This lecture will provide a brief overview of technical considerations involved in diffusion MRI of small animals on preclinical scanners. Applications of diffusion MRI to examine neuroanatomy and brain development in small animals will be covered. We will examine the relations between metrics derived using different diffusion models and acquisition schemes and white matter pathological changes in animal models of injury and disease. In addition, emerging applications of diffusion MRI methods for characterization of brain tissue microstructure in animal models will be explored.
Scientists interested in the technical aspects and applications of diffusion MRI in animal models.
- To get familiar with technical considerations involved in small animal dMRI
- To understand different applications of dMRI in animal models of brain development and white matter pathology
- To explore the emerging applications of dMRI for imaging of brain tissue microstructure
Diffusion MRI (dMRI) has emerged as an increasingly important technique for small animal imaging and preclinical studies. The availability of genetically-modified rodent models has enabled advanced applications of dMRI to examine brain tissue microstructure and its disruption under pathological conditions. dMRI studies in animal models are also pivotal to gain an understanding of the complex relations between the diffusion-weighted NMR signal and underlying tissue microstructure, which is still an area of extensive research. This lecture will provide an overview of technical considerations for dMRI in small animals, and introduce emerging applications of dMRI techniques to examine brain anatomy, development, pathology, and microstructure in animal models.
Before we look at the applications of dMRI, it is helpful to understand the technical considerations involved in dMRI of small animals. It is important to realize that protocols widely used for clinical dMRI cannot be translated directly for animal dMRI on preclinical systems. Compared to the human brain, the rodent brain is typically 3000 times smaller, which requires acquisition at significantly higher spatial resolution to achieve voxel sizes that are anatomically comparable. Current preclinical scanners range in field strength from 4.7-21 T. Both the high resolution and increasing preclinical field strengths preclude the use of single-shot EPI sequences for small animal dMRI with high SNR and contrast. To tackle susceptibility artifacts at ultrahigh field strengths, multi-shot EPI or spin-echo sequences, or readouts with multiple refocusing pulses, e.g., fast spin echo or GRASE, can be used. The choice of sequence and imaging parameters is often dictated by the requisite resolution, imaging time, noise tolerance, and in vivo versus ex vivo applications. When multiple refocusing pulses are used, it is also necessary to correct for phase-related artifacts, e.g., by the use of navigator echoes or reference phase scans.
Neuroanatomy and cortical development
Recent advances in small-animal MR systems (e.g., high performance gradients and RF coils) and imaging pulse sequences have enabled high-resolution dMRI of the rodent brain, both in vivo and ex vivo. For example, 3D diffusion micro-imaging of the mouse brain has been reported at isotropic resolutions of 0.04-0.05 mm [1,2]. High-resolution dMRI of rodent models has been used to examine anatomical changes during brain development. During early development with ongoing myelination, dMRI can provide superior contrasts in the brain compared to relaxation-based (T1- or T2-w) MR contrasts, which are more dependent on myelin content. A number of studies have measured time-related changes in diffusion tensor-derived metrics in gray and white matter structures during development [3,4]. For instance, increase in fractional anisotropy (FA) in major white matter tracts was found to correlate strongly with the degree of myelination. In cortical gray matter, high diffusion anisotropy during development has been related to the microstructural organization of radial glia, and is shown to decline progressively with maturation [5]. Diffusion micro-imaging studies have reported distinct spatiotemporal patterns of diffusion anisotropy changes across cortical regions in the rodent brain [6,7]. DTI, HARDI, and probabilistic tractography techniques have also been used for anatomical phenotyping and to examine altered neuroanatomy and brain plasticity in genetic mouse models, e.g., the reeler mouse [8].
White matter pathology in injury and disease
Diffusion MRI is increasingly used to examine neuropathology in animal models of white matter (WM) injury and diseases. Deciphering the relationship between changes in measured diffusion-weighted MR signal and underlying pathological alterations remains an important goal in dMRI studies. In recent years, studies in rodent models of toxin- or genetically-induced WM disruptions have led to advances in understanding how diffusion-derived metrics are affected by specific pathologies. For instance, in the Shiverer mouse model of genetic dysmyelination, radial or transverse diffusivity, but not axial diffusivity, was shown to be significantly increased compared to wild-type controls [9]. Early studies demonstrated that axial and radial diffusivities derived from DTI could sensitively differentiate between axonal injury and myelin injury, respectively, in rodent models of cuprizone-induced demyelination and retinal ischemia [10,11]. A decrease in axial diffusivity was shown to relate to axonal degeneration, while radial diffusivity was shown to increase and decrease with demyelination and subsequent remyelination, respectively. These observations correlated well with histological findings in the same models.
The relationships between diffusion tensor-derived metrics and underlying microstructural changes, however, are not straightforward. The diffusion-weighted signal can be affected by pathological processes including demyelination, inflammation, axonal damage, edema, and gliosis. These pathologies often coexist, and can exert unique and conflicting effects on the measured signal. For example, cell infiltration in WM regions due to inflammation can affect the diffusion anisotropy and diffusivity measurements [12]. dMRI models more sophisticated than the diffusion tensor model are therefore necessary to develop biomarkers that can distinguish myelin damage from other pathological changes. For instance, diffusion kurtosis imaging (DKI) metrics of mean and radial kurtosis were found to be better indicators of myelin content than conventional DTI measures in two knockout mouse models with varying degrees of hypomyelination [13]. In the mouse model of cuprizone intoxication, increased specificity of compartment-specific axonal water fraction and extra-axonal radial diffusivity parameters to changes in myelination was recently shown, which was validated using electron microscopy [14].
Probing tissue microstructure
Studies in animal models are also pivotal in the development and validation of dMRI methods to extract information about tissue microstructure at sub-voxel length scales. For instance, estimates of axon diameter distribution or density derived from diffusion models (e.g., AxCaliber, ActiveAx) in the rodent and primate corpus callosum [15,16] can be directly compared to histological measurements of the same parameters. Recent studies have investigated the diffusion time-dependence of apparent diffusion coefficient (ADC) in animal models using oscillating gradient spin echo (OGSE) sequences, which can afford sensitivity to the spatial scales of cellular to sub-cellular barriers restricting diffusion [17,18]. For example, ADC maps with increasing frequency showed increased contrast and spatial heterogeneity in a rat model of brain tumor [19], and selective contrast enhancement in cellular layers with high neuronal density in the mouse brain [20]. Axon diameters estimated using OGSE sequences in the rat spinal cord were found to have good agreement with histological measurements [21]. Recent studies in rodent models of hypoxia-ischemia and drug-induced epilepsy [22,23] have further shown the sensitivity of OGSE-based ADC measurements to pathology-induced microstructural changes in the brain.
Work supported in part by NIH grants R03EB017806 and R21NS096249.
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