Treatment planning for MR-guided SBRT of pancreatic tumors on a 1.5 T MR-Linac: A global consensus protocol.

Background and purpose: Treatment planning for MR-guided stereotactic body radiotherapy (SBRT) for pancreatic tumors can be challenging, leading to a wide variation of protocols and practices. This study aimed to harmonize treatment planning by developing a consensus planning protocol for MR-guided pancreas SBRT on a 1.5 T MR-Linac. Materials and methods: A consortium was founded of thirteen centers that treat pancreatic tumors on a 1.5 T MR-Linac. A phased planning exercise was conducted in which centers iteratively created treatment plans for two cases of pancreatic cancer. Each phase was followed by a meeting where the instructions for the next phase were determined. After three phases, a consensus protocol was reached. Results: In the benchmarking phase (phase I), substantial variation between the SBRT protocols became apparent (for example, the gross tumor volume (GTV) D99% ranged between 36.8 - 53.7 Gy for case 1, 22.6 - 35.5 Gy for case 2). The next phase involved planning according to the same basic dosimetric objectives, constraints, and planning margins (phase II), which led to a large degree of harmonization (GTV D99% range: 47.9-53.6 Gy for case 1, 33.9-36.6 Gy for case 2). In phase III, the final consensus protocol was formulated in a treatment planning system template and again used for treatment planning. This not only resulted in further dosimetric harmonization (GTV D99% range: 48.2-50.9 Gy for case 1, 33.5-36.0 Gy for case 2) but also in less variation of estimated treatment delivery times. Conclusion: A global consensus protocol has been developed for treatment planning for MR-guided pancreatic SBRT on a 1.5 T MR-Linac. Aside from harmonizing the large variation in the current clinical practice, this protocol can provide a starting point for centers that are planning to treat pancreatic tumors on MR-Linac systems.

A Phase II Study Evaluating the Effect of Intensity Modulated Postmastectomy Radiation Therapy on Implant Failure Rates in Breast Cancer Patients With Immediate, 2-Stage Implant Reconstruction With an MRI Imaging Correlative Substudy.

PURPOSE: Postmastectomy radiation therapy is a mainstay in the adjuvant treatment of node-positive breast cancer, but it poses risks for women with breast reconstruction. Multibeam intensity-modulated radiation therapy improves dose conformality and homogeneity, potentially reducing complications in breast cancer patients with implant-based reconstruction. To investigate this hypothesis, we conducted a single-arm phase 2 clinical trial of breast cancer patients who underwent mastectomy/axillary dissection and prosthesis-based reconstruction. METHODS AND MATERIALS: The primary endpoint was the rate of implant failure (IF) within 24 months of permanent implant placement, which would be considered an improvement over historical controls if below 16%. IF was defined as removal leading to a flat chest wall or replacement with another reconstruction. Patients were analyzed in 2 cohorts. Cohort 1 (RT-PI) received radiation therapy to the permanent implant. Cohort 2 (RT-TE) received radiation therapy to the TE. IF rates, adverse events, and quality of life were analyzed. Follow-up/postradiation therapy assessments were compared with the baseline/preradiation therapy assessments at 3 to 10 weeks after exchange surgery. A subgroup underwent serial magnetic resonance imaging (MRI) sessions to explore the association between MRI-detected changes and capsular contracture, a known adverse effect of radiation therapy. RESULTS: Between June 2014 and March 2017, 119 women were enrolled. Cohort 1 included 45 patients, and cohort 2 had 74 patients. Among 100 evaluable participants, 25 experienced IF during the study period. IF occurred in 8/42 (19%) and 17/58 (29%) in cohorts 1 and 2, respectively. Among the IFs, the majority were due to capsular contracture (13), infection (7), exposure (3), and other reasons (2). Morphologic shape features observed in longitudinal MRI images were associated with the development of Baker grade 3 to 4 contractures. CONCLUSIONS: The rate of IF in reconstructed breast cancer patients treated with intensity-modulated radiation therapy was similar to, but not improved over, that observed with conventional, 3-dimensional-conformal methods. MRI features show promise for predicting capsular contracture but require validation in larger studies.

MR signature matching (MRSIGMA) implementation for true real-time free-breathing volumetric imaging with sub-200 ms latency on an MR-Linac.

PURPOSE: Develop a true real-time implementation of MR signature matching (MRSIGMA) for free-breathing 3D MRI with sub-200 ms latency on the Elekta Unity 1.5T MR-Linac. METHODS: MRSIGMA was implemented on an external computer with a network connection to the MR-Linac. Stack-of-stars with partial kz sampling was used to accelerate data acquisition and ReconSocket was employed for simultaneous data transmission. Movienet network computed the 4D MRI motion dictionary and correlation analysis was used for signature matching. A programmable 4D MRI phantom was utilized to evaluate MRSIGMA with respect to a ground-truth translational motion reference. In vivo validation was performed on patients with pancreatic cancer, where 15 patients were employed to train Movienet and 7 patients to test the real-time implementation of MRSIGMA. Dice coefficients between real-time MRSIGMA and a retrospectively computed 4D reference were used to evaluate motion tracking performance. RESULTS: Motion dictionary was computed in under 5 s. Signature acquisition and matching presented 173 ms latency on the phantom and 193 ms on patients. MRSIGMA presented a mean error of 1.3-1.6 mm for all phantom experiments, which was below the 2 mm acquisition resolution along the motion direction. The Dice coefficient over time between MRSIGMA and reference contours was 0.88 ± 0.02 (GTV), 0.87 ± 0.02(duodenum-stomach), and 0.78 ± 0.02(small bowel), demonstrating high motion tracking performance for both tumor and organs at risk. CONCLUSION: The real-time implementation of MRSIGMA enabled true real-time free-breathing 3D MRI with sub-200 ms imaging latency on a clinical MR-Linac system, which can be used for treatment monitoring, adaptive radiotherapy and dose accumulation mapping in tumors affected by respiratory motion.

Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system.

Objective. To develop real-time 4D MRI using MR signature matching (MRSIGMA) for volumetric motion imaging in patients with pancreatic cancer on a 1.5T MR-Linac system.Approach. Two consecutive MRI scans with 3D golden-angle radial stack-of-stars acquisitions were performed on ten patients with inoperable pancreatic cancer. The complete first scan (905 angles) was used to compute a 4D motion dictionary including ten pairs of 3D motion images and signatures. The second scan was used for real-time imaging, where each angle (275 ms) was processed separately to match it to one of the dictionary entries. The complete second scan was also used to compute a 4D reference to assess motion tracking performance.Dicecoefficients of the gross tumor volume (GTV) and two organs-at-risk (duodenum-stomach and small bowel) were calculated between signature matching and reference. In addition, volume changes, displacements, center of mass shifts, andDicescores over time were calculated to characterize motion.Main results. Total imaging latency of MRSIGMA (acquisition + matching) was less than 300 ms. TheDicecoefficients were 0.87 ± 0.06 (GTV), 0.86 ± 0.05 (duodenum-stomach), and 0.85 ± 0.05 (small bowel), which indicate high accuracy (high mean value) and low uncertainty (low standard deviation) of MRSIGMA for real-time motion tracking. The center of mass shift was 3.1 ± 2.0 mm (GTV), 5.3 ± 3.0 mm (duodenum-stomach), and 3.4 ± 1.5 mm (small bowel). TheDicescores over time (0.97 ± [0.01-0.03]) were similarly high for MRSIGMA and reference scans in all the three contours.Significance. This work demonstrates the feasibility of real-time 4D MRI using MRSIGMA for volumetric motion tracking on a 1.5T MR-Linac system. The high accuracy and low uncertainty of real-time MRSIGMA is an essential step towards continuous treatment adaptation of tumors affected by real-time respiratory motion and could ultimately improve treatment safety by optimizing ablative dose delivery near gastrointestinal organs.

Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group.

BACKGROUND AND PURPOSE: The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS: Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS: The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION: Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.

Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT.

BACKGROUND: Adaptive radiation treatment (ART) for locally advanced pancreatic cancer (LAPC) requires consistently accurate segmentation of the extremely mobile gastrointestinal (GI) organs at risk (OAR) including the stomach, duodenum, large and small bowel. Also, due to lack of sufficiently accurate and fast deformable image registration (DIR), accumulated dose to the GI OARs is currently only approximated, further limiting the ability to more precisely adapt treatments. PURPOSE: Develop a 3-D Progressively refined joint Registration-Segmentation (ProRSeg) deep network to deformably align and segment treatment fraction magnetic resonance images (MRI)s, then evaluate segmentation accuracy, registration consistency, and feasibility for OAR dose accumulation. METHOD: ProRSeg was trained using five-fold cross-validation with 110 T2-weighted MRI acquired at five treatment fractions from 10 different patients, taking care that same patient scans were not placed in training and testing folds. Segmentation accuracy was measured using Dice similarity coefficient (DSC) and Hausdorff distance at 95th percentile (HD95). Registration consistency was measured using coefficient of variation (CV) in displacement of OARs. Statistical comparison to other deep learning and iterative registration methods were done using the Kruskal-Wallis test, followed by pair-wise comparisons with Bonferroni correction applied for multiple testing. Ablation tests and accuracy comparisons against multiple methods were done. Finally, applicability of ProRSeg to segment cone-beam CT (CBCT) scans was evaluated on a publicly available dataset of 80 scans using five-fold cross-validation. RESULTS: ProRSeg processed 3D volumes (128 × 192 × 128) in 3 s on a NVIDIA Tesla V100 GPU. It's segmentations were significantly more accurate ( p < 0.001 $p<0.001$ ) than compared methods, achieving a DSC of 0.94 ±0.02 for liver, 0.88±0.04 for large bowel, 0.78±0.03 for small bowel and 0.82±0.04 for stomach-duodenum from MRI. ProRSeg achieved a DSC of 0.72±0.01 for small bowel and 0.76±0.03 for stomach-duodenum from public CBCT dataset. ProRSeg registrations resulted in the lowest CV in displacement (stomach-duodenum C V x $CV_{x}$ : 0.75%, C V y $CV_{y}$ : 0.73%, and C V z $CV_{z}$ : 0.81%; small bowel C V x $CV_{x}$ : 0.80%, C V y $CV_{y}$ : 0.80%, and C V z $CV_{z}$ : 0.68%; large bowel C V x $CV_{x}$ : 0.71%, C V y $CV_{y}$ : 0.81%, and C V z $CV_{z}$ : 0.75%). ProRSeg based dose accumulation accounting for intra-fraction (pre-treatment to post-treatment MRI scan) and inter-fraction motion showed that the organ dose constraints were violated in four patients for stomach-duodenum and for three patients for small bowel. Study limitations include lack of independent testing and ground truth phantom datasets to measure dose accumulation accuracy. CONCLUSIONS: ProRSeg produced more accurate and consistent GI OARs segmentation and DIR of MRI and CBCTs compared to multiple methods. Preliminary results indicates feasibility for OAR dose accumulation using ProRSeg.

Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.

BACKGROUND: Dose escalation radiotherapy enables increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL). This motivates the development of automated methods for fast, accurate, and consistent segmentation of PCa DIL. PURPOSE: To construct and validate a model for deep-learning-based automatic segmentation of PCa DIL defined by Gleason score (GS) ≥3+4 from MR images applied to MR-guided radiation therapy. Validate generalizability of constructed models across scanner and acquisition differences. METHODS: Five deep-learning networks were evaluated on apparent diffusion coefficient (ADC) MRI from 500 lesions in 365 patients arising from internal training Dataset 1 (156 lesions in 125 patients, 1.5Tesla GE MR with endorectal coil), testing using Dataset 1 (35 lesions in 26 patients), external ProstateX Dataset 2 (299 lesions in 204 patients, 3Tesla Siemens MR), and internal inter-rater Dataset 3 (10 lesions in 10 patients, 3Tesla Philips MR). The five networks include: multiple resolution residually connected network (MRRN) and MRRN regularized in training with deep supervision implemented into the last convolutional block (MRRN-DS), Unet, Unet++, ResUnet, and fast panoptic segmentation (FPSnet) as well as fast panoptic segmentation with smoothed labels (FPSnet-SL). Models were evaluated by volumetric DIL segmentation accuracy using Dice similarity coefficient (DSC) and the balanced F1 measure of detection accuracy, as a function of lesion aggressiveness and size (Dataset 1 and 2), and accuracy with respect to two-raters (on Dataset 3). Upon acceptance for publication segmentation models will be made available in an open-source GitHub repository. RESULTS: In general, MRRN-DS more accurately segmented tumors than other methods on the testing datasets. MRRN-DS significantly outperformed ResUnet in Dataset2 (DSC of 0.54 vs. 0.44, p < 0.001) and the Unet++ in Dataset3 (DSC of 0.45 vs. p = 0.04). FPSnet-SL was similarly accurate as MRRN-DS in Dataset2 (p = 0.30), but MRRN-DS significantly outperformed FPSnet and FPSnet-SL in both Dataset1 (0.60 vs. 0.51 [p = 0.01] and 0.54 [p = 0.049] respectively) and Dataset3 (0.45 vs. 0.06 [p = 0.002] and 0.24 [p = 0.004] respectively). Finally, MRRN-DS produced slightly higher agreement with experienced radiologist than two radiologists in Dataset 3 (DSC of 0.45 vs. 0.41). CONCLUSIONS: MRRN-DS was generalizable to different MR testing datasets acquired using different scanners. It produced slightly higher agreement with an experienced radiologist than that between two radiologists. Finally, MRRN-DS more accurately segmented aggressive lesions, which are generally candidates for radiative dose ablation.

A model for gastrointestinal tract motility in a 4D imaging phantom of human anatomy.

BACKGROUND: Gastrointestinal (GI) tract motility is one of the main sources for intra/inter-fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose-accumulation algorithms. PURPOSE: To implement GI tract motion in the 4D extended cardiac-torso (XCAT) digital phantom of human anatomy. MATERIALS AND METHODS: Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on literature research. Search criteria included amplitude changes larger than planning risk volume expansions and durations of the order of tens of minutes. The following modes were identified: peristalsis, rhythmic segmentation, high amplitude propagating contractions (HAPCs), and tonic contractions. Peristalsis and rhythmic segmentations were modeled by traveling and standing sinusoidal waves. HAPCs and tonic contractions were modeled by traveling and stationary Gaussian waves. Wave dispersion in the temporal and spatial domain was implemented by linear, exponential, and inverse power law functions. Modeling functions were applied to the control points of the nonuniform rational B-spline surfaces defined in the reference XCAT library. GI motility was combined with the cardiac and respiratory motions available in the standard 4D-XCAT phantom. Default model parameters were estimated based on the analysis of cine MRI acquisitions in 10 patients treated in a 1.5T MR-linac. RESULTS: We demonstrate the ability to generate realistic 4D multimodal images that simulate GI motility combined with respiratory and cardiac motion. All modes of motility, except tonic contractions, were observed in the analysis of our cine MRI acquisitions. Peristalsis was the most common. Default parameters estimated from cine MRI were used as initial values for simulation experiments. It is shown that in patients undergoing stereotactic body radiotherapy for abdominal targets, the effects of GI motility can be comparable or larger than the effects of respiratory motion. CONCLUSION: The digital phantom provides realistic models to aid in medical imaging and radiation therapy research. The addition of GI motility will further contribute to the development, testing, and validation of DIR and dose accumulation algorithms for MR-guided radiotherapy.

A Phase 1 Safety Study of Avelumab Plus Stereotactic Body Radiation Therapy in Malignant Pleural Mesothelioma.

Introduction: Single-agent monoclonal antibody therapy against programmed death-ligand 1 (PD-L1) has modest effects in malignant pleural mesothelioma. Radiation therapy can enhance the antitumor effects of immunotherapy. Nevertheless, the safety of combining anti-PD-L1 therapy with stereotactic body radiation therapy (SBRT) is unknown. We present the results of a phase 1 trial to evaluate the safety of the anti-PD-L1 antibody avelumab plus SBRT in patients with malignant pleural mesothelioma. Methods: This was a single-arm, investigator-initiated trial in patients who progressed on prior chemotherapy. Avelumab was delivered every other week, and SBRT was delivered to one lesion in three to five fractions (minimum of 30 Gy) followed by continuation of avelumab up to 24 months or until disease progression. The primary end point of the study was safety on the basis of grade 3+ nonhematologic adverse events (AEs) within 3 months of SBRT. Results: Thirteen assessable patients received a median of seven cycles (range: 2-26 cycles) of avelumab. There were 27 grade 1, 17 grade 2, four grade 3, and no grade 4 or 5 avelumab-related AEs. The most common were infusion-related allergic reactions (n = 6), anorexia or weight loss (n = 6), fatigue (n = 6), thyroid disorders (n = 5), diarrhea (n = 3), and myalgia or arthralgias (n = 3). There were 10 grade 1, four grade 2, one grade 3, and no grade 4 or 5 SBRT-related AEs. The most common were diarrhea (n = 3), chest pain/myalgia (n = 2), fatigue (n = 2), cough (n = 2), dyspnea (n = 2), and nausea/vomiting (n = 2). Conclusions: Combination avelumab plus SBRT seems tolerable on the basis of the prespecified toxicity end points of the first stage of this Simon two-stage design phase 1 study.

SBRT focal dose intensification using an MR-Linac adaptive planning for intermediate-risk prostate cancer: An analysis of the dosimetric impact of intra-fractional organ changes.

INTRODUCTION: Using an magnetic resonance linear accelerator (MR-Linac) may improve the precision of visible tumor boosting with ultra-hypofractionation by accounting for daily positional changes in the target and organs at risk (OAR). PATIENTS AND METHODS: Fifteen patients with prostate cancer and an MR-detected dominant lesion were treated on the MR-Linac with stereotactic body radiation (SBRT) to 40 Gy in 5 fractions, boosting the gross tumor volume (GTV) to 45 Gy with daily adaptive planning. Imaging was acquired again after initial planning (verification scan), and immediately after treatment (post-treatment scan). Prior to beam-on, additional adjustments were made on the verification scan. Contours were retrospectively adjusted on verification and post-treatment scans, and the daily plan recalculated on these scans to estimate the true dose delivered. RESULTS: The median prostate D95% for plan 1, 2 and 3 was 40.3 Gy, 40.5 Gy and 40.3 Gy and DIL D95% was 45.7 Gy, 45.2 Gy and 44.6 Gy, respectively. Bladder filling was associated with reduced GTV coverage (p = 0.03, plan 1 vs 2) and prostate coverage (p = 0.03, plan 2 vs 3). The D0.035 cc constraint was exceeded on verification and post-treatment plans in 24 % and 33 % of fractions for the urethra, 31 % and 45 % for the bladder, and 35 % and 25 % for the rectum, respectively. CONCLUSION: MR-Linac guided, daily adaptive SBRT with focal boosting of the GTV yields acceptable planned and delivered dosimetry. Adaptive planning with a MR-Linac may reliably deliver the prescribed dose to the intended tumor target.

Risk analysis of the Unity 1.5 T MR-Linac adapt-to-position workflow.

BACKGROUND AND PURPOSE: Newer technologies allow for daily treatment adaptation, providing the ability to account for setup variations and organ motion but comes at the cost of increasing the treatment workflow complexity. One such technology is the adapt-to-position (ATP) workflow on the Unity MR-Linac. Prospective risk assessment of a new workflow allows clinics to catch errors before they occur, especially for processes that include novel and unfamiliar steps. METHODS: As part of a quality management program, failure modes and effects analysis was performed on the ATP treatment workflow following the recommendations of AAPM's Task Group 100. A multidisciplinary team was formed to identify and evaluate failure modes for all the steps taken during a daily treatment workflow. Failure modes of high severity and overall score were isolated and addressed. RESULTS: Mitigations were determined for high-ranking failure modes and implemented into the clinic. High-ranking failure modes existed in all steps of the workflow. Failure modes were then rescored to evaluate the effectiveness of the mitigations. CONCLUSION: Failure modes and effects analysis on the Unity MR-Linac highlighted areas in the ATP workflow that could be prone to failures and allowed our clinic to change the process to be more robust.

Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT).

Vision transformers efficiently model long-range context and thus have demonstrated impressive accuracy gains in several image analysis tasks including segmentation. However, such methods need large labeled datasets for training, which is hard to obtain for medical image analysis. Self-supervised learning (SSL) has demonstrated success in medical image segmentation using convolutional networks. In this work, we developed a self-distillation learning with masked image modeling method to perform SSL for vision transformers (SMIT) applied to 3D multi-organ segmentation from CT and MRI. Our contribution combines a dense pixel-wise regression pretext task performed within masked patches called masked image prediction with masked patch token distillation to pre-train vision transformers. Our approach is more accurate and requires fewer fine tuning datasets than other pretext tasks. Unlike prior methods, which typically used image sets arising from disease sites and imaging modalities corresponding to the target tasks, we used 3,643 CT scans (602,708 images) arising from head and neck, lung, and kidney cancers as well as COVID-19 for pre-training and applied it to abdominal organs segmentation from MRI pancreatic cancer patients as well as publicly available 13 different abdominal organs segmentation from CT. Our method showed clear accuracy improvement (average DSC of 0.875 from MRI and 0.878 from CT) with reduced requirement for fine-tuning datasets over commonly used pretext tasks. Extensive comparisons against multiple current SSL methods were done. Our code is available at: https://github.com/harveerar/SMIT.git.

Stereotactic ablative radiation for pancreatic cancer on a 1.5 Telsa magnetic resonance-linac system.

Purpose: Ablative radiation therapy (A-RT) appears to improve outcomes in locally advanced pancreatic cancer (LAPC) yet requires solutions for respiratory and digestive motion. We report outcomes of A-RT for pancreatic cancer using 1.5 T MR-adaptive treatment delivery. Methods: Between March 2020 and July 2021, we treated 30 patients with pancreatic cancer with 50 Gy in 5 fractions (biologically effective dose [BED10] = 100 Gy10) using a novel compression belt workflow and remote planning on the Unity 1.5 T MR linac system. Cumulative incidence of progression was computed from A-RT initiation with death as a competing risk. Overall (OS) and progression-free survival (PFS) were calculated using Kaplan Meier methods. Results: Of 30 patients, most (73 %) were locally advanced, 4 (13 %) were metastatic, 2 (7 %) were medically inoperable, and 2 (7 %) were locally recurrent. Most (73 %) received FOLFIRINOX prior to A-RT. Median follow-up times from diagnosis and A-RT were 17.6 (IQR 15.8-23.1) and 11.5 months (IQR 9.7-16.1), respectively. Cumulative incidences at 1-year of local and distant progression were 19.3 % (95 %CI 6.7-36.8 %) and 47.4 % (95 %CI 26.7-65.6 %), respectively. Median OS from diagnosis and A-RT were not reached. One-year OS from diagnosis and A-RT were 96.4 % (95 %CI 77.2-99.5 %) and 80.0 % (95 %CI 57.3-91.4 %), respectively. Median and 1-year PFS were 10.1 months (95 %CI 4.4-14.4) and 39.7 % (95 %CI 20.3-58.5 %), respectively. No grade 3 + toxicities were observed. Conclusions: A-RT using the 1.5 T Unity MR Linac resulted in promising LC and OS with no severe toxicity in patients with LAPC despite radiosensitive organs adjacent to the target volumes. Longer follow-up is needed to assess long-term outcomes.

Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System.

Purpose: Commercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-Linac. Methods: The 7-MV flattening filter free (FFF) beam and multi-leaf collimator (MLC) models of a 1.5-T Elekta Unity MR-Linac within Monte Carlo-based Monaco TPS were used to generate an optimized beam model in Eclipse TPS. The MLC dosimetric leaf gap of the beam in Eclipse was determined by matching the dose distribution of Eclipse-generated intensity-modulated radiation therapy (IMRT) plans using the Analytical Anisotropic Algorithm (AAA) algorithm to Monaco plans. The plans were automatically adjusted for different source-to-axis distances (SADs) between the two systems. For IMU check, the treatment plans developed in Monaco were transferred to Eclipse to recalculate the dose using AAA. A plug-in within Eclipse was created to perform a 2D gamma analysis of the AAA and Monte Carlo dose distribution on a beam's eye view parallel plane. Monaco dose distribution was shifted laterally by 2 mm during gamma analysis to account for the impact of magnetic field on electron trajectories. Eclipse doses for posterior beams were corrected for both the Unity couch and the posterior MR coil attenuation. Thirteen patients, each with 4-5 fractions for a variety of tumor sites (pancreas, rectum, and prostate), were tested. Results: After thorough commissioning, the method was implemented as part of the standard clinical workflow. A total of 62 online plans, each with approximately 15 beams, were evaluated. The average per-beam gamma (3%/3 mm) pass rate for plans was 97.9% (range, 95.9% to 98.8%). The average pass rate per beam for all 932 beams used in these plans was 97.9% ± 1.9%, with the lowest per-beam gamma pass rate at 88.4%. The time for the process was within 3.2 ± 0.9 min. Conclusion: The use of a second planning system provides an efficient way to perform IMU checks with clinically acceptable accuracy for online adaptive plans on Unity MR-Linac. This is essential for meeting the safety requirements for second checks as outlined in American Association of Physicists in Medicine Task Group (AAPM TG) reports 114 and 219.

Inter- and intrafraction motion assessment and accumulated dose quantification of upper gastrointestinal organs during magnetic resonance-guided ablative radiation therapy of pancreas patients.

BACKGROUND AND PURPOSE: Stereotactic body radiation therapy (SBRT) of locally advanced pancreatic cancer (LAPC) is challenging due to significant motion of gastrointestinal (GI) organs. The goal of our study was to quantify inter and intrafraction deformations and dose accumulation of upper GI organs in LAPC patients. MATERIALS AND METHODS: Five LAPC patients undergoing five-fraction magnetic resonance-guided radiation therapy (MRgRT) using abdominal compression and daily online plan adaptation to 50 Gy were analyzed. A pre-treatment, verification, and post-treatment MR imaging (MRI) for each of the five fractions (75 total) were used to calculate intra and interfraction motion. The MRIs were registered using Large Deformation Diffeomorphic Metric Mapping (LDDMM) deformable image registration (DIR) method and total dose delivered to stomach_duodenum, small bowel (SB) and large bowel (LB) were accumulated. Deformations were quantified using gradient magnitude and Jacobian integral of the Deformation Vector Fields (DVF). Registration DVFs were geometrically assessed using Dice and 95th percentile Hausdorff distance (HD95) between the deformed and physician's contours. Accumulated doses were then calculated from the DVFs. RESULTS: Median Dice and HD95 were: Stomach_duodenum (0.9, 1.0 mm), SB (0.9, 3.6 mm), and LB (0.9, 2.0 mm). Median (max) interfraction deformation for stomach_duodenum, SB and LB was 6.4 (25.8) mm, 7.9 (40.5) mm and 7.6 (35.9) mm. Median intrafraction deformation was 5.5 (22.6) mm, 8.2 (37.8) mm and 7.2 (26.5) mm. Accumulated doses for two patients exceeded institutional constraints for stomach_duodenum, one of whom experienced Grade1 acute and late abdominal toxicity. CONCLUSION: LDDMM method indicates feasibility to measure large GI motion and accumulate dose. Further validation on larger cohort will allow quantitative dose accumulation to more reliably optimize online MRgRT.

Longitudinal assessment of quality assurance measurements in a 1.5 T MR-linac: Part II-Magnetic resonance imaging.

PURPOSE: To describe and report longitudinal quality assurance (QA) measurements for the magnetic resonance imaging (MRI) component of the Elekta Unity MR-linac during the first year of clinical use in our institution. MATERIALS AND METHODS: The performance of the MRI component of Unity was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor image uniformity, signal-to-noise ratio (SNR), resolution/detectability, slice position/thickness, linearity, central frequency, and geometric accuracy. In anticipation of routine use of quantitative imaging (qMRI), we characterize B0/B1 uniformity and the bias/reproducibility of longitudinal/transverse relaxation times (T1/T2) and apparent diffusion coefficient (ADC). Tolerance levels for QA measurements of qMRI biomarkers are derived from weekly monitoring of T1, T2, and ADC. RESULTS: The 1-year assessment of QA measurements shows that daily variations in each MR quality metric are well below the threshold for failure. Routine testing procedures can reproducibly identify machine issues. The longitudinal three-dimensional (3D) geometric analysis reveals that the maximum distortion in a diameter of spherical volume (DSV) of 20, 30, 40, and 50 cm is 0.4, 0.6, 1.0, and 3.1 mm, respectively. The main source of distortion is gradient nonlinearity. Maximum peak-to-peak B0 inhomogeneity is 3.05 ppm, with gantry induced B0 inhomogeneities an order of magnitude smaller. The average deviation from the nominal B1 is within 2%, with minimal dependence on gantry angle. Mean ADC, T1, and T2 values are measured with high reproducibility. The median coefficient of variation for ADC, T1, and T2 is 1.3%, 1.1%, and 0.5%, respectively. The median bias for ADC, T1, and T2 is -0.8%, -0.1%, and 3.9%, respectively. CONCLUSION: The MRI component of Unity operates within the guidelines and recommendations for scanner performance and stability. Our findings support the recently published guidance in establishing clinically acceptable tolerance levels for image quality. Highly reproducible qMRI measurements are feasible in Unity.

An evaluation of the use of EBT-XD film for SRS/SBRT commissioning of a 1.5 Tesla MR-Linac system.

PURPOSE: The goal of this study was to evaluate the use of EBT-XD film for SRS/SBRT commissioning in a 1.5T hybrid MR-Linac (MRL). METHOD: The output factors (St), from 1x1, 2x2, 3x3 cm2, were measured with film in solid water. The results were compared with (1) the measurements by a PTW diamond detector (CVD) and an Exradin® A26MR ion chamber in 3D water phantom; (2) Monte Carlo calculation by Monaco TPS (MTPS) in water. The inline (IN) and crossline (CR) profiles, measured by films and the CVD, were also compared. An SRS plan with two targets was created in MTPS and was measured with EBT-XD film in a StereoPHANTM phantom serving as an end-to-end test. The 3x3 cm2 was used for film calibration with doses ranging from 0 to 28 Gy. Water was added to the phantom-film-phantom interface to reduce the electron-return-effect (ERE). Films were calibrated with One-scan-dosimetry protocol. RESULTS: The film St were within 1.2% and 2.2% compared to other detectors and MTPS respectively. At the central B-field induced asymmetric region, films were within 0.6% between the CVD and the MTPS, but 5-8% differences were observed in the 40%-5% gradient region in CR due to ERE. The differences in localization and dose were found to be 0.6 mm and 3.3%. The γ(3%/2mm), γ (5%/2mm), γ (5%/1mm) were 97.7%, 99.3%, 94.6%. CONCLUSIONS: Films can provide accurate dosimetric results under ERE and are valuable for commissioning MRL. Using the One-scan-dosimetry protocol with EBT-XD film for MRL increases accuracy and efficiency in commissioning and QA of SRS/SBRT.

Combined Compressed Sensing and SENSE to Enhance Radiation Therapy Magnetic Resonance Imaging Simulation.

PURPOSE: To assess the effect of a combination of compressed sensing and SENSitivity Encoding (SENSE) acceleration techniques on radiation therapy magnetic resonance imaging (MRI) simulation workflows. METHODS AND MATERIALS: Thirty-seven acquisitions were performed with both SENSE-only (SENSE) and combined compressed sensing and SENSE (CS) techniques in 24 patients receiving radiation therapy MRI simulation for a wide range of disease sites. The anatomic field of view prescription and image resolution were identical for both SENSE and CS acquisitions to ensure fair comparison. The acquisition time of all images was recorded to assess time savings. For each image pair, image quality, and ability to contour were assessed by 2 radiation oncologists. Aside from direct image pair comparisons, the feasibility of using CS to improve MRI simulation protocols by increasing image resolution, field of view, and reducing motion artifacts was also evaluated. RESULTS: CS resulted in an average reduction of 27% in scan time with negligible changes in image quality and the ability to contour structures for RT treatment planning compared with SENSE. Physician scoring of image quality and ability to contour shows that while SENSE still has slightly better image quality compared with CS, this observed difference in image quality did not affect the ability to contour. In addition, the higher acceleration capability of CS enabled use of superior-inferior direction phase encoding in a sagittal 3-dimensional T2-weighted scan for substantially improved visibility of the prostatic urethra, which eliminated the need for a Foley catheter in most patients. CONCLUSIONS: The combination of compressed sensing and parallel imaging resulted in marked improvements in the MRI Simulation workflow. The scan time was reduced without significantly affecting image quality in the context of ability to contour. The acceleration capabilities allowed for increased image resolution under similar scanning times as well as significantly improved urethra visualization in prostate simulations.

Dosimetric evaluation of irradiation geometry and potential air gaps in an acrylic miniphantom used for external audit of absolute dose calibration for a hybrid 1.5 T MR-linac system.

INTRODUCTION: To investigate the impact of partial lateral scatter (LS), backscatter (BS) and presence of air gaps on optically stimulated luminescence dosimeter (OSLD) measurements in an acrylic miniphantom used for dosimetry audit on the 1.5 T magnetic resonance-linear accelerator (MR-linac) system. METHODS: The following irradiation geometries were investigated using OSLDs, A26 MR/A12 MR ion chamber (IC), and Monaco Monte Carlo system: (a) IC/OSLD in an acrylic miniphantom (partial LS, partial BS), (b) IC/OSLD in a miniphantom placed on a solid water (SW) stack at a depth of 1.5 cm (partial LS, full BS), (c) IC/OSLD placed at a depth of 1.5 cm inside a 3 cm slab of SW/buildup (full LS, partial BS), and (d) IC/OSLD centered inside a 3 cm slab of SW/buildup at a depth of 1.5 cm placed on top of a SW stack (full LS, full BS). Average of two irradiated OSLDs with and without water was used at each setup. An air gap of 1 and 2 mm, mimicking presence of potential air gap around the OSLDs in the miniphantom geometry was also simulated. The calibration condition of the machine was 1 cGy/MU at SAD = 143.5 cm, d = 5 cm, G90, and 10 × 10 cm2 . RESULTS: The Monaco calculation (0.5% uncertainty and 1.0 mm voxel size) for the four setups at the measurement point were 108.2, 108.1, 109.4, and 110.0 cGy. The corresponding IC measurements were 109.0 ± 0.03, 109.5 ± 0.06, 110.2 ± 0.02, and 109.8 ± 0.03 cGy. Without water, OSLDs measurements were ∼10% higher than the expected. With added water to minimize air gaps, the measurements were significantly improved to within 2.2%. The dosimetric impacts of 1 and 2 mm air gaps were also verified with Monaco to be 13.3% and 27.9% higher, respectively, due to the electron return effect. CONCLUSIONS: A minimal amount of air around or within the OSLDs can cause measurement discrepancies of 10% or higher when placed in a high b-field MR-linac system. Care must be taken to eliminate the air from within and around the OSLD.

Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation.

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies-which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation-can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.