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Purpose: External beam radiotherapy with protons and heavier ions enables a tighter conformation of the applied dose to arbitrarily shaped tumor volumes with respect to photons, but is more sensitive to uncertainties in the radiotherapeutic treatment chain. Consequently, an independent verification of the applied treatment is highly desirable. For this purpose, the irradiation-induced β(+)-emitter distribution within the patient is detected shortly after irradiation by a commercial full-ring positron emission tomography/x-ray computed tomography (PET/CT) scanner installed next to the treatment rooms at the Heidelberg Ion-Beam Therapy Center (HIT). A major challenge to this approach is posed by the small number of detected coincidences. This contribution aims at characterizing the performance of the used PET/CT device and identifying the best-performing reconstruction algorithm under the particular statistical conditions of PET-based treatment monitoring. Moreover, this study addresses the impact of radiation background from the intrinsically radioactive lutetium-oxyorthosilicate (LSO)-based detectors at low counts., Methods: The authors have acquired 30 subsequent PET scans of a cylindrical phantom emulating a patientlike activity pattern and spanning the entire patient counting regime in terms of true coincidences and random fractions (RFs). Accuracy and precision of activity quantification, image noise, and geometrical fidelity of the scanner have been investigated for various reconstruction algorithms and settings in order to identify a practical, well-suited reconstruction scheme for PET-based treatment verification. Truncated listmode data have been utilized for separating the effects of small true count numbers and high RFs on the reconstructed images. A corresponding simulation study enabled extending the results to an even wider range of counting statistics and to additionally investigate the impact of scatter coincidences. Eventually, the recommended reconstruction scheme has been applied to exemplary postirradiation patient data-sets., Results: Among the investigated reconstruction options, the overall best results in terms of image noise, activity quantification, and accurate geometrical recovery were achieved using the ordered subset expectation maximization reconstruction algorithm with time-of-flight (TOF) and point-spread function (PSF) information. For this algorithm, reasonably accurate (better than 5%) and precise (uncertainty of the mean activity below 10%) imaging can be provided down to 80,000 true coincidences at 96% RF. Image noise and geometrical fidelity are generally improved for fewer iterations. The main limitation for PET-based treatment monitoring has been identified in the small number of true coincidences, rather than the high intrinsic random background. Application of the optimized reconstruction scheme to patient data-sets results in a 25% - 50% reduced image noise at a comparable activity quantification accuracy and an improved geometrical performance with respect to the formerly used reconstruction scheme at HIT, adopted from nuclear medicine applications., Conclusions: Under the poor statistical conditions in PET-based treatment monitoring, improved results can be achieved by considering PSF and TOF information during image reconstruction and by applying less iterations than in conventional nuclear medicine imaging. Geometrical fidelity and image noise are mainly limited by the low number of true coincidences, not the high LSO-related random background. The retrieved results might also impact other emerging PET applications at low counting statistics.

Background: Stereotactic body radiation therapy (SBRT) of central lung tumors with photon or proton therapy has a risk of increased toxicity. Treatment planning studies comparing accumulated doses for state‐of‐the‐art treatment techniques, such as MR‐guided radiotherapy (MRgRT) and intensity modulated proton therapy (IMPT), are currently lacking. Purpose: We conducted a comparison of accumulated doses for MRgRT, robustly optimized non‐adaptive IMPT, and online adaptive IMPT for central lung tumors. A special focus was set on analyzing the accumulated doses to the bronchial tree, a parameter linked to high‐grade toxicities. Methods: Data of 18 early‐stage central lung tumor patients, treated at a 0.35 T MR‐linac in eight or five fractions, were analyzed. Three gated treatment scenarios were compared: (S1) online adaptive MRgRT, (S2) non‐adaptive IMPT, and (S3) online adaptive IMPT. The treatment plans were recalculated or reoptimized on the daily imaging data acquired during MRgRT, and accumulated over all treatment fractions. Accumulated dose‐volume histogram (DVH) parameters of the gross tumor volume (GTV), lung, heart, and organs‐at‐risk (OARs) within 2 cm of the planning target volume (PTV) were extracted for each scenario and compared in Wilcoxon signed‐rank tests between S1 & S2, and S1 & S3. Results: The accumulated GTV D98% was above the prescribed dose for all patients and scenarios. Significant reductions (p < 0.05) of the mean ipsilateral lung dose (S2: –8%; S3: –23%) and mean heart dose (S2: –79%; S3: –83%) were observed for both proton scenarios compared to S1. The bronchial tree D0.1cc was significantly lower for S3 (S1: 48.1 Gy; S3: 39.2 Gy; p = 0.005), but not significantly different for S2 (S2: 45.0 Gy; p = 0.094), compared to S1. The D0.1cc for S2 and S3 compared to S1 was significantly (p < 0.05) smaller for OARs within 1–2 cm of the PTV (S1: 30.2 Gy; S2: 24.6 Gy; S3: 23.1 Gy), but not significantly different for OARs within 1 cm of the PTV. Conclusions: A significant dose sparing potential of non‐adaptive and online adaptive proton therapy compared to MRgRT for OARs in close, but not direct proximity of central lung tumors was identified. The near‐maximum dose to the bronchial tree was not significantly different for MRgRT and non‐adaptive IMPT. Online adaptive IMPT achieved significantly lower doses to the bronchial tree compared to MRgRT. [ABSTRACT FROM AUTHOR]

Background: Hybrid devices that combine radiation therapy and MR-imaging have been introduced in the clinical routine for the treatment of lung cancer. This opened up not only possibilities in terms of accurate tumor tracking, dose delivery and adapted treatment planning, but also functional lung imaging. The aim of this study was to show the feasibility of Non-uniform Fourier Decomposition (NuFD) MRI at a 0.35 T MR-Linac as a potential treatment response assessment tool, and propose two signal normalization strategies for enhancing the reproducibility of the results. Methods: Ten healthy volunteers (median age 28 ± 8 years, five female, five male) were repeatedly scanned at a 0.35 T MR-Linac using an optimized 2D+t balanced steady-state free precession (bSSFP) sequence for two coronal slice positions. Image series were acquired in normal free breathing with breaks inside and outside the scanner as well as deep and shallow breathing. Ventilation- and perfusion-weighted maps were generated for each image series using NuFD. For intra-volunteer ventilation map reproducibility, a normalization factor was defined based on the linear correlation of the ventilation signal and diaphragm position of each scan as well as the diaphragm motion amplitude of a reference scan. This allowed for the correction of signal dependency on the diaphragm motion amplitude, which varies with breathing patterns. The second strategy, which can be used for ventilation and perfusion, eliminates the dependency on the signal amplitude by normalizing the ventilation/perfusion maps with the average ventilation/perfusion signal within a selected region-of-interest (ROI). The position and size dependency of this ROI was analyzed. To evaluate the performance of both approaches, the normalized ventilation/perfusion-weighted maps were compared and the deviation of the mean ventilation/perfusion signal from the reference was calculated for each scan. Wilcoxon signed-rank tests were performed to test whether the normalization methods can significantly improve the reproducibility of the ventilation/perfusion maps. Results: The ventilation- and perfusion-weighted maps generated with the NuFD algorithm demonstrated a mostly homogenous distribution of signal intensity as expected for healthy volunteers regardless of the breathing maneuver and slice position. Evaluation of the ROI's size and position dependency showed small differences in the performance. Applying both normalization strategies improved the reproducibility of the ventilation by reducing the median deviation of all scans to 9.1%, 5.7% and 8.6% for the diaphragm-based, the best and worst performing ROI-based normalization, respectively, compared to 29.5% for the non-normalized scans. The significance of this improvement was confirmed by the Wilcoxon signed rank test with p < 0.01 at α = 0.05 . A comparison of the techniques against each other revealed a significant difference in the performance between best ROI-based normalization and worst ROI ( p = 0.01 ) and between best ROI-based normalization and scaling factor ( p = 0.02 ), but not between scaling factor and worst ROI ( p = 0.71 ). Using the ROI-based approach for the perfusion-maps, the uncorrected deviation of 10.2% was reduced to 5.3%, which was shown to be significant ( p < 0.01 ). Conclusions: Using NuFD for non-contrast enhanced functional lung MRI at a 0.35 T MR-Linac is feasible and produces plausible ventilation- and perfusion-weighted maps for volunteers without history of chronic pulmonary diseases utilizing different breathing patterns. The reproducibility of the results in repeated scans significantly benefits from the introduction of the two normalization strategies, making NuFD a potential candidate for fast and robust early treatment response assessment of lung cancer patients during MR-guided radiotherapy. [ABSTRACT FROM AUTHOR]

As one of the latest developments in X-ray computed tomography (CT), photon-counting technology allows spectral detection, demonstrating considerable advantages as compared to conventional CT. In this study, we investigated the use of a first-generation clinical photon-counting computed tomography (PCCT) scanner and estimated proton relative (to water) stopping power (RSP) of tissue-equivalent materials from virtual monoenergetic reconstructions provided by the scanner. A set of calibration and evaluation tissue-equivalent inserts were scanned at 120 kVp. Maps of relative electron density (RED) and effective atomic number (EAN) were estimated from the reconstructed virtual monoenergetic images (VMI) using an approach previously applied to a spectral CT scanner with dual-layer detector technology, which allows direct calculation of RSP using the Bethe-Bloch formula. The accuracy of RED, EAN, and RSP was evaluated by root-meansquare errors (RMSE) averaged over the phantom inserts. The reference RSP values were obtained experimentally using a water column in an ion beam. For RED and EAN, the reference values were calculated based on the mass density and the chemical composition of the inserts. Different combinations of lowand high-energy VMIs were investigated in this study, ranging from 40 to 190 keV. The overall lowest error was achieved using VMIs at 60 and 180 keV, with an RSP accuracy of 1.27% and 0.71% for the calibration and the evaluation phantom, respectively. [ABSTRACT FROM AUTHOR]

Background: The targeting accuracy of proton therapy (PT) for moving soft-tissue tumours is expected to greatly improve by real-time magnetic resonance imaging (MRI) guidance. The integration of MRI and PT at the treatment isocenter would offer the opportunity of combining the unparalleled soft-tissue contrast and real-time imaging capabilities of MRI with the most conformal dose distribution and best dose steering capability provided by modern PT. However, hybrid systems for MR-integrated PT (MRiPT) have not been realized so far due to a number of hitherto open technological challenges. In recent years, various research groups have started addressing these challenges and exploring the technical feasibility and clinical potential of MRiPT. The aim of this contribution is to review the different aspects of MRiPT, to report on the status quo and to identify important future research topics.Methods: Four aspects currently under study and their future directions are discussed: modelling and experimental investigations of electromagnetic interactions between the MRI and PT systems, integration of MRiPT workflows in clinical facilities, proton dose calculation algorithms in magnetic fields, and MRI-only based proton treatment planning approaches.Conclusions: Although MRiPT is still in its infancy, significant progress on all four aspects has been made, showing promising results that justify further efforts for research and development to be undertaken. First non-clinical research solutions have recently been realized and are being thoroughly characterized. The prospect that first prototype MRiPT systems for clinical use will likely exist within the next 5 to 10 years seems realistic, but requires significant work to be performed by collaborative efforts of research groups and industrial partners. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: 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. Material and methods: 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. Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]

Background: Intensity modulated proton therapy (IMPT) of head and neck (H&N) tumors may benefit from plan adaptation to correct for the dose perturbations caused by weight loss and tumor volume changes observed in these patients. As cone beam CT (CBCT) is increasingly considered in proton therapy, it may be possible to use available CBCT images following intensity correction for plan adaptation. This is the first study exploring IMPT plan adaptation on CBCT images corrected and delineated by deformable image registration of the planning CT (pCT) to the CBCT, yielding a virtual CT (vCT).Methods: A Morphons algorithm was used to deform the pCTs and corresponding delineations of 9 H&N cancer patients to a weekly CBCT acquired within ±3 days of a control replanning CT scan (rpCT). The IMPT treatment plans were adapted using the vCT and the adapted and original plans were recalculated on the rpCT for dose/volume parameter evaluation of the impact of adaptation.Results: On the rpCT, the adapted plans were equivalent to the original plans in terms of target volumes D 95 and V 95, but showed a significant reduction of D 2 in these volumes. OAR doses were mostly equivalent or reduced. In particular, the adapted plans did not reduce parotid gland D mean, but the dose to the optical system. For three patients the spinal cord or brain stem received higher, though well below tolerance, maximum dose. Subsequent tightening of the treatment planning constraints for these OARs on new vCT-adapted plans did not degrade target coverage and yielded pCT equivalent plans on the vCT.Conclusions: An offline automated procedure to generate an adapted IMPT plan on CBCT images was developed and investigated. When evaluating the adapted plan on a control rpCT we observed reduced D 2 in target volumes as major improvement. OAR sparing was only partially improved by the procedure. Despite potential limitations in the accuracy of the vCT approach, an improved quality of the adapted plans could be achieved. [ABSTRACT FROM AUTHOR]

Simple Summary: Stereotactic body radiotherapy is used in the treatment of liver tumors. However, adjacent organs at risk (OAR) frequently limit the applicable dose to the target volume. The introduction of hybrid magnetic resonance imaging (MRI)-guided radiotherapy systems may allow dose escalation strategies with better OAR sparing due to improved soft tissue visualization, adaptive treatment planning and real-time motion management. Here we report the feasibility and early results of online adaptive MR-guided radiotherapy of primary and secondary liver tumors in eleven patients. 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 2 toxicity was observed. The technique should be compared to conventional SBRT in further studies to assess the advantages of the technique. 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 BED10 of the PTV prescription doses was 84.4 Gy (range 59.5–112.5 Gy) applied in 3–5 fractions and the mean GTV BED10 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. [ABSTRACT FROM AUTHOR]

• Description of intra-fractional motion management workflow in MRI-guided radiotherapy. • Envisioned workflow with both highest dosimetric accuracy and duty cycle efficiency. • Focus on real-time implementation based on artificial intelligence. MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms. [ABSTRACT FROM AUTHOR]