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The special issue of JCM on "Advances of MRI in Radiation Oncology" provides a unique forum for scientific literature related to MR imaging in radiation oncology. This issue covered many aspects, such as MR technology, motion management, economics, soft-tissue–air interface issues, and disease sites such as the pancreas, spine, sarcoma, prostate, head and neck, and rectum from both camps—the Unity and MRIdian systems. This paper provides additional information on the success and challenges of the two systems. A challenging aspect of this technology is low throughput and the monumental task of education and training that hinders its use for the majority of therapy centers. Additionally, the cost of this technology is too high for most institutions, and hence widespread use is still limited. This article highlights some of the difficulties and how to resolve them. [ABSTRACT FROM AUTHOR]

• Technological innovation in Radiotherapy led to Magnetic Resonance guided RT systems. • Artificial Intelligence can play a significant role in MR guided RT. • Many manual procedures can be automatized and standardized thanks to AI. • Medical Physicists are expected to be major actors in AI clinical implementation. • The current status of AI integration in MRgRT will be presented and discussed. 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. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this work was to develop and benchmark a magnetic resonance (MR)‐guided linear accelerator head model using the GEANT4 Monte Carlo (MC) code. The validated model was compared to the treatment planning system (TPS) and was also used to quantify the electron return effect (ERE) at a lung–water interface. Methods: The average energy, including the spread in the energy distribution, and the radial intensity distribution of the incident electron beam were iteratively optimized in order to match the simulated beam profiles and percent depth dose (PDD) data to measured data. The GEANT4 MC model was then compared to the TPS model using several photon beam tests including oblique beams, an off‐axis aperture, and heterogeneous phantoms. The benchmarked MC model was utilized to compute output factors (OFs) with the 0.35 T magnetic field turned on and off. The ERE was quantified at a lung–water interface by simulating PDD curves with and without the magnetic field for 6.6 × 6.6 cm2 and 2.5 × 2.5 cm2 field sizes. A 2%/2 mm gamma criterion was used to compare the MC model with the TPS data throughout this study. Results: The final incident electron beam parameters were 6.0 MeV average energy with a 1.5 MeV full width at half maximum (FWHM) Gaussian energy spread and a 1.0 mm FWHM Gaussian radial intensity distribution. The MC‐simulated OFs were found to be in agreement with the TPS‐calculated and measured OFs, and no statistical difference was observed between the 0.35 T and 0.0 T OFs. Good agreement was observed between the TPS‐calculated and MC‐simulated data for the photon beam tests with gamma pass rates ranging from 96% to 100%. An increase of 4.3% in the ERE was observed for the 6.6 × 6.6 cm2 field size relative to the 2.5 × 2.5 cm2 field size. The ratio of the 0.35 T PDD to the 0.0 T PDD was found to be up to 1.098 near lung–water interfaces for the 6.6 × 6.6 cm2 field size using the MC model. Conclusions: A vendor‐independent Monte Carlo model has been developed and benchmarked for a 0.35 T/6 MV MR‐linac. Good agreement was obtained between the GEANT4 and TPS models except near heterogeneity interfaces. [ABSTRACT FROM AUTHOR]

Purpose: With advance magnetic resonance (MR)‐guided online adaptive radiotherapy (MRgoART) relying on calculation‐based intensity‐modulated radiation therapy (IMRT) quality assurance (QA), accurate and sensitive QA of the multileaf collimator (MLC) becomes an increasingly essential component for routine machine QA. As such, it is important to assure compliance with the AAPM TG142 guidelines to supplement calculation‐based QA methods for an online adaptive radiotherapy program. We have developed and implemented an efficient and highly sensitive QA procedure using an ionization chamber profiler (ICP) array to enable real‐time characterization of the positional accuracy of a double‐focused and double‐stacked MLC on a clinical MR‐guided radiotherapy (MRgRT) system and to supplement calculation‐based QA for an MRgoART program. Methods: An in‐house MR‐compatible jig was used to position the ICP (detector resolution 5 mm on X/Y axis) at an extended SDD of 108.4 cm to enable each MLC leaf (8.3 mm leaf width at isocenter) to be uniquely determined by two neighboring ion chambers. The MRgRT linac system utilizes a novel jawless, double‐focused, and double‐stacked MLC design such that the upper bank (MLC1) and lower bank (MLC2) are offset by half a leaf width. Positional accuracy was characterized by three methods: single bank half‐beam block (HBB) at central axis, forward slash diagonal (FSD), and backslash diagonal (BSD) at off‐axis. Measurements were performed for each bank in which each leaf occludes half of a detector. A corresponding reference field with the MLC retracted from occlusion was measured. The sensitivities of HBB, FSD, and BSD were evaluated by introducing 0.5–2.5 mm of known errors in 0.5 mm increments, in both positive and negative directions. The relationship between detector response and MLC error was established. Over a 6‐month longitudinal assessment, we have evaluated MLC performance with weekly QA of HBB among cardinal angles, and monthly QA of FSD and BSD. Results: A strong correlation was found between detector response of percentage dose difference and MLC positional error introduced (N = 350 introduced errors) for both HBB and FSD/BSD with coefficient of determination of 0.999 and 0.977, respectively. The relationship between detector response to MLC positional change was found to be 20.65%/mm for HBB and 11.14%/mm for FSD and BSD. At baseline, the mean MLC positional accuracy averaged across all leaves was 0.06 ± 0.27 mm (HBB), 0.04 ± 0.52 mm (FSD), −0.06 ± 0.51 mm (BSD). The mean MLC positional accuracy relative to baseline over the 6‐month assessment was found to be highly reproducible at 0.00 ± 0.12 mm (HBB; N = 28 weeks), −0.02 ± 0.19 mm (FSD; N = 6 months), −0.03 ± 0.19 mm (BSD; N = 6 months). Conclusions: Positional accuracy of a novel jawless, double‐focused, double‐stacked MLC has been characterized and monitored over 6 months with an efficient, highly sensitive, and robust method using an ICP array. This routine QA method supplements calculation‐based IMRT QA for an online adaptive radiotherapy program. Longitudinal assessment demonstrated no‐drift in the MLC calibration. A highly reproducible jig setup allowed the validation of MLC positional accuracy to be within TG142 criteria of ±1 mm for 99% of measurements (i.e., 100% HBB, 95% BSD, 95% FSD) over the 6‐month assessment. [ABSTRACT FROM AUTHOR]

Radiotherapy is an integral component of head/neck squamous cell carcinomas (HNSCCs) treatment, and technological developments including advances in image-guided radiotherapy over the past decades have offered improvements in the technical treatment of these cancers. Integration of magnetic resonance imaging (MRI) into image guidance through the development of MR-guided radiotherapy (MRgRT) offers further potential for refinement of the techniques by which HNSCCs are treated. This article provides an overview of the literature supporting the current use of MRgRT for HNSCC, challenges with its use, and developing research areas. [ABSTRACT FROM AUTHOR]

Treatment of locally advanced adenocarcinoma of the gastroesophageal junction (GEJ) with chemoradiation may be associated with high rates of symptomatic cardiac toxicity. Large margins are typically required to ensure coverage of GEJ tumors with free-breathing volumetric modulated arc therapy (VMAT) radiotherapy. The purpose of this study is to determine whether treatment with tighter margins enabled by maximum-inhalation breath hold (MIBH)-gated intensity modulated radiation therapy (IMRT) on an integrated MRI-linear accelerator system (MR-linac) can decrease radiation doses to the heart and cardiac substructures. Ten patients with locally advanced GEJ adenocarcinoma underwent both free breathing 4-dimensional computed tomography (4DCT) and MIBH MRI simulation scans. MR-linac IMRT plans were created with a 3 mm clinical target volume (CTV) to planning target volume (PTV) isotropic margin and 4DCT VMAT plans were created with a 11, 13, and 9 mm CTV to PTV anisotropic margins in the left-right, cranial-caudal, and anterior-posterior directions according to GEJ-specific PTV expansion recommendations by Voncken et al. Prescription dose to PTV was 50.4 Gy in 28 fractions. Dosimetry to the heart and cardiac substructures was compared with paired t test; p < 0.05 was considered significant. Mean PTV on the MR-linac IMRT plans was significantly smaller compared to the 4DCT VMAT plans (689 cm3 vs 1275 cm3, p < 0.01). Mean dose to the heart and all cardiac substructures was significantly lower in the MR-linac IMRT plans compared to the 4DCT VMAT plans: heart 20.9 Gy vs 27.8 Gy, left atrium 29.6 Gy vs 39.4 Gy, right atrium 20.5 Gy vs 25.6 Gy, left ventricle 21.6 Gy vs 29.6 Gy, and right ventricle 18.7 Gy vs 25.2 Gy (all p values <0.05). MIBH-gated MR-linac IMRT treatment of locally advanced GEJ adenocarcinoma can significantly decrease doses to the heart and cardiac substructures and this may translate to reduced rates of cardiac toxicity. [ABSTRACT FROM AUTHOR]