach is the generation of computed tomography (CT) images from MR scans. However, the critical issue in this process is accurately aligning the MR and CT images, a task that becomes particularly challenging in frequently moving body areas, such as the head-and-neck. Misalignments in these images can result in blurred synthetic CT (sCT) images, adversely affecting the precision and effectiveness of the treatment planning. PURPOSE: This study introduces a novel network that cohesively unifies image generation and registration processes to enhance the quality and anatomical fidelity of sCTs derived from better-aligned MR images. METHODS: The approach synergizes a generation network (G) with a deformable registration network (R), optimizing them jointly in MR-to-CT synthesis. This goal is achieved by alternately minimizing the discrepancies between the generated/registered CT images and their corresponding reference CT counterparts. The generation network employs a UNet architecture, while the registration network leverages an implicit neural representation (INR) of the displacement vector fields (DVFs). We validated this method on a dataset comprising 60 head-and-neck patients, reserving 12 cases for holdout testing. RESULTS: Compared to the baseline Pix2Pix method with MAE 124.95 ± $\pm$ 30.74 HU, the proposed technique demonstrated 80.98 ± $\pm$ 7.55 HU. The unified translation-registration network produced sharper and more anatomically congruent outputs, showing superior efficacy in converting MR images to sCTs. Additionally, from a dosimetric perspective, the plan recalculated on the resulting sCTs resulted in a remarkably reduced discrepancy to the reference proton plans. CONCLUSIONS: This study conclusively demonstrates that a holistic MR-based CT synthesis approach, integrating both image-to-image translation and deformable registration, significantly improves the precision and quality of sCT generation, particularly for the challenging body area with varied anatomic changes between corresponding MR and CT.
ABSTRACT
Objective.To experimentally validate two online adaptive proton therapy (APT) workflows using Gafchromic EBT3 films and optically stimulated luminescent dosimeters (OSLDs) in an anthropomorphic head-and-neck phantom.Approach.A three-field proton plan was optimized on the planning CT of the head-and-neck phantom with 2.0 Gy(RBE) per fraction prescribed to the clinical target volume. Four fractions were simulated by varying the internal anatomy of the phantom. Three distinct methods were delivered: daily APT researched by the Paul Scherrer Institute (DAPTPSI), online adaptation researched by the Massachusetts General Hospital (OAMGH), and a non-adaptive (NA) workflow. All methods were implemented and measured at PSI. DAPTPSIperformed full online replanning based on analytical dose calculation, optimizing to the same objectives as the initial treatment plan. OAMGHperformed Monte-Carlo-based online plan adaptation by only changing the fluences of a subset of proton beamlets, mimicking the planned dose distribution. NA delivered the initial plan with a couch-shift correction based on in-room imaging. For all 12 deliveries, two films and two sets of OSLDs were placed at different locations in the phantom.Main results.Both adaptive methods showed improved dosimetric results compared to NA. For film measurements in the presence of anatomical variations, the [min-max] gamma pass rates (3%/3 mm) between measured and clinically approved doses were [91.5%-96.1%], [94.0%-95.8%], and [67.2%-93.1%] for DAPTPSI, OAMGH, and NA, respectively. The OSLDs confirmed the dose calculations in terms of absolute dosimetry. Between the two adaptive workflows, OAMGHshowed improved target coverage, while DAPTPSIshowed improved normal tissue sparing, particularly relevant for the brainstem.Significance.This is the first multi-institutional study to experimentally validate two different concepts with respect to online APT workflows. It highlights their respective dosimetric advantages, particularly in managing interfractional variations in patient anatomy that cannot be addressed by non-adaptive methods, such as internal anatomy changes.
Subject(s)
Phantoms, Imaging , Proton Therapy , Radiotherapy Planning, Computer-Assisted , Workflow , Proton Therapy/methods , Radiotherapy Planning, Computer-Assisted/methods , Humans , Radiotherapy Dosage , Monte Carlo Method , RadiometryABSTRACT
PURPOSE: Head and neck cancer (HNC) patients in radiotherapy require adaptive treatment plans due to anatomical changes. Deformable image registration (DIR) is used in adaptive radiotherapy, e.g. for deformable dose accumulation (DDA). However, DIR's ill-posedness necessitates addressing uncertainties, often overlooked in clinical implementations. DIR's further clinical implementation is hindered by missing quantitative commissioning and quality assurance tools. This study evaluates one pathway for more quantitative DDA uncertainties. METHODS: For five HNC patients, each with multiple repeated CTs acquired during treatment, a simultaneous-integrated boost (SIB) plan was optimized. Recalculated doses were warped individually using multiple DIRs from repeated to reference CTs, and voxel-by-voxel dose ranges determined an error-bar for DDA. Followed by evaluating, a previously proposed early-stage DDA uncertainty estimation method tested for lung cancer, which combines geometric DIR uncertainties, dose gradients and their directional dependence, in the context of HNC. RESULTS: Applying multiple DIRs show dose differences, pronounced in high dose gradient regions. The patient with largest anatomical changes (-13.1 % in ROI body volume), exhibited 33 % maximum uncertainty in contralateral parotid, with 54 % of voxels presenting an uncertainty >5 %. Accumulation over multiple CTs partially mitigated uncertainties. The estimation approach predicted 92.6 % of voxels within ±5 % to the reference dose uncertainty across all patients. CONCLUSIONS: DIR variations impact accumulated doses, emphasizing DDA uncertainty quantification's importance for HNC patients. Multiple DIR dose warping aids in quantifying DDA uncertainties. An estimation approach previously described for lung cancer was successfully validated for HNC, for SIB plans, presenting different dose gradients, and for accumulated treatments.
Subject(s)
Head and Neck Neoplasms , Proton Therapy , Radiation Dosage , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Head and Neck Neoplasms/radiotherapy , Head and Neck Neoplasms/diagnostic imaging , Humans , Uncertainty , Proton Therapy/methods , Radiotherapy Planning, Computer-Assisted/methods , Image Processing, Computer-Assisted/methods , Tomography, X-Ray ComputedABSTRACT
Objective.Online magnetic resonance imaging (MRI) guidance could be especially beneficial for pencil beam scanned (PBS) proton therapy of tumours affected by respiratory motion. For the first time to our knowledge, we investigate the dosimetric impact of respiratory motion on MRI-guided proton therapy compared to the scenario without magnetic field.Approach.A previously developed analytical proton dose calculation algorithm accounting for perpendicular magnetic fields was extended to enable 4D dose calculations. For two geometrical phantoms and three liver and two lung patient cases, static treatment plans were optimised with and without magnetic field (0, 0.5 and 1.5 T). Furthermore, plans were optimised using gantry angle corrections (0.5 T +5° and 1.5 T +15°) to reproduce similar beam trajectories compared to the 0 T reference plans. The effect of motion was then considered using 4D dose calculations without any motion mitigation and simulating 8-times volumetric rescanning, with motion for the patient cases provided by 4DCT(MRI) data sets. Each 4D dose calculation was performed for different starting phases and the CTV dose coverageV95%and homogeneityD5%-D95%were analysed.Main results.For the geometrical phantoms with rigid motion perpendicular to the beam and parallel to the magnetic field, a comparable dosimetric effect was observed independent of the magnetic field. Also for the five 4DCT(MRI) cases, the influence of motion was comparable for all magnetic field strengths with and without gantry angle correction. On average, the motion-induced decrease in CTVV95%from the static plan was 17.0% and 18.9% for 1.5 T and 0.5 T, respectively, and 19.9% without magnetic field.Significance.For the first time, this study investigates the combined impact of magnetic fields and respiratory motion on MR-guided proton therapy. The comparable dosimetric effects irrespective of magnetic field strength indicate that the effects of motion for future MR-guided proton therapy may not be worse than for conventional PBS proton therapy.
Subject(s)
Lung Neoplasms , Proton Therapy , Humans , Proton Therapy/methods , Motion , Radiometry/methods , Protons , Magnetic Resonance Imaging/methods , Radiotherapy Planning, Computer-Assisted/methods , Four-Dimensional Computed Tomography/methods , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/radiotherapyABSTRACT
PURPOSE: The aim of this work is to investigate the feasibility of the Jagiellonian Positron Emission Tomography (J-PET) scanner for intra-treatment proton beam range monitoring. METHODS: The Monte Carlo simulation studies with GATE and PET image reconstruction with CASToR were performed in order to compare six J-PET scanner geometries. We simulated proton irradiation of a PMMA phantom with a Single Pencil Beam (SPB) and Spread-Out Bragg Peak (SOBP) of various ranges. The sensitivity and precision of each scanner were calculated, and considering the setup's cost-effectiveness, we indicated potentially optimal geometries for the J-PET scanner prototype dedicated to the proton beam range assessment. RESULTS: The investigations indicate that the double-layer cylindrical and triple-layer double-head configurations are the most promising for clinical application. We found that the scanner sensitivity is of the order of 10-5 coincidences per primary proton, while the precision of the range assessment for both SPB and SOBP irradiation plans was found below 1 mm. Among the scanners with the same number of detector modules, the best results are found for the triple-layer dual-head geometry. The results indicate that the double-layer cylindrical and triple-layer double-head configurations are the most promising for the clinical application, CONCLUSIONS:: We performed simulation studies demonstrating that the feasibility of the J-PET detector for PET-based proton beam therapy range monitoring is possible with reasonable sensitivity and precision enabling its pre-clinical tests in the clinical proton therapy environment. Considering the sensitivity, precision and cost-effectiveness, the double-layer cylindrical and triple-layer dual-head J-PET geometry configurations seem promising for future clinical application.
Subject(s)
Proton Therapy , Protons , Feasibility Studies , Positron-Emission Tomography , Proton Therapy/methods , Phantoms, Imaging , Monte Carlo MethodABSTRACT
Background and purpose: Respiratory suppression techniques represent an effective motion mitigation strategy for 4D-irradiation of lung tumors with protons. A magnetic resonance imaging (MRI)-based study applied and analyzed methods for this purpose, including enhanced Deep-Inspiration-Breath-Hold (eDIBH). Twenty-one healthy volunteers (41-58 years) underwent thoracic MR scans in four imaging sessions containing two eDIBH-guided MRIs per session to simulate motion-dependent irradiation conditions. The automated MRI segmentation algorithm presented here was critical in determining the lung volumes (LVs) achieved during eDIBH. Materials and methods: The study included 168 MRIs acquired under eDIBH conditions. The lung segmentation algorithm consisted of four analysis steps: (i) image preprocessing, (ii) MRI histogram analysis with thresholding, (iii) automatic segmentation, (iv) 3D-clustering. To validate the algorithm, 46 eDIBH-MRIs were manually contoured. Sørensen-Dice similarity coefficients (DSCs) and relative deviations of LVs were determined as similarity measures. Assessment of intrasessional and intersessional LV variations and their differences provided estimates of statistical and systematic errors. Results: Lung segmentation time for 100 2D-MRI planes was â¼ 10 s. Compared to manual lung contouring, the median DSC was 0.94 with a lower 95 % confidence level (CL) of 0.92. The relative volume deviations yielded a median value of 0.059 and 95 % CLs of -0.013 and 0.13. Artifact-based volume errors, mainly of the trachea, were estimated. Estimated statistical and systematic errors ranged between 6 and 8 %. Conclusions: The presented analytical algorithm is fast, precise, and readily available. The results are comparable to time-consuming, manual segmentations and other automatic segmentation approaches. Post-processing to remove image artifacts is under development.
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Purpose: To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods: A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results: The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion: The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.