Dosimetric and geometric end-to-end accuracy of a magnetic resonance guided linear accelerator

Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy

Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays available for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites. The main challenge in achieving a widespread clinical implementation of sCT lies in the absence of consensus on sCT commissioning and quality assurance (QA), resulting in variation of sCT approaches across different hospitals. To address this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 to discuss the integration of sCT solutions into clinics and report the process and its outcomes. This position paper focuses on aspects of sCT development and commissioning, outlining key elements crucial for the safe implementation of an MRI-only RT workflow.

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects

MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.

Accumulated dose implications from systematic dose-rate transients in gated treatments with Viewray MRIdian accelerators

The combination of magnetic resonance (MR) imaging and linear accelerators (linacs) into MR-Linacs enables continuous MR imaging and advanced gated treatments of patients. Previously, a dose-rate transient (∼8% reduced dose rate during the initial 0.5 s of each beam) was identified for a Viewray MRIdian MR-Linac (Klavsenet al2022Radiation Measurement106759). Here, the dose-rate transient is studied in more detail at four linacs of the same type at different hospitals. The implications of dose-rate transients were examined for gated treatments. The dose-rate transients were investigated using dose-per pulse measurements with organic plastic scintillators in three experiments: (i) A gated treatment with the scintillator placed in a moving target in a dynamic phantom, (ii) a gated treatment with the same dynamic conditions but with the scintillator placed in a stationary target, and (iii) measurements in a water-equivalent material to examine beam quality deviations at a dose-per-pulse basis. Gated treatments (i) compared with non-gated treatments with a static target in the same setup showed a broadening of accumulated dose profiles due to motion (dose smearing). The linac with the largest dose-rate transient had a reduced accumulated dose of up to (3.1 ± 0.65) % in the center of the PTV due to the combined dose smearing and dose-rate transient effect. Dose-rate transients were found to vary between different machines. Two MR-Linacs showed initial dose-rate transients that could not be identified from conventional linearity tests. The source of the transients includes an initial change in photon fluence rate and an initial change in x-ray beam quality. For gated treatments, this caused a reduction of more than 1% dose delivered at the central part of the beam for the studied, cyclic-motion treatment plan. Quality assurance of this effect should be considered when gated treatment with the Viewray MRIdian is implemented clinically.

Real-time radial reconstruction with domain transform manifold learning for MRI-guided radiotherapy

BACKGROUND

MRI-guidance techniques that dynamically adapt radiation beams to follow tumor motion in real time will lead to more accurate cancer treatments and reduced collateral healthy tissue damage. The gold-standard for reconstruction of undersampled MR data is compressed sensing (CS) which is computationally slow and limits the rate that images can be available for real-time adaptation.

PURPOSE

Once trained, neural networks can be used to accurately reconstruct raw MRI data with minimal latency. Here, we test the suitability of deep-learning-based image reconstruction for real-time tracking applications on MRI-Linacs.

METHODS

We use automated transform by manifold approximation (AUTOMAP), a generalized framework that maps raw MR signal to the target image domain, to rapidly reconstruct images from undersampled radial k-space data. The AUTOMAP neural network was trained to reconstruct images from a golden-angle radial acquisition, a benchmark for motion-sensitive imaging, on lung cancer patient data and generic images from ImageNet. Model training was subsequently augmented with motion-encoded k-space data derived from videos in the YouTube-8M dataset to encourage motion robust reconstruction.

RESULTS

AUTOMAP models fine-tuned on retrospectively acquired lung cancer patient data reconstructed radial k-space with equivalent accuracy to CS but with much shorter processing times. Validation of motion-trained models with a virtual dynamic lung tumor phantom showed that the generalized motion properties learned from YouTube lead to improved target tracking accuracy.

CONCLUSION

AUTOMAP can achieve real-time, accurate reconstruction of radial data. These findings imply that neural-network-based reconstruction is potentially superior to alternative approaches for real-time image guidance applications.

Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations

Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.

Evaluation of an anthropomorphic ion chamber and 3D gel dosimetry head phantom at a 0.35 T MR-linac using separate 1.5 T MR-scanners for gel readout

PURPOSE

To date, no universally accepted technique for the evaluation of the overall dosimetric performance of hybrid integrated magnetic resonance imaging (MR) - linear accelerators (linacs) is available. We report on the suitability and reliability of a novel phantom with modular inserts for combined polymer gel (PG) and ionisation chamber (IC) measurements at a 0.35 T MR-linac.

METHODS

Three 3D-printed, modular head phantoms, based on real patient anatomy, were used for repeated (2 times) PG irradiations of cranial treatment plans on a 0.35 T MR-linac. The PG readout was performed on two 1.5 T diagnostic MR-scanners to reduce scanning time. The PG dose volumes were normalised to the IC dose (normalised dose N1) and to the median planning target volume dose (normalised dose N2). Linearity of the PG dose response was validated and dose profiles, centres of mass (COM) of the 95% isodoses and dose volume histograms (DVH) were compared between planned and measured dose distributions and a 3D gamma analysis was performed.

RESULTS

Dose linearity of the PG was good (R²> 0.99 for all linear fit functions). High agreement was found between planned and measured dose volumes in the dose profiles and DVHs. The largest dose deviation was found in the intermediate dose region (mean dose deviation 0.2Gy; 5.6%). A mean COM offset of 1.2mm indicated high spatial accuracy. Mean 3D gamma passing rates (2%, 2mm) of 83.3% for N1 and 91.6% for N2 dose distributions were determined. When comparing repeated PG measurements to each other, a mean gamma passing rate of 95.7% was found.

CONCLUSION

The new modular phantom was found practical for use at a 0.35 T MR-linac. In contrast to the high dose region, larger mean deviations were found in the mid dose range. The PG measurements showed high reproducibility. The MR-linac performed well in a non-adaptive setting in terms of spatial and dosimetric accuracy.

Quality assurance for on-table adaptive magnetic resonance guided radiation therapy: A software tool to complement secondary dose calculation and failure modes discovered in clinical routine

Online adaption of treatment plans on a magnetic resonance (MR)‐Linac enables the daily creation of new (adapted) treatment plans using current anatomical information of the patient as seen on MR images. Plan quality assurance (QA) relies on a secondary dose calculation (SDC) that is required because a pretreatment measurement is impossible during the adaptive workflow. However, failure mode and effect analysis of the adaptive planning process shows a large number of error sources, and not all of them are covered by SDC. As the complex multidisciplinary adaption process takes place under time pressure, additional software solutions for pretreatment per‐fraction QA need to be used. It is essential to double‐check SDC input to ensure a safe treatment delivery. Here, we present an automated treatment plan check tool for adaptive radiotherapy (APART) at a 0.35 T MR‐Linac. It is designed to complement the manufacturer‐provided adaptive QA tool comprising SDC. Checks performed by APART include contour analysis, electron density map examinations, and fluence modulation complexity controls. For nine of 362 adapted fractions (2.5%), irregularities regarding missing slices in target volumes and organs at risks as well as in margin expansion of target volumes have been found. This demonstrates that mistakes occur and can be detected by additional QA measures, especially contour analysis. Therefore, it is recommended to implement further QA tools additional to what the manufacturer provides to facilitate an informed decision about the quality of the treatment plan.

End-to-end test for fractionated online adaptive MR-guided radiotherapy using a deformable anthropomorphic pelvis phantom

Objective.In MR-guided radiotherapy (MRgRT) for prostate cancer treatments inter-fractional anatomy changes such as bladder and rectum fillings may be corrected by an online adaption of the treatment plan. To clinically implement such complex treatment procedures, however, specific end-to-end tests are required that are able to validate the overall accuracy of all treatment steps from pre-treatment imaging to dose delivery.Approach.In this study, an end-to-end test of a fractionated and online adapted MRgRT prostate irradiation was performed using the so-called ADAM-PETer phantom. The phantom was adapted to perform 3D polymer gel (PG) dosimetry in the prostate and rectum. Furthermore, thermoluminescence detectors (TLDs) were placed at the center and on the surface of the prostate for additional dose measurements as well as for an external dose renormalization of the PG. For the end-to-end test, a total of five online adapted irradiations were applied in sequence with different bladder and rectum fillings, respectively.Main results.A good agreement of measured and planned dose was found represented by highγ-index passing rates (3%/3mmcriterion) of the PG evaluation of98.9%in the prostate and93.7%in the rectum. TLDs used for PG renormalization at the center of the prostate showed a deviation of-2.3%.Significance.The presented end-to-end test, which allows for 3D dose verification in the prostate and rectum, demonstrates the feasibility and accuracy of fractionated and online-adapted prostate irradiations in presence of inter-fractional anatomy changes. Such tests are of high clinical importance for the commissioning of new image-guided treatment procedures such as online adaptive MRgRT.

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

In the past few years, radiotherapy (RT) has experienced a major technological innovation with the development of hybrid machines combining magnetic resonance (MR) imaging and linear accelerators. This new technology for MR-guided cancer treatment has the potential to revolutionize the field of adaptive RT due to the opportunity to provide high-resolution, real-time MR imaging before and during treatment application. However, from a technical point of view, several challenges remain which need to be tackled to ensure safe and robust real-time adaptive MR-guided RT delivery. In this manuscript, several technical challenges to MR-guided RT are discussed. Starting with magnetic field strength tradeoffs, the potential and limitations for purely MR-based RT workflows are discussed. Furthermore, the current status of real-time 3D MR imaging and its potential for real-time RT are summarized. Finally, the potential of quantitative MR imaging for future biological RT adaptation is highlighted.

An end-to-end assessment on the accuracy of adaptive radiotherapy in an MR-linac

PURPOSE

To develop and demonstrate an end-to-end assessment procedure for adaptive radiotherapy (ART) within an MR-guided system.

METHODS AND MATERIALS

A 3D printed pelvic phantom was designed and constructed for use in this study. The phantom was put through the complete radiotherapy treatment chain, with planned internal changes made to model prostate translations and shape changes, allowing an investigation into three ART techniques commonly used. Absolute dosimetry measurements were made within the phantom using both gafchromic film and alanine. Comparisons between treatment planning system (TPS) calculations and measured dose values were made using the gamma evaluation with criteria of 3 mm/3% and 2 mm/2%.

RESULTS

Gamma analysis evaluations for each type of treatment plan adaptation investigated showed a very high agreement with pass rates for each experiment ranging from 98.10% to 99.70% and 92.60% to 97.55%, for criteria of 3%/3 mm and 2%/2 mm respectively. These pass rates were consistent for both shape and position changes. Alanine measurements further supported the results, showing an average difference of 1.98% from the TPS.

CONCLUSION

The end-to-end assessment procedure provided demanding challenges for treatment plan adaptations to demonstrate the capabilities and achieved high consistency in all findings.

Experimental evaluation of four-dimensional Magnetic Resonance Imaging for radiotherapy planning of lung cancer

Radiotherapy planning for lung cancer typically requires both 3D and 4D Computed Tomography (CT) to account for respiratory related movement. 4D Magnetic Resonance Imaging (MRI) with self-navigation offers a potential alternative with greater reliability in patients with irregular breathing patterns and improved soft tissue contrast. In this study 4D-CT and a 4D-MRI Radial Volumetric Interpolated Breath-hold Examination (VIBE) sequence was evaluated with a 4D phantom and 13 patient respiratory patterns, simulating tumour motion. Quantification of motion related tumour displacement in 4D-MRI and 4D-CT found no statistically significant difference in mean motion range. The results demonstrated the potential viability of 4D-MRI for lung cancer treatment planning.