Implications of tissue magnetic susceptibility-related distortion on the rotating magnet in an MR-linac design

Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator

Background and purpose

Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated.

Materials and methods

Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints.

Results

Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL.

Conclusions

The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.

Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network

BACKGROUND

Megavoltage computed tomography (MVCT) has been implemented on many radiotherapy treatment machines for on-board anatomical visualization, localization, and adaptive dose calculation. Implementing an MR-only workflow by synthesizing MVCT from magnetic resonance imaging (MRI) would offer numerous advantages for treatment planning and online adaptation.

PURPOSE

In this work, we sought to synthesize MVCT (sMVCT) datasets from MRI using deep learning to demonstrate the feasibility of MRI-MVCT only treatment planning.

METHODS

MVCTs and T1-weighted MRIs for 120 patients treated for head-and-neck cancer were retrospectively acquired and co-registered. A deep neural network based on a fully-convolutional 3D U-Net architecture was implemented to map MRI intensity to MVCT HU. Input to the model were volumetric patches generated from paired MRI and MVCT datasets. The U-Net was initialized with random parameters and trained on a mean absolute error (MAE) objective function. Model accuracy was evaluated on 18 withheld test exams. sMVCTs were compared to respective MVCTs. Intensity-modulated volumetric radiotherapy (IMRT) plans were generated on MVCTs of four different disease sites and compared to plans calculated onto corresponding sMVCTs using the gamma metric and dose-volume-histograms (DVHs).

RESULTS

MAE values between sMVCT and MVCT datasets were 93.3 ± 27.5, 78.2 ± 27.5, and 138.0 ± 43.4 HU for whole body, soft tissue, and bone volumes, respectively. Overall, there was good agreement between sMVCT and MVCT, with bone and air posing the greatest challenges. The retrospective dataset introduced additional deviations due to sinus filling or tumor growth/shrinkage between scans, differences in external contours due to variability in patient positioning, or when immobilization devices were absent from diagnostic MRIs. Dose distributions of IMRT plans evaluated for four test cases showed close agreement between sMVCT and MVCT images when evaluated using DVHs and gamma dose metrics, which averaged to 98.9 ± 1.0% and 96.8 ± 2.6% analyzed at 3%/3 mm and 2%/2 mm, respectively.

CONCLUSIONS

MVCT datasets can be generated from T1-weighted MRI using a 3D deep convolutional neural network with dose calculation on a sample sMVCT in close agreement with the MVCT. These results demonstrate the feasibility of using MRI-derived sMVCT in an MR-only treatment planning workflow.

Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers

PURPOSE

To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner.

METHODS AND MATERIALS

Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions.

RESULTS

Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D₅₀ at the planning target volume were 0.4% ± 0.6% and 0.3% ± 0.5% at 122 and 488 Hz/mm, respectively.

CONCLUSIONS

The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.

Characterization of spatial distortion in a 0.35 T MRI-guided radiotherapy system

Spatial distortion results in image deformation that can degrade accurate targeting and dose calculations in MRI-guided adaptive radiotherapy. The authors present a comprehensive assessment of a 0.35 T MRI-guided radiotherapy system's spatial distortion using two commercially-available phantoms with regularly spaced markers. Images of the spatial integrity phantoms were acquired using five clinical protocols on the MRI-guided radiotherapy machine with the radiotherapy gantry positioned at various angles. Software was developed to identify and localize all phantom markers using a template matching approach. Rotational and translational corrections were implemented to account for imperfect phantom alignment. Measurements were made to assess uncertainties arising from susceptibility artifacts, image noise, and phantom construction accuracy. For a clinical 3D imaging protocol with a 1.5 mm reconstructed slice thickness, 100% of spheres within a 50 mm radius of isocenter had a 3D deviation of 1 mm or less. Of the spheres within 100 mm of isocenter, 99.9% had a 3D deviation less than 1 mm. 94.8% and 100% of the spheres within 175 mm were found to be within 1 mm and 2 mm of the expected positions in 3D respectively. Maximum 3D distortions within 50 mm, 100 mm and 175 mm of isocenter were 0.76 mm, 1.15 mm and 1.88 mm respectively. Distortions present in images acquired using the real-time imaging sequence were less than 1 mm for 98.1% and 95.0% of the cylinders within 50 mm and 100 mm of isocenter. The corresponding maximum distortion in these regions was 1.10 mm and 1.67 mm. These results may be used to inform appropriate planning target volume (PTV) margins for 0.35 T MRI-guided radiotherapy. Observed levels of spatial distortion should be explicitly considered when using PTV margins of 3 mm or less or in the case of targets displaced from isocenter by more than 50 mm.

CNR considerations for rapid real-time MRI tumor tracking in radiotherapy hybrid devices: Effects of B0 field strength

PURPOSE

This work examines the subject of contrast-to-noise ratio (CNR), specifically between tumor and tissue background, and its dependence on the MRI field strength, B0. This examination is motivated by the recent interest and developments in MRI/radiotherapy hybrids where real-time imaging can be used to guide treatment beams. The ability to distinguish a tumor from background tissue is of primary importance in this field, and this work seeks to elucidate the complex relationship between the CNR and B0 that is too often assumed to be purely linear.

METHODS

Experimentally based models of B0-dependant relaxation for various tumor and normal tissues from the literature were used in conjunction with signal equations for MR sequences suitable for rapid real-time imaging to develop field-dependent predictions for CNR. These CNR models were developed for liver, lung, breast, glioma, and kidney tumors for spoiled gradient-echo, balanced steady-state free precession (bSSFP), and single-shot half-Fourier fast spin echo sequences.

RESULTS

Due to the pattern in which the relaxation properties of tissues are found to vary over B0 field (specifically the T1 time), there was always an improved CNR at lower fields compared to linear dependency. Further, in some tumor sites, the CNR at lower fields was found to be comparable to, or sometimes higher than those at higher fields (i.e., bSSFP CNR for glioma, kidney, and liver tumors).

CONCLUSIONS

In terms of CNR, lower B0 fields have been shown to perform as well or better than higher fields for some tumor sites due to superior T1 contrast. In other sites this effect was less pronounced, reversing the CNR advantage. This complex relationship between CNR and B0 reveals both low and high magnetic fields as viable options for tumor tracking in MRI/radiotherapy hybrids.

Investigation of the 4D composite MR image distortion field associated with tumor motion for MR-guided radiotherapy

PURPOSE

Magnetic resonance (MR) images are affected by geometric distortions due to the specifics of the MR scanner and patient anatomy. Quantifying the distortions associated with mobile tumors is particularly challenging due to real anatomical changes in the tumor's volume, shape, and relative location within the MR imaging volume. In this study, the authors investigate the 4D composite distortion field, which combines the effects of the susceptibility-induced and system-related distortion fields, experienced by mobile lung tumors.

METHODS

The susceptibility (χ) effects were numerically simulated for two specific scenarios: (a) a full motion cycle of a lung tumor due to breathing as depicted on ten phases of a 4D CBCT data set and (b) varying the tumor size and location in lung tissue via a synthetically generated sphere with variable diameter (4-80 mm). The χ simulation procedure relied on the segmentation and generation of 3D susceptibility (χ) masks and computation of the magnetic field by means of finite difference methods. A system-related distortion field, determined with a phantom and image processing algorithm, was used as a reference. The 4D composite distortion field was generated as the vector summation of the χ-induced and system-related fields. The analysis was performed for two orientations of the main magnetic field (B0), which correspond to several MRIgRT system configurations. Specifically, B0 was set along the z-axis as in the case of a cylindrical-bore scanner and in the (x,y)-plane as for a biplanar MR. Computations were also performed for a full revolution at 15° increments in the case of a rotating biplanar magnet. Histograms and metrics such as maximum, mean, and range were used to evaluate the characteristics of the 4D distortion field.

RESULTS

The χ-induced field depends on the change in volume and shape of the moving tumor as well as the local surrounding anatomy. In the case of system-related distortions, the tumor experiences increased field perturbations as it moves further away from the MR isocenter. For a mobile lung tumor, the 4D composite field, corresponding to a 1.5 T field and a readout gradient of 5 mT/m, amounts to 3.0 and 2.8 mm for the MRIgRT system designs featuring B0 oriented along the z-axis (cylindrical-bore scanner) and in the (x,y)-plane (biplanar scanner), respectively. For a rotating biplanar scanner, the composite distortion field varied nonlinearly with the rotation angle. Overall, the dominant contribution to the composite field was from the system-related distortion field. The tumor centroid experienced a systematic shift of 2 mm and showed a negligible perturbation for different B0 values. The dependency on the tumor size was also investigated, namely the max values varied from 1.2 to 2.5 mm for spherical volumes with a diameter between 4 and 80 mm.

CONCLUSIONS

The composite distortion field requires adequate quantification for lung radiation therapy applications such as treatment planning, pretreatment patient setup verification, and real-time treatment delivery guidance. For certain scenarios such as small tumor volumes, the spatial distortions may be corrected by applying systematic shifts derived from a single tumor motion phase. In the case of high readout gradients common to fast imaging applications, the χ distortions were found to be less than 1 mm irrespective of scanner configuration.

Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM

PURPOSE

Distortions in magnetic resonance imaging (MRI) compromise spatial fidelity, potentially impacting delineation and dose calculation. We characterized 2D and 3D large field of view (FOV), sequence-independent distortion at various positions in a 1.0 T high-field open MR simulator (MR-SIM) to implement correction maps for MRI treatment planning.

METHODS

A 36 × 43 × 2 cm(3) phantom with 255 known landmarks (∼1 mm(3)) was scanned using 1.0 T high-field open MR-SIM at isocenter in the transverse, sagittal, and coronal axes, and a 465 × 350 × 168 mm(3) 3D phantom was scanned by stepping in the superior-inferior direction in three overlapping positions to achieve a total 465 × 350 × 400 mm(3) sampled FOV yielding >13 800 landmarks (3D Gradient-Echo, TE/TR/α = 5.54 ms/30 ms/28°, voxel size = 1 × 1 × 2 mm(3)). A binary template (reference) was generated from a phantom schematic. An automated program converted MR images to binary via masking, thresholding, and testing for connectivity to identify landmarks. Distortion maps were generated by centroid mapping. Images were corrected via warping with inverse distortion maps, and temporal stability was assessed.

RESULTS

Over the sampled FOV, non-negligible residual gradient distortions existed as close as 9.5 cm from isocenter, with a maximum distortion of 7.4 mm as close as 23 cm from isocenter. Over six months, average gradient distortions were -0.07 ± 1.10 mm and 0.10 ± 1.10 mm in the x and y directions for the transverse plane, 0.03 ± 0.64 and -0.09 ± 0.70 mm in the sagittal plane, and 0.4 ± 1.16 and 0.04 ± 0.40 mm in the coronal plane. After implementing 3D correction maps, distortions were reduced to <1 pixel width (1 mm) for all voxels up to 25 cm from magnet isocenter.

CONCLUSIONS

Inherent distortion due to gradient nonlinearity was found to be non-negligible even with vendor corrections applied, and further corrections are required to obtain 1 mm accuracy for large FOVs. Statistical analysis of temporal stability shows that sequence independent distortion maps are consistent within six months of characterization.

Spatial Precision in Magnetic Resonance Imaging-Guided Radiation Therapy: The Role of Geometric Distortion

Because magnetic resonance imaging-guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into account relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility-induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility-induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.

Evaluating organ delineation, dose calculation and daily localization in an open-MRI simulation workflow for prostate cancer patients

BACKGROUND

This study describes initial testing and evaluation of a vertical-field open Magnetic Resonance Imaging (MRI) scanner for the purpose of simulation in radiation therapy for prostate cancer. We have evaluated the clinical workflow of using open MRI as a sole modality for simulation and planning. Relevant results related to MRI alignment (vs. CT) reference dataset with Cone-Beam CT (CBCT) for daily localization are presented.

METHODS

Ten patients participated in an IRB approved study utilizing MRI along with CT simulation with the intent of evaluating the MRI-simulation process. Differences in prostate gland volume, seminal vesicles, and penile bulb were assessed with MRI and compared to CT. To evaluate dose calculation accuracy, bulk-density-assignments were mapped onto respective MRI datasets and treated IMRT plans were re-calculated. For image localization purposes, 400 CBCTs were re-evaluated with MRI as the reference dataset and daily shifts compared against CBCT-to-CT registration. Planning margins based on MRI/CBCT shifts were computed using the van Herk formalism.

RESULTS

Significant organ contour differences were noted between MRI and CT. Prostate volumes were on average 39.7% (p = 0.002) larger on CT than MRI. No significant difference was found in seminal vesicle volumes (p = 0.454). Penile bulb volumes were 61.1% higher on CT, without statistical significance (p = 0.074). MRI-based dose calculations with assigned bulk densities produced agreement within 1% with heterogeneity corrected CT calculations. The differences in shift positions for the cohort between CBCT-to-CT registration and CBCT-to-MRI registration are -0.15 ± 0.25 cm (anterior-posterior), 0.05 ± 0.19 cm (superior-inferior), and -0.01 ± 0.14 cm (left-right).

CONCLUSIONS

This study confirms the potential of using an open-field MRI scanner as primary imaging modality for prostate cancer treatment planning simulation, dose calculations and daily image localization.

Feasibility and limitations of bulk density assignment in MRI for head and neck IMRT treatment planning

Head and neck cancers centered at the base of skull are better visualized on MRI than on CT. The purpose of this investigation was to investigate the accuracy of bulk density assignment in head and neck intensity‐modulated radiation therapy (IMRT) treatment plan optimization. Our study investigates dose calculation differences between density‐assigned MRI and CT, and identifies potential limitations related to dental implants and MRI geometrical distortion in the framework of MRI‐only‐based treatment planning. Bulk density assignment was performed and applied onto MRI to generate three MRI image sets with increasing levels of heterogeneity for seven patients: 1) MRIW: all water‐equivalent; 2) MRIW + B: included bone with density of 1.53 g/cm3; and 3) MRIW + B + A: included bone and air. Using identical planning and optimization parameters, MRI‐based IMRT plans were generated and compared to corresponding, forward‐calculated, CT‐based plans on the basis of target coverage, isodose distributions, and dose‐volume histograms (DVHs). Phantom studies were performed to assess the magnitude and spatial dependence of MRI geometrical distortion. MRIW‐based dose calculations overestimated target coverage by 16.1%. Segmentation of bone reduced differences to within 2% of the coverage area on the CT‐based plan. Further segmentation of air improved conformity near air–tissue interfaces. Dental artifacts caused substantial target coverage overestimation even on MRIW + B + A. Geometrical distortion was less than 1 mm in an imaging volume 20 × 20 × 20 cm3 around scanner isocenter, but up to 4 mm at 17 cm lateral to isocenter. Bulk density assignment in the framework of MRI‐only IMRT head and neck treatment planning is a feasible method with certain limitations. Bone and teeth account for the majority of density heterogeneity effects. While soft tissue is well visualized on MRI compared to CT, dental implants may not be visible on MRI and must be identified by other means and assigned appropriate density for accurate dose calculation. Far off‐center geometrical distortion of the body contour near the shoulder region is a potential source of dose calculation inaccuracy.

PACS numbers: 87.61.‐c, 87.55.‐D

Validation of measurement-guided 3D VMAT dose reconstruction on a heterogeneous anthropomorphic phantom

3DVH software (Sun Nuclear Corp., Melbourne, FL) is capable of generating a volumetric patient VMAT dose by applying a volumetric perturbation algorithm based on comparing measurement-guided dose reconstruction and TPS-calculated dose to a cylindrical phantom. The primary purpose of this paper is to validate this dose reconstruction on an anthropomorphic heterogeneous thoracic phantom by direct comparison to independent measurements. The dosimetric insert to the phantom is novel, and thus the secondary goal is to demonstrate how it can be used for the hidden target end-to-end testing of VMAT treatments in lung. A dosimetric insert contains a 4 cm diameter unit-density spherical target located inside the right lung (0.21 g/cm(3) density). It has 26 slots arranged in two orthogonal directions, milled to hold optically stimulated luminescent dosimeters (OSLDs). Dose profiles in three cardinal orthogonal directions were obtained for five VMAT plans with varying degrees of modulation. After appropriate OSLD corrections were applied, 3DVH measurement-guided VMAT dose reconstruction agreed 100% with the measurements in the unit density target sphere at 3%/3 mm level (composite analysis) for all profile points for the four less-modulated VMAT plans, and for 96% of the points in the highly modulated C-shape plan (from TG-119). For this latter plan, while 3DVH shows acceptable agreement with independent measurements in the unit density target, in the lung disagreement with experiment is relatively high for both the TPS calculation and 3DVH reconstruction. For the four plans excluding the C-shape, 3%/3 mm overall composite analysis passing rates for 3DVH against independent measurement ranged from 93% to 100%. The C-shape plan was deliberately chosen as a stress test of the algorithm. The dosimetric spatial alignment hidden target test demonstrated the average distance to agreement between the measured and TPS profiles in the steep dose gradient area at the edge of the 2 cm target to be 1.0 ± 0.7, 0.3 ± 0.3, and 0.3 ± 0.3 mm for the IEC X, Y, and Z directions, respectively.