Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney.

OBJECTIVE: 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. MATERIALS AND METHODS: 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. RESULTS: 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). CONCLUSIONS: These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.

Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation.

Objective.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.Approach.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.Main results.The framework accurately reconstructs high-quality motion-compensated 3D images with 2 mm3isotropic 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.Significance.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.

Real-time motion-including dose estimation of simulated multi-leaf collimator-tracked magnetic resonance-guided radiotherapy.

BACKGROUND: Real-time dose estimation is a key-prerequisite to enable online intra-fraction treatment adaptation in magnetic resonance (MR)-guided radiotherapy (MRgRT). It is an essential component for the assessment of the dosimetric benefits and risks of online adaptive treatments, such as multi-leaf collimator (MLC)-tracking. PURPOSE: We present a proof-of-concept for a software workflow for real-time dose estimation of MR-guided adaptive radiotherapy based on real-time data-streams of the linac delivery parameters and target positions. METHODS: A software workflow, combining our in-house motion management software DynaTrack, a real-time dose calculation engine that connects to a research version of the treatment planning software (TPS) Monaco (v.6.09.00, Elekta AB, Stockholm, Sweden) was developed and evaluated. MR-guided treatment delivery on the Elekta Unity MR-linac was simulated with and without MLC-tracking for three prostate patients, previously treated on the Elekta Unity MR-linac (36.25 Gy/five fractions). Three motion scenarios were used: no motion, regular motion, and erratic prostate motion. Accumulated monitor units (MUs), centre of mass target position and MLC-leaf positions, were forwarded from DynaTrack at a rate of 25 Hz to a Monte Carlo (MC) based dose calculation engine which utilises the research GPUMCD-library (Elekta AB, Stockholm, Sweden). A rigid isocentre shift derived from the selected motion scenarios was applied to a bulk density-assigned session MR-image. The respective electron density used for treatment planning was accessed through the research Monaco TPS. The software workflow including the online dose reconstruction was validated against offline dose reconstructions. Our investigation showed that MC-based real-time dose calculations that account for all linac states (including MUs, MLC positions and target position) were infeasible, hence states were randomly sampled and used for calculation as follows; Once a new linac state was received, a dose calculation with 106 photons was started. Linac states that arrived during the time of the ongoing calculation were put into a queue. After completion of the ongoing calculation, one new linac state was randomly picked from the queue and assigned the MU accumulated from the previous state until the last sample in the queue. The queue was emptied, and the process repeated throughout treatment simulation. RESULTS: On average 27% (23%-30%) of received samples were used in the real-time calculation, corresponding to a calculation time for one linac state of 148 ms. Median gamma pass rate (2%/3 mm local) was 100.0% (99.9%-100%) within the PTV volume and 99.1% (90.1%-99.4.0%) with a 15% dose cut off. Differences in PTVDmean , CTVDmean , RectumD2% , and BladderD2% (offline-online, % of prescribed dose) were below 0.64%. Beam-by-beam comparisons showed deviations below 0.07 Gy. Repeated simulations resulted in standard deviations below 0.31% and 0.12 Gy for the investigated volume and dose criteria respectively. CONCLUSIONS: Real-time dose estimation was successfully performed using the developed software workflow for different prostate motion traces with and without MLC-tracking. Negligible dosimetric differences were seen when comparing online and offline reconstructed dose, enabling online intra-fraction treatment decisions based on estimates of the delivered dose.

Accelerating 4D image reconstruction for magnetic resonance-guided radiotherapy.

Background and purpose: 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. Material and methods: 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. Results: 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. Conclusion: 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.

Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group.

BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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/mm2, 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 (CVD) and calculation methods (CVC). 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. RESULTS: The median (range) CVD and CVC 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 CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION: 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.

Joint radial trajectory correction for accelerated T2 * mapping on an MR-Linac.

BACKGROUND: T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes. PURPOSE: The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac). MATERIALS AND METHODS: The proposed method was validated in a numerical phantom, where two T2 * 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 T2 * 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 T2 * maps reconstructed, with and without trajectory corrections were compared. RESULTS: Numerical simulations demonstrated that, for all noise levels, T2 * 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, T2 * 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, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV). CONCLUSION: 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. T2 * 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.

Incidental coronary artery calcification on non-gated CT thorax correlates with risk of cardiovascular events and death.

OBJECTIVES: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: The presence and severity of CAC assessed on NC-NECG-CTT correlates with short-term cardiovascular events and death. KEY POINTS: • 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.

The future of MRI in radiation therapy: Challenges and opportunities for the MR community.

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.

Quantitative analysis of diffusion weighted imaging in rectal cancer during radiotherapy using a magnetic resonance imaging integrated linear accelerator.

Background and purpose: 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. Materials and methods: Nine patients undergoing treatment on MR-Linac had DWI acquired using b-values 0, 30, 150, 500 s/mm2. Gross tumour volume (GTV) and normal tissue was delineated on DWI throughout treatment and median ADC was calculated using an in-house tool (pyOsirix ®). Results: 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 × 10-3 mm2/s interquartile range (IQ): 1.05-1.17 vs 1.59 × 10-3 mm2/s IQ: 1.37 - 1.64; p = 0.0156), correlating to treatment response. In comparison ADC median for normal tissue remained the same between first and last fraction (1.61 × 10-3 mm2/s IQ: 1.56-1.71 vs 1.67 × 10-3 mm2/s IQ: 1.37-2.00; p = 0.9375). Conclusions: 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.

Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver.

PURPOSE: 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 f1 and f2 and the biexponential and triexponential pseudodiffusion coefficients D* , 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. METHODS: 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/mm2 ) 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. RESULTS: TE-dependence was observed for f (P < .001), f1 (P = .001), and f2 (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f1 : 0.113/0.139/0.146/0.205, f2 : 0.115/0.155/0.182/0.194. D, D* , D1∗ , and D2∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10-4 mm2 /s): 9.45/9.63/9.75/9.41, biexponential D* (10-2 mm2 /s): 5.26/5.52/6.13/5.82, triexponential D1∗ (10-2 mm2 /s): 1.73/2.91/2.25/2.51, triexponential D2∗ (mm2 /s): 0.478/1.385/0.616/0.846. CONCLUSION: f1 and f2 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 f1 and f2 , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.

Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy-A Multicenter Study.

PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: In total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10-3 mm2/s, 0.086, and 28.7 × 10-3 mm2/s in the non-cancerous prostate and 1.19 × 10-3 mm2/s, 0.088, and 28.9 × 10-3 mm2/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 × 10-3 mm2/s, 0.05, and 15.3 × 10-3 mm2/s. In the tumor, these values were 0.44 × 10-3 mm2/s, 0.16, and 76.4 × 10-3 mm2/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. CONCLUSIONS: 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.

Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group.

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.

Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula.

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.

An optimized b-value distribution for triexponential intravoxel incoherent motion (IVIM) in the liver.

PURPOSE: To find an optimized b-value distribution for reproducible triexponential intravoxel incoherent motion (IVIM) exams in the liver. METHODS: 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. RESULTS: 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/mm2 . 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. CONCLUSION: Using optimized b-values, the fit uncertainty in triexponential IVIM can be largely reduced. Ideally, 16 or more b-values should be acquired.

Evaluation of MRI-derived surrogate signals to model respiratory motion.

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.

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

BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium.

BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: On the Unity system, a maximum b-value of 500 s/mm2 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. CONCLUSION: 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.

Delayed contrast dynamics as marker of regional impairment in pulmonary fibrosis using 5D MRI - a pilot study.

OBJECTIVE: 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. METHODS: 20 patients (mean age: 71 years; M:F, 13:7), with chronic fibrosing ILD: n = 12 idiopathic pulmonary fibrosis (IPF) and n = 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. RESULTS: IPF lesions showed later peak enhancement compared to non-IPF (severe: p = 0.01, non-severe: p = 0.003). Severe lesions showed later peak enhancement compared to non-severe lesions, in non-IPF (p = 0.04), but not in IPF (p = 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 (p = 0.003) and non-IPF (p = 0.005). Continuous contrast agent accumulation, without washout, was found only in IPF lesions. CONCLUSIONS: 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. ADVANCES IN KNOWLEDGE: Delayed contrast enhancement patterns allow the assessment of regional lung impairment which could represent different disease stages or phenotypes in ILD.

Automatic reconstruction of the delivered dose of the day using MR-linac treatment log files and online MR imaging.

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.