Publications by authors named "Florian Kamp"

39 Publications

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

Phys Med Biol 2021 Aug 30;66(17). Epub 2021 Aug 30.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.

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 (4DCBCT), 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 4DCBCTwas 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 4DCBCTand 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 4DCBCTcase. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCT), respectively. The 4DCBCTtechnique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.
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http://dx.doi.org/10.1088/1361-6560/ac16e9DOI Listing
August 2021

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

Radiat Oncol 2021 Jul 21;16(1):133. Epub 2021 Jul 21.

Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany.

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 (D, D, D and V) 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.
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http://dx.doi.org/10.1186/s13014-021-01858-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296626PMC
July 2021

CyberKnife radiation therapy as a platform for translational mouse studies.

Int J Radiat Biol 2021 23;97(9):1261-1269. Epub 2021 Jun 23.

Department of Radiation Oncology and CyberKnife Center, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.

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 Kras/Trp53 -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.
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http://dx.doi.org/10.1080/09553002.2021.1934749DOI Listing
June 2021

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

Med Phys 2021 Aug 29;48(8):4148-4159. Epub 2021 Jun 29.

Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.

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.
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http://dx.doi.org/10.1002/mp.14995DOI Listing
August 2021

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

Z Med Phys 2020 Nov 25. Epub 2020 Nov 25.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany. Electronic address:

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 (D, D, D, D) 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 D, D, D and D 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 D over the lungs was 2.3% and D 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.
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http://dx.doi.org/10.1016/j.zemedi.2020.09.004DOI Listing
November 2020

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.

Med Phys 2021 Feb 18;48(2):805-818. Epub 2020 Dec 18.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany.

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 (10 -10 ) 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 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 D 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.
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http://dx.doi.org/10.1002/mp.14596DOI Listing
February 2021

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

Phys Med Biol 2021 02 16;66(5):055006. Epub 2021 Feb 16.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.

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 mm). 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.
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http://dx.doi.org/10.1088/1361-6560/abc937DOI Listing
February 2021

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

Phys Med Biol 2021 02 16;66(5):055005. Epub 2021 Feb 16.

Ludwig-Maximilians-Universität München, Department of Medical Physics, Munich, Germany. These authors have contributed to this work equally.

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 × 10 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.
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http://dx.doi.org/10.1088/1361-6560/abc939DOI Listing
February 2021

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

Z Med Phys 2020 Nov 6. Epub 2020 Nov 6.

Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching bei München, Germany. Electronic address:

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 (ΔD, ΔD, and ΔD 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 (ΔD≥0.3%, ΔD≥15.9%, ΔD≥3.3% and ΔDHI≥0.102) than lung patients with tumor close to soft tissue (ΔD≤0.4%, ΔD≤5.6%, ΔD≤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.
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http://dx.doi.org/10.1016/j.zemedi.2020.10.002DOI Listing
November 2020

Patient-specific CT calibration based on ion radiography for different detector configurations in H, He and C ion pencil beam scanning.

Phys Med Biol 2020 12 22;65(24):245014. Epub 2020 Dec 22.

Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany. Author to whom any correspondence should be addressed.

The empirical conversion of the treatment planning x-ray computed tomography (CT) image to ion stopping power relative to water causes dose calculation inaccuracies in ion beam therapy. A patient-specific calibration of the CT image is enabled by the combination of an ion radiography (iRad) with the forward-projection of the empirically converted CT image along the estimated ion trajectories. This work investigated the patient-specific CT calibration for list-mode and integration-mode detector configurations, with reference to a ground truth ion CT (iCT) image. Analytical simulations of idealized carbon ion and proton trajectories in a numerical anthropomorphic phantom and realistic Monte Carlo simulations of proton, helium and carbon ion pencil beam scanning in a clinical CT image of a head-and-neck patient were considered. Controlled inaccuracy and noise levels were applied to the calibration curve and to the iRad, respectively. The impact of the selection of slices and angles of the iRads, as well as the choice of the optimization algorithm, were investigated. Accurate and robust CT calibration was obtained in analytical simulations of straight carbon ion trajectories. Analytical simulations of non-straight proton trajectories due to scattering suggested limitations for integration-mode but not for list-mode. To make the most of integration-mode, a dedicated objective function was proposed, demonstrating the desired accuracy for sufficiently high proton statistics in analytical simulations. In clinical data the inconsistencies between the iRad and the forward-projection of the ground truth iCT image were in the same order of magnitude as the applied inaccuracies (up to 5%). The accuracy of the CT calibration were within 2%-5% for integration-mode and 1%-3% for list-mode. The feasibility of successful patient-specific CT calibration depends on detector technologies and is primarily limited by these above mentioned inconsistencies that slightly penalize protons over helium and carbon ions due to larger scattering and beam spot size.
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http://dx.doi.org/10.1088/1361-6560/aba319DOI Listing
December 2020

Medical physics challenges in clinical MR-guided radiotherapy.

Radiat Oncol 2020 May 5;15(1):93. Epub 2020 May 5.

Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748, Garching, Germany.

The integration of magnetic resonance imaging (MRI) for guidance in external beam radiotherapy has faced significant research and development efforts in recent years. The current availability of linear accelerators with an embedded MRI unit, providing volumetric imaging at excellent soft tissue contrast, is expected to provide novel possibilities in the implementation of image-guided adaptive radiotherapy (IGART) protocols. This study reviews open medical physics issues in MR-guided radiotherapy (MRgRT) implementation, with a focus on current approaches and on the potential for innovation in IGART.Daily imaging in MRgRT provides the ability to visualize the static anatomy, to capture internal tumor motion and to extract quantitative image features for treatment verification and monitoring. Those capabilities enable the use of treatment adaptation, with potential benefits in terms of personalized medicine. The use of online MRI requires dedicated efforts to perform accurate dose measurements and calculations, due to the presence of magnetic fields. Likewise, MRgRT requires dedicated quality assurance (QA) protocols for safe clinical implementation.Reaction to anatomical changes in MRgRT, as visualized on daily images, demands for treatment adaptation concepts, with stringent requirements in terms of fast and accurate validation before the treatment fraction can be delivered. This entails specific challenges in terms of treatment workflow optimization, QA, and verification of the expected delivered dose while the patient is in treatment position. Those challenges require specialized medical physics developments towards the aim of fully exploiting MRI capabilities. Conversely, the use of MRgRT allows for higher confidence in tumor targeting and organs-at-risk (OAR) sparing.The systematic use of MRgRT brings the possibility of leveraging IGART methods for the optimization of tumor targeting and quantitative treatment verification. Although several challenges exist, the intrinsic benefits of MRgRT will provide a deeper understanding of dose delivery effects on an individual basis, with the potential for further treatment personalization.
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http://dx.doi.org/10.1186/s13014-020-01524-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201982PMC
May 2020

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

Phys Med Biol 2021 02 5;66(4):045008. Epub 2021 Feb 5.

Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany. Author to whom any correspondence should be addressed.

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.
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http://dx.doi.org/10.1088/1361-6560/ab8fc3DOI Listing
February 2021

Modeling RBE-weighted dose variations in irregularly moving abdominal targets treated with carbon ion beams.

Med Phys 2020 Jul 18;47(7):2768-2778. Epub 2020 Apr 18.

Department of Experimental Physics -Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany.

Purpose: To model four-dimensional (4D) relative biological effectiveness (RBE)-weighted dose variations in abdominal lesions treated with scanned carbon ion beam in case of irregular breathing motion.

Methods: The proposed method, referred to as bioWED method, combines the simulation of tumor motion in a patient- and beam-specific water equivalent depth (WED)-space with RBE modeling, aiming at the estimation of RBE-weighted dose changes due to respiratory motion. The method was validated on a phantom, simulating gated and free breathing dose delivery, and on a patient case, for which free breathing irradiation was assumed and both amplitude and baseline breathing irregularities were simulated through a respiratory motion model. We quantified (a) the effect of motion on the equivalent uniform dose (EUD) and the RBE-weighted dose-volume histograms (DVH), by comparing the planned dose distribution with "ground truth" 4D RBE-weighted doses computed using 4D computed tomography data, and (ii) the estimation error, by comparing the doses estimated with the bioWED method to "ground truth" 4D RBE-weighted doses.

Results: In the phantom validation, the estimation error on the EUD was limited with respect to the motion effect and the median estimation error on relevant RBE-weighted DVH metrics remained within 5%. In the patient study, the estimation error as computed on the EUD was smaller than the corresponding motion effect, exhibiting the largest values in the baseline irregularity simulation. However, the median estimation error over all simulations was below 3.2% considering relevant DVH metrics.

Conclusions: In the evaluated cases, the bioWED method showed proper accuracy when compared to deformable image registration-based 4D dose calculation. Therefore, it can be seen as a tool to test treatment plan robustness against irregular breathing motion, although its accuracy decreases as a function of increasing soft tissue deformation and should be evaluated on a larger patient dataset.
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http://dx.doi.org/10.1002/mp.14135DOI Listing
July 2020

The dosimetric impact of replacing the TG-43 algorithm by model based dose calculation for liver brachytherapy.

Radiat Oncol 2020 Mar 9;15(1):60. Epub 2020 Mar 9.

Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, Munich, 81377, Germany.

Purpose: To compare treatment plans for interstitial high dose rate (HDR) liver brachytherapy with Ir calculated according to current-standard TG-43U1 protocol with model-based dose calculation following TG-186 protocol.

Methods: We retrospectively evaluated dose volume histogram (DVH) parameters for liver, organs at risk (OARs) and clinical target volumes (CTVs) of 20 patient cases diagnosed with hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC). Dose calculations on a homogeneous water geometry (TG-43U1 surrogate) and on a computed tomography (CT) based geometry (TG-186) were performed using Monte Carlo (MC) simulations. The CTs were segmented based on a combination of assigning TG-186 recommended tissues to fixed Hounsfield Unit (HU) ranges and using organ contours delineated by physicians. For the liver, V and V were analysed, and for OARs the dose to 1 cubic centimeter (D). Target coverage was assessed by calculating V, V, V and V as well as D and D. For every DVH parameter, median, minimum and maximum values of the deviations of TG-186 from TG-43U1 were analysed.

Results: TG-186-calculated dose was found to be on average lower than dose calculated with TG-43U1. The deviation of highest magnitude for liver parameters was -6.2% of the total liver volume. For OARs, the deviations were all smaller than or equal to -0.5 Gy. Target coverage deviations were as high as -1.5% of the total CTV volume and -3.5% of the prescribed dose.

Conclusions: In this study we found that TG-43U1 overestimates dose to liver tissue compared to TG-186. This finding may be of clinical importance for cases where dose to the whole liver is the limiting factor.
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http://dx.doi.org/10.1186/s13014-020-01492-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063719PMC
March 2020

A new treatment planning approach accounting for prompt gamma range verification and interfractional anatomical changes.

Phys Med Biol 2020 04 29;65(9):095005. Epub 2020 Apr 29.

Ludwig-Maximilians-Universität München, Department of Medical Physics, Munich, Germany.

Prompt gamma (PG) imaging is widely investigated for spot-by-spot in vivo range verification for proton therapy. Previous studies pointed out that the accuracy of prompt gamma imaging is affected by the statistics (number of protons delivered per pencil beam) of the proton beams and the conformity between prompt gamma and dose distribution (PG-dose correlation). Recently a novel approach to re-optimize conventional treatment plans by boosting a few pencil beams with good PG-dose correlation above the statistics limit for reliable PG detectability was proposed. However, up to now, only PG-dose correlation on the planning computed tomography (CT) was considered, not accounting for the fact that the robustness of the PG-dose correlation is not guaranteed in the cases of interfractional anatomical changes. In this work, this approach is further explored with respect to the robustness of the PG-dose correlation of each pencil beam in the case of interfractional anatomical changes. A research computational platform, combining Monte Carlo pre-calculated pencil beams with the analytical Matlab-based treatment planning system (TPS) CERR, is used for treatment planning. Geant4 is used for realistic simulation of the dose delivery and PG generation for all individual pencil beams in the heterogeneous patient anatomy using multiple CT images for representative patient cases (in this work, CTs of one prostate and one head and neck cancer patient are used). First, a Monte Carlo treatment plan is created using CERR. Thereby the PG emission and dose distribution for each individual spot is obtained. Second, PG-dose correlation is quantified using the originally proposed approach as well as a new indicator, which accounts for the sensitivity of individual spots to heterogeneities in the 3D dose distribution. This is accomplished by using a 2D distal surface (dose surface) derived from the 3D dose distribution for each spot. A few pencil beams are selected for each treatment field, based on their PG-dose correlation and dose surface, and then boosted in the new re-optimized treatment plan. All treatment plans are then fully re-calculated with Monte Carlo on the CT scans of the corresponding patient at three different time points. The result shows that all treatment plans are comparable in terms of dose distribution and dose averaged LET distributions. The spots recommended by our indicators maintain good PG-dose correlation in the cases of interfractional anatomical changes, thus ensuring that the proton range shift due to anatomical changes can be monitored. Compared to another proposed spots aggregation approach, our approach shows advantages in terms of the detectability and reliability of PG, especially in presence of heterogeneities.
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http://dx.doi.org/10.1088/1361-6560/ab7d15DOI Listing
April 2020

Real-time 4DMRI-based internal target volume definition for moving lung tumors.

Med Phys 2020 Apr 10;47(4):1431-1442. Epub 2020 Feb 10.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany.

Purpose: In photon radiotherapy, respiratory-induced target motion can be accounted for by internal target volumes (ITV) or mid-ventilation target volumes (midV) defined on the basis of four-dimensional computed tomography (4D-CT). Intrinsic limitations of these approaches can result in target volumes that are not representative for the gross tumor volume (GTV) motion over the course of treatment. To address these limitations, we propose a novel patient-specific ITV definition method based on real-time 4D magnetic resonance imaging (rt-4DMRI).

Methods: Three lung cancer patients underwent weekly rt-4DMRI scans. A total of 24 datasets were included in this retrospective study. The GTV was contoured on breath-hold MR images and propagated to all rt-4DMRI images by deformable image registration. Different targets were created for the first (reference) imaging sessions: ITVs encompassing all GTV positions over the complete (ITV ) or partial acquisition time ( ), ITVs including only voxels with a GTV probability-of-presence (POP) of at least 5% ( ) or 10% ( ), and the mid-ventilation GTV position. Reference planning target volumes ( ) were created by adding margins around the ITVs and midV target volumes. The geometrical overlap of the with from the six to eight subsequent imaging sessions on days n was quantified in terms of the Dice similarity coefficient (DSC), sensitivity [SE: ( )/ ] and precision [PRE: ( )/ ] as surrogates for target coverage and normal tissue sparing.

Results: Patient-specific analysis yielded a high variance of the overlap values of , when different periods within the reference imaging session were sampled. The mid-ventilation-based PTVs were smaller than the ITV-based PTVs. While the SE was high for patients with small breathing pattern variations, changes of the median breathing amplitudes in different imaging sessions led to inferior SE values for the mid-ventilation PTV for one patient. In contrast, and showed higher SE values with a higher robustness against interfractional changes, at the cost of larger target volumes.

Conclusions: The results indicate that rt-4DMRI could be valuable for the definition of target volumes based on the GTV POP to achieve a higher robustness against interfractional changes than feasible with today's 4D-CT-based target definition concepts.
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http://dx.doi.org/10.1002/mp.14023DOI Listing
April 2020

Method to quickly and accurately calculate absorbed dose from therapeutic and stray photon exposures throughout the entire body in individual patients.

Med Phys 2020 Jun 13;47(5):2254-2266. Epub 2020 Mar 13.

Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748, Garching bei München, Germany.

Purpose: Photon radiotherapy techniques typically devote considerable attention to limiting the exposure of healthy tissues outside of the target volume. Numerous studies have shown, however, that commercial treatment planning systems (TPSs) significantly underestimate the absorbed dose outside of the treatment field. The purpose of this study was to test the feasibility of quickly and accurately calculating the total absorbed dose to the whole body from photon radiotherapy in individual patients.

Methods: We created an extended TPS by implementing a physics-based analytical model for the absorbed dose from stray photons during photon therapy into a research TPS. We configured and validated the extended TPS using measurements of 6- and 15-MV photon beams in water-box and anthropomorphic phantoms. We characterized the additional computation time required for therapeutic and stray dose calculations in a 44 × 30 × 180 cm water-box phantom.

Results: The extended TPS achieved superior dosimetric accuracy compared to the research TPS in both water and anthropomorphic phantoms, especially outside of the primary treatment field. In the anthropomorphic phantom, the extended TPS increased the generalized gamma index passing rate by a factor of 10 and decreased the median dosimetric discrepancy in the out-of-field region by a factor of 26. The extended TPS achieved an average discrepancy <1% in and near the treatment field and <1 mGy/Gy far from the treatment field in the anthropomorphic phantom. Characterization of computation time revealed that on average, the extended TPS only required 7% longer than the research TPS to calculate the total absorbed dose.

Conclusions: The results of this work suggest that it is feasible to quickly and accurately calculate whole-body doses inside and outside of the therapeutic treatment field in individual patients on a routine basis using physics-based analytical dose models. This additional capability enables a more personalized approach to minimizing the risk of radiogenic late effects, such as second cancer and cardiac toxicity, as part of the treatment planning process.
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http://dx.doi.org/10.1002/mp.14018DOI Listing
June 2020

CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation.

Phys Med Biol 2019 11 15;64(22):225004. Epub 2019 Nov 15.

Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany. Department of Radiotherapy, Center for Image Sciences, Universitair Medisch Centrum Utrecht, Utrecht, the Netherlands. Department of Medical Physics, Fakultät für Physik, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany. Author to whom correspondence should be addressed.

In presence of inter-fractional anatomical changes, clinical benefits are anticipated from image-guided adaptive radiotherapy. Nowadays, cone-beam CT (CBCT) imaging is mostly utilized during pre-treatment imaging for position verification. Due to various artifacts, image quality is typically not sufficient for photon or proton dose calculation, thus demanding accurate CBCT correction, as potentially provided by deep learning techniques. This work aimed at investigating the feasibility of utilizing a cycle-consistent generative adversarial network (cycleGAN) for prostate CBCT correction using unpaired training. Thirty-three patients were included. The network was trained to translate uncorrected, original CBCT images (CBCT) into planning CT equivalent images (CBCT). HU accuracy was determined by comparison to a previously validated CBCT correction technique (CBCT). Dosimetric accuracy was inferred for volumetric-modulated arc photon therapy (VMAT) and opposing single-field uniform dose (OSFUD) proton plans, optimized on CBCT and recalculated on CBCT. Single-sided SFUD proton plans were utilized to assess proton range accuracy. The mean HU error of CBCT with respect to CBCT decreased from 24 HU for CBCT to  -6 HU. Dose calculation accuracy was high for VMAT, with average pass-rates of 100%/89% for a 2%/1% dose difference criterion. For proton OSFUD plans, the average pass-rate for a 2% dose difference criterion was 80%. Using a (2%, 2 mm) gamma criterion, the pass-rate was 96%. 93% of all analyzed SFUD profiles had a range agreement better than 3 mm. CBCT correction time was reduced from 6-10 min for CBCT to 10 s for CBCT. Our study demonstrated the feasibility of utilizing a cycleGAN for CBCT correction, achieving high dose calculation accuracy for VMAT. For proton therapy, further improvements may be required. Due to unpaired training, the approach does not rely on anatomically consistent training data or potentially inaccurate deformable image registration. The substantial speed-up for CBCT correction renders the method particularly interesting for adaptive radiotherapy.
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http://dx.doi.org/10.1088/1361-6560/ab4d8cDOI Listing
November 2019

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

Acta Oncol 2019 Oct 4;58(10):1429-1434. Epub 2019 Jul 4.

Department of Radiation Oncology, University Hospital, LMU Munich , Munich , Germany.

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. 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. 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. 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.
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http://dx.doi.org/10.1080/0284186X.2019.1630754DOI Listing
October 2019

Erratum: "ScatterNet: A convolutional neural network for cone-beam CT intensity correction" [Med. Phys. 45, 4916-4926 (2018)].

Med Phys 2019 May 23;46(5):2538. Epub 2019 Mar 23.

Faculty of Physics, Department of Medical Physics, Ludwig-Maximilians-Universität Müunchen (LMU Munich), Garching bei München, 85748, Germany.

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http://dx.doi.org/10.1002/mp.13469DOI Listing
May 2019

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

Med Phys 2019 Jul 7;46(7):3268-3277. Epub 2019 Jun 7.

Department of Experimental Physics - Medical Physics, LMU Munich, Munich, Germany.

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

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

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

Conclusions: We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.
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http://dx.doi.org/10.1002/mp.13579DOI Listing
July 2019

Dosimetric accuracy and radiobiological implications of ion computed tomography for proton therapy treatment planning.

Phys Med Biol 2019 06 12;64(12):125008. Epub 2019 Jun 12.

Department of Medical Physics, Ludwig-Maximilians-Universität München, Garching b. München, Germany. The author to whom correspondence may be addressed.

Ion computed tomography (iCT) represents a potential replacement for x-ray CT (xCT) in ion therapy treatment planning to reduce range uncertainties, inherent in the semi-empirical conversion of xCT information into relative stopping power (RSP). In this work, we aim to quantify the increase in dosimetric accuracy associated with using proton-, helium- and carbon-CT compared to conventional xCT for clinical scenarios in proton therapy. Three cases imaged with active beam-delivery using an ideal single-particle-tracking detector were investigated using FLUKA Monte-Carlo (MC) simulations. The RSP accuracy of the iCTs was evaluated against the ground truth at similar physical dose. Next, the resulting dosimetric accuracy was investigated by using the RSP images as a patient model in proton therapy treatment planning, in comparison to common uncertainties associated with xCT. Finally, changes in relative biological effectiveness (RBE) with iCT particle type/spectrum were investigated by incorporating the repair-misrepair-fixation (RMF) model into FLUKA, to enable first insights on the associated biological imaging dose. Helium-CT provided the lowest overall RSP error, whereas carbon-CT offered the highest accuracy for bone and proton-CT for soft tissue. For a single field, the average relative proton beam-range variation was  -1.00%, +0.09%, -0.08% and  -0.35% for xCT, proton-, helium- and carbon-CT, respectively. Using a 0.5%/0.5mm gamma-evaluation, all iCTs offered comparable accuracy with a better than 99% passing rate, compared to 83% for xCT. The RMF model predictions for RBE for cell death relative to a diagnostic xCT spectrum were 0.82-0.85, 0.85-0.89 and 0.97-1.03 for proton-, helium-, and carbon-CT, respectively. The corresponding RBE for DNA double-strand break induction was generally below one. iCT offers great clinical potential for proton therapy treatment planning by providing superior dose calculation accuracy as well as lower physical and potentially biological dose exposure compared to xCT. For the investigated dose level and ideal detector, proton-CT and helium-CT yielded the best performance.
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http://dx.doi.org/10.1088/1361-6560/ab0fdfDOI Listing
June 2019

Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations.

Phys Med Biol 2019 01 24;64(3):035011. Epub 2019 Jan 24.

Department of Medical Physics, Fakultät für Physik, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany.

Image intensity correction is crucial to enable cone beam computed tomography (CBCT) based radiotherapy dose calculations. This study evaluated three different deep learning based correction methods using a U-shaped convolutional neural network architecture (Unet) in terms of their photon and proton dose calculation accuracy. CT and CBCT imaging data of 42 prostate cancer patients were included. For target ground truth data generation, a CBCT correction method based on CT to CBCT deformable image registration (DIR) was used. The method yields a deformed CT called (i) virtual CT (vCT) which is used to generate (ii) corrected CBCT projections allowing the reconstruction of (iii) a final corrected CBCT image. The single Unet architecture was trained using these three different datasets: (Unet1) raw and corrected CBCT projections, (Unet2) raw CBCT and vCT image slices and (Unet3) raw and reference corrected CBCT image slices. Volumetric arc therapy (VMAT) and proton pencil beam scanning (PBS) single field uniform dose (SFUD) plans were optimized on the reference corrected image and recalculated on the obtained Unet-corrected CBCT images. The mean error (ME) and mean absolute error (MAE) for Unet1/2/3 were [Formula: see text] Hounsfield units (HU) and [Formula: see text] HU. The 1% dose difference pass rates were better than 98.4% for VMAT for 8 test patients not seen during training, with little difference between Unets. Gamma evaluation results were even better. For protons a gamma evaluation was employed to account for small range shifts, and [Formula: see text] mm pass rates for Unet1/2/3 were better than [Formula: see text] and 91%. A 3 mm range difference threshold was established. Only for Unet3 the 5th and 95th percentiles of the range difference distributions over all fields, test patients and dose profiles were within this threshold. A single Unet architecture was successfully trained using both CBCT projections and CBCT image slices. Since the results of the other Unets were poorer than Unet3, we conclude that training using corrected CBCT image slices as target data is optimal for PBS SFUD proton dose calculations, while for VMAT all Unets provided sufficient accuracy.
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http://dx.doi.org/10.1088/1361-6560/aaf496DOI Listing
January 2019

Application of variance-based uncertainty and sensitivity analysis to biological modeling in carbon ion treatment plans.

Med Phys 2019 Feb 18;46(2):437-447. Epub 2018 Dec 18.

Department of Radiation Oncology, Technical University of Munich, Klinikum rechts der Isar, Ismaninger Str. 22, 81675, München, Germany.

Purpose: In ion beam therapy, biological models to estimate the relative biological effectiveness (RBE) and subsequently the RBE-weighted dose (RWD) are needed in treatment planning and plan evaluation. The required biological parameters as well as their dependency on ion species and ion energy can typically not be determined directly in experiments for in vivo situations. For that reason they are often derived from in vitro data and biological modeling and subject to large uncertainties. We present a model-independent Monte Carlo (variance-) based uncertainty and Sensitivity Analysis (SA) approach to quantify the impact of different input uncertainties on a simulated carbon ion treatment plan.

Method: The influences of different input uncertainties are examined by variance-based SA methods. In this Monte Carlo approach, a function is evaluated 10 -10 times. For each of those runs, all inputs are changed simultaneously, using random numbers according to their associated uncertainties. Variance-based statistic formalisms then rank the input parameter/uncertainty pairs according to their impact on the result of the function. The method of SA includes an uncertainty analysis and was applied to a two-field spot scanning carbon ion treatment plan for two commonly used biological models and two representative tissue parameter sets.

Results: Based on an exemplary patient case, the application of variance-based SA for biological measures, relevant in (carbon) ion therapy, is demonstrated. A voxel-wise calculation for 2.9 · 10 voxels takes ~6 h. A structure-based SA, which adds an uncertainty band to a RWD-volume histogram (RW-DVH) and shows how to decrease the uncertainty in the most effective way, can be calculated in 0.1-1.5 h (depending on the size of the structure). The uncertainties in RBE, RWD or RW-DVH are broken down to the impact of different uncertainties in the (biological) model input. Biological uncertainties have a higher impact on the resulting RBE and RWD than uncertainties in the physical dose. Excluding the physical dose from the SA only slightly decreased the overall uncertainty, emphasizing the necessity to include biological uncertainties into treatment plan evaluation.

Conclusion: Variance-based SA is a powerful tool to evaluate the impact of uncertainties in (carbon) ion therapy. The number of input parameters that can be examined at once is only limited by computation time. A Monte Carlo-derived, comprehensive uncertainty quantification and a corresponding sensitivity analysis are implemented and provide new information for treatment plan evaluation. A possible future application is a SA-based biologically robust treatment plan optimization using the additional uncertainty information as presented here.
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http://dx.doi.org/10.1002/mp.13306DOI Listing
February 2019

Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study.

Z Med Phys 2019 Aug 14;29(3):249-261. Epub 2018 Nov 14.

Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Am Coulombwall 1, 85748 Garching, Germany. Electronic address:

Inter-fractional variations of breathing pattern and patient anatomy introduce dose uncertainties in proton therapy. One approach to monitor these variations is to utilize the cone-beam computed tomography (CT, CBCT) scans routinely taken for patient positioning, reconstruct them as 4DCBCTs, and generate 'virtual CTs' (vCTs), combining the accurate CT numbers of the diagnostic 4DCT and the geometry of the daily 4DCBCT by using deformable image registration (DIR). In this study different algorithms for 4DCBCT reconstruction and DIR were evaluated. For this purpose, CBCT scans of a moving ex vivo porcine lung phantom with 663 and 2350 projections respectively were acquired, accompanied by an additional 4DCT as reference. The CBCT projections were sorted in 10 phase bins with the Amsterdam-shroud method and reconstructed phase-by-phase using first a FDK reconstruction from the Reconstruction Toolkit (RTK) and again an iterative reconstruction algorithm implemented in the Gadgetron Toolkit. The resulting 4DCBCTs were corrected by DIR of the corresponding 4DCT phases, using both a morphons algorithm from REGGUI and a b-spline deformation from Plastimatch. The resulting 4DvCTs were compared to the 4DCT by visual inspection and by calculating water equivalent thickness (WET) maps from the phantom's surface to the distal edge of a target from various angles. The optimized procedure was successfully repeated with mismatched input phases and on a clinical patient dataset. Proton treatment plans were simulated on the 4DvCTs and the dose distributions compared to the reference based on the 4DCT via gamma pass rate analysis. A combination of iterative reconstruction and morphons DIR yielded the most accurate 4DvCTs, with median WET differences under 2mm and 3%/3mm gamma pass rates per phase between 89% and 99%. These results suggest that image correction of iteratively reconstructed 4DCBCTs with a morphons DIR of the planning CT may yield sufficiently accurate 4DvCTs for daily time resolved proton dose calculations.
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http://dx.doi.org/10.1016/j.zemedi.2018.10.005DOI Listing
August 2019

Dose-guided patient positioning in proton radiotherapy using multicriteria-optimization.

Z Med Phys 2019 Aug 5;29(3):216-228. Epub 2018 Nov 5.

OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Fetscherstr. 74, PF 41, 01307 Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, 01307 Dresden, Germany; German Cancer Consortium (DKTK) partner site Dresden, Germany and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Bautzner Landstr. 400, 01328 Dresden, Germany.

Proton radiotherapy (PT) requires accurate target alignment before each treatment fraction, ideally utilizing 3D in-room X-ray computed tomography (CT) imaging. Typically, the optimal patient position is determined based on anatomical landmarks or implanted markers. In the presence of non-rigid anatomical changes, however, the planning scenario cannot be exactly reproduced and positioning should rather aim at finding the optimal position in terms of the actually applied dose. In this work, dose-guided patient alignment, implemented as multicriterial optimization (MCO) problem, was investigated in the scope of intensity-modulated and double-scattered PT (IMPT and DSPT) for the first time. A method for automatically determining the optimal patient position with respect to pre-defined clinical goals was implemented. Linear dose interpolation was used to access a continuous space of potential patient shifts. Fourteen head and neck (H&N) and eight prostate cancer patients with up to five repeated CTs were included. Dose interpolation accuracy was evaluated and the potential dosimetric advantages of dose-guided over bony-anatomy-based patient alignment investigated by comparison of clinically relevant target and organ-at-risk (OAR) dose-volume histogram (DVH) parameters. Dose interpolation was found sufficiently accurate with average pass-rates of 90% and 99% for an exemplary H&N and prostate patient, respectively, using a 2% dose-difference criterion. Compared to bony-anatomy-based alignment, the main impact of automated MCO-based dose-guided positioning was a reduced dose to the serial OARs (spinal cord and brain stem) for the H&N cohort. For the prostate cohort, under-dosage of the target structures could be efficiently diminished. Limitations of dose-guided positioning were mainly found in reducing target over-dosage due to weight loss for H&N patients, which might require adaptation of the treatment plan. Since labor-intense online quality-assurance is not required for dose-guided patient positioning, it might, nevertheless, be considered an interesting alternative to full online re-planning for initially mitigating the effects of anatomical changes.
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http://dx.doi.org/10.1016/j.zemedi.2018.10.003DOI Listing
August 2019

Toward a new treatment planning approach accounting for in vivo proton range verification.

Phys Med Biol 2018 10 30;63(21):215025. Epub 2018 Oct 30.

Department of Medical Physics, Ludwig-Maximilians-Universität München, Munich, Germany. Author to whom any correspondence should be addressed.

Protons with modern pencil-beam scanning delivery are widely used in state-of-the-art radiotherapy. To reduce the unwanted effect of proton range uncertainties, prompt gamma (PG) monitoring is investigated and considered one of the most promising methods for real-time, in vivo range verification. Despite good correlation between the penetration depth of the PG signal and proton range in most cases, mismatch can occur especially because of tissue heterogeneities. Moreover, detectability and reproducibility of the prompt gamma signal critically depends on counting statistics. Nowadays, conventional treatment planning systems do not account for the degree of correlation between dose and PG signal nor the expected PG signal counting statistics, which considerably influences the possibility of a reliable verification of the intended beam range. Hence, in this project, we investigate a new treatment planning approach, in which the spot-by-spot conformities between PG and dose profiles (PG-dose correlation) as well as PG signal detectability and precision are taken into account based on a TPS optimizer. To investigate the feasibility of this idea, a research computational platform, combining Monte Carlo (MC, Geant4) pre-calculated pencil beams with the analytical Matlab-based TPS engine CERR, is used for treatment planning. Geant4 is employed for realistic simulation of the dose delivery and PG generation of all spots in the heterogeneous patient anatomy given by CT images. First of all, a treatment plan is created using a charged particle extension of CERR. Secondly, the PG fall-off positions of all individual pencil beams are evaluated and compared to the 80% distal dose fall-off positions. Thirdly, the PG-dose correlations of all spots are quantified. A new plan, in which a few spots with the best PG-dose correlation are boosted to ensure PG detectability with good precision, is then made. Finally, the optimized plan is fully recalculated on the same patient CT using Geant4, and the result is evaluated considering both plan quality and beam range monitorability. The evaluation shows that the re-optimized treatment plan is comparable to the initial plan in terms of dose distribution, dose averaged LET distribution and robustness, while fulfilling the set statistical conditions for reliable PG monitoring of the few automatically or manually selected spots. The method could thus complement, and for the selected pencil beams even overcome limitations of, alternative suggested approach such as pencil beam aggregation to provide sufficient counting statistics for precise PG range retrieval with good correlation to the treatment dose.
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http://dx.doi.org/10.1088/1361-6560/aae749DOI Listing
October 2018

ScatterNet: A convolutional neural network for cone-beam CT intensity correction.

Med Phys 2018 Nov 8;45(11):4916-4926. Epub 2018 Oct 8.

Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching bei München, 85748, Germany.

Purpose: To demonstrate a proof-of-concept for fast cone-beam CT (CBCT) intensity correction in projection space by the use of deep learning.

Methods: The CBCT scans and corresponding projections were acquired from 30 prostate cancer patients. Reference shading correction was performed using a validated method (CBCT ), which estimates scatter and other low-frequency deviations in the measured CBCT projections on the basis of a prior CT image obtained from warping the planning CT to the CBCT. A convolutional neural network (ScatterNet) was designed, consisting of an attenuation conversion stage followed by a shading correction stage using a UNet-like architecture. The combined network was trained in 2D, utilizing pairs of measured and corrected projections of the reference method, in order to perform shading correction in projection space before reconstruction. The number of patients used for training, testing, and evaluation was 15, 7, and 8, respectively. The reconstructed CBCT was compared to CBCT in terms of mean and absolute errors (ME and MAE) for the eight evaluation patients (not included in the network training). Volumetric modulated arc photon therapy (VMAT) and intensity-modulated proton therapy (IMPT) plans were generated on CBCT . Dose was recalculated on CBCT to evaluate its dosimetric accuracy. Single-field uniform dose proton plans were utilized for proton range comparison of CBCT and CBCT .

Results: The CBCT showed no cupping artifacts and a considerably smaller MAE and ME with respect to CBCT than the uncorrected CBCT (on average 144 Hounsfield units (HU) vs 46 HU for MAE and 138 HU vs -3 HU for ME). The pass-rates using a 2% dose-difference criterion at 50% dose cut-off, were close to 100% for the VMAT plans of all patients when comparing CBCT to CBCT . For IMPT plans pass-rates were clearly lower, ranging from 15% to 81%. Proton range differences of up to 5 mm occurred.

Conclusions: Using a deep convolutional neural network for CBCT intensity correction was shown to be feasible in the pelvic region for the first time. Dose calculation accuracy on CBCT was high for VMAT, but unsatisfactory for IMPT. With respect to the reference technique (CBCT ), the neural network enabled a considerable increase in speed for intensity correction and might eventually allow for on-the-fly shading correction during CBCT acquisition.
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http://dx.doi.org/10.1002/mp.13175DOI Listing
November 2018

Impact of interpatient variability on organ dose estimates according to MIRD schema: Uncertainty and variance-based sensitivity analysis.

Med Phys 2018 Jul 8;45(7):3391-3403. Epub 2018 Jun 8.

Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching, 85748, Germany.

Purpose: Variance-based sensitivity analysis (SA) is described and applied to the radiation dosimetry model proposed by the Committee on Medical Internal Radiation Dose (MIRD) for the organ-level absorbed dose calculations in nuclear medicine. The uncertainties in the dose coefficients thus calculated are also evaluated.

Methods: A Monte Carlo approach was used to compute first-order and total-effect SA indices, which rank the input factors according to their influence on the uncertainty in the output organ doses. These methods were applied to the radiopharmaceutical (S)-4-(3- F-fluoropropyl)-L-glutamic acid ( F-FSPG) as an example. Since F-FSPG has 11 notable source regions, a 22-dimensional model was considered here, where 11 input factors are the time-integrated activity coefficients (TIACs) in the source regions and 11 input factors correspond to the sets of the specific absorbed fractions (SAFs) employed in the dose calculation. The SA was restricted to the foregoing 22 input factors. The distributions of the input factors were built based on TIACs of five individuals to whom the radiopharmaceutical F-FSPG was administered and six anatomical models, representing two reference, two overweight, and two slim individuals. The self-absorption SAFs were mass-scaled to correspond to the reference organ masses.

Results: The estimated relative uncertainties were in the range 10%-30%, with a minimum and a maximum for absorbed dose coefficients for urinary bladder wall and heart wall, respectively. The applied global variance-based SA enabled us to identify the input factors that have the highest influence on the uncertainty in the organ doses. With the applied mass-scaling of the self-absorption SAFs, these factors included the TIACs for absorbed dose coefficients in the source regions and the SAFs from blood as source region for absorbed dose coefficients in highly vascularized target regions. For some combinations of proximal target and source regions, the corresponding cross-fire SAFs were found to have an impact.

Conclusion: Global variance-based SA has been for the first time applied to the MIRD schema for internal dose calculation. Our findings suggest that uncertainties in computed organ doses can be substantially reduced by performing an accurate determination of TIACs in the source regions, accompanied by the estimation of individual source region masses along with the usage of an appropriate blood distribution in a patient's body and, in a few cases, the cross-fire SAFs from proximal source regions.
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http://dx.doi.org/10.1002/mp.12984DOI Listing
July 2018

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment.

Phys Med Biol 2018 05 29;63(11):115008. Epub 2018 May 29.

Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Netherlands.

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with  >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in  -1.2  ±  1.2 mm (-0.5%  ±  0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.
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http://dx.doi.org/10.1088/1361-6560/aabb60DOI Listing
May 2018
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