Microscopic diffusion anisotropy in the human brain: reproducibility, normal values, and comparison with the fractional anisotropy

DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects

(1) Background: Glioblastoma multiforme (GBM) shows complex mechanisms of spreading of the tumor cells, up to remote areas, and little is still known of these mechanisms, thus we focused on MRI abnormalities observable in the tumor and the brain adjacent to the lesion, up to the contralateral hemisphere, with a special interest on tensor diffusion imaging informing on white matter architecture; (2) Material and Methods: volumes, macroscopic volume (MV), brain-adjacent-tumor (BAT) volume and abnormal color-coded DTI volume (aCCV), and region-of-interest samples (probe volumes, ipsi, and contra lateral to the lesion), with their MRI characteristics, apparent diffusion coefficient (ADC), fractional anisotropy (FA) values, and number of fibers (DTI fiber tracking) were analyzed in patients suffering GBM (n = 15) and metastasis (n = 9), and healthy subjects (n = 15), using ad hoc statistical methods (type I error = 5%) (3) Results: GBM volumes were larger than metastasis volumes, aCCV being larger in GBM and BAT ADC was higher in metastasis, ADC decreased centripetally in metastasis, FA increased centripetally either in GBM or metastasis, MV and BAT FA values were higher in GBM, ipsi FA values of GBM ROIs were higher than those of metastasis, and the GBM ipsi number of fibers was higher than the GBM contra number of fibers; (4) Conclusions: The MV, BAT and especially the aCCV, as well as their related water diffusion characteristics, could be useful biomarkers in oncology and functional oncology.

Elevated Circulating Microparticle Subpopulations in Incidental Cerebral White Matter Hyperintensities: A Multimodal Study

Asymptomatic (or "silent") manifestations of cerebral small vessel disease (CSVD) are widely recognized through incidental findings of white matter hyperintensities (WMHs) as a result of magnetic resonance imaging (MRI). This study aims to examine the potential associations of surrogate markers for the evaluation of white matter integrity in CSVD among asymptomatic individuals through a battery of profiling involving QRISK2 cardiocerebrovascular risk prediction, neuroimaging, neurocognitive evaluation, and microparticles (MPs) titers. Sixty asymptomatic subjects (mean age: 39.83 ± 11.50 years) with low to moderate QRISK2 scores were recruited and underwent neurocognitive evaluation for memory and cognitive performance, peripheral venous blood collection for enumeration of selected MPs subpopulations, and 3T MRI brain scan with specific diffusion MRI (dMRI) sequences inclusive of diffusion tensor imaging (DTI). WMHs were detected in 20 subjects (33%). Older subjects (mean age: 46.00 ± 12.00 years) had higher WMHs prevalence, associated with higher QRISK2 score and reduced processing speed. They also had significantly higher mean percentage of platelet (CD62P)- and leukocyte (CD62L)-derived MPs. No association was found between reduced white matter integrity-especially at the left superior longitudinal fasciculus (LSLF)-with age and neurocognitive function; however, LSLF was associated with higher QRISK2 score, total MPs, and CD62L- and endothelial cell-derived MPs (CD146). Therefore, this study establishes these multimodal associations as potential surrogate markers for "silent" CSVD manifestations in the well-characterized cardiocerebrovascular demographic of relatively young, neurologically asymptomatic adults. Furthermore, to the best of our knowledge, this study is the first to exhibit elevated MP counts in asymptomatic CSVD (i.e., CD62P and CD62L), which warrants further delineation.

Toward Quantification: Microstructure and Magnetic Resonance Fingerprinting

Quantitative magnetic resonance imaging (MRI) is a long-standing challenge. We advocate that the origin of the problem is the simplification applied in commonly used models of the MRI signal relation to the target parameters of biological tissues. Two research fields are briefly reviewed as ways to respond to the challenge of quantitative MRI, both experiencing an exponential growth right now. Microstructure MRI strives to build physiology-based models from cells to signal and, given the signal, back to the cells again. Magnetic resonance fingerprinting aims at efficient simultaneous determination of multiple signal parameters. The synergy of these yet disjoined approaches promises truly quantitative MRI with specific target-oriented diagnostic tools rather than universal imaging methods.

Brain White-Matter Degeneration Due to Aging and Parkinson Disease as Revealed by Double Diffusion Encoding

Microstructure imaging by means of multidimensional diffusion encoding is increasingly applied in clinical research, with expectations that it yields a parameter that better correlates with clinical disability than current methods based on single diffusion encoding. Under the assumption that diffusion within a voxel can be well described by a collection of diffusion tensors, several parameters of this diffusion tensor distribution can be derived, including mean size, variance of sizes, orientational dispersion, and microscopic anisotropy. The information provided by multidimensional diffusion encoding also enables us to decompose the sources of the conventional fractional anisotropy and mean kurtosis. In this study, we explored the utility of the diffusion tensor distribution approach for characterizing white-matter degeneration in aging and in Parkinson disease by using double diffusion encoding. Data from 23 healthy older subjects and 27 patients with Parkinson disease were analyzed. Advanced age was associated with greater mean size and size variances, as well as smaller microscopic anisotropy. By analyzing the parameters underlying diffusion kurtosis, we found that the reductions of kurtosis in aging and Parkinson disease reported in the literature are likely driven by the reduction in microscopic anisotropy. Furthermore, microscopic anisotropy correlated with the severity of motor impairment in the patients with Parkinson disease. The present results support the use of multidimensional diffusion encoding in clinical studies and are encouraging for its future clinical implementation.

Human Cochlear Nucleus on 7 Tesla Diffusion Tensor Imaging: Insights Into Micro-anatomy and Function for Auditory Brainstem Implant Surgery

OBJECTIVE

The cochlear nucleus (CN) is the target of the auditory brainstem implant (ABI). Most ABI candidates have Neurofibromatosis Type 2 (NF2) and distorted brainstem anatomy from bilateral vestibular schwannomas. The CN is difficult to characterize as routine structural MRI does not resolve detailed anatomy. We hypothesize that diffusion tensor imaging (DTI) enables both in vivo localization and quantitative measurements of CN morphology.

STUDY DESIGN

We analyzed 7 Tesla (T) DTI images of 100 subjects (200 CN) and relevant anatomic structures using an MRI brainstem atlas with submillimetric (50 μm) resolution.

SETTING

Tertiary referral center.

PATIENTS

Young healthy normal hearing adults.

INTERVENTION

Diagnostic.

MAIN OUTCOME MEASURES

Diffusion scalar measures such as fractional anisotropy (FA), mean diffusivity (MD), mode of anisotropy (Mode), principal eigenvectors of the CN, and the adjacent inferior cerebellar peduncle (ICP).

RESULTS

The CN had a lamellar structure and ventral-dorsal fiber orientation and could be localized lateral to the inferior cerebellar peduncle (ICP). This fiber orientation was orthogonal to tracts of the adjacent ICP where the fibers run mainly caudal-rostrally. The CN had lower FA compared to the medial aspect of the ICP (0.44 ± 0.09 vs. 0.64 ± 0.08, p < 0.001).

CONCLUSIONS

7T DTI enables characterization of human CN morphology and neuronal substructure. An ABI array insertion vector directed more caudally would better correspond to the main fiber axis of CN. State-of-the-art DTI has implications for ABI preoperative planning and future image guidance-assisted placement of the electrode array.

Evaluation of white matter microstructure in patients with Parkinson's disease using microscopic fractional anisotropy

PURPOSE

Micro fractional anisotropy (μFA) is more accurate than conventional fractional anisotropy (FA) for assessing microscopic tissue properties and can overcome limitations related to crossing white matter fibres. We compared μFA and FA for evaluating white matter changes in patients with Parkinson's disease (PD).

METHODS

We compared FA and μFA measures between 25 patients with PD and 25 age- and gender-matched healthy controls using tract-based spatial statistics (TBSS) analysis. We also examined potential correlations between changes, revealed by conventional FA or μFA, and disease duration or Unified Parkinson's Disease Rating Scale (UPDRS)-III scores.

RESULTS

Compared with healthy controls, patients with PD had significantly reduced μFA values, mainly in the anterior corona radiata (ACR). In the PD group, μFA values (primarily those from the ACR) were significantly negatively correlated with UPDRS-III motor scores. No significant changes or correlations with disease duration or UPDRS-III scores with tissue properties were detected using conventional FA.

CONCLUSION

μFA can evaluate microstructural changes that occur during white matter degeneration in patients with PD and may overcome a key limitation of FA.

Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems

Microstructure imaging techniques based on tensor-valued diffusion encoding have gained popularity within the MRI research community. Unlike conventional diffusion encoding-applied along a single direction in each shot-tensor-valued encoding employs diffusion encoding along multiple directions within a single preparation of the signal. The benefit is that such encoding may probe tissue features that are not accessible by conventional encoding. For example, diffusional variance decomposition (DIVIDE) takes advantage of tensor-valued encoding to probe microscopic diffusion anisotropy independent of orientation coherence. The drawback is that tensor-valued encoding generally requires gradient waveforms that are more demanding on hardware; it has therefore been used primarily in MRI systems with relatively high performance. The purpose of this work was to explore tensor-valued diffusion encoding on clinical MRI systems with varying performance to test its technical feasibility within the context of DIVIDE. We performed whole-brain imaging with linear and spherical b-tensor encoding at field strengths between 1.5 and 7 T, and at maximal gradient amplitudes between 45 and 80 mT/m. Asymmetric gradient waveforms were optimized numerically to yield b-values up to 2 ms/μm2. Technical feasibility was assessed in terms of the repeatability, SNR, and quality of DIVIDE parameter maps. Variable system performance resulted in echo times between 83 to 115 ms and total acquisition times of 6 to 9 minutes when using 80 signal samples and resolution 2×2×4 mm3. As expected, the repeatability, signal-to-noise ratio and parameter map quality depended on hardware performance. We conclude that tensor-valued encoding is feasible for a wide range of MRI systems-even at 1.5 T with maximal gradient waveform amplitudes of 33 mT/m-and baseline experimental design and quality parameters for all included configurations. This demonstrates that tissue features, beyond those accessible by conventional diffusion encoding, can be explored on a wide range of MRI systems.

In vivo microscopic diffusional kurtosis imaging with symmetrized double diffusion encoding EPI

PURPOSE

Diffusional kurtosis imaging (DKI) measures the deviation of the displacement probability from a normal distribution, complementing the data commonly acquired by diffusion MRI. It is important to elucidate the sources of kurtosis contrast, particularly in biological tissues where microscopic kurtosis (intrinsic kurtosis) and diffusional heterogeneity may co-exist.

METHODS

We have developed a technique for microscopic kurtosis MRI, dubbed microscopic diffusional kurtosis imaging (µDKI), using a symmetrized double diffusion encoding (s-DDE) EPI sequence. We compared this newly developed µDKI to conventional DKI methods in both a triple compartment phantom and in vivo.

RESULTS

Our results showed that whereas conventional DKI and µDKI provided similar measurements in a compartment of monosphere beads, kurtosis measured by µDKI was significantly less than that measured by conventional DKI in a compartment of mixed Gaussian pools. For in vivo brain imaging, µDKI showed small yet significantly lower kurtosis measurement in regions of the cortex, CSF, and internal capsule compared to the conventional DKI approach.

CONCLUSIONS

Our study showed that µDKI is less susceptible than conventional DKI to sub-voxel diffusional heterogeneity. Our study also provided important preliminary demonstration of our technique in vivo, warranting future studies to investigate its diagnostic use in examining neurological disorders.

Double diffusion encoding MRI for the clinic

PURPOSE

The purpose of this study is to develop double diffusion encoding (DDE) MRI methods for clinical use. Microscopic diffusion anisotropy measurements from DDE promise greater specificity to changes in tissue microstructure compared with conventional diffusion tensor imaging, but implementation of DDE sequences on whole-body MRI scanners is challenging because of the limited gradient strengths and lengthy acquisition times.

METHODS

A custom single-refocused DDE sequence was implemented on a 3T whole-body scanner. The DDE gradient orientation scheme and sequence parameters were optimized based on a Gaussian diffusion assumption. Using an optimized 5-min DDE acquisition, microscopic fractional anisotropy (μFA) maps were acquired for the first time in multiple sclerosis patients.

RESULTS

Based on simulations and in vivo human measurements, six parallel and six orthogonal diffusion gradient pairs were found to be the minimum number of diffusion gradient pairs necessary to produce a rotationally invariant measurement of μFA. Simulations showed that optimal precision and accuracy of μFA measurements were obtained using b-values between 1500 and 3000 s/mm² . The μFA maps showed improved delineation of multiple sclerosis lesions compared with conventional fractional anisotropy and distinct contrast from T₂ -weighted fluid attenuated inversion recovery and T₁ -weighted imaging.

CONCLUSION

The μFA maps can be measured using DDE in a clinical setting and may provide new opportunities for characterizing multiple sclerosis lesions and other types of tissue degeneration. Magn Reson Med 80:507-520, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Distinguishing neuronal from astrocytic subcellular microstructures using in vivo Double Diffusion Encoded 1H MRS at 21.1 T

Measuring cellular microstructures non-invasively and achieving specificity towards a cell-type population within an interrogated in vivo tissue, remains an outstanding challenge in brain research. Magnetic Resonance Spectroscopy (MRS) provides an opportunity to achieve cellular specificity via the spectral resolution of metabolites such as N-Acetylaspartate (NAA) and myo-Inositol (mI), which are considered neuronal and astrocytic markers, respectively. Yet the information typically obtained with MRS describes metabolic concentrations, diffusion coefficients or relaxation rates rather than microstructures. Understanding how these metabolites are compartmentalized is a challenging but important goal, which so far has been mainly addressed using diffusion models. Here, we present direct in vivo evidence for the confinement of NAA and mI within sub-cellular components, namely, the randomly oriented process of neurons and astrocytes, respectively. Our approach applied Relaxation Enhanced MRS at ultrahigh (21.1 T) field, and used its high ¹H sensitivity to measure restricted diffusion correlations for NAA and mI using a Double Diffusion Encoding (DDE) filter. While very low macroscopic anisotropy was revealed by spatially localized Diffusion Tensor Spectroscopy, DDE displayed characteristic amplitude modulations reporting on confinements in otherwise randomly oriented anisotropic microstructures for both metabolites. This implies that for the chosen set of parameters, the DDE measurements had a biased sensitivity towards NAA and mI sited in the more confined environments of neurites and astrocytic branches, than in the cell somata. These measurements thus provide intrinsic diffusivities and compartment diameters, and revealed subcellular neuronal and astrocytic morphologies in normal in vivo rat brains. The relevance of these measurements towards human applications—which could in turn help understand CNS plasticity as well as diagnose brain diseases—is discussed.

Test-retest reliability of high spatial resolution diffusion tensor and diffusion kurtosis imaging

We assessed the test-retest reliability of high spatial resolution diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Diffusion MRI was acquired using a Siemens 3 Tesla Prisma scanner with 80 mT/m gradients and a 32-channel head coil from each of 3 concussive traumatic brain injury (cTBI) patients and 4 controls twice 0 to 24 days apart. Coefficients of variation (CoV) for DTI parameters were calculated in each DTI Studio parcellated white matter tract at 1.25 mm and 1.75 mm isotropic voxel resolution, as well as DKI parameters at 1.75 mm isotropic. Overall, fractional anisotropy had the best reliability, with mean CoV at 5% for 1.25 mm and 3.5% for 1.75 mm isotropic voxels. Mean CoV for the other DTI metrics were <7.0% for both 1.25 and 1.75 mm isotropic voxels. The mean CoV was ≤4.5% across the DKI metrics. In the commonly injured orbitofrontal and temporal pole regions CoV was <3.5% for all parameters. Thus, with appropriate processing, high spatial resolution advanced diffusion MRI has good to excellent test-retest reproducibility in both human cTBI patients and controls. However, further technical improvements will be needed to reliably discern the most subtle diffusion abnormalities, especially at high spatial resolution.

Determining mean fractional anisotropy using DDCOSY: preliminary results in biological tissues

Complex materials are ubiquitous in science, engineering and nature. One important parameter for characterising their morphology is the degree of anisotropy. Magnetic resonance imaging offers non-invasive methods for quantitative measurements of the materials anisotropy, most commonly via diffusion tensor imaging and the subsequent extraction of the spatially resolved fractional anisotropy (FA) value. Here, we propose an alternative way of determining the FA as a sample average for cases where spatially resolved methods are not needed or not applicable. It is based on a particular diffusion-diffusion correlation spectroscopy protocol, allowing for the extraction of the mean (i.e. sample averaged) FA value. We demonstrate that mean FA values obtained from three anisotropic biological tissues are consistent with those extracted using diffusion tensor imaging. Moreover, we show that differences of mean FA values in healthy and tumour-bearing mouse brains allow to distinguish these tissue types. We anticipate that the proposed method will be beneficial in the wider context of medical and material science. Copyright © 2016 John Wiley & Sons, Ltd.

A Novel Technique for Region and Linguistic Specific nTMS-based DTI Fiber Tracking of Language Pathways in Brain Tumor Patients

Navigated transcranial magnetic stimulation (nTMS) has recently been introduced as a non-invasive tool for functional mapping of cortical language areas prior to surgery. It correlates well with intraoperative neurophysiological monitoring (IONM) findings, allowing defining the best surgical strategy to preserve cortical language areas during surgery for language-eloquent tumors. Nevertheless, nTMS allows only for cortical mapping and postoperative language deficits are often caused by injury to subcortical language pathways. Nowadays, the only way to preoperatively visualize language subcortical white matter tracts consists in DTI fiber tracking (DTI-FT). However, standard DTI-FT is based on anatomical landmarks that vary interindividually and can be obscured by the presence of the tumor itself. It has been demonstrated that combining nTMS with DTI-FT allows for a more reliable visualization of the motor pathway in brain tumor patients. Nevertheless, no description about such a combination has been reported for the language network. The aim of the present study is to describe and assess the feasibility and reliability of using cortical seeding areas defined by error type-specific nTMS language mapping (nTMS-positive spots) to perform DTI-FT in patients affected by language-eloquent brain tumors. We describe a novel technique for a nTMS-based DTI-FT to visualize the complex cortico-subcortical connections of the language network. We analyzed quantitative findings, such as fractional anisotropy values and ratios, and the number of visualized connections of nTMS-positive spots with subcortical pathways, and we compared them with results obtained by using the standard DTI-FT technique. We also analyzed the functional concordance between connected cortical nTMS-positive spots and subcortical pathways, and the likelihood of connection for nTMS-positive vs. nTMS-negative cortical spots. We demonstrated, that the nTMS-based approach, especially what we call the “single-spot” strategy, is able to provide a reliable and more detailed reconstruction of the complex cortico-subcortical language network as compared to the standard DTI-FT. We believe this technique represents a beneficial new strategy for customized preoperative planning in patients affected by tumors in presumed language eloquent location, providing anatomo-functional information to plan language-preserving surgery.

Eddy current compensated double diffusion encoded (DDE) MRI

PURPOSE

Eddy currents might lead to image distortions in diffusion-weighted echo planar imaging. A method is proposed to reduce their effects on double diffusion encoding (DDE) MRI experiments and the thereby derived microscopic fractional anisotropy (μFA).

METHODS

The twice-refocused spin echo scheme was adapted for DDE measurements. To assess the effect of individual diffusion encodings on the image distortions, measurements of a grid of plastic rods in water were performed. The effect of eddy current compensation on μFA measurements was evaluated in the brains of six healthy volunteers.

RESULTS

The use of an eddy current compensation reduced the signal variation. As expected, the distortions caused by the second encoding were larger than those of the first encoding, entailing a stronger need to compensate for them. For an optimal result, however, both encodings had to be compensated. The artifact reduction strongly improved the measurement of the μFA in ventricles and gray matter by reducing the overestimation. An effect of the compensation on absolute μFA values in white matter was not observed.

CONCLUSION

It is advisable to compensate both encodings in DDE measurements for eddy currents. Magn Reson Med 77:328-335, 2017. © 2015 Wiley Periodicals, Inc.

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.

Challenges in the reproducibility of clinical studies with resting state fMRI: An example in early Parkinson's disease

Resting state fMRI (rfMRI) is gaining in popularity, being easy to acquire and with promising clinical applications. However, rfMRI studies, especially those involving clinical groups, still lack reproducibility, largely due to the different analysis settings. This is particularly important for the development of imaging biomarkers. The aim of this work was to evaluate the reproducibility of our recent study regarding the functional connectivity of the basal ganglia network in early Parkinson's disease (PD) (Szewczyk-Krolikowski et al., 2014). In particular, we systematically analysed the influence of two rfMRI analysis steps on the results: the individual cleaning (artefact removal) of fMRI data and the choice of the set of independent components (template) used for dual regression.

Our experience suggests that the use of a cleaning approach based on single-subject independent component analysis, which removes non neural-related sources of inter-individual variability, can help to increase the reproducibility of clinical findings. A template generated using an independent set of healthy controls is recommended for studies where the aim is to detect differences from a “healthy” brain, rather than an “average” template, derived from an equal number of patients and controls. While, exploratory analyses (e.g. testing multiple resting state networks) should be used to formulate new hypotheses, careful validation is necessary before promising findings can be translated into useful biomarkers.

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Reproducibility of clinical findings is crucial for imaging biomarker development.

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We addressed the impact on reproducibility of different analysis settings in rfMRI.

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ICA-based cleaning of rfMRI data increases reproducibility.

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The effect of the template choice for dual regression is evaluated.