Publications by authors named "Guillaume Landry"

85 Publications

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

Phys Med Biol 2021 08 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-021-01858-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296626PMC
July 2021

An empirical artifact correction for proton computed tomography.

Phys Med 2021 Jun 28;86:57-65. Epub 2021 May 28.

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

Purpose: To reduce image artifacts of proton computed tomography (pCT) from a preclinical scanner, for imaging of the relative stopping power (RSP) needed for particle therapy treatment planning using a simple empirical artifact correction method.

Methods: We adapted and employed a correction method previously used for beam-hardening correction in x-ray CT which makes use of a single scan of a custom-built homogeneous phantom with known RSP. Exploiting the linearity of the filtered backprojection operation, a function was found which corrects water-equivalent path lengths (RSP line integrals) in experimental scans using a prototype pCT scanner. The correction function was applied to projection values of subsequent scans of a homogeneous water phantom, a sensitometric phantom with various inserts and an anthropomorphic head phantom. Data were acquired at two different incident proton energies to test the robustness of the method.

Results: Inaccuracies in the detection process caused an offset and known ring artifacts in the water phantom which were considerably reduced using the proposed method. The mean absolute percentage error (MAPE) of mean RSP values of all inserts of the sensitometric phantom and the water phantom was reduced from 0.87% to 0.44% and from 0.86% to 0.48% for the two incident energies respectively. In the head phantom a clear reduction of artifacts was observed.

Conclusions: Image artifacts of experimental pCT scans with a prototype scanner could substantially be reduced both in homogeneous, heterogeneous and anthropomorphic phantoms. RSP accuracy was also improved.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ejmp.2021.05.018DOI 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.
View Article and Find Full Text PDF

Download full-text PDF

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

Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives.

Phys Med 2021 May 19;85:175-191. Epub 2021 May 19.

Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy.

Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast compared to on-board CT-based systems, MRgRT is expected to significantly improve the treatment in many situations. MRgRT systems may extend the management of inter- and intra-fraction anatomical changes, offering the possibility of online adaptation of the dose distribution according to daily patient anatomy and to directly monitor tumor motion during treatment delivery by means of a continuous cine MR acquisition. Online adaptive treatments require a multidisciplinary and well-trained team, able to perform a series of operations in a safe, precise and fast manner while the patient is waiting on the treatment couch. Artificial Intelligence (AI) is expected to rapidly contribute to MRgRT, primarily by safely and efficiently automatising the various manual operations characterizing online adaptive treatments. Furthermore, AI is finding relevant applications in MRgRT in the fields of image segmentation, synthetic CT reconstruction, automatic (on-line) planning and the development of predictive models based on daily MRI. This review provides a comprehensive overview of the current AI integration in MRgRT from a medical physicist's perspective. Medical physicists are expected to be major actors in solving new tasks and in taking new responsibilities: their traditional role of guardians of the new technology implementation will change with increasing emphasis on the managing of AI tools, processes and advanced systems for imaging and data analysis, gradually replacing many repetitive manual tasks.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ejmp.2021.05.010DOI Listing
May 2021

Validation of the collapsed cone algorithm for HDR liver brachytherapy against Monte Carlo simulations.

Brachytherapy 2021 Jul-Aug;20(4):936-947. Epub 2021 May 15.

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

Purpose: To validate the collapsed cone (CC) algorithm against Monte Carlo (MC) simulations for model-based dose calculations in high-dose-rate (HDR) liver brachytherapy.

Methods And Materials: Doses for liver brachytherapy treatment plans of 10 cases were retrospectively recalculated with a model-based approach using Monte Carlo n-Particle Code (MCNP) 6 (Dm,m-MC) and Oncentra Brachy ACE (Dm,m-ACE). Tissue segmentation consisted of assigning uniform compositions and mass densities to predefined Hounsfield Unit (HU) thresholds. Resulting doses were compared according to dose volume histogram parameters typical for clinical routine. These included the percentage liver volume receiving 5 Gy (V5Gy) or 10 Gy (V10Gy), the maximum dose to one cubic centimeter (D1cc) of organs at risk, the clinical target volume (CTV) fractions receiving 150% (V150), 100% (V100), 95% (V95) and 90% (V90) of the prescribed dose and the absolute doses to 95% (D95) and 90% (D90) of the CTV volumes.

Results: Doses from Oncentra Brachy ACE agreed well with MC simulations. Differences were seen far from the source, in low-density regions and bone structures. Median percentage deviations were 1.1% for the liver V5Gy and 0.4% for the liver V10Gy, with deviations of largest magnitude amounting to 2.2% and 1.0%, respectively. Organs at risk had median deviations ranging from 0.3% to 1.5% for D1cc, with outliers ranging up to 4.6%. CTV volume parameter deviations ranged between -1.5% and 0.5%, dose parameter deviations ranged mostly between -2% and 1%, with two outliers at -4.0% and -3.4% for a small CTV.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brachy.2021.03.018DOI Listing
May 2021

Comparison of liver exposure in CT-guided high-dose rate (HDR) interstitial brachytherapy versus SBRT in hepatocellular carcinoma.

Radiat Oncol 2021 May 6;16(1):86. Epub 2021 May 6.

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

Background: In unresectable hepatocellular carcinoma several local ablative treatments are available. Among others, radiation based treatments such as stereotactic body radiotherapy (SBRT) and high-dose rate interstitial brachytherapy (HDR BT) have shown good local control rates.

Methods: We conducted a dose comparison between actually performed HDR BT versus virtually planned SBRT to evaluate the respective clinically relevant radiation exposure to uninvolved liver tissue. Moreover, dose coverage and conformity indices were assessed.

Results: Overall, 46 treatment sessions (71 lesions, 38 patients) were evaluated. HDR BT was applied in a single fraction with a dose prescription of 1 × 15 Gy. D98 was 17.9 ± 1.3 Gy, D50 was 41.8 ± 8.1 Gy. The SBRT was planned with a prescribed dose of 3 × 12.5 Gy (65%-Isodose), D98 was 50.7 ± 3.1 Gy, D2 was 57.0 ± 2.3 Gy, and D50 was 55.2 ± 2.3 Gy. Regarding liver exposure Vliver10Gy was compared to Vliver15.9Gy, Vliver16.2Gy (EQD2 equivalent doses), and Vliver20Gy (clinically relevant dose), all results showed significant differences (p < .001). In a case by case analysis Vliver10Gy was smaller than Vliver20Gy in 38/46 cases (83%). Dmean of the liver was significantly smaller in BT compared to SBRT (p < .001). GTV volume was correlated to the liver exposure and showed an advantage of HDR BT over SBRT in comparison of clinically relevant doses, and for EQD2 equivalent doses. The advantage was more pronounced for greater liver lesions The Conformity Index (CI) was significantly better for BT, while Healthy Tissue Conformity Index (HTCI) and Conformation Number (CN) showed an advantage for SBRT (p < .001).

Conclusion: HDR BT can be advantageous in respect of sparing of normal liver tissue as compared to SBRT, while providing excellent target conformity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-021-01812-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103624PMC
May 2021

Feasibility and Early Clinical Experience of Online Adaptive MR-Guided Radiotherapy of Liver Tumors.

Cancers (Basel) 2021 Mar 26;13(7). Epub 2021 Mar 26.

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

Purpose: To assess the feasibility and early results of online adaptive MR-guided radiotherapy (oMRgRT) of liver tumors.

Methods: We retrospectively examined consecutive patients with primary or secondary liver lesions treated at our institution using a 0.35T hybrid MR-Linac (Viewray Inc., Mountain View, CA, USA). Online-adaptive treatment planning was used to account for interfractional anatomical changes, and real-time intrafractional motion management using online 2D cine MRI was performed using a respiratory gating approach. Treatment response and toxicity were assessed during follow-up.

Results: Eleven patients and a total of 15 lesions were evaluated. Histologies included cholangiocarcinomas and metastases of neuroendocrine tumors, colorectal carcinomas, sarcomas and a gastrointestinal stroma tumor. The median BED of the PTV prescription doses was 84.4 Gy (range 59.5-112.5 Gy) applied in 3-5 fractions and the mean GTV BED was in median 147.9 Gy (range 71.7-200.5 Gy). Online plan adaptation was performed in 98% of fractions. The median overall treatment duration was 53 min. The treatment was feasible and successfully completed in all patients. After a median follow-up of five months, no local failure occurred and no ≥ grade two toxicity was observed. OMRgRT resulted in better PTV coverage and fewer OAR constraint violations.

Conclusion: Early results of MR-linac based oMRgRT for the primary and secondary liver tumors are promising. The treatment was feasible in all cases and well tolerated with minimal toxicity. The technique should be compared to conventional SBRT in further studies to assess the advantages of the technique.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/cancers13071523DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037065PMC
March 2021

Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts.

Sci Rep 2021 03 19;11(1):6418. Epub 2021 Mar 19.

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

Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to automatically extract relevant features from the patient's image and perform a binary classification of the occurrence of a given clinical endpoint. In this work, a 2D-CNN and a 3D-CNN for the binary classification of distant metastasis (DM) occurrence in head and neck cancer patients were extended to perform time-to-event analysis. The newly built CNNs incorporate censoring information and output DM-free probability curves as a function of time for every patient. In total, 1037 patients were used to build and assess the performance of the time-to-event model. Training and validation was based on 294 patients also used in a previous benchmark classification study while for testing 743 patients from three independent cohorts were used. The best network could reproduce the good results from 3-fold cross validation [Harrell's concordance indices (HCIs) of 0.78, 0.74 and 0.80] in two out of three testing cohorts (HCIs of 0.88, 0.67 and 0.77). Additionally, the capability of the models for patient stratification into high and low-risk groups was investigated, the CNNs being able to significantly stratify all three testing cohorts. Results suggest that image-based deep learning models show good reliability for DM time-to-event analysis and could be used for treatment personalisation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-021-85671-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979766PMC
March 2021

Proof of concept image artifact reduction by energy-modulated proton computed tomography (EMpCT).

Phys Med 2021 Jan 20;81:237-244. Epub 2021 Jan 20.

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

Purpose: To reduce imaging artifacts and improve image quality of a specific proton computed tomography (pCT) prototype scanner by combining pCT data acquired at two different incident proton energies to avoid protons stopping in sub-optimal detector sections.

Methods: Image artifacts of a prototype pCT scanner are linked to protons stopping close to internal structures of the scanner's multi-stage energy detector. We aimed at avoiding such protons by acquiring pCT data at two different incident energies and combining the data in post-processing from which artifact-reduced images of the relative stopping power (RSP) were calculated. Energy-modulated pCT (EMpCT) images were assessed visually and quantitatively and compared to the original mono-energetic images in terms of RSP accuracy and noise. Data were acquired for a homogeneous water phantom.

Results: RSP images reconstructed from the mono-energetic datasets displayed local image artifacts which were ring-shaped due to the homogeneity of the phantom. The merged EMpCT dataset achieved a superior visual image quality with reduced artifacts and only minor remaining rings. The inter-quartile range (25/75) of RSP values was reduced from 0.7% with the current standard acquisition to 0.2% with EMpCT due to the reduction of ring artifacts. In this study, dose was doubled compared to a standard scan, but we discuss strategies to reduce excess dose.

Conclusions: EMpCT allows to effectively avoid regions of the energy detector that cause image artifacts. Thereby, image quality is improved.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ejmp.2020.12.012DOI Listing
January 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.zemedi.2020.09.004DOI Listing
November 2020

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

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

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry.

Phys Med Biol 2020 Sep 30. Epub 2020 Sep 30.

Department of Medical Physics, Ludwig-Maximilians-Universitat Munchen, Munchen, Bayern, GERMANY.

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples. Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1088/1361-6560/abbd14DOI Listing
September 2020

Radiotherapy in oncological emergencies: fast-track treatment planning.

Radiat Oncol 2020 Sep 10;15(1):215. Epub 2020 Sep 10.

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

Background And Purpose: To report on our clinical experience with a newly implemented workflow for radiotherapy (RT) emergency treatments, which allows for a fast treatment application outside the regular working-hours, and its clinical applicability.

Methods: Treatment planning of 18 emergency RT patients was carried out using diagnostic computed tomography (CT) without a dedicated RT simulation CT. The cone-beam CT (CBCT) deviations of the first RT treatment were analyzed regarding setup accuracy. Furthermore, feasibility of the "fast-track" workflow was evaluated with respect to dose deviations caused by different Hounsfield unit (HU) to relative electron density (rED) calibrations and RT treatment couch surface shapes via 3D gamma index analysis of exemplary treatment plans. The dosimetric uncertainty introduced by different CT calibrations was quantified.

Results: Mean patient setup vs. CBCT isocenter deviations were (0.49 ± 0.44) cm (x), (2.68 ± 1.63) cm (y) and (1.80 ± 1.06) cm (z) for lateral, longitudinal and vertical directions, respectively. Three out of four dose comparisons between the emergency RT plan calculated on the diagnostic CT and the same plan calculated on the treatment planning CT showed clinically acceptable gamma passing rates, when correcting for surface artifacts. The maximum difference of rED was 0.054, while most parts of the CT calibration curves coincided well.

Conclusion: In an emergency RT setting, the use of diagnostic CT data for treatment planning might be time-saving and was shown to be suitable for many cases, considering reproducibility of patient setup, accuracy of initial patient setup and accuracy of dose-calculation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-020-01657-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488151PMC
September 2020

The role of Monte Carlo simulation in understanding the performance of proton computed tomography.

Z Med Phys 2020 Aug 11. Epub 2020 Aug 11.

Department of Radiation Oncology, Department of Medical Physics, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium, (DKTK), Munich, Germany; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching b. München, Germany.

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.zemedi.2020.06.006DOI Listing
August 2020

Magnetic resonance-guided radiation therapy: the beginning of a new era.

Radiat Oncol 2020 07 8;15(1):163. Epub 2020 Jul 8.

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

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-020-01599-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346330PMC
July 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-020-01524-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201982PMC
May 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

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

Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy.

Phys Med Biol 2019 08 14;64(16):165002. Epub 2019 Aug 14.

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

Proton computed tomography (pCT) has been proposed as an alternative to x-ray computed tomography (CT) for acquiring relative to water stopping power (RSP) maps used for proton treatment planning dose calculations. In parallel, it has been shown that dual energy x-ray CT (DECT) improves RSP accuracy when compared to conventional single energy x-ray CT. This study aimed at directly comparing the RSP accuracy of both modalities using phantoms scanned at an advanced prototype pCT scanner and a state-of-the-art DECT scanner. Two phantoms containing 13 tissue-mimicking inserts of known RSP were scanned at the pCT phase II prototype and a latest generation dual-source DECT scanner (Siemens SOMATOM Definition FORCE). RSP accuracy was compared by mean absolute percent error (MAPE) over all inserts. A highly realistic Monte Carlo (MC) simulation was used to gain insight on pCT image artifacts which degraded MAPE. MAPE was 0.55% for pCT and 0.67% for DECT. The realistic MC simulation agreed well with pCT measurements ([Formula: see text]). Both simulation and experimental results showed ring artifacts in pCT images which degraded the MAPE compared to an ideal pCT simulation ([Formula: see text]). Using the realistic simulation, we could identify sources of artifacts, which are attributed to the interfaces in the five-stage plastic scintillator energy detector and calibration curve interpolation regions. Secondary artifacts stemming from the proton tracker geometry were also identified. The pCT prototype scanner outperformed a state-of-the-art DECT scanner in terms of RSP accuracy (MAPE) for plastic tissue mimicking inserts. Since artifacts tended to concentrate in the inserts, their mitigation may lead to further improvements in the reported pCT accuracy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1088/1361-6560/ab2b72DOI Listing
August 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.

View Article and Find Full Text PDF

Download full-text PDF

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

Erratum: "Current state and future applications of radiological image guidance for particle therapy" [Med. Phys. 45:11, e1086-e1095 (2018)].

Med Phys 2019 Feb 3;46(2):1088. Epub 2019 Jan 3.

Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/mp.13339DOI Listing
February 2019

Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual-layer computed tomography.

Med Phys 2019 Apr 19;46(4):1821-1828. Epub 2019 Feb 19.

Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint-Étienne, CNRS, Inserm, CREATIS, UMR 5220, U1206, F-69373, Lyon, France.

Purpose: The objective of this technical note was to investigate the accuracy of proton stopping power relative to water (RSP) estimation using a novel dual-layer, dual-energy computed tomography (DL-DECT) scanner for potential use in proton therapy planning. DL-DECT allows dual-energy reconstruction from scans acquired at a single x-ray tube voltage V by using two-layered detectors.

Methods: Sets of calibration and evaluation inserts were scanned at a DL-DECT scanner in a custom phantom with variable diameter D (0 to 150 mm) at V of 120 and 140 kV. Inserts were additionally scanned at a synchrotron computed tomography facility to obtain comparative linear attenuation coefficients for energies from 50 to 100 keV, and reference RSP was obtained using a carbon ion beam and variable water column. DL-DECT monoenergetic (mono-E) reconstructions were employed to obtain RSP by adapting the Yang-Saito-Landry (YSL) method. The method was compared to reference RSP via the root mean square error (RMSE) over insert mean values obtained from volumetric regions of interest. The accuracy of intermediate quantities such as the relative electron density (RED), effective atomic number (EAN), and the mono-E was additionally evaluated.

Results: The lung inserts showed higher errors for all quantities and we report RMSE excluding them. RMSE for μ from DL-DECT mono-E was below 1.9%. For the evaluation inserts at D = 150 mm and V = 140 kV, RED RMSE was 1.0%, while for EAN it was 2.9%. RSP RMSE was below 0.8% for all D and V, which did not strongly affect the results.

Conclusions: In this investigation of RSP accuracy from DL-DECT, we have shown that RMSE below 1% can be achieved. It was possible to adapt the YSL method for DL-DECT and intermediate quantities RED and EAN had comparable accuracy to previous publications.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/mp.13404DOI Listing
April 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1088/1361-6560/aaf496DOI Listing
January 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.zemedi.2018.10.005DOI Listing
August 2019
-->