Imaging microstructure with diffusion and susceptibility MR: neuronal density correlation in Disrupted-in-Schizophrenia-1 mutant mice.

PURPOSE: To probe cerebral microstructural abnormalities and assess changes of neuronal density in Disrupted-in-Schizophrenia-1 (DISC1) mice using non-Gaussian diffusion and quantitative susceptibility mapping (QSM). MATERIALS AND METHODS: Brain specimens of transgenic DISC1 mice (n = 8) and control mice (n = 7) were scanned. Metrics of neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging (DKI), as well as QSM, were acquired. Cell counting was performed on Nissl-stained sections. Group differences of imaging metrics and cell density were assessed. Pearson correlations between imaging metrics and cell densities were also examined. RESULTS: Significant increases of neuronal density were observed in the hippocampus of DISC1 mice. DKI metrics such as mean kurtosis exhibited significant group differences in the caudate putamen (P = 0.015), cerebral cortex (P = 0.021), and hippocampus (P = 0.011). However, DKI metrics did not correlate with cell density. In contrast, significant positive correlation between density of neurons and the neurite density index of NODDI in the hippocampus was observed (r = 0.783, P = 0.007). Significant correlation between density of neurons and susceptibility (r = 0.657, P = 0.039), as well as between density of neuroglia and susceptibility (r = 0.750, P = 0.013), was also observed in the hippocampus. CONCLUSION: The imaging metrics derived from DKI were not sensitive specifically to cell density, while NODDI could provide diffusion metrics sensitive to density of neurons. The magnetic susceptibility values derived from the QSM method can serve as a sensitive biomarker for quantifying neuronal density.

Imaging beta amyloid aggregation and iron accumulation in Alzheimer's disease using quantitative susceptibility mapping MRI.

Beta amyloid is a protein fragment snipped from the amyloid precursor protein (APP). Aggregation of these peptides into amyloid plaques is one of the hallmarks of Alzheimer's disease. MR imaging of beta amyloid plaques has been attempted using various techniques, notably with T2* contrast. The non-invasive detectability of beta amyloid plaques in MR images has so far been largely attributed to focal iron deposition accompanying the plaques. It is believed that the T2* shortening effects of paramagnetic iron are the primary source of contrast between plaques and surrounding tissue. Amyloid plaque itself has been reported to induce no magnetic susceptibility effect. We hypothesized that aggregations of beta amyloid would increase electron density and induce notable changes in local susceptibility value, large enough to generate contrast relative to surrounding normal tissues that can be visualized by quantitative susceptibility mapping (QSM) MR imaging. To test this hypothesis, we first demonstrated in a phantom that beta amyloid is diamagnetic and can generate strong contrast on susceptibility maps. We then conducted experiments on a transgenic mouse model of Alzheimer's disease that is known to mimic the formation of human beta amyloid but without neurofibrillary tangles or neuronal death. Over a period of 18 months, we showed that QSM can be used to longitudinally monitor beta amyloid accumulation and accompanied iron deposition in vivo. Individual beta amyloid plaque can also be visualized ex vivo in high resolution susceptibility maps. Moreover, the measured negative susceptibility map and positive susceptibility map could provide histology-like image contrast for identifying deposition of beta amyloid plaques and iron. Finally, we demonstrated that the diamagnetic susceptibility of beta amyloid can also be observed in brain specimens of AD patients. The ability to assess beta amyloid aggregation non-invasively with QSM MR imaging may aid the diagnosis of Alzheimer's disease.

Probing demyelination and remyelination of the cuprizone mouse model using multimodality MRI.

BACKGROUND: Various studies by MRI exhibit that the corpus callosum (CC) is the most vulnerable to cuprizone administration, detecting the demyelination and remyelination process using different MRI parameters are, however, lacking. PURPOSE: To investigate the sensitivity of multiparametric MRI both in vivo and ex vivo for demyelination and remyelination. STUDY TYPE: Prospective. ANIMAL MODEL: A cuprizone mice model with an age-matched control group (n = 5), 4-week cuprizone exposure group followed by 9-week on a normal diet (n = 6), and a 13-week cuprizone exposure group (n = 6). FIELD STRENGTH/SEQUENCE: 3D gradient recalled echo, T2 -weighted, and diffusion tensor imaging (DTI) at 7.0T and 9.4T. ASSESSMENT: Quantification of DTI metrics, quantitative susceptibility mapping (QSM), and T2 -weighted imaging intensity in major white matter bundles. STATISTICAL TESTS: Nonparametric permutation tests were used with a cluster-forming threshold as 3.09 (equivalent to P = 0.001), and the significant level as P = 0.05 with family-wise correction. RESULTS: In vivo susceptibility values increased from -11.7 to -0.7 ppb (P < 0.001) in CC and from -13.7 to -5.1 ppb (P < 0.001) in the anterior commissure (AC) after the 13-week cuprizone exposure. Ex vivo susceptibility values increased from -25.4 to 7.4 ppb (P < 0.001) in CC and from -41.6 to -15.8 ppb (P < 0.001) in AC. Susceptibility values showed high variations to demyelination for in vivo studies (94.0% in CC, 62.8% in AC). Susceptibility values exhibited higher variations than radial diffusivity for ex vivo studies (129.1% vs. 28.3% in CC, 62.0% vs. 25.0% in AC). In addition to the differential susceptibility variations in different white matter tracts, intraregional demyelination variation was also present not only in CC but also in the AC area by voxel-based analysis. DATA CONCLUSION: QSM is sensitive to the demyelination process of cuprizone exposure, which can be a complementary technique to conventional T2 -weighted images and DTI metrics. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1852-1865.

Differential microstructural and morphological abnormalities in mild cognitive impairment and Alzheimer's disease: Evidence from cortical and deep gray matter.

One aim of this study is to use non-Gaussian diffusion kurtosis imaging (DKI) for capturing microstructural abnormalities in gray matter of Alzheimer's disease (AD). The other aim is to compare DKI metrics against thickness of cortical gray matter and volume of deep gray matter, respectively. A cohort of 18 patients with AD, 18 patients with amnestic mild cognitive impairment (MCI), and 18 normal controls underwent morphological and DKI MR imaging. Images were investigated using regions-of-interest-based analyses for deep gray matter and vertex-wise analyses for cortical gray matter. In deep gray matter, more regions showed DKI parametric abnormalities than atrophies at the early MCI stage. Mean kurtosis (MK) exhibited the largest number of significant abnormalities among all DKI metrics. At the later AD stage, diffusional abnormalities were observed in fewer regions than atrophies. In cortical gray matter, abnormalities in thickness were mainly in the medial and lateral temporal lobes, which fit the locations of known early pathological changes. Microstructural abnormalities were predominantly in the parietal and even frontal lobes, which fit the locations of known late pathological changes. In conclusion, MK can complement conventional diffusion metrics for detecting microstructural changes, especially in deep gray matter. This study also provides evidence supporting the notion that microstructural changes predate morphological changes. Hum Brain Mapp 38:2495-2508, 2017. © 2017 Wiley Periodicals, Inc.

Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

PURPOSE: To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. THEORY AND METHODS: STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. RESULTS: MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. CONCLUSION: MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Investigating magnetic susceptibility of human knee joint at 7 Tesla.

PURPOSE: To evaluate the magnetic susceptibility properties of different anatomical structures within the knee joint using quantitative susceptibility mapping (QSM). METHODS: A collagen tissue model was simulated and ex vivo animal cartilage experiments were conducted at 9.4 Tesla (T) to evaluate the B0 orientation-dependent magnetic susceptibility contrast observed in cartilage. Furthermore, nine volunteers (six healthy subjects without knee pain history and three patients with known knee injury, between 29 and 58 years old) were scanned using gradient-echo acquisitions on a high-field 7T MR scanner. Susceptibility values of different tissues were quantified and diseased cartilage and meniscus were compared against that of healthy volunteers. RESULTS: Simulation and ex vivo animal cartilage experiments demonstrated that collagen fibrils exhibit an anisotropic susceptibility. A gradual change of magnetic susceptibility was observed in the articular cartilage from the superficial zone to the deep zone, forming a multilayer ultrastructure consistent with anisotropy of collagen fibrils. Meniscal tears caused a clear reduction of susceptibility contrast between the injured meniscus and surrounding cartilage illustrated by a loss of the sharp boundaries between the two. Moreover, QSM showed more dramatic contrast in the focal degenerated articular cartilage than R2* mapping. CONCLUSION: The arrangement of the collagen fibrils is significant, and likely the most dominant source of magnetic susceptibility anisotropy. Quantitative susceptibility mapping offers a means to characterize magnetic susceptibility properties of tissues in the knee joint. It is sensitive to collagen damage or degeneration and may be useful for evaluating the status of knee diseases, such as meniscal tears and cartilage disease. Magn Reson Med 78:1933-1943, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Magnetic susceptibility anisotropy outside the central nervous system.

Magnetic-susceptibility-based MRI has made important contributions to the characterization of tissue microstructure, chemical composition, and organ function. This has motivated a number of studies to explore the link between microstructure and susceptibility in organs and tissues throughout the body, including the kidney, heart, and connective tissue. These organs and tissues have anisotropic magnetic susceptibility properties and cellular organizations that are distinct from the lipid organization of myelin in the brain. For instance, anisotropy is traced to the epithelial lipid orientation in the kidney, the myofilament proteins in the heart, and the collagen fibrils in the knee cartilage. The magnetic susceptibility properties of these and other tissues are quantified using specific MRI tools: susceptibility tensor imaging (STI), quantitative susceptibility mapping (QSM), and individual QSM measurements with respect to tubular and filament directions determined from diffusion tensor imaging. These techniques provide complementary and supplementary information to that produced by traditional MRI methods. In the kidney, STI can track tubules in all layers including the cortex, outer medulla, and inner medulla. In the heart, STI detected myofibers throughout the myocardium. QSM in the knee revealed three unique layers in articular cartilage by exploiting the anisotropic susceptibility features of collagen. While QSM and STI are promising tools to study tissue susceptibility, certain technical challenges must be overcome in order to realize routine clinical use. This paper reviews essential experimental findings of susceptibility anisotropy in the body, the underlying mechanisms, and the associated MRI methodologies. Copyright © 2016 John Wiley & Sons, Ltd.

Imaging whole-brain cytoarchitecture of mouse with MRI-based quantitative susceptibility mapping.

The proper microstructural arrangement of complex neural structures is essential for establishing the functional circuitry of the brain. We present an MRI method to resolve tissue microstructure and infer brain cytoarchitecture by mapping the magnetic susceptibility in the brain at high resolution. This is possible because of the heterogeneous magnetic susceptibility created by varying concentrations of lipids, proteins and irons from the cell membrane to cytoplasm. We demonstrate magnetic susceptibility maps at a nominal resolution of 10-µm isotropic, approaching the average cell size of a mouse brain. The maps reveal many detailed structures including the retina cell layers, olfactory sensory neurons, barrel cortex, cortical layers, axonal fibers in white and gray matter. Olfactory glomerulus density is calculated and structural connectivity is traced in the optic nerve, striatal neurons, and brainstem nerves. The method is robust and can be readily applied on MRI scanners at or above 7T.

Rapid multi-orientation quantitative susceptibility mapping.

Three-dimensional gradient echo (GRE) is the main workhorse sequence used for susceptibility weighted imaging (SWI), quantitative susceptibility mapping (QSM), and susceptibility tensor imaging (STI). Achieving optimal phase signal-to-noise ratio requires late echo times, thus necessitating a long repetition time (TR). Combined with the large encoding burden of whole-brain coverage with high resolution, this leads to increased scan time. Further, the dipole kernel relating the tissue phase to the underlying susceptibility distribution undersamples the frequency content of the susceptibility map. Scans at multiple head orientations along with calculation of susceptibility through multi-orientation sampling (COSMOS) are one way to effectively mitigate this issue. Additionally, STI requires a minimum of 6 head orientations to solve for the independent tensor elements in each voxel. The requirements of high-resolution imaging with long TR at multiple orientations substantially lengthen the acquisition of COSMOS and STI. The goal of this work is to dramatically speed up susceptibility mapping at multiple head orientations. We demonstrate highly efficient acquisition using 3D-GRE with Wave-CAIPI and dramatically reduce the acquisition time of these protocols. Using R=15-fold acceleration with Wave-CAIPI permits acquisition per head orientation in 90s at 1.1mm isotropic resolution, and 5:35min at 0.5mm isotropic resolution. Since Wave-CAIPI fully harnesses the 3D spatial encoding capability of receive arrays, the maximum g-factor noise amplification remains below 1.30 at 3T and 1.12 at 7T. This allows a 30-min exam for STI with 12 orientations, thus paving the way to its clinical application.

Susceptibility tensor imaging of the kidney and its microstructural underpinnings.

PURPOSE: The purpose of this study was to determine whether susceptibility tensor imaging (STI) could overcome limitations of current techniques to detect tubules throughout the kidney. METHODS: Normal mouse kidneys (n = 4) were imaged at 9.4T using a three-dimensional gradient multi-echo sequence (55-micron isotropic resolution). Phase images from 12 orientations were obtained to compute the susceptibility tensor. Diffusion tensor imaging (DTI) with 12 encoding directions was compared with STI. Tractography was performed to visualize and track the course of tubules with DTI and STI. Confocal microscopy was used to identify which tubular segments of the nephron were detected by DTI and STI. RESULTS: Diffusion anisotropy was limited to the inner medulla of the kidney. DTI did not find a significant number of coherent tubular tracks in the outer medulla or cortex. With STI, we found strong susceptibility anisotropy and many tracks in the inner and outer medulla and in limited areas of the cortex. CONCLUSION: STI was able to track tubules throughout the kidney, whereas DTI was limited to the inner medulla. STI provides a novel contrast mechanism related to local tubule microstructure and may offer a powerful method to study the nephron.

Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range.

Quantitative susceptibility mapping (QSM) is a novel MRI technique for the measurement of tissue magnetic susceptibility in three dimensions. Although numerous algorithms have been developed to solve this ill-posed inverse problem, the estimation of susceptibility maps with a wide range of values is still problematic. In cases such as large veins, contrast agent uptake and intracranial hemorrhages, extreme susceptibility values in focal areas cause severe streaking artifacts. To enable the reduction of these artifacts, whilst preserving subtle susceptibility contrast, a two-level QSM reconstruction algorithm (streaking artifact reduction for QSM, STAR-QSM) was developed in this study by tuning a regularization parameter to automatically reconstruct both large and small susceptibility values. Compared with current state-of-the-art QSM methods, such as the improved sparse linear equation and least-squares (iLSQR) algorithm, STAR-QSM significantly reduced the streaking artifacts, whilst preserving the sharp boundaries for blood vessels of mouse brains in vivo and fine anatomical details of high-resolution mouse brains ex vivo. Brain image data from patients with cerebral hematoma and multiple sclerosis further illustrated the superiority of this method in reducing streaking artifacts caused by large susceptibility sources, whilst maintaining sharp anatomical details. STAR-QSM is implemented in STI Suite, a comprehensive shareware for susceptibility imaging and quantification.

Magnetic susceptibility anisotropy of myocardium imaged by cardiovascular magnetic resonance reflects the anisotropy of myocardial filament α-helix polypeptide bonds.

BACKGROUND: A key component of evaluating myocardial tissue function is the assessment of myofiber organization and structure. Studies suggest that striated muscle fibers are magnetically anisotropic, which, if measurable in the heart, may provide a tool to assess myocardial microstructure and function. METHODS: To determine whether this weak anisotropy is observable and spatially quantifiable with cardiovascular magnetic resonance (CMR), both gradient-echo and diffusion-weighted data were collected from intact mouse heart specimens at 9.4 Tesla. Susceptibility anisotropy was experimentally calculated using a voxelwise analysis of myocardial tissue susceptibility as a function of myofiber angle. A myocardial tissue simulation was developed to evaluate the role of the known diamagnetic anisotropy of the peptide bond in the observed susceptibility contrast. RESULTS: The CMR data revealed that myocardial tissue fibers that were parallel and perpendicular to the magnetic field direction appeared relatively paramagnetic and diamagnetic, respectively. A linear relationship was found between the magnetic susceptibility of the myocardial tissue and the squared sine of the myofiber angle with respect to the field direction. The multi-filament model simulation yielded susceptibility anisotropy values that reflected those found in the experimental data, and were consistent that this anisotropy decreased as the echo time increased. CONCLUSIONS: Though other sources of susceptibility anisotropy in myocardium may exist, the arrangement of peptide bonds in the myofilaments is a significant, and likely the most dominant source of susceptibility anisotropy. This anisotropy can be further exploited to probe the integrity and organization of myofibers in both healthy and diseased heart tissue.

Microstructural origins of gadolinium-enhanced susceptibility contrast and anisotropy.

PURPOSE: MR histology based on magnetic susceptibility can be used to visualize diamagnetic myelin (and its deterioration) in the central nervous system and is facilitated by the application of high magnetic field strengths and paramagnetic contrast agents. Characterizing the effect of these tools will aid in assessing white matter myelin content and microstructure. METHODS: Image data from six gadolinium-perfused mouse brain specimens were acquired at 2.0, 7.0, and 9.4 Tesla. Magnetic susceptibility contrast was analyzed for its dependence on field strength, gadolinium concentration, and white matter fiber orientation. A model for this contrast is presented based on the three-pool model for white matter. RESULTS: The specimen data illustrate that white-gray matter susceptibility contrast is field strength independent. White-gray matter contrast improves significantly as a function of gadolinium contrast agent in the tissue, i.e., white matter appears increasingly more diamagnetic relative to gray matter. The simulated data from the model suggest that susceptibility anisotropy of white matter fiber bundles increases nonlinearly as a function of gadolinium concentration due to contrast agent compartmentalization into the extracellular white matter water pool. CONCLUSION: Using contrast agents in MR histology facilitates white-gray matter susceptibility contrast modulation and the probing of white matter microstructure and orientation.

Multivariate MR biomarkers better predict cognitive dysfunction in mouse models of Alzheimer's disease.

To understand multifactorial conditions such as Alzheimer's disease (AD) we need brain signatures that predict the impact of multiple pathologies and their interactions. To help uncover the relationships between pathology affected brain circuits and cognitive markers we have used mouse models that represent, at least in part, the complex interactions altered in AD, while being raised in uniform environments and with known genotype alterations. In particular, we aimed to understand the relationship between vulnerable brain circuits and memory deficits measured in the Morris water maze, and we tested several predictive modeling approaches. We used in vivo manganese enhanced MRI traditional voxel based analyses to reveal regional differences in volume (morphometry), signal intensity (activity), and magnetic susceptibility (iron deposition, demyelination). These regions included hippocampus, olfactory areas, entorhinal cortex and cerebellum, as well as the frontal association area. The properties of these regions, extracted from each of the imaging markers, were used to predict spatial memory. We next used eigenanatomy, which reduces dimensionality to produce sets of regions that explain the variance in the data. For each imaging marker, eigenanatomy revealed networks underpinning a range of cognitive functions including memory, motor function, and associative learning, allowing the detection of associations between context, location, and responses. Finally, the integration of multivariate markers in a supervised sparse canonical correlation approach outperformed single predictor models and had significant correlates to spatial memory. Among a priori selected regions, expected to play a role in memory dysfunction, the fornix also provided good predictors, raising the possibility of investigating how disease propagation within brain networks leads to cognitive deterioration. Our cross-sectional results support that modeling approaches integrating multivariate imaging markers provide sensitive predictors of AD-like behaviors. Such strategies for mapping brain circuits responsible for behaviors may help in the future predict disease progression, or response to interventions.

Whole mouse brain structural connectomics using magnetic resonance histology.

Diffusion tensor histology holds great promise for quantitative characterization of structural connectivity in mouse models of neurological and psychiatric conditions. There has been extensive study in both the clinical and preclinical domains on the complex tradeoffs between the spatial resolution, the number of samples in diffusion q-space, scan time, and the reliability of the resultant data. We describe here a method for accelerating the acquisition of diffusion MRI data to support quantitative connectivity measurements in the whole mouse brain using compressed sensing (CS). The use of CS allows substantial increase in spatial resolution and/or reduction in scan time. Compared to the fully sampled results at the same scan time, the subtle anatomical details of the brain, such as cortical layers, dentate gyrus, and cerebellum, were better visualized using CS due to the higher spatial resolution. Compared to the fully sampled results at the same spatial resolution, the scalar diffusion metrics, including fractional anisotropy (FA) and mean diffusivity (MD), showed consistently low error across the whole brain (< 6.0%) even with 8.0 times acceleration. The node properties of connectivity (strength, cluster coefficient, eigenvector centrality, and local efficiency) demonstrated correlation of better than 95.0% between accelerated and fully sampled connectomes. The acceleration will enable routine application of this technology to a wide range of mouse models of neurologic diseases.