Dr Andreas Wetscherek
Group Leader: Magnetic Resonance Imaging in Radiotherapy
Biography
Dr Andreas Wetscherek is leading the new Magnetic Resonance Imaging in Radiotherapy Group at the Institute of Cancer Research. He joined the ICR as a postdoctoral training fellow in 2015 and has been working in the Radiotherapy Physics Modelling Group prior to his current appointment.
During his PhD at the German Cancer Research Center (DKFZ) in Heidelberg, he was the first to characterise microvasculature using flow-compensated diffusion-weighted MRI. To accelerate the technique, he spent six months at the Centro de Imágenes Biomédicas in Santiago de Chile. Dr Wetscherek has led several projects in diffusion-weighted MRI, characterising the diffusion of blood, fat and employing oscillating diffusion gradients.
Following his PhD, Dr Wetscherek continued to work as a postdoc at DKFZ developing 4D MR imaging techniques to quantify regional lung motion in fibrotic lung diseases within a multi-disciplinary project connecting medical physics, radiology and medical informatics.
Dr Wetscherek’s research is focused on developing magnetic resonance imaging techniques for radiotherapy with particular application to the UK’s first MR-Linac, which has been treating patients at the ICR since September 2018. He is interested in characterising day-to-day anatomical variations for treatment adaptation and aims to develop functional imaging techniques to inform cancer therapy by predicting treatment response.
After joining the ICR in 2015, Dr Wetscherek’s research focus shifted towards the applications of MR imaging in radiotherapy, optimising the visibility of both tumour and radiosensitive risk organs. He led the development of several high-contrast T2-weighted 4D MR imaging techniques and their implementation on the Elekta Unity MR-Linac. A particular challenge in this context is to shorten acquisition and reconstruction times to enable integration into the clinical workflow.
Recently, Dr Wetscherek’s group has started working on the development of MR imaging techniques, which are tailored to creating synthetic CT images for adaptation of MR-guided radiotherapy to the patient’s exact position and anatomy of the day.
Andreas enjoys running and playing football within the ICR’s team, if he is not suffering from the rough British climate or the rough English football. If forced indoors, he enjoys a competitive board game, in particular Power Grid or chess. As of April 2019, his FIDE rating sits at 2315.
Dr Wetscherek is a member of the Cancer Research UK Convergence Science Centre, which brings together leading researchers in engineering, physical sciences, life sciences and medicine to develop innovative ways to address challenges in cancer.
Types of Publications
Journal articles
PURPOSE: To characterize the diffusion coefficient of human blood for accurate results in intravoxel incoherent motion imaging. METHODS: Diffusion-weighted MRI of blood samples from 10 healthy volunteers was acquired with a single-shot echo-planar-imaging sequence at body temperature. Effects of gradient profile (monopolar or flow-compensated), diffusion time (40-100 ms), and echo time (60-200 ms) were investigated. RESULTS: Although measured apparent diffusion coefficients of blood were larger for flow-compensated than for monopolar gradients, no dependence of the apparent diffusion coefficient on the diffusion time was found. Large differences between individual samples were observed, with results ranging from 1.26 to 1.66 µm2 /ms for flow-compensated and 0.94 to 1.52 µm2 /ms for monopolar gradients. Statistical analysis indicates correlations of the flow-compensated apparent diffusion coefficient with hematocrit (P = 0.007) and hemoglobin (P = 0.017), but not with mean corpuscular volume (P = 0.64). Results of Monte-Carlo simulations support the experimental observations. CONCLUSIONS: Measured blood apparent diffusion coefficient values depend on hematocrit/hemoglobin concentration and applied gradient profile due to non-Gaussian diffusion. Because in vivo measurement is delicate, an estimation based on blood count results could be an alternative. For intravoxel incoherent motion modeling, the use of a blood self-diffusion constant Db = 1.54 ± 0.12 µm2 /ms for flow-compensated and Db = 1.30 ± 0.18 µm2 /ms for monopolar encoding is suggested. Magn Reson Med 79:2752-2758, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
<h4>Background and purpose</h4>The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing.<h4>Materials and methods</h4>A method was developed to calculate midposition and 4D-T2w images of the whole thorax from continuously acquired axial and sagittal 2D-T2w MRI (1.5 × 1.5 × 5.0 mm<sup>3</sup>). The method employed image-derived respiratory surrogates, deformable image registration and super-resolution reconstruction. Volunteer imaging and a respiratory motion phantom were used for validation. The minimum number of dynamic acquisitions needed to calculate a representative midposition image was investigated by retrospectively subsampling the data (10-30 dynamic acquisitions).<h4>Results</h4>Super-resolution 4D-T2w MRI (1.0 × 1.0 × 1.0 mm<sup>3</sup>, 8 respiratory phases) did not suffer from data incompleteness and exhibited reduced stitching artefacts compared to sorted multi-slice MRI. Experiments using a respiratory motion phantom and colour-intensity projection images demonstrated a minor underestimation of the motion range. Midposition diaphragm differences in retrospectively subsampled acquisitions were <1.1 mm compared to the full dataset. 10 dynamic acquisitions were found sufficient to generate midposition MRI.<h4>Conclusions</h4>A motion-modelling and super-resolution method was developed to calculate high quality 4D/midposition T2w MRI from orthogonal 2D-T2w MRI.
<h4>Objectives</h4>The purpose of our study was to assess proton density (PD) and T2 relaxation time of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP) and to evaluate their utility in differentiating the two patterns. Furthermore, we aim to investigate whether these two parameters could help differentiate active-inflammatory and stable-fibrotic lesions in NSIP.<h4>Methods</h4>32 patients (mean age: 69 years; M:F, 1:1) with pathologically proven disease (UIP:NSIP, 1:1), underwent thoracic thin-section multislice CT scan and 1.5T MRI. A total of 437 regions-of-interest (ROIs) were classified at CT as advanced, moderate or mild alterations. Based on multi-echo single-shot TSE sequence acquired at five echo times, with breath-holding at end-expiration and ECG-triggering, entire lung T2 and PD maps were generated from each subject. The T2 relaxation time and the respective signal intensity were quantified by performing a ROI measurement on the T2 and PD maps in the corresponding CT selected areas of the lung.<h4>Results</h4>UIP and NSIP regional patterns could not be differentiated by T2 relaxation times or PD values alone. Overall, a strong positive correlation was found between T2 relaxation and PD in NSIP, r = 0.64, p<0.001; however, this correlation was weak in UIP, r = 0.20, p = 0.01. T2 relaxation showed significant statistical difference between active-inflammatory and stable-fibrotic NSIP regions at all levels, p<0.05, while for the analysis of ventral lesions PD proved no statistical difference, p>0.05.<h4>Conclusions</h4>T2 relaxation times and PD values may provide helpful quantitative information for differentiating NSIP from UIP pattern. These parameters have the potential to differentiate active-inflammatory and stable-fibrotic lesions in NSIP.
<h4>Purpose</h4>Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed.<h4>Methods</h4>The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUV<sub>mean</sub>, SUV<sub>max</sub>, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio.<h4>Results</h4>For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUV<sub>mean</sub>, SUV<sub>max</sub>, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively.<h4>Conclusions</h4>Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.
Despite the utility of tumour characterisation using quantitative parameter maps from multi-b-value diffusion-weighted MRI (DWI), clinicians often prefer the use of the image with highest diffusion-weighting (b-value), for instance for defining regions of interest (ROIs). However, these images are typically degraded by noise, as they do not utilize the information from the full acquisition. We present a principal component analysis (PCA) approach for model-free denoising of DWI data. PCA-denoising was compared to synthetic MRI, where a diffusion model is fitted for each voxel and a denoised image at a given b-value is generated from the model fit. A quantitative comparison of systematic and random errors was performed on data simulated using several diffusion models (mono-exponential, bi-exponential, stretched-exponential and kurtosis). A qualitative visual comparison was also performed for in vivo images in six healthy volunteers and three pancreatic cancer patients. In simulations, the reduction in random errors from PCA-denoising was substantial (up to 55%) and similar to synthetic MRI (up to 53%). Model-based synthetic MRI denoising resulted in substantial (up to 29% of signal) systematic errors, whereas PCA-denoising was able to denoise without introducing systematic errors (less than 2%). In vivo, the signal-to-noise ratio (SNR) and sharpness of PCA-denoised images were superior to synthetic MRI, resulting in clearer tumour boundaries. In the presence of motion, PCA-denoising did not cause image blurring, unlike image averaging or synthetic MRI. Multi-b-value MRI can be denoised model-free with our PCA-denoising strategy that reduces noise to a level similar to synthetic MRI, but without introducing systematic errors associated with the synthetic MRI method.
<h4>Background</h4>Studies on intravoxel incoherent motion (IVIM) imaging are carried out with different acquisition protocols.<h4>Purpose</h4>To investigate the dependence of IVIM parameters on the B<sub>0</sub> field strength when using a bi- or triexponential model.<h4>Study type</h4>Prospective.<h4>Study population</h4>20 healthy volunteers (age: 19-28 years).<h4>Field strength/sequence</h4>Volunteers were examined at two field strengths (1.5 and 3T). Diffusion-weighted images of the abdomen were acquired at 24 b-values ranging from 0.2 to 500 s/mm<sup>2</sup> .<h4>Assessment</h4>ROIs were manually drawn in the liver. Data were fitted with a bi- and a triexponential IVIM model. The resulting parameters were compared between both field strengths.<h4>Statistical tests</h4>One-way analysis of variance (ANOVA) and Kruskal-Wallis test were used to test the obtained IVIM parameters for a significant field strength dependency.<h4>Results</h4>At b-values below 6 s/mm<sup>2</sup> , the triexponential model provided better agreement with the data than the biexponential model. The average tissue diffusivity was D = 1.22/1.00 μm<sup>2</sup> /msec at 1.5/3T. The average pseudodiffusion coefficients for the biexponential model were D<sup>*</sup> = 308/260 μm<sup>2</sup> /msec at 1.5/3T; and for the triexponential model D1* = 81.3/65.9 μm<sup>2</sup> /msec, D2* = 2453/2333 μm<sup>2</sup> /msec at 1.5/3T. The average perfusion fractions for the biexponential model were f = 0.286/0.303 at 1.5/3T; and for the triexponential model f<sub>1</sub> = 0.161/0.174 and f<sub>2</sub> = 0.152/0.159 at 1.5/3T. A significant B<sub>0</sub> dependence was only found for the biexponential pseudodiffusion coefficient (ANOVA/KW P = 0.037/0.0453) and tissue diffusivity (ANOVA/KW: P < 0.001).<h4>Data conclusion</h4>Our experimental results suggest that triexponential pseudodiffusion coefficients and perfusion fractions obtained at different field strengths could be compared across different studies using different B<sub>0</sub> . However, it is recommended to take the field strength into account when comparing tissue diffusivities or using the biexponential IVIM model. Considering published values for oxygenation-dependent transversal relaxation times of blood, it is unlikely that the two blood compartments of the triexponential model represent venous and arterial blood.<h4>Level of evidence</h4>1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1883-1892.
CT-based radiotherapy workflow is limited by poor soft tissue definition in the pelvis and reliance on rigid registration methods. Current image-guided radiotherapy and adaptive radiotherapy models therefore have limited ability to improve clinical outcomes. The advent of MRI-guided radiotherapy solutions provides the opportunity to overcome these limitations with the potential to deliver online real-time MRI-based plan adaptation on a daily basis, a true "plan of the day." This review describes the application of MRI guided radiotherapy in two pelvic tumour sites likely to benefit from this approach.
MR-guided radiotherapy treatment planning utilises the high soft-tissue contrast of MRI to reduce uncertainty in delineation of the target and organs at risk. Replacing 4D-CT with MRI-derived synthetic 4D-CT would support treatment plan adaptation on hybrid MR-guided radiotherapy systems for inter- and intrafractional differences in anatomy and respiration, whilst mitigating the risk of CT to MRI registration errors. Three methods were devised to calculate synthetic 4D and midposition (time-weighted mean position of the respiratory cycle) CT from 4D-T1w and Dixon MRI. The first approach employed intensity-based segmentation of Dixon MRI for bulk-density assignment (sCT<sub>D</sub>). The second step added spine density information using an atlas of CT and Dixon MRI (sCT<sub>DS</sub>). The third iteration used a polynomial function relating Hounsfield units and normalised T1w image intensity to account for variable lung density (sCT<sub>DSL</sub>). Motion information in 4D-T1w MRI was applied to generate synthetic CT in midposition and in twenty respiratory phases. For six lung cancer patients, synthetic 4D-CT was validated against 4D-CT in midposition by comparison of Hounsfield units and dose-volume metrics. Dosimetric differences found by comparing sCT<sub>D,DS,DSL</sub> and CT were evaluated using a Wilcoxon signed-rank test (p = 0.05). Compared to sCT<sub>D</sub> and sCT<sub>DS</sub>, planning on sCT<sub>DSL</sub> significantly reduced absolute dosimetric differences in the planning target volume metrics to less than 98 cGy (1.7% of the prescribed dose) on average. When comparing sCT<sub>DSL</sub> and CT, average radiodensity differences were within 97 Hounsfield units and dosimetric differences were significant only for the planning target volume D99% metric. All methods produced clinically acceptable results for the organs at risk in accordance with the UK SABR consensus guidelines and the LungTech EORTC phase II trial. The overall good agreement between sCT<sub>DSL</sub> and CT demonstrates the feasibility of employing synthetic 4D-CT for plan adaptation on hybrid MR-guided radiotherapy systems.
Diffusion anisotropy in diffusion tensor imaging (DTI) is commonly quantified with normalized diffusion anisotropy indices (DAIs). Most often, the fractional anisotropy (FA) is used, but several alternative DAIs have been introduced in attempts to maximize the contrast-to-noise ratio (CNR) in diffusion anisotropy maps. Examples include the scaled relative anisotropy (sRA), the gamma variate anisotropy index (GV), the surface anisotropy (UA<sub>surf</sub>), and the lattice index (LI). With the advent of multidimensional diffusion encoding it became possible to determine the presence of microscopic diffusion anisotropy in a voxel, which is theoretically independent of orientation coherence. In accordance with DTI, the microscopic anisotropy is typically quantified by the microscopic fractional anisotropy (μFA). In this work, in addition to the μFA, the four microscopic diffusion anisotropy indices (μDAIs) μsRA, μGV, μUA<sub>surf</sub>, and μLI are defined in analogy to the respective DAIs by means of the average diffusion tensor and the covariance tensor. Simulations with three representative distributions of microscopic diffusion tensors revealed distinct CNR differences when differentiating between isotropic and microscopically anisotropic diffusion. q-Space trajectory imaging (QTI) was employed to acquire brain in-vivo maps of all indices. For this purpose, a 15min protocol featuring linear, planar, and spherical tensor encoding was used. The resulting maps were of good quality and exhibited different contrasts, e.g. between gray and white matter. This indicates that it may be beneficial to use more than one μDAI in future investigational studies.
<h4>Background</h4>Magnetic Resonance linear accelerator (MR-linac) systems represent a new type of technology that allows for online MR-guidance for high precision radiotherapy (RT). Currently, the first MR-linac installations are being introduced clinically. Since the imaging performance of these integrated MR-linac systems is critical for their application, a thorough commissioning of the MRI performance is essential. However, guidelines on the commissioning of MR-guided RT systems are not yet defined and data on the performance of MR-linacs are not yet available.<h4>Materials & methods</h4>Here we describe a comprehensive commissioning protocol, which contains standard MRI performance measurements as well as dedicated hybrid tests that specifically assess the interactions between the Linac and the MRI system. The commissioning results of four MR-linac systems are presented in a multi-center study.<h4>Results</h4>Although the four systems showed similar performance in all the standard MRI performance tests, some differences were observed relating to the hybrid character of the systems. Field homogeneity measurements identified differences in the gantry shim configuration, which was later confirmed by the vendor.<h4>Conclusion</h4>Our results highlight the importance of dedicated hybrid commissioning tests and the ability to compare the machines between institutes at this very early stage of clinical introduction. Until formal guidelines and tolerances are defined the tests described in this study may be used as a practical guideline. Moreover, the multi-center results provide initial bench mark data for future MR-linac installations.
2D cine MR imaging may be utilized to monitor rapidly moving tumors and organs-at-risk for real-time adaptive radiotherapy. This study systematically investigates the impact of geometric imaging parameters on the ability of 2D cine MR imaging to guide template-matching-driven autocontouring of lung tumors and abdominal organs. Abdominal 4D MR images were acquired of six healthy volunteers and thoracic 4D MR images were obtained of eight lung cancer patients. At each breathing phase of the images, the left kidney and gallbladder or lung tumor, respectively, were outlined as volumes of interest. These images and contours were used to create artificial 2D cine MR images, while simultaneously serving as 3D ground truth. We explored the impact of five different imaging parameters (pixel size, slice thickness, imaging plane orientation, number and relative alignment of images as well as strategies to create training images). For each possible combination of imaging parameters, we generated artificial 2D cine MR images as training and test images. A template-matching algorithm used the training images to determine the tumor or organ position in the test images. Subsequently, a 3D base contour was shifted to the determined position and compared to the ground truth via centroid distance and Dice similarity coefficient. The median centroid distance between adapted and ground truth contours was 1.56 mm for the kidney, 3.81 mm for the gallbladder and 1.03 mm for the lung tumor (median Dice similarity coefficient: 0.95, 0.72 and 0.93). We observed that a decrease in image resolution led to a modest decrease in localization accuracy, especially for the small gallbladder. However, for all volumes of interest localization accuracy varied substantially more between subjects than due to the different imaging parameters. Automated tumor and organ localization using 2D cine MR imaging and template-matching-based autocontouring is robust against variation of geometric imaging parameters. Future work and optimization efforts of 2D cine MR imaging for real-time adaptive radiotherapy is needed to characterize the influence of sequence- and anatomical site-specific imaging contrast.
Radiotherapy remains the cornerstone of curative treatment for inoperable locally advanced lung cancer, given concomitantly with platinum-based chemotherapy. With poor overall survival, research efforts continue to explore whether integration of advanced radiation techniques will assist safe treatment intensification with the potential for improving outcomes. One advance is the integration of magnetic resonance imaging (MRI) in the treatment pathway, providing anatomical and functional information with excellent soft tissue contrast without exposure of the patient to radiation. MRI may complement or improve the diagnostic staging accuracy of F-18 fluorodeoxyglucose position emission tomography and computerized tomography imaging, particularly in assessing local tumour invasion and is also effective for identification of nodal and distant metastatic disease. Incorporating anatomical MRI sequences into lung radiotherapy treatment planning is a novel application and may improve target volume and organs at risk delineation reproducibility. Furthermore, functional MRI may facilitate dose painting for heterogeneous target volumes and prediction of normal tissue toxicity to guide adaptive strategies. MRI sequences are rapidly developing and although the issue of intra-thoracic motion has historically hindered the quality of MRI due to the effect of motion, progress is being made in this field. Four-dimensional MRI has the potential to complement or supersede 4D CT and 4D F-18-FDG PET, by providing superior spatial resolution. A number of MR-guided radiotherapy delivery units are now available, combining a radiotherapy delivery machine (linear accelerator or cobalt-60 unit) with MRI at varying magnetic field strengths. This novel hybrid technology is evolving with many technical challenges to overcome. It is anticipated that the clinical benefits of MR-guided radiotherapy will be derived from the ability to adapt treatment on the fly for each fraction and in real-time, using 'beam-on' imaging. The lung tumour site group of the Atlantic MR-Linac consortium is working to generate a challenging MR-guided adaptive workflow for multi-institution treatment intensification trials in this patient group.
<h4>Background and purpose</h4>Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients.<h4>Material and methods</h4>Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty.<h4>Results</h4>Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance.<h4>Conclusion</h4>Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance.
Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.
<h4>Objectives</h4>The aim of this study was to develop and verify a method to obtain good temporal resolution T2-weighted 4-dimensional (4D-T2w) magnetic resonance imaging (MRI) by using motion information from T1-weighted 4D (4D-T1w) MRI, to support treatment planning in MR-guided radiotherapy.<h4>Materials and methods</h4>Ten patients with primary non-small cell lung cancer were scanned at 1.5 T axially with a volumetric T2-weighted turbo spin echo sequence gated to exhalation and a volumetric T1-weighted stack-of-stars spoiled gradient echo sequence with golden angle spacing acquired in free breathing. From the latter, 20 respiratory phases were reconstructed using the recently developed 4D joint MoCo-HDTV algorithm based on the self-gating signal obtained from the k-space center. Motion vector fields describing the respiratory cycle were obtained by deformable image registration between the respiratory phases and projected onto the T2-weighted image volume. The resulting 4D-T2w volumes were verified against the 4D-T1w volumes: an edge-detection method was used to measure the diaphragm positions; the locations of anatomical landmarks delineated by a radiation oncologist were compared and normalized mutual information was calculated to evaluate volumetric image similarity.<h4>Results</h4>High-resolution 4D-T2w MRI was obtained. Respiratory motion was preserved on calculated 4D-T2w MRI, with median diaphragm positions being consistent with less than 6.6 mm (2 voxels) for all patients and less than 3.3 mm (1 voxel) for 9 of 10 patients. Geometrical positions were coherent between 4D-T1w and 4D-T2w MRI as Euclidean distances between all corresponding anatomical landmarks agreed to within 7.6 mm (Euclidean distance of 2 voxels) and were below 3.8 mm (Euclidean distance of 1 voxel) for 355 of 470 pairs of anatomical landmarks. Volumetric image similarity was commensurate between 4D-T1w and 4D-T2w MRI, as mean percentage differences in normalized mutual information (calculated over all respiratory phases and patients), between corresponding respiratory phases of 4D-T1w and 4D-T2w MRI and the tie-phase of 4D-T1w and 3-dimensional T2w MRI, were consistent to 0.41% ± 0.37%. Four-dimensional T2w MRI displayed tumor extent, structure, and position more clearly than corresponding 4D-T1w MRI, especially when mobile tumor sites were adjacent to organs at risk.<h4>Conclusions</h4>A methodology to obtain 4D-T2w MRI that retrospectively applies the motion information from 4D-T1w MRI to 3-dimensional T2w MRI was developed and verified. Four-dimensional T2w MRI can assist clinicians in delineating mobile lesions that are difficult to define on 4D-T1w MRI, because of poor tumor-tissue contrast.
<h4>Purpose</h4>The pseudo-diffusion coefficient D* in intravoxel incoherent motion (IVIM) imaging was found difficult to seize. Flow-compensated diffusion gradients were used to test the validity of the commonly assumed biexponential limit and to determine not only D*, but also characteristic timescale τ and velocity v of the incoherent motion.<h4>Theory and methods</h4>Bipolar and flow-compensated diffusion gradients were inserted into a flow-compensated single-shot EPI sequence. Images were obtained from a pipe-shaped flow phantom and from healthy volunteers. To calculate the IVIM signal outside the biexponential limit, a formalism based on normalized phase distributions was developed.<h4>Results</h4>The flow-compensated diffusion gradients caused less signal attenuation than the bipolar ones. A signal dependence on the duration of the flow-compensated gradients was found at low b-values in the volunteer datasets. The characteristic IVIM parameters were estimated to be v = 4.60 ± 0.34 mm/s and τ = 144 ± 10 ms for liver and v = 3.91 ± 0.54 mm/s and τ = 224 ± 47 ms for pancreas.<h4>Conclusion</h4>Our results strongly indicate that the biexponential limit does not adequately model the diffusion signal in liver and pancreas. By using both bipolar and flow-compensated diffusion gradients of different duration, the characteristic timescale and velocity of the incoherent motion can be determined.
<h4>Purpose</h4>To develop four-dimensional (4D) respiratory time-resolved MRI based on free-breathing acquisition of radial MR data with very high undersampling.<h4>Methods</h4>We propose the 4D joint motion-compensated high-dimensional total variation (4D joint MoCo-HDTV) algorithm, which alternates between motion-compensated image reconstruction and artifact-robust motion estimation at multiple resolution levels. The algorithm is applied to radial MR data of the thorax and upper abdomen of 12 free-breathing subjects with acquisition times between 37 and 41 s and undersampling factors of 16.8. Resulting images are compared with compressed sensing-based 4D motion-adaptive spatio-temporal regularization (MASTeR) and 4D high-dimensional total variation (HDTV) reconstructions.<h4>Results</h4>For all subjects, 4D joint MoCo-HDTV achieves higher similarity in terms of normalized mutual information and cross-correlation than 4D MASTeR and 4D HDTV when compared with reference 4D gated gridding reconstructions with 8.4 ± 1.1 times longer acquisition times. In a qualitative assessment of artifact level and image sharpness by two radiologists, 4D joint MoCo-HDTV reveals higher scores (P < 0.05) than 4D HDTV and 4D MASTeR at the same undersampling factor and the reference 4D gated gridding reconstructions, respectively.<h4>Conclusions</h4>4D joint MoCo-HDTV enables time-resolved image reconstruction of free-breathing radial MR data with undersampling factors of 16.8 while achieving low-streak artifact levels and high image sharpness. Magn Reson Med 77:1170-1183, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
<h4>Purpose</h4>Flow-compensated (FC) diffusion-weighted MRI (DWI) for intravoxel-incoherent motion (IVIM) modeling allows for a more detailed description of tissue microvasculature than conventional IVIM. The long acquisition time of current FC-IVIM protocols, however, has prohibited clinical application. Therefore, we developed an optimized abdominal FC-IVIM acquisition with a clinically feasible scan time.<h4>Methods</h4>Precision and accuracy of the FC-IVIM parameters were assessed by fitting the FC-IVIM model to signal decay curves, simulated for different acquisition schemes. Diffusion-weighted acquisitions were added subsequently to the protocol, where we chose the combination of b-value, diffusion time and gradient profile (FC or bipolar) that resulted in the largest improvement to its accuracy and precision. The resulting two optimized FC-IVIM protocols with 25 and 50 acquisitions (FC-IVIM<sub>opt25</sub> and FC-IVIM<sub>opt50</sub> ), together with a complementary acquisition consisting of 50 diffusion-weighting (FC-IVIM<sub>comp</sub> ), were acquired in repeated abdominal free-breathing FC-IVIM imaging of seven healthy volunteers. Intersession and intrasession within-subject coefficient of variation of the FC-IVIM parameters were compared for the liver, spleen, and kidneys.<h4>Results</h4>Simulations showed that the performance of FC-IVIM improved in tissue with larger perfusion fraction and signal-to-noise ratio. The scan time of the FC-IVIM<sub>opt25</sub> and FC-IVIM<sub>opt50</sub> protocols were 8 and 16 min. The best in vivo performance was seen in FC-IVIM<sub>opt50</sub> . The intersession within-subject coefficients of variation of FC-IVIM<sub>opt50</sub> were 11.6%, 16.3%, 65.5%, and 36.0% for FC-IVIM model parameters diffusivity, perfusion fraction, characteristic time and blood flow velocity, respectively.<h4>Conclusions</h4>We have optimized the FC-IVIM protocol, allowing for clinically feasible scan times (8-16 min).
<h4>Purpose</h4>Diffusion times longer than 50 ms are typically probed with stimulated-echo sequences. Varying the diffusion time in stimulated-echo sequences affects the T<sub>1</sub> weighting of subcompartments, complicating the analysis of diffusion time dependence. Although inversion recovery preparation could be used to change the T<sub>1</sub> weighting, it cannot ensure equal T<sub>1</sub> weighting at arbitrary mixing times. In this article, a sequence that ensures constant T<sub>1</sub> weighting over a wide range of diffusion times is presented.<h4>Methods</h4>The proposed sequence features 2 independent longitudinal storage periods: TM<sub>1</sub> and TM<sub>2</sub> . Diffusion encoding is performed during TM<sub>1</sub> , effectively coupling the diffusion time and TM<sub>1</sub> . Equal T<sub>1</sub> weighting at arbitrary diffusion times is realized by keeping the total mixing time TM<sub>1</sub> + TM<sub>2</sub> constant. The sequence was compared with conventional stimulated-echo measurements of diffusion in a 2-compartment phantom consisting of distilled water and paraffinum perliquidum. Additionally, in vivo DTI of the brain was carried out for 8 healthy volunteers with diffusion times ranging from 50 to 500 ms.<h4>Results</h4>Diffusion time dependence of the axial and radial diffusivity was detected in the brain. Both sequences resulted in almost identical diffusivities in white matter. In regions containing partial volumes of gray and white matter, a dependency on T<sub>1</sub> weighting was observed.<h4>Conclusion</h4>In accordance with previous studies, little variance of T<sub>1</sub> values appeared to be present in healthy white matter. However, this is likely different in diseased tissue. Here, the proposed sequence can be effective in differentiating between diffusion time dependence and T<sub>1</sub> weighting effects.
BACKGROUND AND PURPOSE:Anatomical changes during external beam radiotherapy prevent the accurate delivery of the intended dose distribution. Resolving the delivered dose, which is currently unknown, is crucial to link radiotherapy doses to clinical outcomes and ultimately improve the standard of care. MATERIAL AND METHODS:In this study, we present a dose reconstruction workflow based on data routinely acquired during MR-guided radiotherapy. It employs 3D MR images, 2D cine MR images and treatment machine log files to calculate the delivered dose taking intrafractional motion into account. The developed pipeline was used to measure anatomical changes and assess their dosimetric impact in 89 prostate radiotherapy fractions delivered with a 1.5 T MR-linac at our institute. RESULTS:Over the course of radiation delivery, the CTV shifted 0.6 mm ± 2.1 mm posteriorly and 1.3 mm ± 1.5 mm inferiorly. When extrapolating the dose changes in each case to 20 fractions, the mean clinical target volume D98% and clinical target volume D50% dose-volume metrics decreased by 1.1 Gy ± 1.6 Gy and 0.1 Gy ± 0.2 Gy, respectively. Bladder D3% did not change (0.0 Gy ± 1.2 Gy), while rectum D3% decreased by 1.0 Gy ± 2.0 Gy. Although anatomical changes and their dosimetric impact were small in the majority of cases, large intrafractional motion caused the delivered dose to substantially deviate from the intended plan in some fractions. CONCLUSIONS:The presented end-to-end workflow is able to reliably, non-invasively and automatically reconstruct the delivered prostate radiotherapy dose by processing MR-linac treatment log files and online MR images. In the future, we envision this workflow to be adapted to other cancer sites and ultimately to enter widespread clinical use.
<h4>Objective</h4>To analyse delayed contrast dynamics of fibrotic lesions in interstitial lung disease (ILD) using five dimensional (5D) MRI and to correlate contrast dynamics with disease severity.<h4>Methods</h4>20 patients (mean age: 71 years; M:F, 13:7), with chronic fibrosing ILD: <i>n</i> = 12 idiopathic pulmonary fibrosis (IPF) and <i>n</i> = 8 non-IPF, underwent thin-section multislice CT as part of the standard diagnostic workup and additionally MRI of the lung. 2 min after contrast injection, a radial gradient echo sequence with golden-angle spacing was acquired during 5 min of free-breathing, followed by 5D image reconstruction. Disease was categorized as severe or non-severe according to CT morphological regional severity. For each patient, 10 lesions were analysed.<h4>Results</h4>IPF lesions showed later peak enhancement compared to non-IPF (severe: <i>p</i> = 0.01, non-severe: <i>p</i> = 0.003). Severe lesions showed later peak enhancement compared to non-severe lesions, in non-IPF (<i>p</i> = 0.04), but not in IPF (<i>p</i> = 0.35). There was a tendency towards higher accumulation and washout rates in IPF compared to non-IPF in non-severe disease. Severe lesions had lower washout rate than non-severe ones in both IPF (<i>p</i> = 0.003) and non-IPF (<i>p</i> = 0.005). Continuous contrast agent accumulation, without washout, was found only in IPF lesions.<h4>Conclusions</h4>Contrast agent dynamics are influenced by type and severity of pulmonary fibrosis, which might enable a more thorough characterisation of disease burden. The regional impairment is of particular interest in the context of antifibrotic treatments and was characterised using a non-invasive, non-irradiating, free-breathing method.<h4>Advances in knowledge</h4>Delayed contrast enhancement patterns allow the assessment of regional lung impairment which could represent different disease stages or phenotypes in ILD.
An MR-Linac can provide motion information of tumour and organs-at-risk before, during, and after beam delivery. However, MR imaging cannot provide real-time high-quality volumetric images which capture breath-to-breath variability of respiratory motion. Surrogate-driven motion models relate the motion of the internal anatomy to surrogate signals, thus can estimate the 3D internal motion from these signals. Internal surrogate signals based on patient anatomy can be extracted from 2D cine-MR images, which can be acquired on an MR-Linac during treatment, to build and drive motion models. In this paper we investigate different MRI-derived surrogate signals, including signals generated by applying principal component analysis to the image intensities, or control point displacements derived from deformable registration of the 2D cine-MR images. We assessed the suitability of the signals to build models that can estimate the motion of the internal anatomy, including sliding motion and breath-to-breath variability. We quantitatively evaluated the models by estimating the 2D motion in sagittal and coronal slices of 8 lung cancer patients, and comparing them to motion measurements obtained from image registration. For sagittal slices, using the first and second principal components on the control point displacements as surrogate signals resulted in the highest model accuracy, with a mean error over patients around 0.80 mm which was lower than the in-plane resolution. For coronal slices, all investigated signals except the skin signal produced mean errors over patients around 1 mm. These results demonstrate that surrogate signals derived from 2D cine-MR images, including those generated by applying principal component analysis to the image intensities or control point displacements, can accurately model the motion of the internal anatomy within a single sagittal or coronal slice. This implies the signals should also be suitable for modelling the 3D respiratory motion of the internal anatomy.
<h4>Background and purpose</h4>Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems.<h4>Materials and methods</h4>Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients.<h4>Results</h4>On the Unity system, a maximum b-value of 500 s/mm<sup>2</sup> should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment.<h4>Conclusion</h4>We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.
<h4>Purpose</h4>To find an optimized b-value distribution for reproducible triexponential intravoxel incoherent motion (IVIM) exams in the liver.<h4>Methods</h4>A numeric optimization of b-value distributions was performed using the triexponential IVIM equation and 27 different IVIM parameter sets. Starting with an initially optimized distribution of 6 b-values, the number of b-values was increased stepwise. Each new b-value was chosen from a set of 64 predefined b-values based on the computed summed relative mean error of the fitted triexponential IVIM parameters. This process was repeated for up to 100 b-values. In simulations and in vivo measurements, optimized b-value distributions were compared to 4 representative distributions found in literature.<h4>Results</h4>The first 16 optimized b-values were 0, 0.3, 0.3, 70, 200, 800, 70, 1, 3.5, 5, 70, 1.2, 6, 45, 1.5, and 60 in units of s/mm<sup>2</sup> . Low b-values were much more frequent than high b-values. The optimized b-value distribution resulted in a higher fit stability compared to distributions used in literature in both, simulation and in vivo measurements. Using more than 6 b-values, ideally 16 or more, increased the fit stability considerably.<h4>Conclusion</h4>Using optimized b-values, the fit uncertainty in triexponential IVIM can be largely reduced. Ideally, 16 or more b-values should be acquired.
<h4>Background and purpose</h4>Magnetic 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.<h4>Materials and methods</h4>MRI 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.<h4>Results</h4>For 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.<h4>Conclusions</h4>This 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.
Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.
<h4>Purpose</h4>Intravoxel incoherent motion (IVIM) studies are performed with different acquisition protocols. Comparing them requires knowledge of echo time (TE) dependencies. The TE-dependence of the biexponential perfusion fraction f is well-documented, unlike that of its triexponential counterparts f<sub>1</sub> and f<sub>2</sub> and the biexponential and triexponential pseudodiffusion coefficients D<sup>*</sup> , D1∗ , and D2∗ . The purpose was to investigate the TE-dependence of these parameters and to check whether the triexponential pseudodiffusion compartments are associated with arterial and venous blood.<h4>Methods</h4>Fifteen healthy volunteers (19-58 y; mean: 24.7 y) underwent diffusion-weighted imaging of the abdomen with 24 b-values (0.2-800 s/mm<sup>2</sup> ) at TEs of 45, 60, 75, and 90 ms. Regions of interest (ROIs) were manually drawn in the liver. One set of bi- and triexponential IVIM parameters per volunteer and TE was determined. The TE-dependence was assessed with the Kruskal-Wallis test.<h4>Results</h4>TE-dependence was observed for f (P < .001), f<sub>1</sub> (P = .001), and f<sub>2</sub> (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f<sub>1</sub> : 0.113/0.139/0.146/0.205, f<sub>2</sub> : 0.115/0.155/0.182/0.194. D, D<sup>*</sup> , D1∗ , and D2∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10<sup>-4</sup> mm<sup>2</sup> /s): 9.45/9.63/9.75/9.41, biexponential D<sup>*</sup> (10<sup>-2</sup> mm<sup>2</sup> /s): 5.26/5.52/6.13/5.82, triexponential D1∗ (10<sup>-2</sup> mm<sup>2</sup> /s): 1.73/2.91/2.25/2.51, triexponential D2∗ (mm<sup>2</sup> /s): 0.478/1.385/0.616/0.846.<h4>Conclusion</h4>f<sub>1</sub> and f<sub>2</sub> show similar TE-dependence as f, ie, increase with rising TE; an effect that must be accounted for when comparing different studies. The diffusion and pseudodiffusion coefficients might be compared without TE correction. Because of the similar TE-dependence of f<sub>1</sub> and f<sub>2</sub> , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.
<h4>Purpose</h4>Daily quantitative MR imaging during radiotherapy of cancer patients has become feasible with MRI systems integrated with linear accelerators (MR-linacs). Quantitative images could be used for treatment response monitoring. With intravoxel incoherent motion (IVIM) MRI, it is possible to acquire perfusion information without the use of contrast agents. In this multicenter study, daily IVIM measurements were performed in prostate cancer patients to identify changes that potentially reflect response to treatment.<h4>Materials and methods</h4>Forty-three patients were included, treated with 20 fractions of 3 Gy on a 1.5 T MR-linac. IVIM measurements were performed on each treatment day. The diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) were calculated based on the median signal intensities in the non-cancerous prostate and the tumor. Repeatability coefficients (RCs) were determined based on the first two treatment fractions. Separate linear mixed-effects models were constructed for the three IVIM parameters.<h4>Results</h4>In total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10<sup>-3</sup> mm<sup>2</sup>/s, 0.086, and 28.7 × 10<sup>-3</sup> mm<sup>2</sup>/s in the non-cancerous prostate and 1.19 × 10<sup>-3</sup> mm<sup>2</sup>/s, 0.088, and 28.9 × 10<sup>-3</sup> mm<sup>2</sup>/s in the tumor, for D, f, and D*, respectively. The repeatability coefficients for D, f, and D* in the non-cancerous prostate were 0.09 × 10<sup>-3</sup> mm<sup>2</sup>/s, 0.05, and 15.3 × 10<sup>-3</sup> mm<sup>2</sup>/s. In the tumor, these values were 0.44 × 10<sup>-3</sup> mm<sup>2</sup>/s, 0.16, and 76.4 × 10<sup>-3</sup> mm<sup>2</sup>/s. The mixed effects analysis showed an increase in D of the tumors over the course of treatment, while remaining stable in the non-cancerous prostate. The f and D* increased in both the non-cancerous prostate and tumor.<h4>Conclusions</h4>It is feasible to perform daily IVIM measurements on an MR-linac system. Although the repeatability coefficients were high, changes in IVIM perfusion parameters were measured on a group level, indicating that IVIM has potential for measuring treatment response.
<h4>Background and purpose</h4>Magnetic resonance imaging integrated linear accelerator (MR-Linac) platforms enable acquisition of diffusion weighted imaging (DWI) during treatment providing potential information about treatment response. Obtaining DWI on these platforms is technically different from diagnostic magnetic resonance imaging (MRI) scanners. The aim of this project was to determine feasibility of obtaining DWI and calculating apparent diffusion coefficient (ADC) parameters longitudinally in rectal cancer patients on the MR-Linac.<h4>Materials and methods</h4>Nine patients undergoing treatment on MR-Linac had DWI acquired using b-values 0, 30, 150, 500 s/mm<sup>2</sup>. Gross tumour volume (GTV) and normal tissue was delineated on DWI throughout treatment and median ADC was calculated using an in-house tool (pyOsirix ®).<h4>Results</h4>Seven out of nine patients were included in the analysis; all demonstrated downstaging at follow-up. A total of 63 out of 70 DWI were analysed (7 excluded due to poor image quality). An increasing trend of ADC median for GTV (1.15 × 10<sup>-3</sup> mm<sup>2</sup>/s interquartile range (IQ): 1.05-1.17 vs 1.59 × 10<sup>-3</sup> mm<sup>2</sup>/s IQ: 1.37 - 1.64; <i>p = 0.0156</i>), correlating to treatment response. In comparison ADC median for normal tissue remained the same between first and last fraction (1.61 × 10<sup>-3</sup> mm<sup>2</sup>/s IQ: 1.56-1.71 vs 1.67 × 10<sup>-3</sup> mm<sup>2</sup>/s IQ: 1.37-2.00; p = 0.9375).<h4>Conclusions</h4>DWI assessment in rectal cancer patients on MR-Linac is feasible. Initial results provide foundations for further studies to determine DWI use for treatment adaptation in rectal cancer.
BACKGROUND AND PURPOSE: 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. METHODS: Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. RESULTS: For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. CONCLUSION: Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.
OBJECTIVE: We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). METHODS: A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). RESULTS: Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. CONCLUSIONS: The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
<h4>Background and purpose</h4>The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it.<h4>Materials and methods</h4>Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm<sup>2</sup>, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CV<sub>D</sub>) and calculation methods (CV<sub>C</sub>). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group.<h4>Results</h4>The median (range) CV<sub>D</sub> and CV<sub>C</sub> were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CV<sub>C</sub> to 0.04 (0.01-0.16). CV<sub>D</sub> was comparable between ROI types.<h4>Conclusion</h4>Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.
<h4>Objectives</h4>To assess coronary artery calcification (CAC) on non-contrast non-ECG-gated CT thorax (NC-NECG-CTT) and to evaluate its correlation with short-term risk of cardiovascular disease (CVD) events and death.<h4>Methods</h4>Single-institution retrospective study including all patients 40-70 years old who underwent NC-NECG-CTT over a period of 6 months. Individuals with known CVD were excluded. The presence of CAC was assessed and quantified by the Agatston score (CACS). CAC severity was defined as mild (< 100), moderate (100-400), or severe (> 400). CVD events (including CVD death, myocardial infarction, revascularisation procedures, ischaemic stroke, acute peripheral atherosclerotic ischaemia), and all-cause mortality over a median of 3.5 years were recorded. Cox proportional-hazards regression modelling was performed including CACS, age, gender and CVD risk factors (smoking, hypertension, diabetes mellitus, dyslipidaemia, and family history of CVD).<h4>Results</h4>Of the total 717 eligible cases, 325 (45%) had CAC. In patients without CAC, there was only one CVD event, compared to 26 CVD events including 5 deaths in patients with CAC. The presence and severity of CAC correlated with CVD events (p < 0.001). A CACS > 100 was significantly associated with both CVD events, hazard ratio (HR) 5.74, 95% confidence interval: 2.19-15.02; p < 0.001, and all-cause mortality, HR 1.7, 95% CI: 1.08-2.66; p = 0.02. Ever-smokers with CAC had a significantly higher risk for all-cause mortality compared to never-smokers (p = 0.03), but smoking status was not an independent predictor for CVD events in any subgroup category of CAC severity.<h4>Conclusions</h4>The presence and severity of CAC assessed on NC-NECG-CTT correlates with short-term cardiovascular events and death.<h4>Key points</h4>• Patients aged 40-70 years old without known CVD but with CAC on NC-NECG-CTT have a higher risk of CVD events compared to those without CAC. • CAC (Agatston) score above 100 confers a 5.7-fold increase in the risk of short-term CVD events in these patients. • The presence and severity of CAC on NC-NECG-CTT may have prognostic and therapeutic implications.
<h4>Background and purpose</h4>Physiological motion impacts the dose delivered to tumours and vital organs in external beam radiotherapy and particularly in particle therapy. The excellent soft-tissue demarcation of 4D magnetic resonance imaging (4D-MRI) could inform on intra-fractional motion, but long image reconstruction times hinder its use in online treatment adaptation. Here we employ techniques from high-performance computing to reduce 4D-MRI reconstruction times below two minutes to facilitate their use in MR-guided radiotherapy.<h4>Material and methods</h4>Four patients with pancreatic adenocarcinoma were scanned with a radial stack-of-stars gradient echo sequence on a 1.5T MR-Linac. Fast parallelised open-source implementations of the extra-dimensional golden-angle radial sparse parallel algorithm were developed for central processing unit (CPU) and graphics processing unit (GPU) architectures. We assessed the impact of architecture, oversampling and respiratory binning strategy on 4D-MRI reconstruction time and compared images using the structural similarity (SSIM) index against a MATLAB reference implementation. Scaling and bottlenecks for the different architectures were studied using multi-GPU systems.<h4>Results</h4>All reconstructed 4D-MRI were identical to the reference implementation (SSIM > 0.99). Images reconstructed with overlapping respiratory bins were sharper at the cost of longer reconstruction times. The CPU + GPU implementation was over 17 times faster than the reference implementation, reconstructing images in 60 ± 1 s and hyper-scaled using multiple GPUs.<h4>Conclusion</h4>Respiratory-resolved 4D-MRI reconstruction times can be reduced using high-performance computing methods for online workflows in MR-guided radiotherapy with potential applications in particle therapy.
<h4>Background</h4>T<sub>2</sub> <sup>*</sup> mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T<sub>2</sub> <sup>*</sup> maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes.<h4>Purpose</h4>The purpose of this work is to demonstrate the feasibility of the accelerated T<sub>2</sub> <sup>*</sup> mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac).<h4>Materials and methods</h4>The proposed method was validated in a numerical phantom, where two T<sub>2</sub> <sup>*</sup> mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T<sub>2</sub> <sup>*</sup> maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T<sub>2</sub> <sup>*</sup> maps reconstructed, with and without trajectory corrections were compared.<h4>Results</h4>Numerical simulations demonstrated that, for all noise levels, T<sub>2</sub> <sup>*</sup> maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T<sub>2</sub> <sup>*</sup> maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T<sub>2</sub> <sup>*</sup> maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV).<h4>Conclusion</h4>Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T<sub>2</sub> <sup>*</sup> maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.
<i>Objective.</i>Respiratory motion of lung tumours and adjacent structures is challenging for radiotherapy. Online MR-imaging cannot currently provide real-time volumetric information of the moving patient anatomy, therefore limiting precise dose delivery, delivered dose reconstruction, and downstream adaptation methods.<i>Approach.</i>We tailor a respiratory motion modelling framework towards an MR-Linac workflow to estimate the time-resolved 4D motion from real-time data. We develop a multi-slice acquisition scheme which acquires thick, overlapping 2D motion-slices in different locations and orientations, interleaved with 2D surrogate-slices from a fixed location. The framework fits a motion model directly to the input data without the need for sorting or binning to account for inter- and intra-cycle variation of the breathing motion. The framework alternates between model fitting and motion-compensated super-resolution image reconstruction to recover a high-quality motion-free image and a motion model. The fitted model can then estimate the 4D motion from 2D surrogate-slices. The framework is applied to four simulated anthropomorphic datasets and evaluated against known ground truth anatomy and motion. Clinical applicability is demonstrated by applying our framework to eight datasets acquired on an MR-Linac from four lung cancer patients.<i>Main results.</i>The framework accurately reconstructs high-quality motion-compensated 3D images with 2 mm<sup>3</sup>isotropic voxels. For the simulated case with the largest target motion, the motion model achieved a mean deformation field error of 1.13 mm. For the patient cases residual error registrations estimate the model error to be 1.07 mm (1.64 mm), 0.91 mm (1.32 mm), and 0.88 mm (1.33 mm) in superior-inferior, anterior-posterior, and left-right directions respectively for the building (application) data.<i>Significance.</i>The motion modelling framework estimates the patient motion with high accuracy and accurately reconstructs the anatomy. The image acquisition scheme can be flexibly integrated into an MR-Linac workflow whilst maintaining the capability of online motion-management strategies based on cine imaging such as target tracking and/or gating.
<h4>Objective</h4>Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers.<h4>Materials and methods</h4>In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length.<h4>Results</h4>Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001).<h4>Conclusions</h4>These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.