| 1. |
- Ahlgren, André, et al.
(författare)
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Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data.
- 2016
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 29:5, s. 640-649
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit. © 2016 The Authors NMR in Biomedicine published by John Wiley & Sons Ltd.
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| 2. |
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| 3. |
- Alexander, Daniel C., et al.
(författare)
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Imaging brain microstructure with diffusion MRI : Practicality and applications
- 2019
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 32:4, s. 3841-3841
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Forskningsöversikt (refereegranskat)abstract
- This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.
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| 4. |
- Borga, Magnus, et al.
(författare)
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Validation of a Fast Method for Quantification of Intra-abdominal and Subcutaneous Adipose Tissue for Large Scale Human Studies
- 2015
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Ingår i: NMR in Biomedicine. - : John Wiley & Sons. - 1099-1492 .- 0952-3480. ; 28:12, s. 1747-1753
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Tidskriftsartikel (refereegranskat)abstract
- Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as magnetic resonance imaging (MRI) has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles for the use of MRI in large scale studies. In this study we assess the validity of the recently proposed fat-muscle-quantitation-system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using SliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by both analysis methods, (Pearson correlation r = 0.97 p<0.001), with the AMRATM Profiler analysis being significantly faster (~3 mins) than the conventional SliceOmatic approach (~40 mins). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 vs SliceOmatic 4.73 ± 1.75 litres, p=0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6 % for IAAT and 1.1 % for ASAT, the inter-observer coefficient of variation was 1.4 % for IAAT and 1.2 % for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.
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| 5. |
- Brabec, Jan, et al.
(författare)
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Time-dependent diffusion in undulating thin fibers : Impact on axon diameter estimation
- 2020
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 33:3
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Tidskriftsartikel (refereegranskat)abstract
- Diffusion MRI may enable non-invasive mapping of axonal microstructure. Most approaches infer axon diameters from effects of time-dependent diffusion on the diffusion-weighted MR signal by modeling axons as straight cylinders. Axons do not, however, propagate in straight trajectories, and so far the impact of the axonal trajectory on diameter estimation has been insufficiently investigated. Here, we employ a toy model of axons, which we refer to as the undulating thin fiber model, to analyze the impact of undulating trajectories on the time dependence of diffusion. We study time-dependent diffusion in the frequency domain and characterize the diffusion spectrum by its height, width, and low-frequency behavior (power law exponent). Results show that microscopic orientation dispersion of the thin fibers is the main parameter that determines the characteristics of the diffusion spectra. At lower frequencies (longer diffusion times), straight cylinders and undulating thin fibers can have virtually identical spectra. If the straight-cylinder assumption is used to interpret data from undulating thin axons, the diameter is overestimated by an amount proportional to the undulation amplitude and microscopic orientation dispersion of the fibers. At higher frequencies (shorter diffusion times), spectra from cylinders and undulating thin fibers differ. The low-frequency behavior of the spectra from the undulating thin fibers may also differ from that of cylinders, because the power law exponent of undulating fibers can reach values below 2 for experimentally relevant frequency ranges. In conclusion, we argue that the non-straight nature of axonal trajectories should not be overlooked when analyzing and interpreting diffusion MRI data.
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| 6. |
- Brinkhof, S., et al.
(författare)
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Uncompromised MRI of knee cartilage while incorporating sensitive sodium MRI
- 2019
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492.
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Tidskriftsartikel (refereegranskat)abstract
- Sodium imaging is able to assess changes in ion content, linked to glycosaminoglycan content, which is important to guide orthopeadic procedures such as articular cartilage repair. Sodium imaging is ideally performed using double tuned RF coils, to combine high resolution morphological imaging with biochemical information from sodium imaging to assess ion content. The proton image quality of such coils is often harshly degraded, with up to 50% of SNR or severe acceleration loss as compared to single tuned coils. Reasons are that the number of proton receive channels often severely reduced and double tuning will degrade the intrinsic sensitivity of the RF coil on at least one of the nuclei. However, the aim of this work was to implement a double-tuned sodium/proton knee coil setup without deterioration of the proton signal whilst being able to achieve acquisition of high SNR sodium images. A double-tuned knee coil was constructed as a shielded birdcage optimized for sodium and compromised for proton. To exclude any compromise, the proton part of the birdcage is used for transmit only and interfaced to RF amplifiers that can fully mitigate the reduced efficiency. In addition, a 15 channel single tuned proton receiver coil was embedded within the double-resonant birdcage to maintain optimal SNR and acceleration for proton imaging. To validate the efficiency of our coil, the designed coil was compared with the state-of-the-art single-tuned alternative at 7 T. B1+ corrected SNR maps were used to compare both coils on proton performance and g-factor maps were used to compare both coils on acceleration possibilities. The newly constructed double-tuned coil was shown to have comparable proton quality and acceleration possibilities to the single-tuned alternative while also being able to acquire high SNR sodium images.
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| 7. |
- Chakwizira, Arthur, et al.
(författare)
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Diffusion MRI with pulsed and free gradient waveforms : effects of restricted diffusion and exchange
- 2023
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 36:1
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Tidskriftsartikel (refereegranskat)abstract
- Monitoring time-dependence with diffusion MRI yields observables sensitive to compartment sizes (restricted diffusion) and membrane permeability (water exchange). However, restricted diffusion and exchange have opposite effects on the diffusion-weighted signal, which can lead to errors in parameter estimates. In this work, we propose a signal representation that incorporates the effects of both restricted diffusion and exchange up to second order in b-value and is compatible with gradient waveforms of arbitrary shape. The representation features mappings from a gradient waveform to two scalars that separately control the sensitivity to restriction and exchange. We demonstrate that these scalars span a two-dimensional space that can be used to choose waveforms that selectively probe restricted diffusion or exchange, eliminating the correlation between the two phenomena. We found that waveforms with specific but unconventional shapes provide an advantage over conventional pulsed and oscillating gradient acquisitions. We also show that parametrisation of waveforms into a two-dimensional space can be used to understand protocols from other approaches that probe restricted diffusion and exchange. For example, we found that the variation of mixing time in filter-exchange imaging corresponds to variation of our exchange-weighting scalar at a fixed value of the restriction-weighting scalar. The proposed signal representation was evaluated using Monte Carlo simulations in identical parallel cylinders with hexagonal and random packing as well as parallel cylinders with gamma-distributed radii. Results showed that the approach is sensitive to sizes in the interval 4 - 12 μm and exchange rates in the simulated range of 0 to 20 s -1 , but also that there is a sensitivity to the extracellular geometry. The presented theory constitutes a simple and intuitive description of how restricted diffusion and exchange influence the signal as well as a guide to protocol design capable of separating the two effects.
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| 8. |
- Eigentler, Thomas Wilhelm, et al.
(författare)
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Wideband Self-Grounded Bow-Tie Antenna for Thermal MR
- 2020
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 33:5
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this study was the design, implementation, evaluation and application of a compact wideband self-grounded bow-tie (SGBT) radiofrequency (RF) antenna building block that supports anatomical proton (H-1) MRI, fluorine (F-19) MRI, MR thermometry and broadband thermal intervention integrated in a whole-body 7.0 T system. Design considerations and optimizations were conducted with numerical electromagnetic field (EMF) simulations to facilitate a broadband thermal intervention frequency of the RF antenna building block. RF transmission (B-1(+)) field efficiency and specific absorption rate (SAR) were obtained in a phantom, and the thigh of human voxel models (Ella, Duke) for H-1 and F-19 MRI at 7.0 T. B-1(+) efficiency simulations were validated with actual flip-angle imaging measurements. The feasibility of thermal intervention was examined by temperature simulations (f = 300, 400 and 500 MHz) in a phantom. The RF heating intervention (P-in = 100 W, t = 120 seconds) was validated experimentally using the proton resonance shift method and fiberoptic probes for temperature monitoring. The applicability of the SGBT RF antenna building block for in vivo H-1 and F-19 MRI was demonstrated for the thigh and forearm of a healthy volunteer. The SGBT RF antenna building block facilitated F-19 and H-1 MRI at 7.0 T as well as broadband thermal intervention (234-561 MHz). For the thigh of the human voxel models, a B-1(+) efficiency >= 11.8 mu T/root kW was achieved at a depth of 50 mm. Temperature simulations and heating experiments in a phantom demonstrated a temperature increase Delta T >7 K at a depth of 10 mm. The compact SGBT antenna building block provides technology for the design of integrated high-density RF applicators and for the study of the role of temperature in (patho-) physiological processes by adding a thermal intervention dimension to an MRI device (Thermal MR).
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| 9. |
- Einarsson, Emma, et al.
(författare)
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The role of cartilage glycosaminoglycan structure in gagCEST
- 2020
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 33:5
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Tidskriftsartikel (refereegranskat)abstract
- Glycosaminoglycan (GAG) chemical exchange saturation transfer (gagCEST) is a potential method for cartilage quality assessment. The aim of this study was to investigate how the gagCEST effect depends on the types and molecular organization of GAG typically found in articular cartilage. gagCEST was performed on different concentrations of GAG in various forms: free chains of chondroitin sulfate (CS) of different types (-A and -C) and GAG bound to protein in aggregated and nonaggregated aggrecan extracted from calf articular cartilage. The measured magnetization transfer ratio asymmetry (MTRasym ) was compared with known GAG concentrations or GAG concentrations determined through biochemical analysis. The gagCEST effect was assessed through the linear regression coefficient with 95% confidence interval of MTRasym per GAG concentration. We observed a lower gagCEST effect in phantoms containing a mixture of CS-A and CS-C compared with phantoms containing mainly CS-A. The difference in response corresponds well to the difference in CS-A concentration. GAG bound in aggrecan from calf articular cartilage, where CS-A is assumed to be the major type of GAG, produed a similar gagCEST effect as that observed for free CS-A. The effect was also similar for aggregated (ie, bound to hyaluronic acid) and nonaggregated aggrecan. In conclusion, our results indicate that the aggrecan structure in itself does not impact the gagCEST effect, but that the effect is strongly dependent on GAG type. In phantoms, the current implementation of gagCEST is sensitive to CS-A while for CS-C, the main GAG component in mature human articular cartilage, the sensitivity is limited. This difference in gagCEST sensitivity between GAG types detected in phantoms is a strong motivation to also explore the possibility of a similar effect in vivo.
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| 10. |
- Ferizi, U., et al.
(författare)
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Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison
- 2017
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 30:9, s. Article no e3734 -
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Tidskriftsartikel (refereegranskat)abstract
- A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.
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