1. 
 Eigentler, Thomas Wilhelm, et al.
(författare)

Wideband SelfGrounded BowTie Antenna for Thermal MR
 2020

Ingår i: NMR in Biomedicine.  09523480 . 10991492. ; 33:5

Tidskriftsartikel (refereegranskat)abstract
 The objective of this study was the design, implementation, evaluation and application of a compact wideband selfgrounded bowtie (SGBT) radiofrequency (RF) antenna building block that supports anatomical proton (H1) MRI, fluorine (F19) MRI, MR thermometry and broadband thermal intervention integrated in a wholebody 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 (B1(+)) field efficiency and specific absorption rate (SAR) were obtained in a phantom, and the thigh of human voxel models (Ella, Duke) for H1 and F19 MRI at 7.0 T. B1(+) efficiency simulations were validated with actual flipangle 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 (Pin = 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 H1 and F19 MRI was demonstrated for the thigh and forearm of a healthy volunteer. The SGBT RF antenna building block facilitated F19 and H1 MRI at 7.0 T as well as broadband thermal intervention (234561 MHz). For the thigh of the human voxel models, a B1(+) 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 highdensity 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).


2. 
 Ferizi, Uran, et al.
(författare)

Diffusion MRI microstructure models with in vivo human brain Connectome data : Results from a multigroup comparison
 2017

Ingår i: NMR in Biomedicine.  : John Wiley and Sons.  09523480 . 10991492. ; 30:9

Tidskriftsartikel (refereegranskat)abstract
 A large number of mathematical models have been proposed to describe the measured signal in diffusionweighted (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 threequarters 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 diffusionbased 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 nonGaussian (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 signalpredicting strategies, such as bootstrapping or crossvalidation, 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.


3. 
 Gillies, P., et al.
(författare)

Quantification of MRS data in the frequency domain using a wavelet filter, an approximated Voigt lineshape model and prior knowledge
 2006

Ingår i: NMR in Biomedicine.  09523480 . 10991492. ; 19:5, s. 617626

Tidskriftsartikel (refereegranskat)abstract
 Quantification of MRS spectra is a challenging problem when a large baseline is present along with a low signal to noise ratio. This work investigates a robust fitting technique that yields accurate peak areas under these conditions. Using simulated long echo time 1H MRS spectra with low signal to noise ratio and a large baseline component, both the accuracy and reliability of the fit in the frequency domain were greatly improved by reducing the number of fitted parameters and making full use of all the known information concerning the Voigt lineshape. Using an appropriate first order approximation to a popular approximation of the Voigt lineshape, a significant improvement in the estimate of the area of a known spectral peak was obtained with a corresponding reduction in the residual. Furthermore, this improved parameter choice resulted in a large reduction in the number of iterations of the leastsquares fitting routine. On the other hand, making use of the known centre frequency differences of the component resonances gave negligible improvement. A wavelet filter was used to remove the baseline component. In addition to performing a Monte Carlo study, these fitting techniques were also applied to a set of 10 spectra acquired from healthy human volunteers.Again, the same reduced parameter model gave the lowest value for X2 in each case.


4. 
 Henningsson, Markus, et al.
(författare)

Myocardial arterial spin labeling in systole and diastole using flowsensitive alternating inversion recovery with parallel imaging and compressed sensing
 2021

Ingår i: NMR in Biomedicine.  : WILEY.  09523480 . 10991492. ; 34:2

Tidskriftsartikel (refereegranskat)abstract
 Quantitative myocardial perfusion can be achieved without contrast agents using flowsensitive alternating inversion recovery (FAIR) arterial spin labeling. However, FAIR has an intrinsically low sensitivity, which may be improved by mitigating the effects of physiological noise or by increasing the area of artifactfree myocardium. The aim of this study was to investigate if systolic FAIR may increase the amount of analyzable myocardium compared with diastolic FAIR and its effect on physiological noise. Furthermore, we compare parallel imaging acceleration with a factor of 2 with compressed sensing acceleration with a factor of 3 for systolic FAIR. Twelve healthy subjects were scanned during rest on a 3 T scanner using diastolic FAIR with parallel imaging factor 2 (FAIRPI2(D)), systolic FAIR with the same acceleration (FAIRPI2(S)) and systolic FAIR with compressed sensing factor 3 (FAIRCS3(S)). The number of analyzable pixels in the myocardium, temporal signaltonoise ratio (TSNR) and mean myocardial blood flow (MBF) were calculated for all methods. The number of analyzable pixels using FAIRCS3(S) (663 +/ 55) and FAIRPI2(S) (671 +/ 58) was significantly higher than for FAIRPI2(D) (507 +/ 82; P = .001 for both), while there was no significant difference between FAIRPI2(S) and FAIRCS3(S). The mean TSNR of the midventricular slice for FAIRPI2(D) was 11.4 +/ 3.9, similar to that of FAIRCS3(S,) which was 11.0 +/ 3.3, both considerably higher than for FAIRPI2(S,) which was 8.4 +/ 3.1 (P < .05 for both). Mean MBF was similar for all three methods. The use of compressed sensing accelerated systolic FAIR benefits from an increased number of analyzable myocardial pixels compared with diastolic FAIR without suffering from a TSNR penalty, unlike systolic FAIR with parallel imaging acceleration.


5. 
 Karlsson, Anette, 1986, et al.
(författare)

The effect on precision and T1 bias comparing two flip angles when estimating muscle fat infiltration using fatreferenced chemical shiftencoded imaging
 2021

Ingår i: NMR in Biomedicine.  : John Wiley & Sons.  09523480 . 10991492.

Tidskriftsartikel (refereegranskat)abstract
 Investigation of the effect on accuracy and precision of different parameter settings is important for quantitative Magnetic Resonance Imaging. The purpose of this study was to investigate T1bias and precision for muscle fat infiltration (MFI) using fatreferenced chemical shift magnetic resonance imaging at 5° and 10° flip angle. This [MB1] experimental study was done on forty postmenopausal women using 3T MRI test and retest images using 4point 3D spoiled gradient multiecho acquisition including real and imaginary images for reconstruction acquired at Flip angles 5° and 10°. Postprocessing included T2* correction and fatreferenced calibration of the fat signal. The mean MFI was calculated in six different automatically segmented muscle regions using both the fatreferenced fat signal and the fat fraction calculated from the fat and water image pair for each acquisition. The variance of the difference between mean MFI from test and retest was used as measure of precision. The SNR characteristics were analyzed by measuring difference of the full width half maximum of the fat signal distribution using Student’s ttest.There was no difference in the mean fatreferenced MFI at different flip angles with the fatreferenced technique, which was the case using the fat fraction. No significant difference in the precision was found in any of the muscles analyzed. However, the full width half maximum of the fat signal distribution was significantly lower at 10° flip angle compared to 5°. Fatreferenced MFI is insensitive to T1 bias in chemical shift magnetic resonance imaging enabling usage of a higher and more SNR effective flip angle. The lower fullwidthat halfmaximum in fatreferenced MFI at 10° indicates that high flip angle acquisition is advantageous although no significant differences in precision was observed comparing 5° and 10°.


6. 
 Li, JingRebecca, et al.
(författare)

Practical computation of the diffusion MRI signal of realistic neurons based on Laplace eigenfunctions
 2020

Ingår i: NMR in Biomedicine.  : John Wiley and Sons Ltd.  09523480 . 10991492. ; 33:10

Tidskriftsartikel (refereegranskat)abstract
 The complex transverse water proton magnetization subject to diffusionencoding magnetic field gradient pulses in a heterogeneous medium such as brain tissue can be modeled by the BlochTorrey partial differential equation. The spatial integral of the solution of this equation in realistic geometry provides a goldstandard reference model for the diffusion MRI signal arising from different tissue microstructures of interest. A closed form representation of this reference diffusion MRI signal called matrix formalism, which makes explicit the link between the Laplace eigenvalues and eigenfunctions of the biological cell and its diffusion MRI signal, was derived 20 years ago. In addition, once the Laplace eigendecomposition has been computed and saved, the diffusion MRI signal can be calculated for arbitrary diffusionencoding sequences and bvalues at negligible additional cost. Up to now, this representation, though mathematically elegant, has not been often used as a practical model of the diffusion MRI signal, due to the difficulties of calculating the Laplace eigendecomposition in complicated geometries. In this paper, we present a simulation framework that we have implemented inside the MATLABbased diffusion MRI simulator SpinDoctor that efficiently computes the matrix formalism representation for realistic neurons using the finite element method. We show that the matrix formalism representation requires a few hundred eigenmodes to match the reference signal computed by solving the BlochTorrey equation when the cell geometry originates from realistic neurons. As expected, the number of eigenmodes required to match the reference signal increases with smaller diffusion time and higher bvalues. We also convert the eigenvalues to a length scale and illustrate the link between the length scale and the oscillation frequency of the eigenmode in the cell geometry. We give the transformation that links the Laplace eigenfunctions to the eigenfunctions of the BlochTorrey operator and compute the BlochTorrey eigenfunctions and eigenvalues. This work is another step in bringing advanced mathematical tools and numerical method development to the simulation and modeling of diffusion MRI.


7. 
 Liu, Chunlei, et al.
(författare)

Multimodal integration of diffusion MRI for better characterization of tissue biology
 2019

Ingår i: NMR in Biomedicine.  : John Wiley & Sons.  09523480 . 10991492. ; 32:4

Forskningsöversikt (refereegranskat)abstract
 The contrast in diffusionweighted MR images is due to variations of diffusion properties within the examined specimen. Certain microstructural information on the underlying tissues can be inferred through quantitative analyses of the diffusionsensitized MR signals. In the first part of the paper, we review two types of approach for characterizing diffusion MRI signals: Blochs equations with diffusion terms, and statistical descriptions. Specifically, we discuss expansions in terms of cumulants and orthogonal basis functions, the confinement tensor formalism and tensor distribution models. Further insights into the tissue properties may be obtained by integrating diffusion MRI with other techniques, which is the subject of the second part of the paper. We review examples involving magnetic susceptibility, structural tensors, internal field gradients, transverse relaxation and functional MRI. Integrating information provided by other imaging modalities (MR based or otherwise) could be a key to improve our understanding of how diffusion MRI relates to physiology and biology.


8. 


9. 
 Nilsson, Markus, et al.
(författare)

Resolution limit of cylinder diameter estimation by diffusion MRI : The impact of gradient waveform and orientation dispersion
 2017

Ingår i: NMR in Biomedicine.  : John Wiley and Sons.  09523480 . 10991492. ; 30:7

Tidskriftsartikel (refereegranskat)abstract
 Diffusion MRI has been proposed as a noninvasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intraaxonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with squarewave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 6080mT/m) was found to be between 4 and 8μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300mT/m, the limit was reduced to between 2 and 5μm.


10. 
 Nyblom, Hanna K., et al.
(författare)

Glucoseinduced de novo synthesis of fatty acyls causes proportional increases in INS1E cellular lipids
 2008

Ingår i: NMR in Biomedicine.  09523480 . 10991492. ; 21:4, s. 357365

Tidskriftsartikel (refereegranskat)abstract
 Raised concentrations of glucose for extended periods of time have detrimental effects on the insulinproducing Pcell. As de novo synthesis of lipids has been observed under such conditions, it was hypothesized that newly formed lipids may preferentially contain saturated fatty acids, which in particular have been associated with impaired betacell function. Glucoseinduced de novo synthesis of fatty acids in INS1E cells cultured in 5.5, 11, 20 or 27 mM glucose for 5 days was assessed by highresolution magicanglespinning (HRMAS) NMR spectroscopy and gas chromatographymass spectrometry (GCMS). The glucose origin of the increase in fatty acyls was verified by replacing glucose with [1C13]glucose during culture followed by analysis with twodimensional H1C13 NMR spectroscopy. The composition of the fatty acyls was determined by GCMS. Fatty acyls determined by HRMAS H1 NMR spectroscopy were increased fivefold in INS1E cells cultured in 20 or 27mM glucose compared with cells cultured in 5.5mM glucose. The five most abundant fatty acids with their relative percentages in INS1E cells cultured in 5.5 mM glucose were oleate (33%), palmitate (25%), stearate (19%), octadecenoate (13%) and palmitoleate (4.4%). These proportions were not affected by glucoseinduced de novo synthesis in INS1E cells cultured in 11, 20 or 27 mM glucose. It is concluded that glucoseinduced de novo lipid synthesis results in accumulation of both saturated and unsaturated fatty acids in specific proportions that are identical with those present under control conditions.

