29 research outputs found

    Cartesian vs radial MR-STAT: An efficiency and robustness study

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    MR Spin TomogrAphy in Time-domain (“MR-STAT”) is quantitative MR technique in which multiple quantitative parameters are estimated from a single short scan by solving a large-scale non-linear optimization problem. In this work we extended the MR-STAT framework to non-Cartesian gradient trajectories. Cartesian MR-STAT and radial MR-STAT were compared in terms of time-efficiency and robustness in simulations, gel phantom measurements and in vivo measurements. In simulations, we observed that both Cartesian and radial MR-STAT are highly robust against undersampling. Radial MR-STAT does have a lower spatial encoding power because the outer corners of k-space are never sampled. However, especially in T2, this is compensated by a higher dynamic encoding power that comes from sampling the k-space center with each readout. In gel phantom measurements, Cartesian MR-STAT was observed to be robust against overfitting whereas radial MR-STAT suffered from high-frequency artefacts in the parameter maps at later iterations. These artefacts are hypothesized to be related to hardware imperfections and were (partially) suppressed with image filters. The time-efficiencies were higher for Cartesian MR-STAT in all vials. In-vivo, the radial reconstruction again suffered from overfitting artefacts. The robustness of Cartesian MR-STAT over the entire range of experiments may make it preferable in a clinical setting, despite radial MR-STAT resulting in a higher T1 time-efficiency in white matter

    GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language

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    PURPOSE: MR-STAT is a relatively new multiparametric quantitative MRI technique in which quantitative paramater maps are obtained by solving a large-scale nonlinear optimization problem. Managing reconstruction times is one of the main challenges of MR-STAT. In this work we leverage GPU hardware to reduce MR-STAT reconstruction times. A highly optimized, GPU-compatible Bloch simulation toolbox is developed as part of this work that can be utilized for other quantitative MRI techniques as well. METHODS: The Julia programming language was used to develop a flexible yet highly performant and GPU-compatible Bloch simulation toolbox called BlochSimulators.jl. The runtime performance of the toolbox is benchmarked against other Bloch simulation toolboxes. Furthermore, a (partially matrix-free) modification of a previously presented (matrix-free) MR-STAT reconstruction algorithm is proposed and implemented using the Julia language on GPU hardware. The proposed algorithm is combined with BlochSimulators.jl and the resulting MR-STAT reconstruction times on GPU hardware are compared to previously presented MR-STAT reconstruction times. RESULTS: The BlochSimulators.jl package demonstrates superior runtime performance on both CPU and GPU hardware when compared to other existing Bloch simulation toolboxes. The GPU-accelerated partially matrix-free MR-STAT reconstruction algorithm, which relies on BlochSimulators.jl, allows for reconstructions of 68 seconds per two-dimensional (2D slice). CONCLUSION: By combining the proposed Bloch simulation toolbox and the partially matrix-free reconstruction algorithm, 2D MR-STAT reconstructions can be performed in the order of one minute on a modern GPU card. The Bloch simulation toolbox can be utilized for other quantitative MRI techniques as well, for example for online dictionary generation for MR Fingerprinting

    Efficient performance analysis and optimization of transient-state sequences for multiparametric magnetic resonance imaging

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    In transient-state multiparametric MRI sequences such as Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT), MR fingerprinting, or hybrid-state imaging, the flip angle pattern of the RF excitation varies over the sequence. This gives considerable freedom to choose an optimal pattern of flip angles. For pragmatic reasons, most optimization methodologies choose for a single-voxel approach (i.e., without taking the spatial encoding scheme into account). Particularly in MR-STAT, the context of spatial encoding is important. In the current study, we present a methodology, called BLock Analysis of a K-space-domain Jacobian (BLAKJac), which is sufficiently fast to optimize a sequence in the context of a predetermined phase-encoding pattern. Based on MR-STAT acquisitions and reconstructions, we show that sequences optimized using BLAKJac are more reliable in terms of actually achieved precision than conventional single-voxel–optimized sequences. In addition, BLAKJac provides analytical tools that give insights into the performance of the sequence in a very limited computation time. Our experiments are based on MR-STAT, but the theory is equally valid for other transient-state multiparametric methods

    Water diffusion and T2 quantification in transient-state MRI: the effect of RF pulse sequence.

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    In quantitative measurement of the (Formula presented.) value of tissues, the diffusion of water molecules has been recognized as a confounder. This is most notably so for transient-state quantitative mapping techniques, which allow simultaneous estimation of (Formula presented.) and (Formula presented.). In prior work, apparently conflicting conclusions are presented on the level of diffusion-induced bias on the T2 estimate. So far there is a lack of studies on the effect of the RF pulse angle sequence on the level of diffusion-induced bias. In this work, we show that the specific transient-state RF pulse sequence has a large effect on this level of bias. In particular, the bias level is strongly influenced by the mean value of the RF pulse angles. Also, for realistic values of the spoiling gradient area, we infer that the diffusion-induced bias is negligible for non-liquid human tissues; yet, for phantoms, the effect can be substantial (15% of the true (Formula presented.) value) for some RF pulse sequences. This should be taken into account in validation procedures

    Who lives in a pear tree under the sea? A first look at tree reefs as a complex natural biodegradable structure to enhance biodiversity in marine systems

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    Hard substrates play an important role in global marine systems as settlement surface for sessile reef-forming species such as corals, seaweeds, and shellfish. In soft-sediment systems, natural hard substrates such as stones, bedrock and driftwood are essential as they support diverse assemblages of reef-associated species. However, availability of these hard substrates has been declining in many estuaries and shallow seas worldwide due to human impacts. This is also the case in the Dutch Wadden Sea, where natural hard substrates have gradually disappeared due to burial by sand and/or active removal by humans. In addition, driftwood that was historically imported from rivers has been nullified by upstream logging and coastal damming of estuaries. To investigate the historic ecological role of wood presence in the Wadden Sea as settlement substrate and fish habitat, we constructed three meter high artificial reefs made of felled pear trees. Results demonstrate that these reefs rapidly developed into hotspots of biodiversity. Within six months, the tree-reefs were colonized by sessile hard substrate associated species, with a clear vertical zonation of the settled species. Macroalgae and barnacles were more abundant on the lower parts of the reef, while bryozoans were more dominant on the upper branches. In addition, six fish species were observed on the reefs, while only two species were caught on sandy control sites. Moreover, the abundance of fish on the reefs was five times higher. Individuals of the most commonly caught species, the five-bearded rockling Ciliata mustela, were also larger on the reef. These patterns also hold true for common prawn, Palaemon serratus, which were also larger and ten times more numerous on the reefs. Present findings indicate that the reintroduction of tree-reefs as biodegradable, structurally complex hard substrates can increase local marine biodiversity in soft-sediment systems within relatively short time scales.</p

    High SNR full brain relaxometry at 7T by accelerated MR-STAT

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    Purpose: To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T. Methods: To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measured (Formula presented.) -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity to (Formula presented.) inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency. Results: The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including the (Formula presented.) -mapping. After (Formula presented.) -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%–2.1% (WM-GM) for T1 and 4.3%–5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency. Conclusion: We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T

    A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging

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    Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm 3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future

    The seafloor from a trait perspective:A comprehensive life history dataset of soft sediment macrozoobenthos

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    Biological trait analysis (BTA) is a valuable tool for evaluating changes in community diversity and its link to ecosystem processes as well as environmental and anthropogenic perturbations. Trait-based analytical techniques like BTA rely on standardised datasets of species traits. However, there are currently only a limited number of datasets available for marine macrobenthos that contain trait data across multiple taxonomic groups. Here, we present an open-access dataset of 16 traits for 235 macrozoobenthic species recorded throughout multiple sampling campaigns of the Dutch Wadden Sea; a dynamic soft bottom system where humans have long played a substantial role in shaping the coastal environment. The trait categories included in this dataset cover a variety of life history strategies that are tightly linked to ecosystem functioning and the resilience of communities to (anthropogenic) perturbations and can advance our understanding of environmental changes and human impacts on the functioning of soft bottom systems

    Synthetic MRI with Magnetic Resonance Spin TomogrAphy in Time-Domain (MR-STAT): Results from a Prospective Cross-Sectional Clinical Trial

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    BACKGROUND: Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) can reconstruct whole-brain multi-parametric quantitative maps (eg, T 1 , T 2 ) from a 5-minute MR acquisition. These quantitative maps can be leveraged for synthetization of clinical image contrasts. PURPOSE: The objective was to assess image quality and overall diagnostic accuracy of synthetic MR-STAT contrasts compared to conventional contrast-weighted images. STUDY TYPE: Prospective cross-sectional clinical trial. POPULATION: Fifty participants with a median age of 45 years (range: 21-79 years) consisting of 10 healthy participants and 40 patients with neurological diseases (brain tumor, epilepsy, multiple sclerosis or stroke). FIELD STRENGTH/SEQUENCE: 3T/Conventional contrast-weighted imaging (T 1 /T 2 weighted, proton density [PD] weighted, and fluid-attenuated inversion recovery [FLAIR]) and a MR-STAT acquisition (2D Cartesian spoiled gradient echo with varying flip angle preceded by a non-selective inversion pulse). ASSESSMENT: Quantitative T 1 , T 2 , and PD maps were computed from the MR-STAT acquisition, from which synthetic contrasts were generated. Three neuroradiologists blinded for image type and disease randomly and independently evaluated synthetic and conventional datasets for image quality and diagnostic accuracy, which was assessed by comparison with the clinically confirmed diagnosis. STATISTICAL TESTS: Image quality and consequent acceptability for diagnostic use was assessed with a McNemar's test (one-sided α = 0.025). Wilcoxon signed rank test with a one-sided α = 0.025 and a margin of Δ = 0.5 on the 5-level Likert scale was used to assess non-inferiority. RESULTS: All data sets were similar in acceptability for diagnostic use (≥3 Likert-scale) between techniques (T 1 w:P = 0.105, PDw:P = 1.000, FLAIR:P = 0.564). However, only the synthetic MR-STAT T 2 weighted images were significantly non-inferior to their conventional counterpart; all other synthetic datasets were inferior (T 1 w:P = 0.260, PDw:P = 1.000, FLAIR:P = 1.000). Moreover, true positive/negative rates were similar between techniques (conventional: 88%, MR-STAT: 84%). DATA CONCLUSION: MR-STAT is a quantitative technique that may provide radiologists with clinically useful synthetic contrast images within substantially reduced scan time. EVIDENCE LEVEL: 1 Technical Efficacy: Stage 2

    Feasibility of cardiac-synchronized quantitative T1 and T2 mapping on a hybrid 1.5 Tesla magnetic resonance imaging and linear accelerator system

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    Background and Purpose: The heart is important in radiotherapy either as target or organ at risk. Quantitative T1 and T2 cardiac magnetic resonance imaging (qMRI) may aid in target definition for cardiac radioablation, and imaging biomarker for cardiotoxicity assessment. Hybrid MR-linac devices could facilitate daily cardiac qMRI of the heart in radiotherapy. The aim of this work was therefore to enable cardiac-synchronized T1 and T2 mapping on a 1.5 T MR-linac and test the reproducibility of these sequences on phantoms and in vivo between the MR-linac and a diagnostic 1.5 T MRI scanner. Materials and methods: Cardiac-synchronized MRI was performed on the MR-linac using a wireless peripheral pulse-oximeter unit. Diagnostically used T1 and T2 mapping sequences were acquired twice on the MR-linac and on a 1.5 T MR-simulator for a gel phantom and 5 healthy volunteers in breath-hold. Phantom T1 and T2 values were compared to gold-standard measurements and percentage errors (PE) were computed, where negative/positive PE indicate underestimations/overestimations. Manually selected regions-of-interest were used for in vivo intra/inter scanner evaluation. Results: Cardiac-synchronized T1 and T2 qMRI was enabled after successful hardware installation on the MR-linac. From the phantom experiments, the measured T1/T2 relaxation times had a maximum percentage error (PE) of -4.4%/-8.8% on the MR-simulator and a maximum PE of -3.2%/+8.6% on the MR-linac. Mean T1/T2 of the myocardium were 1012 ± 34/51 ± 2 ms on the MR-simulator and 1034 ± 42/51 ± 1 ms on the MR-linac. Conclusions: Accurate cardiac-synchronized T1 and T2 mapping is feasible on a 1.5 T MR-linac and might enable novel plan adaptation workflows and cardiotoxicity assessments
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