MR-guided Radiotherapy Systems Research Articles

Experimental determination of magnetic field quality conversion factors for eleven ionization chambers in 1.5 T and 0.35 T MR-linac systems.

The static magnetic field present in magnetic resonance (MR)-guided radiotherapy systems can influence dose deposition and charged particle collection in air-filled ionization chambers. Thus, accurately quantifying the effect of the magnetic field on ionization chamber response is critical for output calibration. Formalisms for reference dosimetry in a magnetic field have been proposed, whereby a magnetic field quality conversion factor kB,Q is defined to account for the combined effects of the magnetic field on the radiation detector. Determination of kB,Q in the literature has focused on Monte Carlo simulation studies, with experimental validation limited to only a few ionization chamber models. The purpose of this study is to experimentally measure kB,Q for 11 ionization chamber models in two commercially available MR-guided radiotherapy systems: Elekta Unity and ViewRay MRIdian. Eleven ionization chamber models were characterized in this study: Exradin A12, A12S, A28, and A26, PTW T31010, T31021, and T31022, and IBA FC23-C, CC25, CC13, and CC08. The experimental method to measure kB,Q utilized cross-calibration against a reference Exradin A1SL chamber. Absorbed dose to water was measured for the reference A1SL chamber positioned parallel to the magnetic field with its centroid placed at the machine isocenter at a depth of 10cm in water for a 10 × 10cm2 field size at that depth. Output was subsequently measured with the test chamber at the same point of measurement. kB,Q for the test chamber was computed as the ratio of reference dose to test chamber output, with this procedure repeated for each chamber in each MR-guided radiotherapy system. For the high-field 1.5 T Elekta Unity system, the dependence of kB,Q on the chamber orientation relative to the magnetic field was quantified by rotating the chamber about the machine isocenter. Measured kB,Q values for our test dataset of ionization chamber models ranged from 0.991 to 1.002, and 0.995 to 1.004 for the Elekta Unity and ViewRay MRIdian, respectively, with kB,Q tending to increase as the chamber sensitive volume increased. Measured kB,Q values largely agreed within uncertainty to published Monte Carlo simulation data and available experimental data. kB,Q deviation from unity was minimized for ionization chamber orientation parallel or antiparallel to the magnetic field, with increased deviations observed at perpendicular orientations. Overall (k=1) uncertainty in the experimental determination of the magnetic field quality conversion factor, kB,Q was 0.71% and 0.72% for the Elekta Unity and ViewRay MRIdian systems, respectively. For a high-field MR-linac, the characterization of ionization chamber performance as angular orientation varied relative to the magnetic field confirmed that the ideal orientation for output calibration is parallel. For most of these chamber models, this study represents the first experimental characterization of chamber performance in clinical MR-linac beams. This is a critical step toward accurate output calibration for MR-guided radiotherapy systems and the measured kB,Q values will be an important reference data source for forthcoming MR-linac reference dosimetry protocols.

Assessment of intrafractional motion of the cervix-uterus by MR-guided radiotherapy system†.

The uterus is known as one of the moving organs. We evaluated the movement of the uterus during irradiation and the effects of changes in the surrounding organs using a magnetic resonance (MR)-guided radiotherapy system. Seven patients with cervical cancer underwent pre- and posttreatment MR imaging to assess changes in the positioning of the uterus and cervix as well as the alterations in bladder and rectal volume. The study revealed that the movements of the uterus were greater than that of the cervix and showed a tendency to correlate with the bladder rather than the rectum. We also examined whether intrafractional motion could lead to insufficient dose coverage of the clinical target volume (CTV), specifically focusing on the D98% of the CTV in the uterine body and cervix. The impact of intrafractional motion on the D98% varied among patients, with one out of the seven patients experiencing an average dosimetric change of -2.6Gy in the uterus, although larger planning target volume margins of 1.5cm were applied, therefore, indicating the need for individualized optimal margins in each case. Online adaptive radiotherapy offers the advantage of modifying the treatment plan when irradiating moving organs, such as the uterus. However, it should be noted that this approach may result in longer overall treatment times compared with the traditional methods. Therefore, we must carefully consider the influence of intrafractional organ motions when opting for such a treatment.

Urethral Interfractional Geometric and Dosimetric Variations of Prostate Cancer Patients: A Study Using an Onboard MRI.

PurposeFor a cohort of prostate cancer patients treated on an MR-guided radiotherapy (MRgRT) system, we retrospectively analyzed urethral interfractional geometric and dosimetric variations based on onboard MRIs acquired at different timepoints and evaluated onboard prostatic urethra visualization for urethra-focused online adaptive RT.MethodsTwenty-six prostate cancer patients were prospectively scanned on a 0.35-T MRgRT system using an optimized T2-weighted HASTE sequence at simulation and final fraction. Two radiation oncologists (RO1 and RO2) contoured the urethras on all HASTE images. The simulation and final fraction HASTE images were rigidly registered, and urethral interobserver and interfractional geometric variation was evaluated using the 95th percentile Hausdorff distance (HD95), mean distance to agreement (MDA), center-of-mass shift (COMS), and DICE coefficient. For dosimetric analysis, simulation and final fraction HASTE images were registered to the 3D bSSFP planning MRI and 3D bSSFP final setup MRI, respectively. Both ROs’ urethra contours were transferred from HASTE images for initial treatment plan optimization and final fraction dose estimation separately. Stereotactic body radiotherapy (SBRT) plans, 40 Gy in 5 fractions, were optimized to meet clinical constraints, including urethral V42Gy ≤0.03 cc, on the planning MRI. The initial plan was then forward calculated on the final setup MRI to estimate urethral dose on the final fraction and evaluate urethral dosimetric impact due to anatomy change.ResultsThe average interobserver HD95, MDA, COMS, and DICE were 2.85 ± 1.34 mm, 1.02 ± 0.36 mm, 3.16 ± 1.61 mm, and 0.58 ± 0.15, respectively. The average interfractional HD95, MDA, COMS, and DICE were 3.26 ± 1.54 mm, 1.29 ± 0.54 mm, 3.34 ± 2.01 mm, and 0.49 ± 0.18, respectively. All patient simulation MRgRT plans met all clinical constraints. For RO1 and RO2, 23/26 (88%) and 21/26 (81%) patients’ final fraction estimated urethral dose did not meet the planned constraint. The average urethral V42Gy change was 0.48 ± 0.58 cc.ConclusionUrethral interfractional motion and anatomic change can result in daily treatment violating urethral constraints. Onboard MRI with good visualization of the prostatic urethra can be a valuable tool to help better protect the urethra through patient setup or online adaptive RT.

The impact of an educational tool in cervix image registration across three imaging modalities.

Accurate image registration is vital in cervical cancer where changes in both planning target volume (PTV) and organs at risk (OARs) can make decisions regarding image registration complicated. This work aims to determine the impact of a dedicated educational tool compared with experience gained in MR-guided radiotherapy (MRgRT). 10 therapeutic radiographers acted as observers and were split into two groups based on previous experience with MRgRT and Monaco treatment planning system. Three CBCT-CT, three MR-CT and two MR-MR registrations were completed per patient by each observer. Observers recorded translations, time to complete image registration and confidence. Data were collected in two phases; prior to and following the introduction of a cervix registration guide. No statistically significant differences were noted between imaging modalities. Each group was assessed independently pre- and post-education, no statistically significant differences were noted in either CBCT-CT or MR-CT imaging. Group 1 MR-MR imaging showed a statistically significant reduction in interobserver variability (p=0.04), in Group 2, the result was not statistically significant (p=0.06). Statistically significant increases in confidence were seen in all three modalities (p≤0.05). At The Christie NHS Foundation Trust, radiographers consistently registered images across three different imaging modalities regardless of their previous experience. The implementation of an image registration guide had limited impact on inter- and intraobserver variability. Radiographers' confidence showed statistically significant improvements following the use of the registration manual. This work helps evaluate training methods for novel roles that are developing in MRgRT.

Assessment of a novel commercial large field of view phantom for comprehensive MR imaging quality assurance of a 0.35T MRgRT system

Consistent quality assurance (QA) programs are vital to MR‐guided radiotherapy (MRgRT), for ensuring treatment is delivered accurately and the onboard MRI system is providing the expected image quality. However, daily imaging QA with a dedicated phantom is not common at many MRgRT centers, especially with large phantoms that cover a field of view (FOV), similar to the human torso. This work presents the first clinical experience with a purpose‐built phantom for large FOV daily and periodic comprehensive quality assurance (QUASAR™ MRgRT Insight Phantom (beta)) from Modus Medical Devices Inc. (Modus QA) on an MRgRT system. A monthly American College of Radiology (ACR) QA phantom was also imaged for reference. Both phantoms were imaged on a 0.35T MR‐Linac, a 1.5T Philips wide bore MRI, and a 3.0T Siemens MRI, with T1‐weighted and T2‐weighted acquisitions. The Insight phantom was imaged in axial and sagittal orientations. Image quality tests including geometric accuracy, spatial resolution accuracy, slice thickness accuracy, slice position accuracy, and image intensity uniformity were performed on each phantom, following their respective instruction manuals. The geometric distortion test showed similar distortions of –1.7 mm and –1.9 mm across a 190 mm and a 283 mm lengths for the ACR and MRgRT Insight phantoms, respectively. The MRgRT Insight phantom utilized a modulation transform function (MTF) for spatial resolution evaluation, which showed decreased performance on the lower B0 strength MRIs, as expected, and could provide a good daily indicator of machine performance. Both the Insight and ACR phantoms showed a match with scan parameters for slice thickness analysis. During the imaging and analysis of this novel MRgRT Insight phantom the authors found setup to be straightforward allowing for easy acquisition each day, and useful image analysis parameters for tracking MRI performance.

Glioma Radiation Therapy on a High Field 1.5 MR-Linac: Workflow and Initial Experience

The development of high-field strength MR-guided radiotherapy systems enables daily MR imaging, the opportunity for adaptive radiotherapy, and functional imaging acquisition. This study reports the workflow implementation, treatment times, and initial experience of glioma radiotherapy on the 1.5T MR-Linac (MRL).Selected glioma patients treated with concurrent chemoradiation (chemoRT) between October 2019 and August 2020 were identified from a prospective database. All patients were treated on the MRL with backup plans on conventional Linac if the MRL was unavailable. Workflow timings were recorded and online adaptive plans were generated using the Adapt-To-Position (ATP) workflow derived from a pre-beam T1-weighted MRI. Temporal variation within the FLAIR hyperintense region (FHR) was assessed by the Dice similarity coefficient (DSC) and relative FHR volumes, compared to the initial FLAIR contour at the first MRL fraction. Multi-parametric images were acquired on the MR-Linac during radiation treatment, including diffusion-weighted imaging (DWI), chemical exchange saturation transfer (CEST), magnetization transfer (MT), and blood oxygenation level dependent (BOLD) resting-state fMRI. The behavior of selected functional parameter values was investigated within the FHR at the imaged fractions.Ten high grade glioma patients completed chemoRT to a median dose of 60 Gy (range, 54-60 Gy) in 30 fractions (range, 30-33), receiving a total of 287 fractions on the MRL. The mean in-room time per fraction was 37.3 minutes (range, 24-51 minutes), and 42.9 minutes if including post-beam research imaging. Three patients (30%) required re-planning between fractions 15 to 19 due to progression of tumor and/or edema identified on daily MRL imaging. At the 10, 20, and 30 day post-first fraction time points, 3, 3, and 4 patients had a FLAIR volume that changed by at least 20% relative to the first MRL fraction, respectively. Multi-parametric images including DWI, CEST, MT, and BOLD resting-state fMRI were successfully acquired on the MR-Linac. The median apparent diffusion coefficients (ADC) within the FHR and volumes of FLAIR were significantly correlated when the data from all patients and time points were pooled (r = 0.68, P < 10-3).We report the first clinical series of glioma patients treated with chemoRT on the MRL. The workflow and treatment times were clinically acceptable, and daily online MRL imaging triggered adaptive re-planning for selected patients. Acquisition of multi-parametric imaging sequences was feasible on the MRL during routine treatment workflow. ADC parameter changes could be reliably tracked during chemoRT, and mature clinical outcomes data is anticipated to define the role of functional imaging in adaptive radiotherapy.C. Tseng: Advisory Board; Sanofi. H. Chen: Employee; North York General Hospital. J. Stewart: None. A. Lau: None. R. Chan: None. L.S. Lawrence: Student affiliated with University of Toronto; Sunnybrook Research Institute. M. Campbell: None. S.D. Myrehaug: Advisory Board; Novartis AG.H. Soliman: None. Z.A. Husain: Independent Contractor; RadOncQuestions LLC. Research Grant; Merck. Travel Expenses; Elekta; NIH Head and neck PULA task force. J. Detsky: None. P. Maralani: None. B.M. Keller: None. M.E. Ruschin: Patent/License Fees/Copyright; Elekta AB.A. Sahgal: Research Grant; Elekta.

Toward magnetic resonance fingerprinting for low-field MR-guided radiation therapy.

The acquisition of multiparametric quantitative magnetic resonance imaging (qMRI) is becoming increasingly important for functional characterization of cancer prior to- and throughout the course of radiation therapy. The feasibility of a qMRI method known as magnetic resonance fingerprinting (MRF) for rapid T1 and T2 mapping was assessed on a low-field MR-linac system. A three-dimensional MRF sequence was implemented on a 0.35T MR-guided radiotherapy system. MRF-derived measurements of T1 and T2 were compared to those obtained with gold standard single spin echo methods, and the impacts of the radiofrequency field homogeneity and scan times ranging between 6 and 48 min were analyzed by acquiring between 1 and 8 spokes per time point in a standard quantitative system phantom. The short-term repeatability of MRF was assessed over three measurements taken over a 10-h period. To evaluate transferability, MRF measurements were acquired on two additional MR-guided radiotherapy systems. Preliminary human volunteer studies were performed. The phantom benchmarking studies showed that MRF is capable of mapping T1 and T2 values within 8% and 10% of gold standard measures, respectively, at 0.35T. The coefficient of variation of T1 and T2 estimates over three repeated scans was<5% over a broad range of relaxation times. The T1 and T2 times derived using a single-spoke MRF acquisition across three scanners were near unity and mean percent errors in T1 and T2 estimates using the same phantom were<3%. The mean percent differences in T1 and T2 as a result of truncating the scan time to 6 min over the large range of relaxation times in the system phantom were 0.65% and 4.05%, respectively. The technical feasibility and accuracy of MRF on a low-field MR-guided radiation therapy device has been demonstrated. MRF can be used to measure accurate T1 and T2 maps in three dimensions from a brief 6-min scan, offering strong potential for efficient and reproducible qMRI for future clinical trials in functional plan adaptation and tumor/normal tissue response assessment.

Evaluation of super-resolution on 50 pancreatic cancer patients with real-time cine MRI from 0.35T MRgRT

MR-guided radiotherapy (MRgRT) systems provide excellent soft tissue imaging immediately prior to and in real time during radiation delivery for cancer treatment. However, 2D cine MRI often has limited spatial resolution due to high temporal resolution. This work applies a super resolution machine learning framework to 3.5 mm pixel edge length, low resolution (LR), sagittal 2D cine MRI images acquired on a MRgRT system to generate 0.9 mm pixel edge length, super resolution (SR), images originally acquired at 4 frames per second (FPS). LR images were collected from 50 pancreatic cancer patients treated on a ViewRay MR-LINAC. SR images were evaluated using three methods. 1) The first method utilized intrinsic image quality metrics for evaluation. 2) The second used relative metrics including edge detection and structural similarity index (SSIM). 3) Finally, automatically generated tumor contours were created on both low resolution and super resolution images to evaluate target delineation and compared with DICE and SSIM. Intrinsic image quality metrics all had statistically significant improvements for SR images versus LR images, with mean (±1 SD) BRISQUE scores of 29.65 ± 2.98 and 42.48 ± 0.98 for SR and LR, respectively. SR images showed good agreement with LR images in SSIM evaluation, indicating there was not significant distortion of the images. Comparison of LR and SR images with paired high resolution (HR) 3D images showed that SR images had a mean (±1 SD) SSIM value of 0.633 ± 0.063 and LR a value of 0.587 ± 0.067 (p ≪ 0.05). Contours generated on SR images were also more robust to noise addition than those generated on LR images. This study shows that super resolution with a machine learning framework can generate high spatial resolution images from 4fps low spatial resolution cine MRI acquired on the ViewRay MR-LINAC while maintaining tumor contour quality and without significant acquisition or post processing delay.

Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac

PurposeTo describe the implementation and initial results of using Chemical Exchange Saturation Transfer (CEST) for monitoring patients with central nervous system (CNS) tumours treated using a 1.5 tesla MR-guided radiotherapy system. MethodsCNS patients were treated with up to 30 fractions (total dose up to 60 Gy) using a 1.5 T Elekta Unity MR-Linac. CEST scans were obtained in 54 subjects at one or more time points during treatment. CEST metrics, including the amide magnetization transfer ratio (MTRAmide), nuclear Overhauser effect (NOE) MTR (MTRNOE) and asymmetry, were quantified in phantoms and CNS patients. The signal was investigated between tumour and white matter, across time, and across disease categories including high- and low-grade tumours. ResultsThe gross tumour volume (GTV) exhibited lower MTRAmide and MTRNOE and higher asymmetry compared to contralateral normal appearing white matter. Signal changes in the GTV during fractionated radiotherapy were observed. There were differences between high- and low-grade tumours, with higher CEST asymmetry associated with higher grade disease. ConclusionCEST MRI using a 1.5 T MR-Linac was demonstrated to be feasible for in vivo imaging of CNS tumours. CEST images showed tumour/white-matter contrast, temporal CEST signal changes, and associations with tumour grade. These results show promise for the eventual goal of using metabolic imaging to inform the design of adaptive radiotherapy protocols.

Evaluation of T2-Weighted MRI for Visualization and Sparing of Urethra with MR-Guided Radiation Therapy (MRgRT) On-Board MRI.

Simple SummaryStereotactic body radiation therapy (SBRT) has become a standard of care option for prostate cancer patients, utilizing large fractionated dose to shorten treatment times. However, genitourinary (GU) toxicity associated with urethral injury remains prevalent due to non-trivial urethra delineation and sparing at treatment planning and treatment delivery. The aim of our study was to evaluate two optimized urethral MRI sequences (3D HASTE and 3D TSE) with a 0.35T MR-guided radiotherapy (MRgRT) system for urethral visibility and delineation. Among 11 prostate cancer patients, a radiation oncologist qualitatively scored MRgRT 3D HASTE as having the best urethra visibility, superior to CT, clinical MRgRT 3D bSSFP, MRgRT 3D TSE, and similar to diagnostic 3T (2D/3D) T2-weighetd MRI. Moreover, urethra contours from different imaging and clinical workflows demonstrated significant urethra localization variability. Optimized 3D MRgRT HASTE can provide urethral visualization and delineation within an MRgRT workflow for urethral sparing, avoiding cross-modality/system registration errors.Purpose: To evaluate urethral contours from two optimized urethral MRI sequences with an MR-guided radiotherapy system (MRgRT). Methods: Eleven prostate cancer patients were scanned on a MRgRT system using optimized urethral 3D HASTE and 3D TSE. A resident radiation oncologist contoured the prostatic urethra on the patients’ planning CT, diagnostic 3T T2w MRI, and both urethral MRIs. An attending radiation oncologist reviewed/edited the resident’s contours and additionally contoured the prostatic urethra on the clinical planning MRgRT MRI (bSSFP). For each image, the resident radiation oncologist, attending radiation oncologist, and a senior medical physicist qualitatively scored the prostatic urethra visibility. Using MRgRT 3D HASTE-based contouring workflow as baseline, prostatic urethra contours drawn on CT, diagnostic MRI, clinical bSSFP and 3D TSE were evaluated relative to the contour on 3D HASTE using 95th percentile Hausdorff distance (HD95), mean-distance-to-agreement (MDA), and DICE coefficient. Additionally, prostatic urethra contrast-to-noise-ratios (CNR) were calculated for all images. Results: For two out of three observers, the urethra visibility score for 3D HASTE was significantly higher than CT, and clinical bSSFP, but was not significantly different from diagnostic MRI. The mean HD95/MDA/DICE values were 11.35 ± 3.55 mm/5.77 ± 2.69 mm/0.07 ± 0.08 for CT, 7.62 ± 2.75 mm/3.83 ± 1.47 mm/0.12 ± 0.10 for CT + diagnostic MRI, 5.49 ± 2.32 mm/2.18 ± 1.19 mm/0.35 ± 0.19 for 3D TSE, and 6.34 ± 2.89 mm/2.65 ± 1.31 mm/0.21 ± 0.12 for clinical bSSFP. The CNR for 3D HASTE was significantly higher than CT, diagnostic MRI, and clinical bSSFP, but was not significantly different from 3D TSE. Conclusion: The urethra’s visibility scores showed optimized urethral MRgRT 3D HASTE was superior to the other tested methodologies. The prostatic urethra contours demonstrated significant variability from different imaging and workflows. Urethra contouring uncertainty introduced by cross-modality registration and sub-optimal imaging contrast may lead to significant treatment degradation when urethral sparing is implemented to minimize genitourinary toxicity.

Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system.

PurposeTo estimate the overall spatial distortion on clinical patient images for a 0.35 T MR‐guided radiotherapy system.MethodsTen patients with head‐and‐neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post‐processing. The images were rigidly registered and landmark‐based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone‐tissue, soft tissue, or air‐tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed.ResultsThe average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0–1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p‐values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in‐plane radial distance from the image center along the longitudinal axis of the MR.ConclusionSpatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient‐specific spatial distortions.

Synthetic CT generation from weakly paired MR images using cycle-consistent GAN for MR-guided radiotherapy.

The online version contains supplementary material available at 10.1007/s13534-021-00195-8.

Prediction of soft tissue sarcoma response to radiotherapy using longitudinal diffusion MRI and a deep neural network with generative adversarial network-based data augmentation.

The goal of this study was to predict soft tissue sarcoma response to radiotherapy (RT) using longitudinal diffusion-weighted MRI (DWI). A novel deep-learning prediction framework along with generative adversarial network (GAN)-based data augmentation was investigated for the response prediction. Thirty soft tissue sarcoma patients who were treated with five-fraction hypofractionated radiation therapy (RT, 6Gy×5) underwent diffusion-weighted MRI three times throughout the RT course using an MR-guided radiotherapy system. Pathologic treatment effect (TE) scores, ranging from 0-100%, were obtained from the post-RT surgical specimen as a surrogate of patient treatment response. Patients were divided into three classes based on the TE score (TE≤20%, 20%<TE<90%, TE≥90%). Apparent diffusion coefficient (ADC) maps of the tumor from the three time points were combined as 3-channel images. An auxiliary classifier generative adversarial network (ACGAN) was trained on 20 patients to augment the data size. A total of 15,000 synthetic images were generated for each class. A prediction model based on a previously described VGG-19 network was trained using the synthesized data, validated on five unseen validation patients, and tested on the remaining five test patients. The entire process was repeated seven times, each time shuffling the training, validation, and testing datasets such that each patient was tested at least once during the independent test stage. Prediction performance for slice-based prediction and patient-based prediction was evaluated. The average training and validation accuracies were 86.5%±1.6% and 84.8%±1.8%, respectively, indicating that the generated samples were good representations of the original patient data. Among the seven rounds of testing, slice by slice prediction accuracy ranged from 81.6% to 86.8%. The overall accuracy of the independent test sets was 83.3%. For patient-based prediction, 80% was achieved in one round and 100% was achieved in the remaining six rounds. The mean accuracy was 97.1%. This study demonstrated the potential to use deep learning to predict the pathologic treatment effect from longitudinal DWI. Accuracies of 83.3% and 97.1% were achieved on independent test sets for slice-based and patient-based prediction respectively.

Review of MR-Guided Radiotherapy for Esophageal Cancer.

In this review, we outline the potential benefits and the future role of MRI and MR-guided radiotherapy (MRgRT) in the management of esophageal cancer. Although not currently used in most clinical practice settings, MRI is a useful non-invasive imaging modality that provides excellent soft tissue contrast and the ability to visualize cancer physiology. Chemoradiation therapy with or without surgery is essential for the management of locally advanced esophageal cancer. MRI can help stage esophageal cancer, delineate the gross tumor volume (GTV), and assess the response to chemoradiotherapy. Integrated MRgRT systems can help overcome the challenge of esophageal motion due to respiratory motion by using real-time imaging and tumor tracking with respiratory gating. With daily on-table MRI, shifts in tumor position and tumor regression can be taken into account for online-adaptation. The combination of accurate GTV visualization, respiratory gating, and online adaptive planning, allows for tighter treatment volumes and improved sparing of the surrounding normal organs. This could lead to a reduction in radiotherapy induced cardiac toxicity, pneumonitis and post-operative complications. Tumor physiology as seen on diffusion weighted imaging or dynamic contrast enhancement can help individualize treatments based on the response to chemoradiotherapy. Patients with a complete response on MRI can be considered for organ preservation while patients with no response can be offered an earlier resection. In patients with a partial response to chemoradiotherapy, areas of residual cancer can be targeted for dose escalation. The tighter and more accurate targeting enabled with MRgRT may enable hypofractionated treatment schedules.

Technical Note: Validation of an automatic ACR phantom quality assurance tool for an MR-guided radiotherapy system.

To modify and evaluate an automatic American College of Radiology (ACR) phantom analysis toolbox for ACR quality assurance (QA) on a low-field MR-guided radiotherapy system (ViewRay). An open-source toolbox was modified for ACR QA of a 0.35T MRI system (ViewRay MRIdian). A total of 17 ACR datasets were evaluated, including 10 datasets acquired from different systems across the world, and seven datasets acquired at our center between 2014 and 2020. All required ACR tests, geometric accuracy (GA), high-contrast spatial resolution (HCSR), slice thickness accuracy (ST), slice position accuracy (SP), percent integral uniformity (PIU), percentage signal ghosting (PSG), and low-contrast object detectability (LCOD), were assessed manually and using the toolbox automatically. Measurements between manual and automatic analysis were compared. Precision, recall, and accuracy were calculated, where the manual results were used as the ground truth. The software took less than 2min to complete all seven tests, which usually requires 40min or more if analyzed manually. Overall, the automatic measurement was consistent with the manual result. The absolute differences between the two measurements were 0.72±0.66 (mm), 0.01±0.03, 0.50±0.60 (mm), 0.39±0.41 (mm), 1.01±1.00 (%), 0.0016±0.0019, and 2.79±2.29 for the seven tests. The precision of the automatic toolbox was 100% for all tests, indicating that a test would 100% pass a manual analysis if it had passed the automatic analysis. Recall and accuracy were≥96% for GA, HCSR, SP, PIU, PSG, and LCOD tests, and 91% for the ST test. An automatic ACR QA tool was adopted and evaluated for the low-field MR-guided radiotherapy (MRgRT) system. Overall, the toolbox provided comparable results as manual analysis, and reduced the processing time from over 40min to <2min. This toolbox holds the potential to be widely adopted either as a second check tool or partially replace human measurement for MRgRT programs using the same system.

Imaging and radiation isocentre determination for inline MR-guided radiotherapy systems – proof of principle using MR-phantom with embedded monolithic silicon detector

Multiple vendors are now offering real-time MRI-guided radiotherapy systems. Quality assurance of the imaging and radiation isocentre alignment is an essential component of the QA programme for any linear accelerator used for delivering image-guided radiotherapy. In this work, the authors describe the design and feasibility testing of a device that combines a high resolution monolithic silicon strip detector with an MRI visible phantom for characterisation of optical, MR imaging and radiation isocentre for inline MR-guided radiotherapy systems.

Optimizing MR-Guided Radiotherapy for Breast Cancer Patients.

Current research in radiotherapy (RT) for breast cancer is evaluating neoadjuvant as opposed to adjuvant partial breast irradiation (PBI) with the aim of reducing the volume of breast tissue irradiated and therefore the risk of late treatment-related toxicity. The development of magnetic resonance (MR)–guided RT, including dedicated MR-guided RT systems [hybrid machines combining an MR scanner with a linear accelerator (MR-linac) or 60Co sources], could potentially reduce the irradiated volume even further by improving tumour visibility before and during each RT treatment. In this position paper, we discuss MR guidance in relation to each step of the breast RT planning and treatment pathway, focusing on the application of MR-guided RT to neoadjuvant PBI.

Influence of 0.35T magnetic field on the response of EBT3 and EBT-XD radiochromic films.

To investigate the inconsistency of recent literature on the effect of magnetic field on the response of radiochromic films, we studied the influence of 0.35T magnetic field on dosimetric response of EBT3 and EBT-XD GafchromicTM films. Two different models of radiochromic films, EBT3 and EBT-XD, were investigated. Pieces of films samples from two different batches for each model were irradiated at different dose levels ranging from 1 to 20Gy using 6MV flattening filter free (FFF) x-rays generated by a clinical MR-guided radiotherapy system (B=0.35T). Film samples from the same batch were irradiated at corresponding dose levels using 6MV FFF beam from a conventional linac (B=0) for comparison. The net optical density was measured 48h postirradiation using a flatbed scanner. The absorbance spectra were also measured over 500-700nm wavelength range using a fiber-coupled spectrometer with 2.5nm resolution. To study the effect of fractionated dose delivery to EBT3 (/EBT-XD) films, 8 (/16)Gy dose was delivered in four 2 (/4)Gy fractions with 24h interval between fractions. No significant difference was found in the net optical density and net absorbance of the films irradiated with or without the presence of magnetic field. No dependency on the orientation of the film during irradiation with respect to the magnetic field was observed. The fractionated dose delivery resulted in the same optical density as delivering the whole dose in a single fraction. The 0.35T magnetic field employed in the ViewRay® MR-guided radiotherapy system did not show any significant influence on the response of EBT3 and EBT-XD GafchromicTM films.

Shape Constrained Fully Convolutional DenseNet with Adversarial Training for Multi-organ Segmentation on Head and Neck Low Field MR Images

MR guided radiotherapy provides images not only for patient positioning but also for online adaptive radiotherapy. Accurate delineation of organs-at-risk (OARs) on Head and Neck (H&N) MR images is valuable to both initial treatment planning and adaptive planning, but manual contouring is laborious and inconsistent. A novel method based on the generative adversarial network (GAN) with shape constraint (SC-GAN) is developed for fully automated H&N OARs segmentation on CT and low field MRI. A deep supervised fully convolutional DenseNet is employed as the segmentation network for voxel-wise prediction. A CNN based discriminator network is then utilized to correct predicted errors and image-level inconsistency between the prediction and ground truth. An additional shape representation loss between the prediction and ground truth in the latent shape space is integrated into the segmentation and adversarial loss functions to reduce false positivity and constrain the predicted shapes. The proposed segmentation method was first benchmarked on a public H&N database including 32 patients, and then on 25 0.35T MR images obtained from an MR guided radiotherapy system. The OARs include brainstem, optical chiasm, larynx (MR only), mandible, pharynx (MR only), parotid glands (both left and right), optical nerves (both left and right), and submandibular glands (both left and right, CT only). The performance of the proposed SC-GAN was compared with GAN alone and GAN with SRM but without the Densenet (GAN-SRM) to quantify the contributions of shape constraint and DenseNet in the deep neural network segmentation. The proposed SC-GAN slightly but consistently improves the segmentation accuracy on the benchmark H&N CT images compared with our previous deep segmentation network, which outperformed other published methods on the same or similar CT H&N dataset. On the low field MR dataset, the following average Dice’s indices were obtained using improved SC-GAN: 0.916 (Brainstem), 0.589 (Optical chiasm), 0.816 (Mandible), 0.703 (Optical nerves), 0.799 (Larynx), 0.706 (Pharynx), and 0.845 (Parotid glands). The average surface distances ranged from 0.68mm (Brainstem) to 1.70mm (Larynx). The 95% surface distance ranged from 1.48mm (Left optical nerve) to 3.92mm (Larynx). Compared with CT, using 95% surface distance evaluation, the automated segmentation accuracy is higher on MR for the brainstem, optical chiasm, optical nerves and parotids, and lower for the mandible. The SC-GAN performance is superior to GAN-SRM, which is more accurate than GAN alone on both the CT and MR datasets. The segmentation time for one patient is 14 seconds using a single GPU. The shape constrained FCNN is further improved by incorporating GAN and DenseNet. With the novel method, we showed that the low field MR images acquired on a MR guided radiation radiotherapy system can support accurate and fully automated segmentation of both bony and soft tissue OARs for adaptive radiotherapy.

Synthetic 4D-CT of the thorax for treatment plan adaptation on MR-guided radiotherapy systems

MR-guided radiotherapy treatment planning utilises the high soft-tissue contrast of MRI to reduce uncertainty in delineation of the target and organs at risk. Replacing 4D-CT with MRI-derived synthetic 4D-CT would support treatment plan adaptation on hybrid MR-guided radiotherapy systems for inter- and intrafractional differences in anatomy and respiration, whilst mitigating the risk of CT to MRI registration errors.Three methods were devised to calculate synthetic 4D and midposition (time-weighted mean position of the respiratory cycle) CT from 4D-T1w and Dixon MRI. The first approach employed intensity-based segmentation of Dixon MRI for bulk-density assignment (sCTD). The second step added spine density information using an atlas of CT and Dixon MRI (sCTDS). The third iteration used a polynomial function relating Hounsfield units and normalised T1w image intensity to account for variable lung density (sCTDSL). Motion information in 4D-T1w MRI was applied to generate synthetic CT in midposition and in twenty respiratory phases. For six lung cancer patients, synthetic 4D-CT was validated against 4D-CT in midposition by comparison of Hounsfield units and dose-volume metrics. Dosimetric differences found by comparing sCTD,DS,DSL and CT were evaluated using a Wilcoxon signed-rank test (p = 0.05).Compared to sCTD and sCTDS, planning on sCTDSL significantly reduced absolute dosimetric differences in the planning target volume metrics to less than 98 cGy (1.7% of the prescribed dose) on average. When comparing sCTDSL and CT, average radiodensity differences were within 97 Hounsfield units and dosimetric differences were significant only for the planning target volume D99% metric. All methods produced clinically acceptable results for the organs at risk in accordance with the UK SABR consensus guidelines and the LungTech EORTC phase II trial. The overall good agreement between sCTDSL and CT demonstrates the feasibility of employing synthetic 4D-CT for plan adaptation on hybrid MR-guided radiotherapy systems.