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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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Purpose: MRI is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearities (GNLs) limit anatomical accuracy, potentially compromising the quality of tumor treatments. In addition, slow MR acquisition and reconstruction limit the potential for effective image guidance. Here, we demonstrate a deep learning-based method that rapidly reconstructs distortion-corrected images from raw k-space data for MR-guided radiotherapy applications., Methods: We leverage recent advances in interpretable unrolling networks to develop a Distortion-Corrected Reconstruction Network (DCReconNet) that applies convolutional neural networks (CNNs) to learn effective regularizations and nonuniform fast Fourier transforms for GNL-encoding. DCReconNet was trained on a public MR brain dataset from 11 healthy volunteers for fully sampled and accelerated techniques, including parallel imaging (PI) and compressed sensing (CS). The performance of DCReconNet was tested on phantom, brain, pelvis, and lung images acquired on a 1.0T MRI-Linac. The DCReconNet, CS-, PI-and UNet-based reconstructed image quality was measured by structural similarity (SSIM) and RMS error (RMSE) for numerical comparisons. The computation time and residual distortion for each method were also reported., Results: Imaging results demonstrated that DCReconNet better preserves image structures compared to CS- and PI-based reconstruction methods. DCReconNet resulted in the highest SSIM (0.95 median value) and lowest RMSE (<0.04) on simulated brain images with four times acceleration. DCReconNet is over 10-times faster than iterative, regularized reconstruction methods., Conclusions: DCReconNet provides fast and geometrically accurate image reconstruction and has the potential for MRI-guided radiotherapy applications., (© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach., (© 2022. Springer Nature Limited.)

Purpose: A radiotherapy system with a fixed treatment beam and a rotating patient positioning system could be smaller, more robust and more cost effective compared to conventional rotating gantry systems. However, patient rotation could cause anatomical deformation and compromise treatment delivery. In this work, we demonstrate an image-guided treatment workflow with a fixed beam prototype system that accounts for deformation during rotation to maintain dosimetric accuracy., Methods: The prototype system consists of an Elekta Synergy linac with the therapy beam orientated downward and a custom-built patient rotation system (PRS). A phantom that deforms with rotation was constructed and rotated within the PRS to quantify the performance of two image guidance techniques: motion compensated cone-beam CT (CBCT) for pre-treatment volumetric imaging and kilovoltage infraction monitoring (KIM) for real-time image guidance. The phantom was irradiated with a 3D conformal beam to evaluate the dosimetric accuracy of the workflow., Results: The motion compensated CBCT was used to verify pre-treatment position and the average calculated position was within -0.3 ± 1.1 mm of the phantom's ground truth position at 0°. KIM tracked the position of the target in real-time as the phantom was rotated and the average calculated position was within -0.2 ± 0.8 mm of the phantom's ground truth position. A 3D conformal treatment delivered on the prototype system with image guidance had a 3%/2 mm gamma pass rate of 96.3% compared to 98.6% delivered using a conventional rotating gantry linac., Conclusions: In this work, we have shown that image guidance can be used with fixed-beam treatment systems to measure and account for changes in target position in order to maintain dosimetric coverage during horizontal rotation. This treatment modality could provide a viable treatment option when there insufficient space for a conventional linear accelerator or where the cost is prohibitive.