LETTER • OPEN ACCESSFirst patients treated with a 1.5 T MRI-Linac: clinical proof of concept of a high-precision, highfield MRI guided radiotherapy treatment AbstractThe integration of 1.5 T MRI functionality with a radiotherapy linear accelerator (linac) has been pursued since 1999 by the UMC Utrecht in close collaboration with Elekta and Philips. The idea behind this integrated device is to offer unrivalled, online and real-time, soft-tissue visualization of the tumour and the surroundings for more precise radiation delivery. The proof of concept of this device was given in 2009 by demonstrating simultaneous irradiation and MR imaging on phantoms, since then the device has been further developed and commercialized by Elekta. The aim of this work is to demonstrate the clinical feasibility of online, high-precision, high-field MRI guidance of radiotherapy using the first clinical prototype MRI-Linac.Four patients with lumbar spine bone metastases were treated with a 3 or 5 beam step-and-shoot IMRT plan. The IMRT plan was created while Letter Institute of Physics and Engineering in MedicineOriginal content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 3 Author to whom any correspondence should be addressed. the patient was on the treatment table and based on the online 1.5 T MR images; pre-treatment CT was deformably registered to the online MRI to obtain Hounsfield values. Bone metastases were chosen as the first site as these tumors can be clearly visualized on MRI and the surrounding spine bone can be detected on the integrated portal imager. This way the portal images served as an independent verification of the MRI based guidance to quantify the geometric precision of radiation delivery. Dosimetric accuracy was assessed post-treatment from phantom measurements with an ionization chamber and film. Absolute doses were found to be highly accurate, with deviations ranging from 0.0% to 1.7% in the isocenter. The geometrical, MRI based targeting as confirmed using portal images was better than 0.5 mm, ranging from 0.2 mm to 0.4 mm.In conclusion, high precision, high-field, 1.5 T MRI guided radiotherapy is clinically feasible.

An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of [Formula: see text] mm and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.

a b s t r a c tBackground and purpose: Patients were treated at our institute for single and multiple lymph node oligometastases on the 1.5T MR-linac since August 2018. The superior soft-tissue contrast and additional software features of the MR-linac compared to CBCT-linacs allow for online adaptive treatment planning. The purpose of this study was to perform a target coverage and dose criteria based evaluation of the clinically delivered online adaptive radiotherapy treatment compared with conventional CBCT-linac treatment. Materials and methods: Patient data was used from 14 patients with single lymph node oligometastases and 6 patients with multiple (2-3) metastases. All patients were treated on the 1.5T MR-linac with a prescribed dose of 5 Â 7 Gy to 95% of the PTV and a CBCT-linac plan was created for each patient. The difference in target coverage between these plans was compared and plans were evaluated based on dose criteria for each fraction after calculating the CBCT-plan on the daily anatomy. The GTV coverage was evaluated based on the online planning and the post-delivery MRI. Results: For both single and multiple lymph node oligometastases the GTV V 35Gy had a median value of 100% for both the MR-linac plans and CBCT-plans pre-and post-delivery and did not significantly differ. The percentage of plans that met all dose constraints was improved from 19% to 84% and 20% to 67% for single and multiple lymph node cases, respectively. Conclusion: Target coverage and dose criteria based evaluation of the first clinical 1.5T MR-linac SBRT treatments of lymph node oligometastases compared with conventional CBCT-linac treatment shows a smaller amount of unplanned violations of high dose criteria. The GTV coverage was comparable. Benefit is primarily gained in patients treated for multiple lymph node oligometastases: geometrical deformations are accounted for, dose can be delivered in one plan and margins can be reduced.

Background and purpose: Daily online adaptation of the clinical target volume (CTV) using MR-guided radiotherapy enables margin reduction of the planning target volume (PTV). This study describes the implementation and initial experience of MR-guided radiotherapy on the 1.5T MR-linac and evaluates treatment time, patient compliance, and target coverage, including an initial assessment of margin reduction. Materials and methods: Patients were treated on a 1.5T MR-linac (7MV, FFF). At each fraction a 3D T2 weighted (T2w) MR-sequence was acquired on which the CTV was adapted after a deformable registration of the contours from the pre-planning CT scan. Based on the new contours a full online replanning was done after which a new 3D T2w MR-sequence was acquired for position verification. A 5 field Intensity Modulated Radiotherapy (IMRT) plan was delivered. Results: Forty-three patients with rectal cancer were treated with 25 Gy in 5 fractions of which 18 with reduced margins. In total, 204 of 215 fractions were delivered on the MR-linac all of which obtained a clinically acceptable treatment plan. Median in-room time per fraction was 48 min (interquartile range 8). No fractions were canceled or interrupted because of patient intolerance. CTV coverage after margin reduction was good on all post-treatment scans but one due to passing gas. Conclusion: MR-guided radiotherapy using daily full online recontouring and replanning on a 1.5T MRlinac for rectal cancer is feasible and currently takes about 48 min per fraction.

Background: Structure delineation is a necessary, yet time-consuming manual procedure in radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and automatise this procedure, obtaining promising results. With the advent of magnetic resonance imaging (MRI)-guided radiotherapy, MR-based segmentation is becoming increasingly relevant. However, the majority of the studies investigated automatic contouring based on computed tomography (CT). Purpose: In this study, we investigate the feasibility of clinical use of deep learning-based automatic OARs delineation on MRI. Materials and methods: We included 150 patients diagnosed with prostate cancer who underwent MR-only radiotherapy. A three-dimensional (3D) T1-weighted dual spoiled gradient-recalled echo sequence was acquired with 3T MRI for the generation of the synthetic-CT. The first 48 patients were included in a feasibility study training two 3D convolutional networks called DeepMedic and dense V-net (dV-net) to segment bladder, rectum and femurs. A research version of an atlas-based software was considered for comparison. Dice similarity coefficient, 95% Hausdorff distances (HD 95), and mean distances were calculated against clinical delineations. For eight patients, an expert RTT scored the quality of the contouring for all the three methods. A choice among the three approaches was made, and the chosen approach was retrained on 97 patients and implemented for automatic use in the clinical workflow. For the successive 53 patients, Dice, HD 95 and mean distances were calculated against the clinically used delineations.