Elizabeth B. Hutchinson

Functional Reactivity of Cerebral Capillaries

The spatiotemporal evolution of cerebral microcirculatory adjustments to functional brain stimulation is the fundamental determinant of the functional specificity of hemodynamically weighted neuroimaging signals. Very little data, however, exist on the functional reactivity of capillaries, the vessels most proximal to the activated neuronal population. Here, we used two-photon laser scanning microscopy, in combination with intracranial electrophysiology and intravital video microscopy, to explore the changes in cortical hemodynamics, at the level of individual capillaries, in response to steady-state forepaw stimulation in an anesthetized rodent model. Overall, the microcirculatory response to functional stimulation was characterized by a pronounced decrease in vascular transit times (20% ± 8%), a dilatation of the capillary bed (10.9% ± 1.2%), and significant increases in red blood cell speed (33.0% ± 7.7%) and flux (19.5% ± 6.2%). Capillaries dilated more than the medium-caliber vessels, indicating a decreased heterogeneity in vessel volumes and increased blood flow-carrying capacity during neuronal activation relative to baseline. Capillary dilatation accounted for an estimated ˜18% of the total change in the focal cerebral blood volume. In support of a capacity for focal redistribution of microvascular flow and volume, significant, though less frequent, local stimulation-induced decreases in capillary volume and erythrocyte speed and flux also occurred. The present findings provide further evidence of a strong functional reactivity of cerebral capillaries and underscore the importance of changes in the capillary geometry in the hemodynamic response to neuronal activation.

Spatial flow-volume dissociation of the cerebral microcirculatory response to mild hypercapnia

The spatial and temporal response of the cerebral microcirculation to mild hypercapnia was investigated via two-photon laser-scanning microscopy. Cortical vessels, traversing the top 200 microm of somatosensory cortex, were visualized in alpha-chloralose-anesthetized Sprague-Dawley rats equipped with a cranial window. Intraluminal vessel diameters, transit times of fluorescent dextrans and red blood cells (RBC) velocities in individual capillaries were measured under normocapnic (PaCO2= 32.6 +/- 2.6 mm Hg) and slightly hypercapnic (PaCO2= 45 +/- 7 mm Hg) conditions. This gentle increase in PaCO2 was sufficient to produce robust and significant increases in both arterial and venous vessel diameters, concomitant to decreases in transit times of a bolus of dye from artery to venule (14%, P < 0.05) and from artery to vein (27%, P < 0.05). On the whole, capillaries exhibited a significant increase in diameter (16 +/- 33%, P < 0.001, n = 393) and a substantial increase in RBC velocities (75 +/- 114%, P < 0.001, n = 46) with hypercapnia. However, the response of the cerebral microvasculature to modest increases in PaCO2 was spatially heterogeneous. The maximal relative dilatation (range: 5-77%; mean +/- SD: 25 +/- 34%, P < 0.001, n = 271) occurred in the smallest capillaries (1.6 microm-4.0 microm resting diameter), while medium and larger capillaries (4.4 microm-6.8 microm resting diameter) showed no significant changes in diameter (P > 0.08, n = 122). In contrast, on average, RBC velocities increased less in the smaller capillaries (39 +/- 5%, P < 0.002, n = 22) than in the medium and larger capillaries (107 +/- 142%, P < 0.003, n = 24). Thus, the changes in capillary RBC velocities were spatially distinct from the observed volumetric changes and occurred to homogenize cerebral blood flow along capillaries of all diameters.

Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure.

Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole-brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-to-noise ratio in clinically achievable scan durations of less than 10min. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques.

Quantitative MRI and DTI Abnormalities During the Acute Period Following CCI in the Ferret.

Abstract During the acute time period following traumatic brain injury (TBI), noninvasive brain imaging tools such as magnetic resonance imaging (MRI) can provide important information about the clinical and pathological features of the injury and may help predict long-term outcomes. In addition to standard imaging approaches, several quantitative MRI techniques including relaxometry and diffusion MRI have been identified as promising reporters of cellular alterations after TBI and may provide greater sensitivity and specificity for identifying brain abnormalities especially in mild TBI. However, for these imaging tools to be useful, it is crucial to define their relationship with the neurophysiological response to brain injury. Recently, a model of controlled cortical impact (CCI) has been developed in the ferret which has many advantages compared with rodent models (e.g., gyrencephalic cortex and high white matter volume). The objective of this study was to evaluate quantitative MRI metrics in the ferret CCI model, including T2 values and diffusion tensor imaging (DTI) metrics, during the acute time period. Longitudinal quantitative comparisons of in vivo MRI and DTI metrics were evaluated to identify abnormalities and characterize their spatial patterns in the ferret brain. Ex vivo MRI and DTI maps were then compared with histological staining for glial and neuronal abnormalities. The main findings of this article describe T2, diffusivity, and anisotropy markers of tissue change during the acute time period following mild TBI, and ex vivo analyses suggest that MRI and DTI markers are sensitive to subtle cellular alterations in this model. This was confirmed by comparison with immunohistochemistry, also showing altered markers in regions of MRI and DTI change.

A defect in myoblast fusion underlies Carey-Fineman-Ziter syndrome

Multinucleate cellular syncytial formation is a hallmark of skeletal muscle differentiation. Myomaker, encoded by Mymk (Tmem8c), is a well-conserved plasma membrane protein required for myoblast fusion to form multinucleated myotubes in mouse, chick, and zebrafish. Here, we report that autosomal recessive mutations in MYMK (OMIM 615345) cause Carey-Fineman-Ziter syndrome in humans (CFZS; OMIM 254940) by reducing but not eliminating MYMK function. We characterize MYMK-CFZS as a congenital myopathy with marked facial weakness and additional clinical and pathologic features that distinguish it from other congenital neuromuscular syndromes. We show that a heterologous cell fusion assay in vitro and allelic complementation experiments in mymk knockdown and mymkinsT/insT zebrafish in vivo can differentiate between MYMK wild type, hypomorphic and null alleles. Collectively, these data establish that MYMK activity is necessary for normal muscle development and maintenance in humans, and expand the spectrum of congenital myopathies to include cell-cell fusion deficits.

DR-TAMAS: Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical Structures

In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain data and its main goal is to achieve an accurate alignment of all brain structures, including white matter (WM), gray matter (GM), and spaces containing cerebrospinal fluid (CSF). Currently most DTI-based spatial normalization algorithms emphasize alignment of anisotropic structures. While some diffusion-derived metrics, such as diffusion anisotropy and tensor eigenvector orientation, are highly informative for proper alignment of WM, other tensor metrics such as the trace or mean diffusivity (MD) are fundamental for a proper alignment of GM and CSF boundaries. Moreover, it is desirable to include information from structural MRI data, e.g., T1-weighted or T2-weighted images, which are usually available together with the diffusion data. The fundamental property of DR-TAMAS is to achieve global anatomical accuracy by incorporating in its cost function the most informative metrics locally. Another important feature of DR-TAMAS is a symmetric time-varying velocity-based transformation model, which enables it to account for potentially large anatomical variability in healthy subjects and patients. The performance of DR-TAMAS is evaluated with several data sets and compared with other widely-used diffeomorphic image registration techniques employing both full tensor information and/or DTI-derived scalar maps. Our results show that the proposed method has excellent overall performance in the entire brain, while being equivalent to the best existing methods in WM.

A framework for accurate determination of the T2 distribution from multiple echo magnitude MRI images

Measurement of the T2 distribution in tissues provides biologically relevant information about normal and abnormal microstructure and organization. Typically, the T2 distribution is obtained by fitting the magnitude MR images acquired by a multi-echo MRI pulse sequence using an inverse Laplace transform (ILT) algorithm. It is well known that the ideal magnitude MR signal follows a Rician distribution. Unfortunately, studies attempting to establish the validity and efficacy of the ILT algorithm assume that these input signals are Gaussian distributed. Violation of the normality (or Gaussian) assumption introduces unexpected artifacts, including spurious cerebrospinal fluid (CSF)-like long T2 components; bias of the true geometric mean T2 values and in the relative fractions of various components; and blurring of nearby T2 peaks in the T2 distribution. Here we apply and extend our previously proposed magnitude signal transformation framework to map noisy Rician-distributed magnitude multi-echo MRI signals into Gaussian-distributed signals with high accuracy and precision. We then perform an ILT on the transformed data to obtain an accurate T2 distribution. Additionally, we demonstrate, by simulations and experiments, that this approach corrects the aforementioned artifacts in magnitude multi-echo MR images over a large range of signal-to-noise ratios.

Establishing the ferret as a gyrencephalic animal model of traumatic brain injury: Optimization of controlled cortical impact procedures

BACKGROUND Although rodent TBI studies provide valuable information regarding the effects of injury and recovery, an animal model with neuroanatomical characteristics closer to humans may provide a more meaningful basis for clinical translation. The ferret has a high white/gray matter ratio, gyrencephalic neocortex, and ventral hippocampal location. Furthermore, ferrets are amenable to behavioral training, have a body size compatible with pre-clinical MRI, and are cost-effective. NEW METHODS We optimized the surgical procedure for controlled cortical impact (CCI) using 9 adult male ferrets. We used subject-specific brain/skull morphometric data from anatomical MRIs to overcome across-subject variability for lesion placement. We also reflected the temporalis muscle, closed the craniotomy, and used antibiotics. We then gathered MRI, behavioral, and immunohistochemical data from 6 additional animals using the optimized surgical protocol: 1 control, 3 mild, and 1 severely injured animals (surviving one week) and 1 moderately injured animal surviving sixteen weeks. RESULTS The optimized surgical protocol resulted in consistent injury placement. Astrocytic reactivity increased with injury severity showing progressively greater numbers of astrocytes within the white matter. The density and morphological changes of microglia amplified with injury severity or time after injury. Motor and cognitive impairments scaled with injury severity. COMPARISON WITH EXISTING METHOD(S) The optimized surgical methods differ from those used in the rodent, and are integral to success using a ferret model. CONCLUSIONS We optimized ferret CCI surgery for consistent injury placement. The ferret is an excellent animal model to investigate pathophysiological and behavioral changes associated with TBI.

Diffusion MRI and the detection of alterations following traumatic brain injury

This article provides a review of brain tissue alterations that may be detectable using diffusion magnetic resonance imaging MRI (dMRI) approaches and an overview and perspective on the modern dMRI toolkits for characterizing alterations that follow traumatic brain injury (TBI). Noninvasive imaging is a cornerstone of clinical treatment of TBI and has become increasingly used for preclinical and basic research studies. In particular, quantitative MRI methods have the potential to distinguish and evaluate the complex collection of neurobiological responses to TBI arising from pathology, neuroprotection, and recovery. dMRI provides unique information about the physical environment in tissue and can be used to probe physiological, architectural, and microstructural features. Although well‐established approaches such as diffusion tensor imaging are known to be highly sensitive to changes in the tissue environment, more advanced dMRI techniques have been developed that may offer increased specificity or new information for describing abnormalities. These tools are promising, but incompletely understood in the context of TBI. Furthermore, model dependencies and relative limitations may impact the implementation of these approaches and the interpretation of abnormalities in their metrics. The objective of this paper is to present a basic review and comparison across dMRI methods as they pertain to the detection of the most commonly observed tissue and cellular alterations following TBI.

Population based MRI and DTI templates of the adult ferret brain and tools for voxelwise analysis

ABSTRACT Non‐invasive imaging has the potential to play a crucial role in the characterization and translation of experimental animal models to investigate human brain development and disorders, especially when employed to study animal models that more accurately represent features of human neuroanatomy. The purpose of this study was to build and make available MRI and DTI templates and analysis tools for the ferret brain as the ferret is a well‐suited species for pre‐clinical MRI studies with folded cortical surface, relatively high white matter volume and body dimensions that allow imaging with pre‐clinical MRI scanners. Four ferret brain templates were built in this study – in‐vivo MRI and DTI and ex‐vivo MRI and DTI – using brain images across many ferrets and region of interest (ROI) masks corresponding to established ferret neuroanatomy were generated by semi‐automatic and manual segmentation. The templates and ROI masks were used to create a web‐based ferret brain viewing software for browsing the MRI and DTI volumes with annotations based on the ROI masks. A second objective of this study was to provide a careful description of the imaging methods used for acquisition, processing, registration and template building and to demonstrate several voxelwise analysis methods including Jacobian analysis of morphometry differences between the female and male brain and bias‐free identification of DTI abnormalities in an injured ferret brain. The templates, tools and methodological optimization presented in this study are intended to advance non‐invasive imaging approaches for human‐similar animal species that will enable the use of pre‐clinical MRI studies for understanding and treating brain disorders. HighlightsThe ferret is a human‐relevant species for studying the brain with a folded cortical surface and high white matter volume as well as body dimensions that enable neuroimaging studies using pre‐clinical MRI scanners.In‐vivo and ex‐vivo MRI and DTI templates were built for the ferret brain using optimized template building tools including diffeomorphic and diffusion tensor based registration.The brain volume was parcellated into regions of interest using a combination of automatic and manual segmentation with reference to known ferret neuroanatomy.Several demonstrations are presented to illustrate voxelwise and template based analysis approaches that may be advantageous for use in neuroimaging studies.The templates and masks are available as downloadable files and were also used to generate a web‐based viewer for browsing the ferret brain images and maps as well as for open annotation of information about brain regions or contribution of images.