MRI-guided Radiotherapy System Research Articles

Development of Prostate Bed Delineation Consensus Guidelines for Magnetic Resonance Image-Guided Radiotherapy and Assessment of Its Effect on Interobserver Variability

Background and purposeThe use of MRI in radiotherapy planning is becoming more widespread, particularly with the emergence of MRI-guided radiotherapy (MRIgRT) systems. Existing guidelines for defining the prostate bed clinical target volume (CTV) show considerable heterogeneity. This study aims to establish baseline interobserver variability (IOV) for prostate bed CTV contouring on MRI, develop international consensus guidelines and evaluate its effect on IOV. Methods and MaterialsParticipants delineated the CTV on three MRI scans, obtained from the xxx xxx MR-Linac, as per their normal practice. Radiation oncologist contours were visually examined for discrepancies and interobserver comparisons were evaluated against Simultaneous Truth and Performance Level Estimate (STAPLE) contours using overlap metrics (Dice similarity coefficient and Cohen's Kappa), distance metrics (mean distance to agreement and Hausdorff distance) and volume measurements.. A literature review of post-radical prostatectomy local recurrence patterns was performed and presented alongside IOV results to the participants. Consensus guidelines were collectively constructed and IOV assessment was repeated using these guidelines. ResultsSixteen radiation oncologists’ contours were included in the final analysis. Visual evaluation demonstrated significant differences in the superior, inferior and anterior borders. Baseline IOV assessment indicated moderate agreement for the overlap metrics whilst volume and distance metrics demonstrated greater variability. Consensus for optimal prostate bed CTV boundaries was established during a virtual meeting. Post-guideline development, a decrease in IOV was observed. The maximum volume ratio decreased from 4.7 to 3.1 and volume coefficient of variation reduced from 40% to 34%. The mean Dice similarity coefficient rose from 0.72 to 0.75 and the mean distance to agreement decreased from 3.63mm to 2.95mm. ConclusionsInterobserver variability in prostate bed contouring exists amongst international genitourinary experts, although this is lower than previously reported. Consensus guidelines for MRI-based prostate bed contouring have been developed and this has resulted in an improvement in contouring concordance. However, IOV persists and strategies such as an education program, development of a contouring atlas and further refinement of the guidelines may lead to additional improvements.

SP-0995 An ESTRO-ACROP guideline on quality assurance and medical physics commissioning of online MRI-guided radiotherapy systems based on a consensus expert opinion

SP-0995 An ESTRO-ACROP guideline on quality assurance and medical physics commissioning of online MRI-guided radiotherapy systems based on a consensus expert opinion

Dosimetric Implications of Margin-Reduced MRI-Guided Stereotactic Body Radiotherapy to the Prostate Bed Following Radical Prostatectomy: Post-Hoc Analysis of a Phase II Study

<h3>Purpose/Objective(s)</h3> Due to the highly deformable and mobile nature of the target volume and adjacent organs at risk (OARs), generous planning target volume (PTV) margins have historically been used in the context of radiotherapy after radical prostatectomy. MRI-guided radiotherapy systems have improved on-board imaging capabilities and the ability to perform automatic beam holds based on pre-specified structures. Herein, we evaluate the dosimetric implications of interfraction variations in the clinical target volumes (CTV) and OARs in patients receiving margin-reduced MRI-guided stereotactic body radiotherapy (SBRT) to the prostate bed. <h3>Materials/Methods</h3> 31 consecutive patients received MRI-guided SBRT to the prostate bed (30 – 34 Gy in 5 fractions) without adaptive planning on a phase II study. The OAR volumes, CTV, and PTV (created using a 3 mm isotropic expansion of the CTV) were retrospectively contoured on on-board 0.35T MRIs obtained prior to each fraction (n=155). Geometric comparisons were made between the initial planning contours and the 5 daily contours for each patient using change in volume and Dice similarity coefficient (DSC) calculations. Coverage of the CTV and PTV was assessed (CTV V95% >93% and PTV V95% >90%), as were bladder and rectal dose constraints (Bladder Dmax <36.7 Gy, Bladder V32.5 Gy <35%, Rectum Dmax <36.7 Gy, Rectum V27.5 Gy <45%, Rectum 32.5 Gy <30%, and Rectal Wall V24 <50%). <h3>Results</h3> The median change in volume was -24.5% (interquartile range [IQR], -35.5 – -2.2%) for the bladder, 6.95% (IQR, -6.94 – 23.0%) for the rectum, -0.2% (IQR, -8.3 – 8.7%) for the rectal wall, 0.48% (IQR, -3.87 – 7.6%) for the CTV, and -0.48% (IQR, -5.12 – 6.53%) for the PTV. The median DSC was 0.79 (IQR, 0.73 – 0.84) for the bladder, 0.76 (IQR, 0.69 – 0.81) for the rectum, 0.35 (IQR, 0.28 – 0.44) for the rectal wall, 0.89 (IQR, 0.83 – 0.93) for the CTV, and 0.90 (IQR, 0.87 – 0.95) for the PTV. 145/155 fractions (93.5%) met the CTV V95% >93% target and 134/155 fractions (86.5%) met both the CTV V95% >93% and PTV V95% >90% targets. When calculated over 5 cumulative fractions, 29/31 patients (93.5%) met the CTV goal of V95% >93%. 62/155 fractions (40%) failed at least one OAR constraint. The mean number of fractions per patient that failed at least one OAR constraint was 2/5 (median, 1; range, 0 – 5). <h3>Conclusion</h3> With MRI-guidance, a reduction of the PTV margin to 3 mm isotropically allows for adequate CTV coverage in over 90% of patients without the need for adaptive planning. However, OAR constraints are not met in 40% of delivered fractions despite meeting all dose constraints at the time of treatment planning. Online dose prediction and, if indicated, adaptive radiotherapy can optimize this to allow for improved OAR protection and potentially allow for further reductions in the PTV expansion while maintaining adequate CTV coverage.

SPIO-enhanced 0.35T MRI-guided radiotherapy for liver malignancies: usefulness in tumor visualization.

The purpose of this study was to investigate the changes of tumor-to-liver signal ratio in a 0.35T MRI-guided radiotherapy system and to evaluate the usefulness and pitfalls of superparamagnetic iron oxide (SPIO) administration for visualization of liver tumors. Forty-two patients treated with MRI-guided stereotactic ablative radiotherapy (SABR) for liver tumors were included in this study. The tumor-to-liver signal ratios before and after SPIO administration were retrospectively assessed and compared on true fast imaging with steady-state precession (FISP). Before SPIO administration, liver tumors were either invisible or barely visible in 15 cases (36%), but all tumors became visible after SPIO administration. The mean values of tumor-to-liver signal ratio before and after SPIO administration were 0.939 ± 0.201 and 1.336 ± 0.300, respectively (mean ± standard deviation, p < 0.001). In six (14%) patients, liver tumors were visible on true FISP imaging before SPIO administration, but became invisible after administration. This study showed that liver tumors that are invisible on true FISP imaging can be made visible by administration of SPIO, and that MRI-guided SABR can be performed accurately. This is the first report to examine the usefulness of liver-specific contrast agent superparamagnetic iron oxides in 0.35T MRI-guided radiation therapy. Liver tumors that are invisible on true fast imaging with steady-state precession can be made visible by administration of superparamagnetic iron oxides.

Retour d’expérience clinique à propos des 200 premiers patients traités au MRIdian® à l’Institut Paoli-Calmettes

Several centers have recently been equipped with MRI-guided radiotherapy systems, including the Paoli-Calmettes Institute which was the first French center to start this activity. We report in this article our early experience. Data related to patients treated on the MRIdian® (Viewray®) were prospectively collected. Procedures concerning the implementation of the system and internal organizational issues were summarized. Between February 2019 and March 2020, 201 patients were treated: 40% of treatments were normofractionated (n=70) and 60% used hypofractionation (n=105). The reported monthly occupancy rate at one, six and twelve months was 30%, 62%, and 90%. The distribution of normofractionated treatments was dominated by prostatic (29%) and pancreatic (26%) cancers, followed by abdomino-pelvic irradiations for gynecological cancers (12%) or lymph node diseases (12%) and boosts for rectal or vaginal cancers (11%). Regarding treatments with moderate hypofractionation (dose by fraction between 3 and 5Gy), they corresponded mainly to integrated boost for abdomino-pelvic lymph nodes (38%), while the stereotaxic treatments primarily concerned hepatic lesions (15%), bones (30%). The MRIdian® was initially used widely in our service corresponding to a learning curve for MRI guidance. This new tool for image-guided radiotherapy helped us to secure our practice providing solutions for both inter and intra-fraction movements making it possible to reduce the additional margin in order to better protect the organs at risk. The main technical difference with conventional accelerators is the possibility of performing adaptive radiotherapy in real time, the start of which was more gradual.

Technical Note: Effects of rotating gantry on magnetic field and eddy currents in 0.35 T MRI-guided radiotherapy (MR-IGRT) system.

The purpose of this study was to identify the cause of severe image artifacts that occurred during gantry rotation in a 0.35 T MRI-Linac by comparing measurements of eddy currents, center frequency, and field inhomogeneities made with the gantry in motion and stationary. Gradient and B0 eddy currents were calculated from the free induction decays (FIDs) resulting from selective excitation at a temporal resolution of 200ms/measurement. B0 eddy currents were also calculated from FIDs acquired with nonselective excitation at a temporal resolution of 100ms/measurement. Center frequencies and B0 inhomogeneities were measured by acquiring FIDs with a repetition time (TR) of 290ms. Cartesian and radial 2D true fast imaging with steady-state precession (TrueFISP) pulse sequences used in real-time MRI-guided radiation therapy (MR-IGRT) were acquired. To assess artifact severity, the normalized root mean square error (nRMSE) was calculated between a reference MRI (static gantry) and MRIs acquired during gantry rotation for each serial acquisition. Image artifacts were qualitatively graded as nominal, minor, or severe. Measurements were conducted while the gantry was rotated through its entire range for both clockwise and counterclockwise. Measurements during gantry rotation were compared to measurements with a stationary gantry (every 30°). Severe image artifacts were observed 22-35% of the time while the gantry was rotating. Short time constant eddy currents were not affected by gantry rotation. The peak to peak center frequency and FWHM rose by factors of 13.2-14.5 and 1.1-1.6, respectively, for the rotating versus stationary gantry. The magnitude of the center frequency offset and field inhomogeneities depended on the direction of the gantry rotation. Image artifacts during gantry rotation were primarily caused by center frequency variations and field inhomogeneities. Therefore, dynamic B0 compensation techniques should be able to reduce artifacts during gantry rotation.

Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group

Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.

Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy.

MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.

Evaluating dose constraints for radiation induced liver damage following magnetic resonance image guided Stereotactic Body radiotherapy

This study reports dose corresponding to visible radiation induced liver damage following Stereotactic Body Radiation Therapy (SBRT) for liver metastasis, and the optimal time for follow up scans using post radiation imaging. Diagnostic magnetic resonance scans of nine patients treated with liver SBRT using a 0.35 T MRI-guided radiotherapy system were analyzed. The dice coefficients between the region of visible liver damage and the delivered dose were calculated. A median dose of 35 Gy correlated most closely with the visible radiation induced liver damage. We compared scans over two to nine months and observed maximal dice coefficients at two to five months post radiation. We have presented a new method for developing treatment planning guidelines for liver SBRT.

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.

Treatment effect prediction for sarcoma patients treated with preoperative radiotherapy using radiomics features from longitudinal diffusion-weighted MRIs

The objective of this study was to explore radiomics features from longitudinal diffusion-weighted MRIs (DWIs) for pathologic treatment effect prediction in patients with localized soft tissue sarcoma (STS) undergoing hypofractionated preoperative radiotherapy (RT). Thirty patients with localized STS treated with preoperative hypofractionated RT were recruited to this longitudinal imaging study. DWIs were acquired at three time points using a 0.35 T MRI-guided radiotherapy system. Treatment effect score (TES) was obtained from the post-surgery pathology as a surrogate of treatment outcome. Patients were divided into two groups based on TES. Response prediction was first performed using a support vector machine (SVM) with only mean apparent diffusion coefficient (ADC) or delta ADC to serve as the benchmark. Radiomics features were then extracted from tumor ADC maps at each of the three time points. Logistic regression and SVM were constructed to predict the TES group using features selected by univariate analysis and sequential forward selection. Classification performance using SVM with features from different time points and with or without delta radiomics were evaluated. Prediction performance using only mean ADC or delta ADC was poor (area under the curve (AUC) < 0.7). For the radiomics study using features from all time points and corresponding delta radiomics, SVM significantly outperformed logistic regression (AUC of 0.91 ± 0.05 v.s. 0.85 ± 0.06). Prediction AUC values using single or multiple time points without delta radiomics were all below 0.74. Including delta radiomics of mid- or post-treatment relative to the baseline drastically boosted the prediction. In this work, an SVM model was built to predict the TES using radiomics features from longitudinal DWI. Based on this study, we found that use of mean ADC, delta ADC, or radiomics features alone was not sufficient for response prediction, and including delta radiomics features of mid- or post-treatment relative to the baseline can optimize the prediction of TES, a pathologic and clinical endpoint.

Comparison of gross tumor volumes of pulmonary metastasis defined by CT and MRI in 0.345 T MRI-guided radiotherapy.

Objective:To assess the difference in gross tumor volumes (GTVs) defined by CT (GTV-CT) and by low magnetic field strength (0.345 T) MRI (GTV-MRI) in patients simulated for MRI-guided radiotherapy forlung metastasis.Methods:28 patients (148 lesions) who underwent CT and MRI simulation with the tri-60Co MRI-guided radiotherapy system (MRIdian, ViewRay) were included in this study. GTV-CT and GTV-MRI were compared using the paired t-test. The equivalence of variance between GTV-CT and GTV-MRI of small lesions (GTV-CT <1 ml) and large ones (GTV-CT >= 1 ml) was evaluated using F-test. The correlation between GTV-CT and GTV-MRI was evaluated by the correlation coefficient.Results:GTV-MRI was 120% larger than GTV-CT (p < 0.001) for small lesions, whereas GTV-MRI was 40% larger than GTV-CT (p < 0.001) for large lesions. In small lesions, the variation in GTV-MRI was significantly larger than that of GTV-CT (p < 0.001). There was no significant difference in the variation of GTV-MRI and GTV-CT in large lesions (p = 0.121). The correlation coefficient for small lesions was 0.93, whereas that for large lesions was 0.99, with large lesions having better correlation.Conclusions:GTV-MRI was larger than GTV-CT and the correlation between GTV-MRI and GTV-CT was better in large lesions. If the tumor volume is 1 ml or larger, the lesion can be accurately monitored even with a low magnetic field strength MRI.Advances in knowledge:This study is the first clinical report to evaluate the tolerability of MRI images in 0.345 T MRI-guided radiotherapy for lung metastasis. GTV contoured by MRI was larger than GTV by CT, and this tendency was more pronounced in small tumors of less than 1 ml.

A convolutional neural network for contouring metastatic lymph nodes on diffusion-weighted magnetic resonance images for assessment of radiotherapy response.

Retrieving quantitative parameters from magnetic resonance imaging (MRI), e.g. for early assessment of radiotherapy treatment response, necessitates contouring regions of interest, which is time-consuming and prone to errors. This becomes more pressing for daily imaging on MRI-guided radiotherapy systems. Therefore, we trained a deep convolutional neural network to automatically contour involved lymph nodes on diffusion-weighted (DW) MRI of head and neck cancer (HNC) patients receiving radiotherapy. DW-images from 48 HNC patients (18 induction-chemotherapy+chemoradiotherapy; 30 definitive chemoradiotherapy) with 68 involved lymph nodes were obtained on a diagnostic 1.5T MR-scanner prior to and 2-3 timepoints throughout treatment. A radiation oncologist delineated the lymph nodes on the b=50s/mm2 images. A 3D U-net was trained to contour involved lymph nodes. Its performance was evaluated in all 48 patients using 8-fold cross-validation and calculating the Dice similarity coefficient (DSC) and the absolute difference in median apparent diffusion coefficient (ΔADC) between the manual and generated contours. Additionally, the performance was evaluated in an independent dataset of three patients obtained on a 1.5T MR-Linac. In the definitive chemoradiotherapy patients (n=96 patients/lymphnodes/timepoints) the DSC was 0.87 (0.81-0.91) [median (1st-3rd quantiles)] and ΔADC was 1.9% (0.8-3.4%) and both remained stable throughout treatment. The network performed worse in the patients receiving induction-chemotherapy (n=65), with DSC=0.80 (0.71-0.87) and ΔADC=3.3% (1.6-8.0%). The network performed well on the MR-Linac data (n=8) with DSC=0.80 (0.75-0.82) and ΔADC=4.0% (0.6-9.1%). We established accurate automatic contouring of involved lymph nodes for HNC patients on diagnostic and MR-Linac DW-images.

A motion prediction confidence estimation framework for prediction-based radiotherapy gating.

Motion prediction can compensate for latency in image-guided radiotherapy and has been an active area of research. However, motion predictions are subject to error and variations. We have developed and evaluated a novel motion prediction confidence estimation framework to improve the efficacy and robustness of prediction-based radiotherapy gating decision-making. The specific scenario of adaptive gating in magnetic resonance imaging (MRI)-guided radiotherapy is studied as an example, but the method generalizes to other modalities and motion management setups. The proposed prediction confidence estimator is based on a generic training/testing paradigm and consists of a weighted combination of three components: the prediction model's goodness of fit, variation in the prediction using a leave-one-out process and the velocity of the tracked target. Roughly, these terms quantify respectively the consistency between prediction and the training data, the robustness of model inference, and the stability due to target speed. The weight parameters and the action level in triggering beam-off decision are optimized. The method is assessed and validated in 8 healthy volunteer and 13 patient studies using a 0.35T MRI-guided radiotherapy system predicting 0.25-0.33s ahead. The effect of the action level on the predicted gating decision accuracy, beam-on positive predictive value (PPV) and median distance between the predicted and ground-truth target centroids were evaluated. Statistical significance was evaluated using a paired t-test. The tradeoff between these performance metrics and gating duty cycle was assessed. Use of the confidence estimator threshold increased gating accuracy by up to 2.42%, increased PPV by up to 3.00%, and reduced the median centroid distance up to 0.28mm. The confidence estimator threshold on average increased gating accuracy to 96.5% (P=2.08×10-4 ), increased PPV to 96.7% (P=1.46×10-5 ), reduced the median centroid distance to 0.54mm (P=1.71×10-5 ) at the cost of reducing the gating duty cycle by 14.3% to 48.5%. Hyperparameter tuning revealed that contrary to intuition, the velocity term offered only minimal performance improvement in some cases but also introduced potential stability issues. The combination of goodness of fit and leave-one-out prediction variation provided the most effective confidence estimator, yielding universally better performance in gating decisions. Confidence estimation utilizing prediction model fitness criterion and validation principles can complement prediction methods to guide MRI-guided radiotherapy gating. Results from both volunteer and patient studies showed improved gating quality.

An image regression motion prediction technique for MRI-guided radiotherapy evaluated in single-plane cine imaging.

To develop and evaluate a novel motion prediction method for magnetic resonance image (MRI)-guided radiotherapy applications. This method, which we deem "image regression," predicts future tissue motion based on a weighted combination of previously observed motion states. Motion predictions are derived from a sliding window of recent motion states which are defined by a temporal sequence of images. A key advantage of this method compared to other motion prediction methods is that its computational complexity scales weekly with the number of spatial points predicted. Applications of gating latency reduction and improvement in deformable registration-based target tracking are demonstrated. The image regression (IR) motion prediction method was developed and evaluated using 26.9h of real-time imaging acquired from eight healthy volunteers and 13 patients using a 0.35T MRI-guided radiotherapy system. Motion predictions were performed 0.25-0.33s into the future using a weighted sum of previously observed motion states with image similarity-derived weights. The set of previously observed motion states were continuously updated to incorporate the changes in breathing patterns. The accuracy of the predicted radiotherapy gating decision, beam-on positive predictive value (PPV), and predicted vs ground-truth target centroid position errors are reported. The IR technique was compared against no prediction, linear extrapolation, and an established autoregressive linear prediction algorithm. The usage of IR to initialize the deformable registration and enhance the target tracking was demonstrated in the healthy volunteer studies. Deformable registration with IR initialization was compared to the initialization performed by current clinical software: no initialization, previous image registration initialization and linear motion extrapolation initialization. The average IR-predicted radiation beam gating decision accuracy was 95.8%, with a PPV of 95.7%, and median and 95th percentile centroid position errors of 0.63 and 2.08mm, respectively. Compared to the autoregressive linear prediction method, gating accuracy was 1.15% greater, PPV was 1.61% greater, and median and 95th percentile centroid distances were 0.21 and 0.23mm smaller. The IR-initialized registration on average converged within 0.50mm of the ground-truth position in fewer than 10 iterations whereas the next best initialization method required more than 25 iterations. Image regression motion prediction has the potential to reduce the gating latencies and improve the speed and accuracy of deformable registration-based target tracking in MRI-guided radiotherapy.

ReconSocket: a low-latency raw data streaming interface for real-time MRI-guided radiotherapy

With the recent advent of hybrid MRI-guided radiotherapy systems, continuous intra-fraction MR imaging for motion monitoring has become feasible. The ability to perform real-time custom image reconstructions is however often lacking. In this work we present a low-latency streaming solution, ReconSocket, which provides a real-time stream of k-space data from the magnetic resonance imaging (MRI) to custom reconstruction servers.We determined the performance of the data streaming by measuring the streaming latency (i.e. non-zero time delay due to data transfer and processing) and jitter (i.e. deviations from periodicity) using an ultra-fast 1D MRI acquisition of a moving phantom. Simultaneously, its position was recorded with near-zero time delay. The feasibility of low-latency custom reconstructions was tested by measuring the imaging latency (i.e. time delay between physical change and appearance of that change on the image) for several non-Cartesian 2D and 3D acquisitions using an in-house implemented reconstruction server.The measured streaming latency of the ReconSocket interface was ms. 98% of the incoming data packets arrived within a jitter range of 367 s. This shows that the ReconSocket interface can provide reliable real-time access to MRI data, acquired during the course of a MRI-guided radiotherapy fraction.The total imaging latency was measured to be 221 ms (2D) and 3889 ms (3D) for exemplary acquisitions, using the custom image reconstruction server. These imaging latencies are approximately equal to half of the temporal footprint (Tacq/2) of the respective 2D and 3D golden-angle radial sequences. For radial sequences, it was previously showed that Tacq/2 is the expected contribution of only the data acquisition to the total imaging latency. Indeed, the contribution of the non-Cartesian reconstruction to the total imaging latency was minor (<10%): 21 ms for 2D, 300 ms for 3D, indicating that the acquisition, i.e. the physical encoding of the image itself is the major contributor to the total imaging latency.

MRI-Guided SABR of Spinal Metastases: A Safety and Quality Comparison of Co-60 and Linac Treatments

MRI-guided radiotherapy systems visualize the spinal cord and cauda equina for spine SABR (stereotactic ablative radiotherapy) setup and tracking of motion during treatment. However, concerns have been raised regarding the dosimetric limitations of the first generation of Co-60 MRI-guided systems. In prior work, we demonstrated excellent visualization of spinal structures and tolerance for Co-60 MRI-guided spine treatments. In this work we demonstrate dosimetric improvements for Linac based MRI guided SABR based on recalculation of the original Co-60 plans. Nine spinal metastases were treated with Co-60 MRI-guided radiotherapy at our institution from May 2016 to January 2017. Seven received a single 16 Gy dose and two received 30 and 24Gy in three fractions. Coverage was at least 80% (acceptable deviation per RTOG 0631, prefer >90%) in all cases. Contours were based on the International Spine Radiosurgery Consortium Consensus. Objectives are based on RTOG 0631 protocol. OAR objectives for single fraction are: spinal cord V10Gy<0.35 cc, V14Gy<0.03 cc, partial cord V10Gy<10% and cauda equina V16Gy<0.03cc. Dose spillage objectives for single fraction are volume of 105% isodose out of PTV <3 cc (V105% out of PTV <3cc), V115% out of PTV 0.0 cc, and conformity index < 1.5. OAR objectives for three fractions are based on NRG BR001 protocol: spinal cord V22.5Gy<0.03cc, V13Gy<1.2cc, cauda equina V25.5Gy<0.03cc and V21.9Gy<5cc. Dose spillage objectives were the same as the single fraction cases. Linac-based MRI guided SABR plans were generated for the Co-60 MRI guided SABR cases using vendor supplied software. Co-60. Organ at risk (OAR) objectives were met in all cases. However, dose spillage for Co-60 plans would often be considered unacceptable by RTOG 0631 protocol: median V105% out of PTV: 22.8 cc (11.4 cc – 26.9 cc) and median V115% out of PTV: 0.3 cc (0.0 cc – 8.2 cc). Treatment was delivered considering that this dose spillage was mostly into para-spinal soft tissues and not into OARs. No adverse effects have been observed, and all cases had excellent visualization of spinal anatomy with real-time patient motion tracking and gating. Linac. All OAR objectives were met in all cases. Dose spillage for Linac plans were either per RTOG 0631 protocol or acceptable deviation in all cases. Median V105% out of PTV: 1.4cc (0.18 cc – 3.0 cc) with V115% out of PTV 0.0cc. Co-60 MRI-guided SABR achieves an adequate target coverage and OAR sparing for spinal osseous metastases. Treatments are safe, well tolerated, and excellent setup and real-time guidance of treatment are observed. However, dose spillage guidelines were not achieved in many Co-60 delivered cases due to MLC width and cobalt penumbra. However, dose spillage guidelines can be met with newer generation Linac-MRI systems. MRI guidance can improve safety and dose escalation for spine SABR given clear visualization of the cord and other structures during treatment.

Two-dimensional EPID dosimetry for an MR-linac: Proof of concept.

At our institute, in vivo patient dose distributions are reconstructed for all treatments delivered using conventional linacs from electronic portal imaging device (EPID) transit images acquired during treatment using a simple back-projection model. Currently, the clinical implementation of MRI-guided radiotherapy systems, which aims for online and real-time adaptation of the treatment plan, is progressing. In our department, the MR-linac (Unity, Elekta AB, Stockholm, Sweden) is now in clinical use. The aim of this work is to demonstrate the feasibility of two-dimensional (2D) EPID dosimetric verification for the magnetic resonance (MR)-linac by comparing back-projected EPID doses to ionization chamber (IC) array dose distributions. Our conventional back-projection algorithm was adapted for the MR-linac. The most important changes involve modeling of the attenuation by and scatter from the cryostat. The commissioning process involved the acquisition of square field EPID measurements using various phantom setups (varying SSD, phantom thickness, and field size). Commissioning models were created for gantry 0°, 90°, and 180° and verified by comparing EPID-reconstructed 2D dose distributions to measurements made with the OCTAVIUS 1500 IC array (PTW, Freiburg, Germany) for two prostate and one rectum IMRT plans (25 beams total). The average of the γ parameters (y-mean and y-pass rate) and the dose difference at a reference point were reported. Due to their construction, the attenuation of couch, bridge, and cryostat shows a much stronger dependence on gantry angle in the MR-linac compared to conventional linacs. We present a method to correct for these effects. This method is validated by dose reconstruction of the 25 intensity-modulated radiation therapy beams recorded at a certain gantry angle using the model of another gantry angle, combined with the correction method. For dose verification performed at a gantry angle identical to the commissioned model, the average y-mean and y-pass rate values (3% global dose, 2mm, 10% isodose) were 0.37±0.07 and 98.1, 95% CI [98.1±2.4], respectively. The average dose difference at the reference point was -0.5%±1.8%. Verification at gantry angles different from the commissioned model (i.e., using the gantry angle dependent correction) reported 0.39±0.08 and 97.6, 95% CI [96.9, 98.3] average y-mean and y-pass rate values. The average dose difference at the reference point was -0.1%±1.8%. The EPID dosimetry back-projection model was successfully adapted for the MR-linac at gantry 0°, 90°, and 180°, accounting for the presence of the MRI housing between phantom (or patient) and the EPID. A method to account for the gantry angle dependence was also tested reporting similar results.

On-line Adaptive Radiotherapy Using MRI-Guided Technique

In our institution, we installed MRI-guided radiotherapy system (MRIdian, ViewRay Inc.), allowing to perform on-line adaptive radiotherapy (ART). The MRIdian has three 60Co sources with 120 degrees apart, equipped with MRI system using a static magnetic field of 0.35 T. The tumor can be monitored and identified in real-time Cine-MRI during treatments, and gated-radiotherapy is possible based on the boundaries. On-line ART can provide the optimum delivery where high dose coverages to the tumor and sparing dose to health organs can be achieved. However, patient specific QA in on-line ART has a limitation of activities, because patients stay in the couth while planning. In this report, we summarized the commissioning of the MRIdian, and the patient specific QA established in on-line ART was described.

Multislice motion modeling for MRI-guided radiotherapy gating.

On-board magnetic resonance imaging (MRI) greatly enhances real-time target tracking capability during radiotherapy treatments. However, multislice and volumetric MRI techniques are frame rate limited and introduce unacceptable latency between the target moving out of position and the beam being turned off. We present a technique to estimate continuous volumetric tissue motion using motion models built from a repeated acquisition of a stack of MR slices. Applications including multislice target visualization and out-of-slice motion estimation during MRI-guided radiotherapy are demonstrated. Eight healthy volunteer studies were performed using a 0.35T MRI-guided radiotherapy system. Images were acquired at three frames per second in an interleaved fashion across ten adjacent sagittal slice positions covering 4.5cm using a balanced steady-state-free precession sequence. A previously published five-dimensional (5D) linear motion model used for MRI-guided radiotherapy gating was extended to include multiple slices. This model utilizes an external respiratory bellows signal recorded during imaging to simultaneously estimate motion across all imaged slices. For comparison to an image-based approach, the manifold learning technique local linear embedding (LLE) was used to derive a respiratory surrogate for motion modeling. Manifolds for every slice were aligned during LLE in a group-wise fashion, enabling motion estimation outside the current imaged slice using a motion model, a process which we denote as mSGA. Additionally, a method is developed to evaluate out-of-slice motion estimates. The multislice motion model was evaluated in a single slice with each newly acquired image using a leave-one-out approach. Model-generated gating decision accuracy and beam-on positive predictive value (PPV) are reported along with the median and 95th percentile distance between model and ground truth target centroids. The average model gating decision accuracy and PPV across all volunteer studies was 93.7% and 92.8% using the 5D model, and 96.8% and 96.1% using the mSGA model, respectively. The median and 95th percentile distance between model and ground truth target centroids was 0.91 and 2.90mm, respectively, using the 5D model and 0.58 and 1.49mm using the mSGA model, averaged over all eight subjects. The mSGA motion model provided a statistically significant improvement across all evaluation metrics compared to the external surrogate-based 5D model. The proposed techniques for out-of-slice target motion estimation demonstrated accuracy likely sufficient for clinical use. Results indicate the mSGA model may provide higher accuracy, however, the external surrogate-based model allows for unbiased invivo accuracy evaluation.