Real-time auto-adaptive margin generation for MLC-tracked radiotherapy.

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing [Formula: see text] in the underdosed area about [Formula: see text] and [Formula: see text], respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors

Motion compensation for MRI-guided radiotherapy

Radiotherapy aims to deliver a lethal radiation dose to cancer cells immersed in the body using a high energetic photon beam. Due to physiologic motion of the human anatomy (e.g. caused by filling of internal organs or breathing), the target volume is under permanent motion during irradiation, diluting the applied dose into regions around the target volume. Traditionally, the target volume is expanded about margins encompassing the geometric uncertainty in order to retain the target dose. As a result, however, unwanted dose to nearby organs at risk is increased significantly, which effectively limits the use of clinically promising treatment techniques such as hypo-fractionated therapies to treat cancer more effectively and economically. This thesis develops motion compensation techniques for radiotherapy using MR-imaging integrated into a novel treatment device, the MR-linac, which allows to resolve the current anatomy state during ongoing radiation with diagnostic MR-image quality. As a result the geometric uncertainty of the target positions is reduced which enables new, more effective radiotherapy paradigms. In the first chapters of this thesis, integrated MRI is employed to automatically register volumetric changes in the human anatomy. It is described how significant acceleration of this registration process can be achieved by spatially undersampling volumetric MRI-acquisitions. The calculations showed, that the MR-imaging time speed could theoretically be increased by 300% with only minor losses in registration quality. The on-line volumetric imaging feature was subsequently used to observe the anatomic motion during simulated delivery of a novel treatment scheme for the therapy of renal cell carcinoma. Significant motion could be revealed, eventually causing target dose variations of more than 10% and significant migration of the target dose into the adjacent organs at risk. Used on-line, new intra-fraction options, such as replanning or emergency beam stop could be implemented using the constantly refreshed calculation of dose delivered to the patient. The beam shaping unit (multileaf collimator, MLC) integrated in the MR-linac features real-time control of the geometry of the treatment beam. Potentially, optimal target conformity can be achieved by steering the beam in synchrony with the moving target. In order to assess the expected performance of such target tracking on an MR-linac, the Elekta Agility 160 MLC, was assessed using an experimental imaging pipeline. Low mechanic latencies of under 20ms could be shown, which enables real-time MLC tracking with minimal geometric errors. In order to compensate for residual tracking errors caused by latencies of the mechanical part and software processing, a novel tracking margin generator was designed, which aimed to retain target dose coverage. In experiments, the margin generator could show significant reductions of underdosages caused by MLC tracking errors. Considering the remarkable scalability of the integrated imaging and beam shaping options offered by the MR-linac, a multitude of novel treatment techniques become available. As described in this thesis, rapid target tracking, dose reconstruction and combinations thereof can be implemented using theon-board MR-imaging. In order to apply the described techniques to patients, stringent quality assessment and autonomous feedback processes have to be implemented for the clinical practice

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 (T acq/2) of the respective 2D and 3D golden-angle radial sequences. For radial sequences, it was previously showed that T acq/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

Technical note: MLC racking performance on the Elekta unity MRI-linac : MLC-tracking performance on the Elekta unity MRI-linac

Recently, multileaf collimator (MLC)-tracking has been technically and clinically demonstrated showing promising improvements of radiotherapy of mobile sites. Furthermore, magnetic resonance imaging (MRI)-guided treatments have shown to provide superior targetting performance due to on-line soft-tissue imaging. Hitherto, the combination of MLC-tracking and MRI has not been investigated using clinically released hardware. In this note we aim to describe the technical feasibilty of such a combination on a clinically operating MRI-linac. The MLC-tracking system is characterized by quantifying the latencies and geometric errors produced by the system. In order to reach optimization recommendations, the tracking system was first characterized using a quasi-ideal position sensor, isolating the performance of the MLC only. Subsequently, the analysis was repeated using real-time MRI as the positioning source for the MLC. For the isolated MLC, we found latencies of 20.67 ms and minimal overshooting behaviour. The latencies for MRI-guidance were 347.45 ms at 4 Hz imaging and 204 ms at 8 Hz. We showed that MLC-tracking on the Elekta Unity using integrated MRI is technically supported and feasible. The isolated analysis of the MLC demonstrated the negligible contribution of the MLC in MRI-guided tracking. The latency and geometric errors caused by the sampling properties of MRI exceed the MLC-related errors by several factors. Most gain for real-time MRI-based adaptive radiotherapy can therefore be realized by optimizing and accelerating the MRI acquisition process

On the suitability of Elekta's Agility 160 MLC for tracked radiation delivery : closed-loop machine performance

For motion adaptive radiotherapy, dynamic multileaf collimator tracking can be employed to reduce treatment margins by steering the beam according to the organ motion. The Elekta Agility 160 MLC has hitherto not been evaluated for its tracking suitability. Both dosimetric performance and latency are key figures and need to be assessed generically, independent of the used motion sensor. In this paper, we propose the use of harmonic functions directly fed to the MLC to determine its latency during continuous motion. Furthermore, a control variable is extracted from a camera system and fed to the MLC. Using this setup, film dosimetry and subsequent. statistics are performed, evaluating the response when tracking (MRI)-based physiologic motion in a closed-loop. The delay attributed to the MLC itself was shown to be a minor contributor to the overall feedback chain as compared to the impact of imaging components such as MRI sequences. Delay showed a linear phase behaviour of the MLC employed in continuously dynamic applications, which enables a general MLC-characterization. Using the exemplary feedback chain, dosimetry showed a vast increase in pass rate employing. statistics. In this early stage, the tracking performance of the Agility using the test bench yielded promising results, making the technique eligible for translation to tracking using clinical imaging modalities

On-line 3D motion estimation using low resolution MRI

Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible. MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information. In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated. Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with (2.5 mm)3 voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. (5 mm)3. In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality

On-line 3D motion estimation using low resolution MRI

Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible. MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information. In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated. Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with (2.5 mm)3 voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. (5 mm)3. In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality

On-line MR imaging for dose validation of abdominal radiotherapy

For quality assurance and adaptive radiotherapy, validation of the actual delivered dose is crucial.Intrafractional anatomy changes cannot be captured satisfactorily during treatment with hitherto available imaging modalitites. Consequently, dose calculations are based on the assumption of static anatomy throughout the treatment. However, intra- and interfraction anatomy is dynamic and changes can be significant.In this paper, we investigate the use of an MR-linac as a dose tracking modality for the validation of treatments in abdominal targets where both respiratory and long-term peristaltic and drift motion occur.The on-line MR imaging capability of the modality provides the means to perform respiratory gating of both delivery and acquisition yielding a model-free respiratory motion management under free breathing conditions.In parallel to the treatment, the volumetric patient anatomy was captured and used to calculate the applied dose. Subsequently, the individual doses were warped back to the planning grid to obtain the actual dose accumulated over the entire treatment duration. Ultimately, the planned dose was validated by comparison with the accumulated dose.Representative for a site subject to breathing modulation, two kidney cases (25 Gy target dose) demonstrated the working principle on volunteer data and simulated delivery. The proposed workflow successfully showed its ability to track local dosimetric changes. Integration of the on-line anatomy information could reveal local dose variations  -2.3-1.5 Gy in the target volume of a volunteer dataset. In the adjacent organs at risk, high local dose errors ranging from  -2.5 to 1.9 Gy could be traced back

Characterization of imaging latency for real-time MRI-guided radiotherapy

Hybrid MR-linac systems can use fast dynamic MR sequences for tumor tracking and adapt the radiation treatment in real-time. For this the imaging latency must be as short as possible. This work describes how different acquisition parameters influence this latency. First, the latency was measured for Cartesian readouts with phase encode orderings linear, reverse-linear, and high-low. Second, the latency was measured for radial readouts with linear and golden angle profile orderings. To reduce the latency, a spatio-temporal (k-t) filter that suppresses the k-space center of earlier acquired spokes was implemented for the golden angle sequence. For Cartesian readouts a high-low ordering achieved a three times lower latency compared to a linear ordering with our sampling parameters. For radial readouts the filter was able to reduce the acquisition latency from half the acquisition time to a quarter of the acquisition time. The filter did not compromise the signal-to-noise ratio and the artifact power