Distortion In Magnetic Resonance Imaging Research Articles

Association between dental restorations and artefacts on head magnetic resonance images in paediatric patients.

Magnetic resonance imaging (MRI) has become an important diagnostic tool for paediatric patients. The association between dental restorations and MRI artefacts/distortions, however, is unclear. To investigate the association between dental restorations and artefacts in head MRI in children. This retrospective analysis included patients who underwent head MRI and dental examination at Ramathibodi Hospital from January 2015 to March 2021. From dental records and dental radiographs, a dentist reviewed the amount and type of restorative materials used. Two radiologists examined the MRI scans in five sequences for the presence of distortions and quantified the magnitude and grading of any artefacts. Ninety-four patients aged 3-15 years were included. Twenty-four patients who received preformed metal crowns (PMCs) had MRI distortions. Subjects with no restorations or with tooth-coloured material or amalgam restorations or both did not exhibit distortions. The number of PMCs was related to the size of an artefact. Almost all distortions were confined to the oral cavity and maxillary sinus and did not affect the diagnostic brain area. Among the commonly used dental restorative materials for children, only PMCs were associated with artefacts on head MRI scans.

Proton range uncertainty caused by synthetic computed tomography generated with deep learning from pelvic magnetic resonance imaging

Background In proton therapy, it is disputed whether synthetic computed tomography (sCT), derived from magnetic resonance imaging (MRI), permits accurate dose calculations. On the one hand, an MRI-only workflow could eliminate errors caused by, e.g., MRI-CT registration. On the other hand, the extra error would be induced due to an sCT generation model. This work investigated the systematic and random model error induced by sCT generation of a widely discussed deep learning model, pix2pix. Material and Methods An open-source image dataset of 19 patients with cancer in the pelvis was employed and split into 10, 5, and 4 for training, testing, and validation of the model, respectively. Proton pencil beams (200 MeV) were simulated on the real CT and generated sCT using the tool for particle simulation (TOPAS). Monte Carlo (MC) dropout was used for error estimation (50 random sCT samples). Systematic and random model errors were investigated for sCT generation and dose calculation on sCT. Results For sCT generation, random model error near the edge of the body (∼200 HU) was higher than that within the body (∼100 HU near the bone edge and <10 HU in soft tissue). The mean absolute error (MAE) was 49 ± 5, 191 ± 23, and 503 ± 70 HU for the whole body, bone, and air in the patient, respectively. Random model errors of the proton range were small (<0.2 mm) for all spots and evenly distributed throughout the proton fields. Systematic errors of the proton range were −1.0(±2.2) mm and 0.4(±0.9)%, respectively, and were unevenly distributed within the proton fields. For 4.5% of the spots, large errors (>5 mm) were found, which may relate to MRI-CT mismatch due to, e.g., registration, MRI distortion anatomical changes, etc. Conclusion The sCT model was shown to be robust, i.e., had a low random model error. However, further investigation to reduce and even predict and manage systematic error is still needed for future MRI-only proton therapy.

Radiological Parameters for Gamma Knife Radiosurgery.

Accurate lesion targeting is the essence of stereotactic radiosurgery. With the currently available imaging modalities, scanning has become quick and robust providing a high degree of spatial resolution resulting in optimal contrast between normal and abnormal tissues. Magnetic resonance imaging (MRI) forms the backbone of Leksell radiosurgery. It produces images with excellent soft tissue details highlighting the target and surrounding "at-risk" structures conspicuously. However, one must be aware of the MRI distortions that may arise during treatment. Computed tomography (CT) has quick acquisition times giving excellent bony information but inferior soft tissue details. To avail benefits of both these modalities and overcome their individual fallacies and shortcomings, they are often co-registered/fused for stereotactic guidance. Vascular lesions like an arteriovenous malformation (AVM) are best planned with cerebral digital subtraction angiography (DSA) in conjunction with MRI. In specific cases, specialized imaging methods like magnetic resonance (MR) spectroscopy, positron emission tomography (PET), magneto-encephalography (MEG), etc., may be added to the treatment planning for stereotactic radiosurgery (SRS).

The Impact of System-Related Magnetic Resonance Imaging Geometric Distortion in Stereotactic Radiotherapy: A Case Report

Magnetic resonance imaging (MRI) is now essential in stereotactic radiotherapy (SRT) planning for brain tumors because of its excellence in soft-tissue contrast and high spatial resolution. However, MRI distortion is sometimes difficult to recognize, and it may cause large misalignments in radiotherapy planning. In this case report, we will show how much difference in the dose distribution of SRT can be made by using MRI without distortion correction.

Evaluating metallic artefact of biodegradable magnesium-based implants in magnetic resonance imaging

Magnesium (Mg) implants have shown to cause image artefacts or distortions in magnetic resonance imaging (MRI). Yet, there is a lack of information on how the degradation of Mg-based implants influences the image quality of MRI examinations. In this study, Mg-based implants are analysed in vitro, ex vivo, and in the clinical setting for various magnetic field strengths with the aim to quantify metallic artefact behaviour. In vitro corroded Mg-based screws and a titanium (Ti) equivalent were imaged according to the ASTM F2119. Mg-based and Ti pins were also implanted into rat femurs for different time points and scanned to provide insights on the influence of soft and hard tissue on metallic artefact. Additionally, MRI data of patients with scaphoid fractures treated with CE-approved Mg-based compression screws (MAGNEZIX®) were analysed at various time points post-surgery. The artefact production of the Mg-based material decreased as implant material degraded in all settings. The worst-case imaging scenario was determined to be when the imaging plane was selected to be perpendicular to the implant axis. Moreover, the Mg-based implant outperformed the Ti equivalent in all experiments by producing lower metallic artefact (p < 0.05). This investigation demonstrates that Mg-based implants generate significantly lower metallic distortion in MRI when compared to Ti. Our positive findings suggest and support further research into the application of Mg-based implants including post-operative care facilitated by MRI monitoring of degradation kinetics and bone/tissue healing processes.

MRI Distortion Correction and Robot-to-MRI Scanner Registration for an MRI-Guided Robotic System.

Magnetic resonance imaging (MRI) guided robotic procedures require safe robotic instrument navigation and precise target localization. This depends on reliable tracking of the instrument from MR images, which requires accurate registration of the robot to the scanner. A novel differential image based robot-to-MRI scanner registration approach is proposed that utilizes a set of active fiducial coils, where background subtraction method is employed for coil detection. In order to use the presented preoperative registration approach jointly with the real-time high speed MRI image acquisition and reconstruction methods in real-time interventional procedures, the effects of the geometric MRI distortion in robot to scanner registration is analyzed using a custom distortion mapping algorithm. The proposed approach is validated by a set of target coils placed within the workspace, employing multi-planar capabilities of the scanner. Registration and validation errors are respectively 2.05 mm and 2.63 mm after the distortion correction showing an improvement of respectively 1.08 mm and 0.14 mm compared to the results without distortion correction.

Dedicated holmium microsphere administration device for MRI-guided interstitial brain microbrachytherapy

Microbrachytherapy with radioactive holmium-166 (166Ho) microspheres (MS) has the potential to be an effective treatment method for brain malignancies. Direct intratumoural delivery of 166Ho-MS and dose coverage of the whole tumour are crucial requirements. However, currently no dedicated instruments for controlled intratumoural delivery exist. This study presents an administration device that facilitates this novel magnetic resonance imaging (MRI) -guided intervention. The bioceramic alumina oxide cannula creates a straight channel for a superelastic nitinol precurved stylet to control spatial deposition of Ho-MS. End-point accuracy of the stylet was measured during insertions in phantoms. Imaging tests were performed in a 3 Tesla MRI-scanner to quantify instrument-induced artefacts. Additionally, the feasibility of non-radioactive holmium-165 (165Ho)-MS delivery with the administration device was evaluated in a brain tumour simulant. Absolute stylet tip error was 0.88 ± 0.61 mm, instrument distortion in MRI depended on needle material and orientation and dose delivery of 165Ho-MS in a brain tumour phantom was possible. This study shows that the administration device can accurately place the stylet for injection of Ho-MS and that visualization can be performed with MRI.

A Python software to evaluate geometric discrepancies between stereotactic CT and MR images in radiosurgery

Due to its excellent soft tissue contrast, magnetic resonance imaging (MRI) is widely used for target delineation in stereotactic radiosurgery. However, because of a number of factors (inhomogeneity of the constant magnetic field, nonlinearity of the gradient fields, etc.), MR images are more susceptible to spatial distortion as opposed to Computed tomography (CT) images, which could be considered as the reference studies in terms of the accuracy of target localization. It is crucial to assess the geometric errors in MR images as the accuracy of dose delivery strongly depends on MRI quality. One of the ways of MRI distortion evaluation is to scan a phantom with multiple marker points on both CT and MRI scanner and compare coordinates of the points defined on CT and MR images, respectively. Performing this test as a routine part of MRI quality assurance (QA) program for stereotactic radiosurgery is complicated by lack of a software for the automatic calculations of the discrepancies.The aim of our work was to develop a software to calculate discrepancies between stereotactic coordinates of the phantom’s plastic rods defined on the MR and CT images of the Elekta MR phantom. A special Python software was developed and the spatial accuracy of the stereotactic MR images was assessed. The calculated total differences between the coordinates of the CT and T1 weighted MR images, CT and T2 weighted MR images exceeded 1 mm in 3,5%, 0.1% of the points, respectively. Using the software in clinic routines could both speed up the time needed for the test performance and eliminate subjective visual assessment of the discrepancies.

Integration of spatial distortion effects in a 4D computational phantom for simulation studies in extra-cranial MRI-guided radiation therapy: Initial results.

Spatial distortions in magnetic resonance imaging (MRI) are mainly caused by inhomogeneities of the static magnetic field, nonlinearities in the applied gradients, and tissue-specific magnetic susceptibility variations. These factors may significantly alter the geometrical accuracy of the reconstructed MR image, thus questioning the reliability of MRI for guidance in image-guided radiation therapy. In this work, we quantified MRI spatial distortions and created a quantitative model where different sources of distortions can be separated. The generated model was then integrated into a four-dimensional (4D) computational phantom for simulation studies in MRI-guided radiation therapy at extra-cranial sites. A geometrical spatial distortion phantom was designed in four modules embedding laser-cut PMMA grids, providing 3520 landmarks in a field of view of (345×260×480)mm3 . The construction accuracy of the phantom was verified experimentally. Two fast MRI sequences for extra-cranial imaging at 1.5T were investigated, considering axial slices acquired with online distortion correction, in order to mimic practical use in MRI-guided radiotherapy. Distortions were separated into their sources by acquisition of images with gradient polarity reversal and dedicated susceptibility calculations. Such a separation yielded a quantitative spatial distortion model to be used for MR imaging simulations. Finally, the obtained spatial distortion model was embedded into an anthropomorphic 4D computational phantom, providing registered virtual CT/MR images where spatial distortions in MRI acquisition can be simulated. The manufacturing accuracy of the geometrical distortion phantom was quantified to be within 0.2mm in the grid planes and 0.5mm in depth, including thickness variations and bending effects of individual grids. Residual spatial distortions after MRI distortion correction were strongly influenced by the applied correction mode, with larger effects in the trans-axial direction. In the axial plane, gradient nonlinearities caused the main distortions, with values up to 3mm in a 1.5T magnet, whereas static field and susceptibility effects were below 1mm. The integration in the 4D anthropomorphic computational phantom highlighted that deformations can be severe in the region of the thoracic diaphragm, especially when using axial imaging with 2D distortion correction. Adaptation of the phantom based on patient-specific measurements was also verified, aiming at increased realism in the simulation. The implemented framework provides an integrated approach for MRI spatial distortion modeling, where different sources of distortion can be quantified in time-dependent geometries. The computational phantom represents a valuable platform to study motion management strategies in extra-cranial MRI-guided radiotherapy, where the effects of spatial distortions can be modeled on synthetic images in a virtual environment.

A modular phantom and software to characterize 3D geometric distortion in MRI

Magnetic resonance imaging (MRI) offers outstanding soft tissue contrast that may reduce uncertainties in target and organ-at-risk delineation and enable online adaptive image-guided treatment. Spatial distortions resulting from non-linearities in the gradient fields and non-uniformity in the main magnetic field must be accounted for across the imaging field-of-view to prevent systematic errors during treatment delivery. This work presents a modular phantom and software application to characterize geometric distortion (GD) within the large field-of-view MRI images required for radiation therapy simulation. The modular phantom is assembled from a series of rectangular foam blocks containing high-contrast fiducial markers in a known configuration. The modular phantom design facilitates transportation of the phantom between different MR scanners and MR-guided linear accelerators and allows the phantom to be adapted to fit different sized bores or coils. The phantom was evaluated using a 1.5 T MR-guided linear accelerator (MR-Linac) and 1.5 T and 3.0 T diagnostic scanners. Performance was assessed by varying acquisition parameters to induce image distortions in a known manner. Imaging was performed using T1 and T2 weighted pulse sequences with 2D and 3D distortion correction algorithms and the receiver bandwidth (BW) varied as 250–815 Hz pixel−1. Phantom set-up reproducibility was evaluated across independent set-ups. The software was validated by comparison with a non-modular phantom. Average geometric distortion was 0.94 ± 0.58 mm for the MR-Linac, 0.90 ± 0.53 mm for the 1.5 T scanner, and 1.15 ± 0.62 mm for the 3.0 T scanner, for a 400 mm diameter volume-of-interest. GD increased, as expected, with decreasing BW, and with the 2D versus 3D correction algorithm. Differences in GD attributed to phantom set-up were 0.13 mm or less. Differences in GD for the two software applications were less than 0.07 mm. A novel modular phantom was developed to evaluate distortions in MR images for radiation therapy applications.

Fast geometric distortion correction using a deep neural network: Implementation for the 1 Tesla MRI-Linac system.

Combining high-resolution magnetic resonance imaging (MRI) with a linear accelerator (Linac) as a single MRI-Linac system provides the capability to monitor intra-fractional motion and anatomical changes during radiotherapy, which facilitates more accurate delivery of radiation dose to the tumor and less exposure to healthy tissue. The gradient nonlinearity (GNL)-induced distortions in MRI, however, hinder the implementation of MRI-Linac system in image-guided radiotherapy where highly accurate geometry and anatomy of the target tumor is indispensable. To correct the geometric distortions in MR images, in particular, for the 1 Tesla (T) MRI-Linac system, a deep fully connected neural network was proposed to automatically learn the intricate relationship between the undistorted (theoretical) and distorted (real) space. A dataset, consisting of spatial samples acquired by phantom measurement that covers both inside and outside the working diameter of spherical volume (DSV), was utilized for training the neural network, which offers the ability to describe subtle deviations of the GNL field within the entire region of interest (ROI). The performance of the proposed method was evaluated on MR images of a three-dimensional (3D) phantom and the pelvic region of an adult volunteer scanned in the 1T MRI-Linac system. The experimental results showed that the severe geometric distortions within the entire ROI had been successfully corrected with an error less than the pixel size. Also, the presented network is highly efficient, which achieved significant improvement in terms of computational efficiency compared to existing methods. The feasibility of the presented deep neural network for characterizing the GNL field deviations in the 1T MRI-Linac system was demonstrated in this study, which shows promise in facilitating the MRI-Linac system to be routinely implemented in real-time MRI-guided radiotherapy.

Audit feasibility for geometric distortion in magnetic resonance imaging for radiotherapy.

Background and purposeMagnetic Resonance Imaging (MRI) is increasingly being used in radiotherapy (RT). However, geometric distortions are a known challenge of using MRI in RT. The aim of this study was to demonstrate feasibility of a national audit of MRI geometric distortions. This was achieved by assessing large field of view (FOV) MRI distortions on a number of scanners used clinically for RT.Materials and methodsMRI scans of a large FOV MRI geometric distortion phantom were acquired on 11 MRI scanners that are used clinically for RT in the UK. The mean and maximum distortions and variance between scanners were reported at different distances from the isocentre.ResultsFor a small FOV representing a brain (100–150 mm from isocentre) all distortions were < 2 mm except for the maximum distortion of one scanner. For a large FOV representing a head and neck/pelvis (200–250 mm from isocentre) mean distortions were < 2 mm except for one scanner, maximum distortions were > 10 mm in some cases. The variance between scanners was low and was found to increase with distance from isocentre.ConclusionsThis study demonstrated feasibility of the technique to be repeated in a country wide geometric distortion audit of all MRI scanners used clinically for RT. Recommendations were made for performing such an audit and how to derive acceptable limits of distortion in such an audit.

Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery.

Magnetic resonance imaging (MRI) is a crucial factor in optimal treatment planning for stereotactic radiosurgery. To further the awareness of possible errors in MRI, this work aimed to investigate the magnitude of susceptibility induced MRI distortions for intracranial organs at risk (OARs) and test the effectiveness of actively shimming these distortions. Distortion maps for 45 exams of 42 patients (18 on a 1.5 T MRI scanner, 27 on a 3 T MRI scanner) were calculated based on a high-bandwidth double-echo gradient echo sequence. The investigated OARs were brainstem, chiasm, eyes, and optic nerves. The influence of active shimming was investigated by comparing unshimmed 1.5 T data with shimmed 3 T data and comparing the results to a model based prediction. The median distortion for the different OARs was found to be between 0.13 and 0.18 mm for 1.5 T and between 0.11 and 0.13 mm for 3 T. The maximum distortion was found to be between 1.3 and 1.7 mm for 1.5 T and between 1.1 and 1.4 mm for 3 T. The variation of values was much higher for 1.5 T than for 3 T across all investigated OARs. Active shimming was found to reduce distortions by a factor of 2.3 to 2.9 compared to the expected values. Using a safety margin for OARs of 1 mm would have encompassed 99.8% of the distortions. Since distortions are inversely proportional to the readout bandwidth, they can be further reduced by increasing the bandwidth. Additional error sources like gradient nonlinearities need to be addressed separately.

Evaluation of Long-term Fluctuation of Geometric Distortion in MRI for Radiation Therapy Planning by Using an Automatic Analysis Tool

High tissue contrast in magnetic resonance imaging (MRI) allows better radiotherapy planning. However, geometric distortion in MRI induces inaccuracies affecting such planning, making it necessary to evaluate the characteristics of such geometric distortion. Although many studies have considered geometric distortion, most of these involved measurements performed only a few times. In this study, we evaluated MRI device-specific geometric distortion over long term and measured its variation by using an automatic analysis tool. The result showed that geometric distortion increased with distance from the center along both lateral and longitudinal directions. Specifically, the average distortion rate and average diameter error over the full measurement period increased by up to 1.02% and 1.96 mm, respectively, when using T1 weighted Image (WI) 3D fast spoiled gradient echo (FSPGR) at R15. In the case of T2 WI 2D fast spin echo (FSE) at R15, the standard deviation of the distortion rate and diameter error increased up to 0.38%, 0.72 mm, respectively. We conclude that periodic quality assurance of geometric distortion should be performed in order to maintain geometric distortion within allowable values.

Measurement of isocenter alignment accuracy and image distortion of an 0.35 T MR-Linac system

For hybrid devices combining magnetic resonance (MR) imaging and a linac for radiation treatment, the isocenter accuracy as well as image distortions have to be checked. This study presents a new phantom to investigate MR-Linacs in a single measurement in terms of (i) isocentricity of the irradiation and (ii) alignment of the irradiation and imaging isocenter relative to each other using polymer dosimetry gel as well as (iii) 3-dimensional (3D) geometric MR image distortions. The evaluation of the irradiated gel was performed immediately after irradiation with the imaging component of the 0.35 T MR-Linac using a T2-weighted turbo spin-echo sequence. Eight plastic grid sheets within the phantom allow for measurement of geometric distortions in 3D by comparing the positions of the grid intersections (control points) within the MR-image with their nominal position obtained from a CT-scan. The distance of irradiation and imaging isocenter in 3D was found to be (0.8 ± 0.9) mm for measurements with 32 image acquisitions. The mean distortion over the whole phantom was (0.60 ± 0.28) mm and 99.8% of the evaluated control points had distortions below 1.5 mm. These geometrical uncertainties have to be considered by additional safety margins.

Safety and Efficacy of MRI Scans in Patients With Implanted Microvascular Coupling Devices.

To demonstrate the safety and compatibility of microvascular couplers in patients undergoing postoperative magnetic resonance imaging (MRI) scans. Retrospective case series. A consecutive review of 1,252 patients undergoing free tissue transfer for head and neck reconstruction at Oregon Health and Sciences University (OHSU) between 2010 and 2017 who had microvascular coupler Synovis, Baxter Deerfield, IL (Synovis Life Technologies, Saint Paul, MN) implantation were reviewed. One hundred fifteen patients had a subsequent MRI scan, which consisted of a variety of Phillips (Amsterdam, Netherlands) MRI machines ranging from 1.0 to 3.0 Tesla (T) in magnetic strength. These 115 patients underwent 121 free flaps with 131 couplers (including 32 flow couplers) utilized for venous anastomoses. Couplers ranged in size from 1.5 to 4.0 mm (3.0 mm [42%] followed by 3.5 mm [21%], 2.5 mm [19%], 2.0 mm [10%], 4.0 mm [6%], and 1.5 mm [2%]. Three hundred fifty-nine MRI scans (2 days to 91 months postoperatively) were obtained with 233 MRIs for cancer surveillance, and the remaining were obtained for neurologic disease, injury, or evaluation for metastases. No complications occurred related to the MRI and the metallic components of the coupler or other metal implants, such as reconstruction bars, vascular clips, or metallic surgical mesh. Additionally, no radiology report commented on MRI distortion due to the coupler placement, which contrasts the distortion seen with the other metallic implants. Microvascular couplers and their constitutive stainless-steel pins have not been found to cause any complications in a large series of consecutive patients undergoing multiple MRIs with magnetic strength up to 3 T. The U.S. Food and Drug Administration advocates medical alert notification for patients with couplers; however, hesitation regarding potential MRI scanning for surveillance or otherwise is unwarranted. 4 Laryngoscope, 130:1428-1430, 2020.

45 Quantification of geometric distortion on MR images and evaluation of the impact of distortion correction

Introduction Magnetic resonance (MR) images have proven very useful for target definition in radiotherapy. However, geometric distortions might be of concern. In this study, a GE software based solution to correct geometric distortions is evaluated. The amount of residual distortions on corrected MRI is then quantified and used to determine PTV margins. Methods Axial T1 gradient-echo sequences of an MR compatible phantom and of patients with brain metastases were acquired on a 3T MRI. All patients were injected with Gadolinium. MR images were corrected for geometric distortion using the default algorithm implemented on our acquisition software, leading to two sets of MR images per acquisition (corrected and uncorrected). The gross tumor volume (GTV) was then contoured by a physician on both corrected and uncorrected MR images of the patients. Acquisition parameters were the ones commonly used in clinical practice for intracranial tumors. The MR phantom external contour was drawn on both corrected and uncorrected MR images, and used to deform uncorrected images to match corrected images. The amplitude of the displacement vector field was used to identify the main regions of the image undergoing large geometric distortions (Figs. 1 and 2). The same work was done on patients using the external surface of the patients. Geometric distortions were quantified using visible markers on both CT and MR images (Fig. 3). Results The main regions affected by geometric distortion were identified using the vector displacement field. These regions are located apart from the machine isocenter in the transverse direction (Figs. 4 and 5). Maximum distortions measured on the phantom for uncorrected MR images ranged from 1 to 2 mm for slices located near the isocenter and until 3 mm for the most distant slices. Distortions remained below 1 mm in corrected MRI. Considering patient images, a maximum distance of 2 mm was observed between the GTVs contoured on both corrected and uncorrected MRI (Fig. 6). Conclusions Our results point out the importance of using a correction for geometric distortions in MR images. Without being corrected for, distortions might reach several millimeters. The correction algorithm we used significantly reduces the amount of distortion in the images, particularly in regions located away from the isocenter. Quantification of residual distortions was made on phantom. However, additional sources of distortions might be of interest when patients are considered as for example the difference in magnetic susceptibility among tissues. We are currently investigating a multimodal approach based on CT-MRI registration to quantify patient-specific distortions. Download : Download high-res image (570KB) Download : Download full-size image

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

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. 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 488Hz/mm at 3T. 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. Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2mm 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 200mm from the isocenter was 2.17mm. For all patients, voxels with distortion shifts of more than 2mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122Hz/mm and 488Hz/mm at 3T. 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 488Hz/mm, respectively. 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.

Development of a dedicated phantom for multi-target single-isocentre stereotactic radiosurgery end to end testing.

PurposeThe aim of this project was to design and manufacture a cost‐effective end‐to‐end (E2E) phantom for quantifying the geometric and dosimetric accuracy of a linear accelerator based, multi‐target single‐isocenter (MTSI) frameless stereotactic radiosurgery (SRS) technique.MethodA perspex Multi‐Plug device from a Sun Nuclear ArcCheck phantom (Sun Nuclear, Melbourne, FL) was enhanced to make it more applicable for MTSI SRS E2E testing. The following steps in the SRS chain were then analysed using the phantom: magnetic resonance imaging (MRI) distortion, planning computed tomography (CT) scan and MRI image registration accuracy, phantom setup accuracy using CBCT, dosimetric accuracy using ion chamber, planar film dose measurements and coincidence of linear accelerator mega‐voltage (MV), and kilo‐voltage (kV) isocenters using Winston‐Lutz testing (WLT).ResultsThe dedicated E2E phantom was able to successfully quantify the geometric and dosimetric accuracy of the MTSI SRS technique. MRI distortions were less than 0.5 mm, or half a voxel size. The average MRI‐CT registration accuracy was 0.15 mm (±0.31 mm), 0.20 mm (±0.16 mm), and 0.39 mm (±0.11 mm) in the superior/inferior, left/right and, anterior/posterior directions, respectively. The phantom setup accuracy using CBCT was better than 0.2 mm and 0.1°. Point dose measurements were within 5% of the treatment planning system predicted dose. The comparison of planar film doses to the planning system dose distributions, performed using gamma analysis, resulted in pass rates greater than 97% for 3%/1 mm gamma criteria. Finally, off‐axis WLT showed MV/kV coincidence to be within 1 mm for off‐axis distances up to 60 mm.ConclusionA novel, versatile and cost‐effective phantom for comprehensive E2E testing of MTSI SRS treatments was developed, incorporating multiple detector types and fiducial markers. The phantom is capable of quantifying the accuracy of each step in the MTSI SRS planning and treatment process.

Assessment of image co-registration accuracy for frameless gamma knife surgery.

Image co-registration is used in frameless gamma knife radiosurgery (GKSRS) to assign a stereotactic coordinate system and verify patient setup before irradiation. The accuracy of co-registration with cone beam computed tomography (CBCT) images of a Gamma Knife IconTM (GK Icon) was assessed, and the effects of the region of co-registration (ROC) were studied. CBCT-to-CBCT co-registration is used for patient setup verification, and its accuracy was examined by co-registering CBCT images taken at various configurations with a reference CBCT series. The accuracy of stereotactic coordinate assignment was investigated by co-registering stereotactic CT images with CBCT images taken at various configurations. An anthropomorphic phantom was used, and the coordinates of fifteen landmarks inside the phantom were measured. The co-registration accuracy between stereotactic magnetic resonance (MR) and CBCT images was evaluated using images from forty-one patients. The positions of the anterior and posterior commissures were measured in both a fiducial marker-based system and a co-registered system. To assess the effects of MR image distortions, co-registration was performed with four different ranges, and the accuracy of the results was compared. Co-registration between CBCT images gave a mean three-dimensional deviation of 0.2 ± 0.1 mm. The co-registration of stereotactic CT images with CBCT images produced a mean deviation of 0.5 ± 0.2 mm. The co-registration of MR images with CBCT images resulted in the smallest three-dimensional difference (0.8 ± 0.3 mm) when a co-registration region covering the skull base area was applied. The image co-registration errors in frameless GKSRS were similar to the imaging errors of frame-based GKSRS. The lower portion of the patient’s head, including the base of the skull, is recommended for the ROC.