Brain and Head-and-Neck MRI in Immobilization Mask: A Practical Solution for MR-Only Radiotherapy

In brain/head-and-neck radiotherapy (RT), thermoplastic immobilization masks guarantee reproducible patient positioning in treatment position between MRI, CT, and irradiation. Since immobilization masks do not fit in the diagnostic MR head/head-and-neck coils, flexible surface coils are used for MRI imaging in clinical practice. These coils are placed around the head/neck, in contact with the immobilization masks. However, the positioning of these flexible coils is technician dependent, thus leading to poor image reproducibility. Additionally, flexible surface coils have an inferior signal-to-noise-ratio (SNR) compared to diagnostic coils. The aim of this work was to create a new immobilization setup which fits into the diagnostic MR coils in order to enhance MR image quality and reproducibility. For this purpose, a practical immobilization setup was constructed. The performances of the standard clinical and the proposed setups were compared with four tests: SNR, image quality, motion restriction, and reproducibility of inter-fraction subject positioning. The new immobilization setup resulted in 3.4 times higher SNR values on average than the standard setup, except directly below the flexible surface coils where similar SNR was observed. Overall, the image quality was superior for brain/head-and-neck images acquired with the proposed RT setup. Comparable motion restriction in feet-head/left-right directions (maximum motion ≈1 mm) and comparable inter-fraction repositioning accuracy (mean inter-fraction movement 1 ± 0.5 mm) were observed for the standard and the new setup

Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy.

To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time adaptation, motion must be quickly estimated with low latency. The motion estimate is used to adapt the radiation beam to the current anatomy, yielding a more conformal dose distribution. As the MR acquisition is the largest component of latency, deep learning (DL) may reduce the total latency by enabling much higher undersampling factors compared to conventional reconstruction and motion estimation methods. The benefit of DL on image reconstruction and motion estimation was investigated for obtaining accurate deformation vector fields (DVFs) with high temporal resolution and minimal latency. 2D cine MRI acquired at 1.5 T from 135 abdominal cancer patients were retrospectively included in this study. Undersampled radial golden angle acquisitions were retrospectively simulated. DVFs were computed using different combinations of conventional- and DL-based methods for image reconstruction and motion estimation, allowing a comparison of four approaches to achieve real-time motion estimation. The four approaches were evaluated based on the end-point-error and root-mean-square error compared to a ground-truth optical flow estimate on fully-sampled images, the structural similarity (SSIM) after registration and time necessary to acquire k-space, reconstruct an image and estimate motion. The lowest DVF error and highest SSIM were obtained using conventional methods up to [Formula: see text]. For undersampling factors [Formula: see text], the lowest DVF error and highest SSIM were obtained using conventional image reconstruction and DL-based motion estimation. We have found that, with this combination, accurate DVFs can be obtained up to [Formula: see text] with an average root-mean-square error up to 1 millimeter and an SSIM greater than 0.8 after registration, taking 60 milliseconds. High-quality 2D DVFs from highly undersampled k-space can be obtained with a high temporal resolution with conventional image reconstruction and a deep learning-based motion estimation approach for real-time adaptive MRI-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

MRI B 0 homogeneity and geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac

This work aimed to quantify any principal magnetic field (B 0) inhomogeneity and changes in MR image geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac. This situation occurs for around a second between treatment beams during current image guided radiotherapy treatment and would occur frequently in foreseeable real-time adaptive radiotherapy treatment. Pixel by pixel maps of B 0 inhomogeneity were obtained via repeated high temporal resolution pulse sequences with the linac gantry static at 36 gantry angles spaced ten degrees apart, and in continuous rotation at both 1 and 2 rpm. Individual B 0 maps were subtracted from average maps across all data and the residual peak to peak inhomogeneity was calculated for each. The bulk geometric shift and change in physical extent of a 10 cm diameter spherical flood phantom during continuous linac gantry rotation at 1 and 2 rpm was compared to the static gantry case for two pulse sequences: the real-time clinical monitoring bFFE sequence and a non-clinical EPI sequence, chosen for its susceptibility to geometric distortion. The peak to peak inhomogeneity in the deviation-from-average ppm maps, plotted against gantry angle with the gantry in continuous rotation at 1 and 2 rpm were negligibly different from equivalent data obtained with the gantry static. The real-time clinical monitoring pulse sequence was shown to give negligible geometric distortion during continuous gantry motion, whilst a non-clinical EPI sequence showed bulk shifts of the order of one pixel and gantry angle dependent changes in extent, demonstrating the sensitivity of the chosen method. MR imaging on the Elekta Unity MR-Linac with the gantry in continuous motion is negligibly different from the static gantry case with current clinical pulse sequences. Real-time tracking and treatment plan adaptation using MR images obtained with the linac gantry in motion is possible

Intrafraction motion quantification and planning target volume margin determination of head-and-neck tumors using cine magnetic resonance imaging

PURPOSE: To quantify intrafractional motion to determine population-based radiotherapy treatment margins for head-and-neck tumors. METHODS: Cine MR imaging was performed in 100 patients with head-and-neck cancer on a 3T scanner in a radiotherapy treatment setup. MR images were analyzed using deformable image registration (optical flow algorithm) and changes in tumor contour position were used to calculate the tumor motion. The tumor motion was used together with patient setup errors (450 patients) to calculate population-based PTV margins. RESULTS: Tumor motion was quantified in 84 patients (12/43/29 nasopharynx/oropharynx/larynx, 16 excluded). The mean maximum (95th percentile) tumor motion (swallowing excluded) was: 2.3 mm in superior, 2.4 mm in inferior, 1.8 mm in anterior and 1.7 mm in posterior direction. PTV margins were: 2.8 mm isotropic for nasopharyngeal tumors, 3.2 mm isotropic for oropharyngeal tumors and 4.3 mm in inferior-superior and 3.2 mm in anterior-posterior for laryngeal tumors, for our institution. CONCLUSIONS: Intrafractional head-and-neck tumor motion was quantified and population-based PTV margins were calculated. Although the average tumor motion was small (95th percentile motion <3.0 mm), tumor motion varied considerably between patients (0.1-12.0 mm). The intrafraction motion expanded the CTV-to-PTV with 1.7 mm for laryngeal tumors, 0.6 mm for oropharyngeal tumors and 0.2 mm for nasopharyngeal tumors

Optimizing 4-dimensional magnetic resonance imaging data sampling for respiratory motion analysis of pancreatic tumors

PURPOSE: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. METHODS AND MATERIALS: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. RESULTS: The MRI navigator was found to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. CONCLUSIONS: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients

Design and feasibility of a flexible, on-body, high impedance coil receive array for a 1.5 T MR-linac

The lack of radiation-attenuating tuning capacitors in high impedance coils (HICs) make HICs an interesting building block of receive arrays for MRI-guided radiotherapy (MRIgRT). Additionally, their flexibility and limited channel coupling allow for low-density support materials, which are likely to be more radiation transparent (radiolucent). In this work, we introduce the use of HICs in receive arrays for MRIgRT treatments. We discuss the design and show the dosimetric feasibility of a HIC receive array that has a high channel count and aims to improve the imaging performance of the 1.5 T MR-linac. Our on-body design comprises an anterior and posterior element, which each feature a 2 × 8 channel layout (32 channels total). The anterior element is flexible, while the posterior element is rigid to support the patient. Mockups consisting of support materials and conductors were built, irradiated, and optimized to minimize impact on the surface dose (7% of the dose maximum) and dose at depth (≤0.8% under a single conductor and _1.4% under a conductor crossing). Anatomical motion and the use of multiple beam angles will ensure that these slight dose changes at depth are clinically insignificant. Subsequently, several functional, single-channel HIC imaging prototypes and a 5-channel array were built to assess the performance in terms of signalto-noise ratio (SNR). The performance was compared to the clinical MR-linac array and showed that the 5-channel imaging prototype outperformed the clinical array in terms of SNR and channel coupling. Imaging performance was not affected by the radiation beam. In conclusion, the use of HICs allowed for the design of our flexible, on-body receive array for MRIgRT. The design was shown to be dosimetrically feasible and improved the SNR. Future research with a full array will need to show the gain in parallel imaging performance and thus acceleration

Non-rigid CT/CBCT to CBCT registration for online external beam radiotherapy guidance

Image-guided external beam radiotherapy (EBRT) allows radiation dose deposition with a high degree of accuracy and precision. Guidance is usually achieved by estimating the displacements, via image registration, between cone beam computed tomography (CBCT) and computed tomography (CT) images acquired at different stages of the therapy. The resulting displacements are then used to reposition the patient such that the location of the tumor at the time of treatment matches its position during planning. Moreover, ongoing research aims to use CBCT-CT image registration for online plan adaptation.&#13; However, CBCT images are usually acquired using a small number of X-Ray projections and/or low beam intensities. This often leads to the images being subject to low contrast, low signal-to-noise ratio and artifacts, which ends-up hampering the image registration process. Previous studies addressed this by integrating additional image processing steps into the registration procedure. However, these steps are usually designed for particular image acquisition schemes, therefore limiting their use on a case-by-case basis.&#13; In the current study we address CT to CBCT and CBCT to CBCT registration by the means of the recently proposed EVolution registration algorithm. Contrary to previous approaches, EVolution does not require the integration of additional image processing steps in the registration scheme. Moreover, the algorithm requires a low number of input parameters, is easily parallelizable and provides an elastic deformation on a point-by-point basis. Results have shown that relative to a pure CT-based registration, the intrinsic artifacts present in typical CBCT images only have a sub-millimeter impact on the accuracy and precision of the estimated deformation. In addition, the algorithm has low computational requirements, which are compatible with online image-based guidance of EBRT treatments.&#13