Online adaptive MR-guided radiotherapy for rectal cancer; feasibility of the workflow on a 1.5T MR-linac: clinical implementation and initial experience.

BACKGROUND AND PURPOSE: Daily online adaptation of the clinical target volume (CTV) using MR-guided radiotherapy enables margin reduction of the planning target volume (PTV). This study describes the implementation and initial experience of MR-guided radiotherapy on the 1.5T MR-linac and evaluates treatment time, patient compliance, and target coverage, including an initial assessment of margin reduction. MATERIALS AND METHODS: Patients were treated on a 1.5T MR-linac (7MV, FFF). At each fraction a 3D T2 weighted (T2w) MR-sequence was acquired on which the CTV was adapted after a deformable registration of the contours from the pre-planning CT scan. Based on the new contours a full online replanning was done after which a new 3D T2w MR-sequence was acquired for position verification. A 5 field Intensity Modulated Radiotherapy (IMRT) plan was delivered. RESULTS: Forty-three patients with rectal cancer were treated with 25 Gy in 5 fractions of which 18 with reduced margins. In total, 204 of 215 fractions were delivered on the MR-linac all of which obtained a clinically acceptable treatment plan. Median in-room time per fraction was 48 min (interquartile range 8). No fractions were canceled or interrupted because of patient intolerance. CTV coverage after margin reduction was good on all post-treatment scans but one due to passing gas. CONCLUSION: MR-guided radiotherapy using daily full online recontouring and replanning on a 1.5T MR-linac for rectal cancer is feasible and currently takes about 48 min per fraction.

Technical feasibility of magnetic resonance fingerprinting on a 1.5T MRI-linac.

Hybrid MRI-linac (MRL) systems enable daily multiparametric quantitative MRI to assess tumor response to radiotherapy. Magnetic resonance fingerprinting (MRF) may provide time efficient means of rapid multiparametric quantitative MRI. The accuracy of MRF, however, relies on adequate control over system imperfections, such as eddy currents and [Formula: see text], which are different and not as well established on MRL systems compared to diagnostic systems. In this study we investigate the technical feasibility of gradient spoiled 2D MRF on a 1.5T MRL. We show with phantom experiments that the MRL generates reliable MRF signals that are temporally stable during the day and have good agreement with spin-echo reference measurements. Subsequent in-vivo MRF scans in healthy volunteers and a patient with a colorectal liver metastasis showed good image quality, where the quantitative values of selected organs corresponded with the values reported in literature. Therefore we conclude that gradient spoiled 2D MRF is feasible on a 1.5T MRL with similar performance as on a diagnostic system. The precision and accuracy of the parametric maps are sufficient for further investigation of the clinical utility of MRF for online quantitatively MRI-guided radiotherapy.

The noise navigator: a surrogate for respiratory-correlated 4D-MRI for motion characterization in radiotherapy.

Respiratory-correlated 4D-MRI can characterize respiratory-induced motion of tumors and organs-at-risk for radiotherapy treatment planning and is a necessity for image guidance of moving tumors treated on an MRI-linac. Essential for 4D-MRI generation is a robust respiratory surrogate signal. We investigated the feasibility of the noise navigator as respiratory surrogate signal for 4D-MRI generation. The noise navigator is based on the respiratory-induced modulation of the thermal noise variance measured by the receive coils during MR acquisition and thus is inherently present and synchronized with MRI data acquisition. Additionally, the noise navigator can be combined with any rectilinear readout strategy (e.g. radial and cartesian) and is independent of MR image contrast and imaging orientation. For radiotherapy applications, the noise navigator provides a robust respiratory signal for patients scanned with an elevated coil setup. This is particularly attractive for widely used cartesian sequences where currently a non-interfering self-navigation means is lacking for MRI-based simulation and MRI-guided radiotherapy. The feasibility of 4D-MRI generation with the noise navigator as respiratory surrogate signal was demonstrated for both cartesian and radial readout strategies in radiotherapy setup on four healthy volunteers and two radiotherapy patients on a dedicated 1.5 T MRI scanner and two radiotherapy patients on a 1.5 T MRI-linac system. Moreover, the respiratory-correlated 4D-MR images showed liver motion comparable to a reference 2D cine MRI series for the volunteers. For 2D cartesian cine MRI acquisitions, both the noise navigator and respiratory bellows were benchmarked against an image navigator. Respiratory phase detection based on the noise navigator agreed 1.4 times better with the image navigator than the respiratory bellows did. For a 3D Stack-of-Stars acquisitions, the noise navigator was compared to radial self-navigation and a 1.7 times higher respiratory phase detection agreement was observed than for the respiratory bellows compared to radial self-navigation.

Assessment of 3D motion modeling performance for dose accumulation mapping on the MR-linac by simultaneous multislice MRI.

Hybrid MR-linac systems enable intrafraction motion monitoring during radiation therapy. Since time-resolved 3D MRI is still challenging, various motion models have been developed that rely on time-resolved 2D imaging. Continuous validation of these models is important for accurate dose accumulation mapping. In this study we used 2D simultaneous multislice (SMS) imaging to improve the PCA-based motion modeling method developed previously (Stemkens et al 2016 Phys. Med. Biol. 61 5335-55). From the additional simultaneously acquired slices, several independent motion models could be generated, which allowed for an assessment of the sensitivity of the motion model to the location of the time-resolved 2D slices. Additionally, the best model could be chosen at every time-point, increasing the method's robustness. Imaging experiments were performed in six healthy volunteers using three simultaneous slices, which generated three independent models per volunteer. For each model the motion traces of the liver tip and both kidneys were estimated. We found that the location of the 2D slices influenced the model's error in five volunteers significantly with a p -value <0.05, and that selecting the best model at every time-point can improve the method. This allows for more accurate and robust motion characterization in MR-guided radiotherapy.

Nuts and bolts of 4D-MRI for radiotherapy.

Magnetic resonance imaging (MRI) is increasingly being used in the radiotherapy workflow because of its superior soft tissue contrast and high flexibility in contrast. In addition to anatomical and functional imaging, MRI can also be used to characterize the physiologically induced motion of both the tumor and organs-at-risk. Respiratory-correlated 4D-MRI has gained large interest as an alternative to 4D-CT for the characterization of respiratory motion throughout the thorax and abdomen. These 4D-MRI data sets consist of three spatial dimensions and the respiratory phase or amplitude over the fourth dimension (opposed to time-resolved 4D-MRI that represents time in the fourth dimension). Over the last 15 years numerous methods have been presented in literature. This review article provides a comprehensive overview of the various 4D-MRI techniques, and describes the differences in MRI data acquisition and 4D data set generation from a methodological point of view. The current status and future perspective of these techniques are highlighted, and the requirements for safe introduction into the clinic (e.g. method validation) are discussed.

Emerging role of MRI in radiation therapy.

Advances in multimodality imaging, providing accurate information of the irradiated target volume and the adjacent critical structures or organs at risk (OAR), has made significant improvements in delivery of the external beam radiation dose. Radiation therapy conventionally has used computed tomography (CT) imaging for treatment planning and dose delivery. However, magnetic resonance imaging (MRI) provides unique advantages: added contrast information that can improve segmentation of the areas of interest, motion information that can help to better target and deliver radiation therapy, and posttreatment outcome analysis to better understand the biologic effect of radiation. To take advantage of these and other potential advantages of MRI in radiation therapy, radiologists and MRI physicists will need to understand the current radiation therapy workflow and speak the same language as our radiation therapy colleagues. This review article highlights the emerging role of MRI in radiation dose planning and delivery, but more so for MR-only treatment planning and delivery. Some of the areas of interest and challenges in implementing MRI in radiation therapy workflow are also briefly discussed. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;48:1468-1478.

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.

Respiratory motion model based on the noise covariance matrix of a receive array.

PURPOSE: Tracking of the internal anatomy by means of a motion model that uses the MR-derived motion fields and noise covariance matrix (NCM) dynamic as a surrogate signal. METHODS: A 2D respiratory motion model was developed based on the MR-derived motion fields and the NCM of a receive array used in MRI. Temporal dynamics of the NCM were used as a motion surrogate for a linear correspondence motion model. The model performance was tested on five healthy volunteers with a liver as the target. The motion fields were calculated from the cineMR frames with an optical flow registration tool. RESULTS: The model estimated the liver motion with an average residual error of 2.3 mm (13% of the motion amplitude). The model formation takes 3 min and the model latency was 0.5 s in the current implementation. The limiting factor for the latency is the current update time of the NCM (0.48 s), which in principle can be reduced to 0.004 s with an alternative way to determine the NCM. CONCLUSIONS: The 2D respiratory motion of the liver can be effectively estimated with the linear motion model that uses the temporal behavior of the NCM as motion surrogate. Magn Reson Med 79:1730-1735, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

4D MR imaging using robust internal respiratory signal.

The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.