An intravoxel oriented flow model for diffusion‐weighted imaging of the kidney

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOF_f) is applied to diffusion‐weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion‐weighted images were acquired with six b values between 0 and 800 s/mm² and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOF_f model to IVIM and DTI. In the majority of voxels the proposed IVOF_f model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow‐related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOF_f model describes diffusion‐weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.     

Degeneracy in model parameter estimation for multi‐compartmental diffusion in neuronal tissue

The ultimate promise of diffusion MRI (dMRI) models is specificity to neuronal microstructure, which may lead to distinct clinical biomarkers using noninvasive imaging. While multi‐compartment models are a common approach to interpret water diffusion in the brain in vivo, the estimation of their parameters from the dMRI signal remains an unresolved problem. Practically, even when q space is highly oversampled, nonlinear fit outputs suffer from heavy bias and poor precision. So far, this has been alleviated by fixing some of the model parameters to a priori values, for improved precision at the expense of accuracy. Here we use a representative two‐compartment model to show that fitting fails to determine the five model parameters from over 60 measurement points. For the first time, we identify the reasons for this poor performance. The first reason is the existence of two local minima in the parameter space for the objective function of the fitting procedure. These minima correspond to qualitatively different sets of parameters, yet they both lie within biophysically plausible ranges. We show that, at realistic signal‐to‐noise ratio values, choosing between the two minima based on the associated objective function values is essentially impossible. Second, there is an ensemble of very low objective function values around each of these minima in the form of a pipe. The existence of such a direction in parameter space, along which the objective function profile is very flat, explains the bias and large uncertainty in parameter estimation, and the spurious parameter correlations: in the presence of noise, the minimum can be randomly displaced by a very large amount along each pipe. Our results suggest that the biophysical interpretation of dMRI model parameters crucially depends on establishing which of the minima is closer to the biophysical reality and the size of the uncertainty associated with each parameter. Copyright © 2015 John Wiley & Sons, Ltd.     

Considerations for measuring the fractional anisotropy of metabolites with diffusion tensor spectroscopy

Diffusion tensor spectroscopy of metabolites in brain is challenging because of their lower diffusivity (i.e. less signal attenuation for a given b value) and much poorer signal‐to‐noise ratio relative to water. Although diffusion tensor acquisition protocols have been studied in detail for water, they have not been evaluated systematically for the measurement of the fractional anisotropy of metabolites such as N‐acetylaspartate, creatine and choline in the white and gray matter of human brain. Diffusion tensor spectroscopy was performed in vivo with variable maximal b values (1815 or 5018 s/mm²). Experiments were also performed on simulated spectra and isotropic alcohol phantoms of various diffusivities, ranging from approximately 0.54 × 10^?3 to 0.13 × 10^?3 mm²/s, to assess the sensitivity of diffusion tensor spectroscopic parameters to low diffusivity, noise and b value. The low maximum b value of 1815 s/mm² yielded elevated fractional anisotropy (0.53–0.60) of N‐acetylaspartate in cortical gray matter relative to the more isotropic value (0.25–0.30) obtained with a higher b value of 5018 s/mm²; in contrast, the fractional anisotropy of white matter was consistently anisotropic with the different maximal b values (i.e. 0.43–0.54 for b = 1815 s/mm² and 0.47–0.51 for b = 5018 s/mm²). Simulations, phantoms and in vivo data indicate that greater signal attenuation, to a degree, is desirable for the accurate quantification of diffusion‐weighted spectra for slowly diffusing metabolites. Copyright © 2010 John Wiley & Sons, Ltd.     

Detection of acute nervous system injury with advanced diffusion‐weighted MRI: a simulation and sensitivity analysis

Diffusion‐weighted imaging (DWI) is a powerful tool to investigate the microscopic structure of the central nervous system (CNS). Diffusion tensor imaging (DTI), a common model of the DWI signal, has a demonstrated sensitivity to detect microscopic changes as a result of injury or disease. However, DTI and other similar models have inherent limitations that reduce their specificity for certain pathological features, particularly in tissues with complex fiber arrangements. Methods such as double pulsed field gradient (dPFG) and q‐vector magic angle spinning (qMAS) have been proposed to specifically probe the underlying microscopic anisotropy without interference from the macroscopic tissue organization. This is particularly important for the study of acute injury, where abrupt changes in the microscopic morphology of axons and dendrites manifest as focal enlargements known as beading. The purpose of this work was to assess the relative sensitivity of DWI measures to beading in the context of macroscopic fiber organization and edema. Computational simulations of DWI experiments in normal and beaded axons demonstrated that, although DWI models can be highly specific for the simulated pathologies of beading and volume fraction changes in coherent fiber pathways, their sensitivity to a single idealized pathology is considerably reduced in crossing and dispersed fibers. However, dPFG and qMAS have a high sensitivity for beading, even in complex fiber tracts. Moreover, in tissues with coherent arrangements, such as the spinal cord or nerve fibers in which tract orientation is known a priori, a specific dPFG sequence variant decreases the effects of edema and improves specificity for beading. Collectively, the simulation results demonstrate that advanced DWI methods, particularly those which sample diffusion along multiple directions within a single acquisition, have improved sensitivity to acute axonal injury over conventional DTI metrics and hold promise for more informative clinical diagnostic use in CNS injury evaluation. Copyright © 2015 John Wiley & Sons, Ltd.     

DTI at long diffusion time improves fiber tracking

While diffusion‐tensor‐imaging tractography provides remarkable in vivo anatomical connectivity of the central nervous system, the majority of DTI studies to date are predominantly limited to tracking large white‐matter fibers. This study investigated DTI tractography using long diffusion time (t_diff) to improve tracking of thinner fibers in fixed rhesus monkey brains. Stimulated Echo Acquisition Mode (STEAM) sequence on a 3T Siemens TRIO was modified to include a diffusion module. DTI was acquired using STEAM with t_diff of 48 and 192 ms with matched signal‐to‐noise ratios (SNR). Comparisons were also made with the conventional double‐spin echo (DSE) at a short t_diff of 45 ms. Not only did the fractional anisotropy increase significantly with the use of long diffusion time, but directional entropy measures indicated that there was an increased coherence amongst neighboring tensors. Further, the magnitude of the major eigenvector was larger at the t_diff = 192 ms as compared to the short t_diff. Probabilistic connectivity maps at long t_diff showed larger areas of connectivity with the use of long diffusion time, which traversed deeper into areas of low anisotropy. With tractography, it was found that the length of the fibers, increased by almost 10% in the callosal fibers that branch into the paracentral gyrus, the precentral gyrus and the post central gyrus. A similar increase of about 20% was observed in the fibers of the internal capsule. These findings offer encouraging data that DTI at long diffusion time could improve tract tracing of small fibers in areas of low fractional anisotropy (FA), such as at the interfaces of white matter and grey matter. Copyright © 2010 John Wiley & Sons, Ltd.     

Fractional anisotropy and mean diffusivity: comparison between 3.0-T and 1.5-T diffusion tensor imaging with parallel imaging using histogram and region of interest analysis

We performed a comparison study focusing on differences in fractional anisotropy (FA) and mean diffusivity (MD) between 3-T and 1.5-T diffusion tensor imaging (DTI) with parallel imaging. Thirty healthy volunteers underwent DTI with an eight-channel phased-array coil at both 3 T and 1.5 T. Histogram and region of interest (ROI) analyses were performed. Paired t tests were applied for statistical analysis. Signal-to-noise ratios of these regions were also measured. For histogram analysis, peak location of FA was significantly lower at 3 T than at 1.5 T (P = 0.04). Mean FA was significantly higher at 3 T than at 1.5 T (P = 0.002). Peak location of MD was significantly lower at 3 T than at 1.5 T (P < 0.001). Mean MD was significantly lower at 3 T than at 1.5 T (P < 0.001). In ROI analysis, FA was significantly larger at 3 T than at 1.5 T in the centrum semiovale (P < 0.001), middle cerebellar peduncle (P < 0.001), cerebral peduncle (P = 0.006), posterior limb of the internal capsule (P = 0.007), genu (P < 0.001) and splenium (P < 0.001). FA was significantly lower at 3 T than at 1.5 T in the globus pallidus (P < 0.001). MD was significantly smaller at 3 T than at 1.5 T in the globus pallidus (P = 0.007), thalamus (P < 0.001), centrum semiovale (P < 0.001), middle cerebellar peduncle (P < 0.001), cerebral peduncle (P = 0.01), posterior limb of the internal capsule (P < 0.001), genu (P = 0.01) and splenium (P < 0.001). Significant differences in FA and MD exist between 3 T and 1.5 T for whole-brain histogram analysis and ROI analysis.     

High‐resolution diffusion tensor imaging of the human kidneys using a free‐breathing,multi‐slice,targeted field of view approach

Fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) can be used to image the kidneys without any contrast media. FA of the medulla has been shown to correlate with kidney function. It is expected that higher spatial resolution would improve the depiction of small structures within the kidney. However, the achievement of high spatial resolution in renal DTI remains challenging as a result of respiratory motion and susceptibility to diffusion imaging artefacts. In this study, a targeted field of view (TFOV) method was used to obtain high‐resolution FA maps and colour‐coded diffusion tensor orientations, together with measures of the medullary and cortical FA, in 12 healthy subjects. Subjects were scanned with two implementations (dual and single kidney) of a TFOV DTI method. DTI scans were performed during free breathing with a navigator‐triggered sequence. Results showed high consistency in the greyscale FA, colour‐coded FA and diffusion tensors across subjects and between dual‐ and single‐kidney scans, which have in‐plane voxel sizes of 2 × 2 mm² and 1.2 × 1.2 mm², respectively. The ability to acquire multiple contiguous slices allowed the medulla and cortical FA to be quantified over the entire kidney volume. The mean medulla and cortical FA values were 0.38 ± 0.017 and 0.21 ± 0.019, respectively, for the dual‐kidney scan, and 0.35 ± 0.032 and 0.20 ± 0.014, respectively, for the single‐kidney scan. The mean FA between the medulla and cortex was significantly different (p < 0.001) for both dual‐ and single‐kidney implementations. High‐spatial‐resolution DTI shows promise for improving the characterization and non‐invasive assessment of kidney function. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.     

Precision and accuracy of diffusion kurtosis estimation and the influence of b‐value selection

Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non‐Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b‐values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b‐value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b‐value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b‐values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b‐values less than 1 ms/μm², whereas maximal b‐values of about 2.5 ms/μm² were found to be optimal in WM. Protocols including additional higher order terms of the cumulant expansion were found to provide higher accuracy for the more commonly used b‐value regime in GM, but were associated with higher error in WM. Averaged over multiple voxels, a net average error of around 15% for both WM and GM was observed for the optimal b‐value choice. These results suggest caution when using DKI generated metrics for microstructural modeling and when comparing results obtained using different fitting techniques and b‐values.     

Multiband diffusion‐weighted MRI of the eye and orbit free of geometric distortions using a RARE‐EPI hybrid

Diffusion‐weighted imaging (DWI) provides information on tissue microstructure. Single‐shot echo planar imaging (EPI) is the most common technique for DWI applications in the brain, but is prone to geometric distortions and signal voids. Rapid acquisition with relaxation enhancement [RARE, also known as fast spin echo (FSE)] imaging presents a valuable alternative to DWI with high anatomical accuracy. This work proposes a multi‐shot diffusion‐weighted RARE‐EPI hybrid pulse sequence, combining the anatomical integrity of RARE with the imaging speed and radiofrequency (RF) power deposition advantage of EPI. The anatomical integrity of RARE‐EPI was demonstrated and quantified by center of gravity analysis for both morphological images and diffusion‐weighted acquisitions in phantom and in vivo experiments at 3.0 T and 7.0 T. The results indicate that half of the RARE echoes in the echo train can be replaced by EPI echoes whilst maintaining anatomical accuracy. The reduced RF power deposition of RARE‐EPI enabled multiband RF pulses facilitating simultaneous multi‐slice imaging. This study shows that diffusion‐weighted RARE‐EPI has the capability to acquire high fidelity, distortion‐free images of the eye and the orbit. It is shown that RARE‐EPI maintains the immunity to B₀ inhomogeneities reported for RARE imaging. This benefit can be exploited for the assessment of ocular masses and pathological changes of the eye and the orbit.     

Effects of hypotonic stress and ouabain on the apparent diffusion coefficient of water at cellular and tissue levels in Aplysia

There is evidence that physiological or pathological cell swelling is associated with a decrease of the apparent diffusion coefficient (ADC) of water in tissues, as measured with MRI. However the mechanism remains unclear. Magnetic resonance microscopy, performed on small tissue samples, has the potential to distinguish effects occurring at cellular and tissue levels. A three‐dimensional diffusion prepared fast imaging with steady‐state free precession sequence for MR microscopy was implemented on a 17.2 T imaging system and used to investigate the effect of two biological challenges known to cause cell swelling, exposure to a hypotonic solution or to ouabain, on Aplysia nervous tissue. The ADC was measured inside isolated neuronal soma and in the region of cell bodies of the buccal ganglia. Both challenges resulted in an ADC increase inside isolated neuronal soma (+31 ± 24% and +30 ± 11%, respectively) and an ADC decrease at tissue level in the buccal ganglia (?12 ± 5% and ?18 ± 8%, respectively). A scenario involving a layer of water molecules bound to the inflating cell membrane surface is proposed to reconcile this apparent discrepancy. Copyright © 2014 John Wiley & Sons, Ltd.     

Reproducibility of tract‐specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 tesla

Damage to specific white matter tracts within the spinal cord can often result in the particular neurological syndromes that characterize myelopathies such as traumatic spinal cord injury. Noninvasive visualization of these tracts with imaging techniques that are sensitive to microstructural integrity is an important clinical goal. Diffusion tensor imaging (DTI)‐ and magnetization transfer (MT)‐derived quantities have shown promise in assessing tissue health in the central nervous system. In this paper, we demonstrate that DTI of the cervical spinal cord can reliably discriminate sensory (dorsal) and motor (lateral) columns. From data derived from nine healthy volunteers, two raters quantified column‐specific parallel (λ_||) and perpendicular (λ_?) diffusivity, fractional anisotropy (FA), mean diffusivity (MD), and MT‐weighted signal intensity relative to cerebrospinal fluid (MTCSF) over two time‐points separated by more than 1 week. Cross‐sectional means and standard deviations of these measures in the lateral and dorsal columns were as follows: λ_||: 2.13 ± 0.14 and 2.14 ± 0.11 μm²/ms; λ_?: 0.67 ± 0.16 and 0.61 ± 0.09 μm²/ms; MD: 1.15 ± 0.15 and 1.12 ± 0.08 μm²/ms; FA: 0.68 ± 0.06 and 0.68 ± 0.05; MTCSF: 0.52 ± 0.05 and 0.50 ± 0.05. We examined the variability and interrater and test‐retest reliability for each metric. These column‐specific MR measurements are expected to enhance understanding of the intimate structure‐function relationship in the cervical spinal cord and may be useful for the assessment of disease progression. Copyright © 2009 John Wiley & Sons, Ltd.     

Improvement of accuracy of diffusion MRI using real‐time self‐gated data acquisition

Diffusion‐weighted and diffusion tensor MR imaging (DWI, DTI) techniques are generally performed with signal averaging of multiple measurements to improve the signal‐to‐noise ratio (SNR) and the accuracy of the diffusion measurement. Any discrepancy in the images between different averages causes errors which reduce the accuracy of the diffusion MRI measurements. In this report, a motion artifact reduction scheme with a real‐time self‐gated (RTSG) data acquisition for diffusion MRI using two‐dimensional echo planar imaging (2D EPI) is described. A subject's translational and rotational motions during application of the diffusion gradients induce an additional phase term and a shift of the echo‐peak position in the k‐space, respectively. These motions also reduce the magnitude of the echo‐peak. Based on these properties, we present a new scheme which monitors the position and the magnitude of the largest echo‐peak in the k‐space. The position and the magnitude of each average is compared to those of early averaging shot to determine if the differences are within or beyond the given threshold values. Motion corrupted data are reacquired in real time. Our preliminary results using RTSG indicate an improvement of both SNR and the accuracy of diffusion MRI measurements. Copyright © 2009 John Wiley & Sons, Ltd.     

The apparent dependence of the diffusion coefficient of N-acetylaspartate upon magnetic field strength: evidence of an interaction with NMR methodology

An inverse relationship between applied magnetic field strength and the apparent diffusion coefficient (ADC) of several important brain metabolites including N-acetyl-l-aspartate (NAA), choline and creatine, measured in vivo using proton magnetic resonance spectroscopy (MRS), has been reported. In this investigation, using phantom studies of NAA at magnetic field strengths of 3 and 7 T, these observations have been verified under controlled MRS conditions in vitro, and the ADC of NAA has been found to vary inversely with magnetic field strength, decreasing at a rate of 2.5%/T at 20 degrees C. We have also assessed whether the effect is a function of a systemic bias in methodology, or if the effect is actually on the rate of molecular diffusion. This was done using an MRS-independent method for measurement of molecular diffusion in NAA phantoms at 0, 0.025 and 7 T applied magnetic field strengths. As a result, it has been demonstrated that the observed apparent magnetic field dependence of the ADC of NAA is a consequence of the NMR measurement and is apparently not a real effect on molecular diffusion.     

On the magnetic field dependence of deuterium metabolic imaging

Deuterium metabolic imaging (DMI) is a novel MR‐based method to spatially map metabolism of deuterated substrates such as [6,6'‐²H₂]‐glucose in vivo. Compared with traditional ¹³C‐MR‐based metabolic studies, the MR sensitivity of DMI is high due to the larger ²H magnetic moment and favorable T₁ and T₂ relaxation times. Here, the magnetic field dependence of DMI sensitivity and transmit efficiency is studied on phantoms and rat brain postmortem at 4, 9.4 and 11.7 T. The sensitivity and spectral resolution on human brain in vivo are investigated at 4 and 7 T before and after an oral dose of [6,6'‐²H₂]‐glucose. For small animal surface coils (Ø 30 mm), the experimentally measured sensitivity and transmit efficiency scale with the magnetic field to a power of +1.75 and ?0.30, respectively. These are in excellent agreement with theoretical predictions made from the principle of reciprocity for a coil noise‐dominant regime. For larger human surface coils (Ø 80 mm), the sensitivity scales as a +1.65 power. The spectral resolution increases linearly due to near‐constant linewidths. With optimal multireceiver arrays the acquisition of DMI at a nominal 1 mL spatial resolution is feasible at 7 T.     

Short‐ and long‐term reproducibility of BOLD signal change induced by breath‐holding at 1.5 and 3 T

Cerebrovascular reactivity (CVR) can give insight into the cerebrovascular function. CVR can be estimated by measuring a blood‐oxygen‐level‐dependent (BOLD) response combined with breath‐holding (BH). The reproducibility of this technique has been addressed and existing studies have focused on short‐term reproducibility using a 3 T magnetic resonance imaging (MRI) system. However, little is known about the long‐term reproducibility of this procedure and the corresponding reproducibility using a 1.5 T MRI system. Here, we systematically examined the short‐ and long‐term reproducibility of BOLD responses to BH across field strengths. Nine subjects participated in three MRI sessions separated by 30 minutes (sessions 1 and 2: short term) and 68–92 days (sessions 1 and 3, long term) at both 1.5 and 3 T MRI. Our findings revealed that significant differences between field strengths were detected in the activated gray matter volume and BOLD signal change (both P < 0.001), with smaller magnitudes at 1.5 T. However, activation patterns were reproducible, independent of the time interval, brain region or field strength. All interscan coefficient of variation values were below the 33% fiducial limit, and the intraclass correlation coefficient values were above 0.4, which is usually considered the acceptability limit in functional studies. These findings suggest that the response of BOLD signal to BH for assessing CVR is reproducible over time at 1.5 and 3 T. This technique can be considered a tool for monitoring longitudinal changes in patients with cerebrovascular diseases, and its use should be encouraged for clinical 1.5 T MRI systems.     

Probing metabolite diffusion at ultra‐short time scales in the mouse brain using optimized oscillating gradients and “short”‐echo‐time diffusion‐weighted MRS

Measuring diffusion at ultra‐short time scales may yield information about short‐range intracellular structure and cytosol viscosity. However, reaching such time scales usually requires oscillating gradients, which in turn imply long echo times T_E. Here we propose a new kind of stretched oscillating gradient that allows us to increase diffusion‐weighting b while preserving spectral and temporal properties of the gradient modulation. We used these optimized gradients to measure metabolite diffusion in the mouse brain down to effective diffusion times of 1 ms while keeping T_E relatively short (60 ms). At such T_E, a significant macromolecule signal could still be observed and used as an internal reference of approximately null diffusivity, which proved critical to discard datasets corrupted by some motion artifact. The methods introduced here may be useful to improve the accuracy and precision of metabolite apparent diffusion coefficient measurements with oscillating gradients.     

Determination of the appropriate b value and number of gradient directions for high‐angular‐resolution diffusion‐weighted imaging

High‐angular‐resolution diffusion‐weighted imaging (HARDI) is one of the most common MRI acquisition schemes for use with higher order models of diffusion. However, the optimal b value and number of diffusion‐weighted (DW) directions for HARDI are still undetermined, primarily as a result of the large number of available reconstruction methods and corresponding parameters, making it impossible to identify a single criterion by which to assess performance. In this study, we estimate the minimum number of DW directions and optimal b values required for HARDI by focusing on the angular frequency content of the DW signal itself. The spherical harmonic (SH) series provides the spherical analogue of the Fourier series, and can hence be used to examine the angular frequency content of the DW signal. Using high‐quality data acquired along 500 directions over a range of b values, we estimate that SH terms above l = 8 are negligible in practice for b values up to 5000 s/mm², implying that a minimum of 45 DW directions is sufficient to fully characterise the DW signal. l > 0 SH terms were found to increase as a function of b value, levelling off at b = 3000 s/mm², suggesting that this value already provides the highest achievable angular resolution. In practice, it is recommended to acquire more than the minimum of 45 DW directions to avoid issues with imperfections in the uniformity of the DW gradient directions and to meet signal‐to‐noise requirements of the intended reconstruction method. Copyright © 2013 John Wiley & Sons, Ltd.     

Fast and accurate initialization of the free‐water imaging model parameters from multi‐shell diffusion MRI

Cerebrospinal fluid partial volume effect is a known bias in the estimation of Diffusion Tensor Imaging (DTI) parameters from diffusion MRI data. The Free‐Water Imaging model for diffusion MRI data adds a second compartment to the DTI model, which explicitly accounts for the signal contribution of extracellular free‐water, such as cerebrospinal fluid. As a result the DTI parameters obtained through the free‐water model are corrected for partial volume effects, and thus better represent tissue microstructure. In addition, the model estimates the fractional volume of free‐water, and can be used to monitor changes in the extracellular space. Under certain assumptions, the model can be estimated from single‐shell diffusion MRI data. However, by using data from multi‐shell diffusion acquisitions, these assumptions can be relaxed, and the fit becomes more robust. Nevertheless, fitting the model to multi‐shell data requires high computational cost, with a non‐linear iterative minimization, which has to be initialized close enough to the global minimum to avoid local minima and to robustly estimate the model parameters. Here we investigate the properties of the main initialization approaches that are currently being used, and suggest new fast approaches to improve the initial estimates of the model parameters. We show that our proposed approaches provide a fast and accurate initial approximation of the model parameters, which is very close to the final solution. We demonstrate that the proposed initializations improve the final outcome of non‐linear model fitting.     

Analysis of errors in diffusion kurtosis imaging caused by slice crosstalk in simultaneous multi‐slice imaging

Simultaneous multi‐slice (SMS) imaging techniques accelerate diffusion MRI data acquisition. However, slice separation is imperfect and results in residual signal leakage between the simultaneously excited slices. The resulting consistent bias may adversely affect diffusion model parameter estimation. Although this bias is usually small and might not affect the simplified diffusion tensor model significantly, higher order diffusion models such as kurtosis are likely to be more susceptible to such effects. In this work, two SMS reconstruction techniques and an alternative acquisition approach were tested to quantify the effects of slice crosstalk on diffusion kurtosis parameters. In reconstruction, two popular slice separation algorithms, slice GRAPPA and split‐slice GRAPPA, are evaluated to determine the effect of slice leakage on diffusion kurtosis metrics. For the alternative acquisition, the slice pairings were varied across diffusion weighted images such that the signal leakage does not come from the same overlapped slice for all diffusion encodings. Simulation results demonstrated the potential benefits of randomizing the slice pairings. However, various experimental factors confounded the advantages of slice pair randomization. In volunteer experiments, region‐of‐interest analyses found high metric errors with each of the SMS acquisitions and reconstructions in the brain white matter.