Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy

Distinct characteristics and severity of brain magnetic resonance imaging lesions in women and men with multiple sclerosis assessed using verified texture analysis measures

Background and goal

In vivo characterization of brain lesion types in multiple sclerosis (MS) has been an ongoing challenge. Based on verified texture analysis measures from clinical magnetic resonance imaging (MRI), this study aimed to develop a method to identify two extremes of brain MS lesions that were approximately severely demyelinated (sDEM) and highly remyelinated (hREM), and compare them in terms of common clinical variables.

Method

Texture analysis used an optimized gray-level co-occurrence matrix (GLCM) method based on FLAIR MRI from 200 relapsing-remitting MS participants. Two top-performing metrics were calculated: texture contrast and dissimilarity. Lesion identification applied a percentile approach according to texture values calculated: ≤ 25 percentile for hREM and ≥75 percentile for sDEM.

Results

The sDEM had a greater total normalized volume yet smaller average size, and worse MRI texture than hREM. In lesion distribution mapping, the two lesion types appeared to overlap largely in location and were present the most in the corpus callosum and periventricular regions. Further, in sDEM, the normalized volume was greater and in hREM, the average size was smaller in men than women. There were no other significant results in clinical variable-associated analyses.

Conclusion

Percentile statistics of competitive MRI texture measures may be a promising method for probing select types of brain MS lesion pathology. Associated findings can provide another useful dimension for improved measurement and monitoring of disease activity in MS. The different characteristics of sDEM and hREM between men and women likely adds new information to the literature, deserving further confirmation.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a co mplex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods.

NEW METHOD

We originated novel texture analysis and machine learning approaches for classifying MS pathology subtypes as compared with 2 common advanced MRI measures: magnetization transfer ratio (MTR) and fractional anisotropy (FA). Texture analysis used an optimized grey level co-occurrence matrix method with histology-informed 7T T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) from 15 MS and 12 control brain specimens. DTI analysis took an innovative approach that assessed the texture across diffusion directions upsampled from 30 to 90. Tissue types included de- and re-myelinated lesions and normal-appearing areas in both grey and white matter, and diffusely abnormal white matter. Data analyses were stepwise, including: (1) group-wise classification using random forest algorithms based on all or individual imaging parameters; (2) parameter importance ranking; and (3) pairwise analysis using top-ranked features.

RESULTS

Texture analysis performed better than MTR and FA, with T2 texture performed the best. T2 texture measures ranked the highest in classifying most grey and white matter tissue types, including de- versus re-myelinated lesions and among grey matter lesion subtypes (accuracy=0.86-0.59; kappa=0.60-0.41). Diffusion texture best differentiated normal appearing and control white matter.

COMPARISON WITH EXISTING METHODS

There is no established method in imaging for differentiating MS pathology subtypes. In combined texture analysis and machine learning studies, there is also no direct evidence comparing conventional with advanced MRI measures for assessing MS pathology. Further, this study is unique in conducting innovative texture analysis with DTI following data-augmentation using robust methods.

CONCLUSIONS

T2 and diffusion MRI texture analysis integrated with machine learning may be valuable approaches for characterizing MS pathology.

White Matter Injury After Intracerebral Hemorrhage

Spontaneous intracerebral hemorrhage (ICH) accounts for 15% of all stroke cases. ICH is a devastating form of stroke associated with high morbidity, mortality, and disability. Preclinical studies have explored the mechanisms of neuronal death and gray matter damage after ICH. However, few studies have examined the development of white matter injury (WMI) following ICH. Research on WMI indicates that its pathophysiological presentation involves axonal damage, demyelination, and mature oligodendrocyte loss. However, the detailed relationship and mechanism between WMI and ICH remain unclear. Studies of other acute brain insults have indicated that WMI is strongly correlated with cognitive deficits, neurological deficits, and depression. The degree of WMI determines the short- and long-term prognosis of patients with ICH. This review demonstrates the structure and functions of the white matter in the healthy brain and discusses the pathophysiological mechanism of WMI following ICH. Our review reveals that the development of WMI after ICH is complex; therefore, comprehensive treatment is essential. Understanding the relationship between WMI and other brain cells may reveal therapeutic targets for the treatment of ICH.

Impairments of white matter tracts and connectivity alterations in five cognitive networks of patients with multiple sclerosis

INTRODUCTION

MS is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and speed of information processing. Here, we analyzed the white matter damage and topological organization of white matter tracts in specific brain regions responsible for cognition in MS.

METHODS

Brain DTI, rs-fMRI, T1, T2, and T2-FLAIR were acquired for 22 MS subjects and 22 healthy controls. Automatic brain parcellation was performed on T1-weighted images. Skull-stripped T1-weighted intensity inverted images were co-registered to the b0 image. Diffusion-weighted images were processed to perform whole brain tractography. The rs-fMRI data were processed, and the connectivity matrixes were analyzed to identify significant differences in the network of nodes between the two groups using NBS analysis. In addition, diffusion entropy maps were produced from DTI data sets using in-house software.

RESULTS

MS subjects exhibited significantly reduced mean FA and entropy in 38 and 34 regions, respectively, out of a total of 54 regions. The connectivity values in both structural and functional analyses were decreased in most regions of the default mode network and in four other cognitive networks in MS subjects compared to healthy controls. MS also induced significant reduction in the normalized hippocampus and corpus callosum volumes; the normalized hippocampus volume was significantly correlated with EDSS scores.

CONCLUSION

MS subjects have significant white matter damage and reduction of FA and entropy in various brain regions involved in cognitive networks. Structural and functional connectivity within the default mode network and an additional four cognitive networks exhibited significant changes compared with healthy controls.

Diffusion MR imaging acquisition and analytics for microstructural delineation in preclinical models of TBI

Significant progress has been made toward improving both the acquisition of clinical diffusion-weighted imaging (DWI) data and its analysis in the uninjured brain, through various techniques including a large number of model-based solutions that have been proposed to fit for multiple tissue compartments, and multiple fibers per voxel. While some of these techniques have been applied to clinical traumatic brain injury (TBI) research, the majority of these technological enhancements have yet to be fully implemented in the preclinical arena of TBI animal model-based research. In this review, we describe the requirement for preclinical, MRI-based efforts to provide systematic confirmation of the applicability of some of these models as indicators of tissue pathology within the injured brain. We review how current DWI techniques are currently being used in animal TBI models, and describe how both acquisition and analytic techniques could be extended to leverage the progress made in clinical work. Finally, we highlight remaining gaps in the preclinical pipeline from data acquisition to final analysis that currently have no real, preclinical-based correlate.

White Matter Injury in Early Brain Injury after Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) is a major cause of high morbidity, disability, and mortality in the field of neurovascular disease. Most previous SAH studies have focused on improving cerebral blood flow, reducing cerebral vasospasm, reducing neuronal calcium overload, and other treatments. While these studies showed exciting findings in basic science, therapeutic strategies based on the findings have not significantly improved neurological outcomes in patients with SAH. Currently, the only drug proven to effectively reduce the neurological defects of SAH patients is nimodipine. Current advances in imaging technologies in the field of stroke have confirmed that white matter injury (WMI) plays an important role in the prognosis of types of stroke, and suggests that WMI protection is essential for functional recovery and poststroke rehabilitation. However, WMI injury in relation to SAH has remained obscure until recently. An increasing number of studies suggest that the current limitations for SAH treatment are probably linked to overlooked WMI in previous studies that focused only on neurons and gray matter. In this review, we discuss the biology and functions of white matter in the normal brain, and discuss the potential pathophysiology and mechanisms of early brain injury after SAH. Our review demonstrates that WMI encompasses multiple substrates, and, therefore, more than one pharmacological approach is necessary to preserve WMI and prevent neurobehavioral impairment after SAH. Strategies targeting both neuronal injury and WMI may potentially provide a novel future for SAH knowledge and treatment.

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.

White matter changes in patients with mild traumatic brain injury: MRI perspective

This review focuses on white matter (WM) changes in mild traumatic brain injury (mTBI) as assessed by multimodal MRI. All the peer reviewed publications on WM changes in mTBI from January 2011 through September 2016 are included in this review. This review is organized as follows: introduction to mTBI, the basics of multimodal MRI techniques that are potentially useful for probing the WM integrity, summary and critical evaluation of the published literature on the application of multimodal MRI techniques to assess the changes of WM in mTBI, and correlation of MRI measures with behavioral deficits. The MRI–pathology correlation studies based on preclinical models of mTBI are also reviewed. Finally, the author's perspective of future research directions is described.

Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke

PURPOSE

Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery.

METHODS

We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study.

RESULTS

Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls.

CONCLUSION

Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.

White matter changes after stroke in type 2 diabetic rats measured by diffusion magnetic resonance imaging

Diffusion-related magnetic resonance imaging parametric maps may be employed to characterize white matter of brain. We hypothesize that entropy of diffusion anisotropy may be most effective for detecting therapeutic effects of bone marrow stromal cell treatment of ischemia in type 2 diabetes mellitus rats. Type 2 diabetes mellitus was induced in adult male Wistar rats. These rats were then subjected to 2 h of middle cerebral artery occlusion, and received bone marrow stromal cell (5 × 10⁶, n = 8) or an equal volume of saline (n = 8) via tail vein injection at three days after middle cerebral artery occlusion. Magnetic resonance imaging was performed on day one and then weekly for five weeks post middle cerebral artery occlusion. The diffusion metrics complementarily permitted characterization of axons and axonal myelination. All six magnetic resonance imaging diffusion metrics, confirmed by histological measures, demonstrated that bone marrow stromal cell treatment significantly (p < 0.05) improved magnetic resonance imaging diffusion indices of white matter in type 2 diabetes mellitus rats after middle cerebral artery occlusion compared with the saline-treated rats. Superior to the fractional anisotropy metric that provided measures related to organization of neuronal fiber bundles, the entropy metric can also identify microstructures and low-density axonal fibers of cerebral tissue after stroke in type 2 diabetes mellitus rats.

Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex

Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat’s exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called “barrel cortex” of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal functionality in humans suffering TBI. Such detailed understanding of the specific changes in an individual patient’s cortex can allow for treatment to be tailored to the neuronal changes in that particular patient’s brain in TBI, a precision that is currently unavailable with any technique.

Diffusion-Derived Magnetic Resonance Imaging Measures of Longitudinal Microstructural Remodeling Induced by Marrow Stromal Cell Therapy after Traumatic Brain Injury

Using magnetic resonance imaging (MRI) and an animal model of traumatic brain injury (TBI), we investigated the capacity and sensitivity of diffusion-derived measures, fractional anisotropy (FA), and diffusion entropy, to longitudinally identify structural plasticity in the injured brain in response to the transplantation of human bone marrow stromal cells (hMSCs). Male Wistar rats (300-350g, n = 30) were subjected to controlled cortical impact TBI. At 6 h or 1 week post-injury, these rats were intravenously injected with 1 mL of saline (at 6 h or 1 week, n = 5/group) or with hMSCs in suspension (∼3 × 10⁶ hMSCs, at 6 h or 1 week, n = 10/group). In vivo MRI measurements and sensorimotor function estimates were performed on all animals pre-injury, 1 day post-injury, and weekly for 3 weeks post-injury. Bielschowsky's silver and Luxol fast blue staining were used to reveal the axon and myelin status, respectively, with and without cell treatment after TBI. Based on image data and histological observation, regions of interest encompassing the structural alterations were made and the values of FA and entropy were monitored in these specific brain regions. Our data demonstrate that administration of hMSCs after TBI leads to enhanced white matter reorganization particularly along the boundary of contusional lesion, which can be identified by both FA and entropy. Compared with the therapy performed at 1 week post-TBI, cell intervention executed at 6 h expedites the brain remodeling process and results in an earlier functional recovery. Although FA and entropy present a similar capacity to dynamically detect the microstructural changes in the tissue regions with predominant orientation of fiber tracts, entropy exhibits a sensitivity superior to that of FA, in probing the structural alterations in the tissue areas with complex fiber patterns.

Recent imaging advances in neurology

Over the recent years, the application of neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) has considerably advanced the understanding of complex neurological disorders. PET is a powerful molecular imaging tool, which investigates the distribution and binding of radiochemicals attached to biologically relevant molecules; as such, this technique is able to give information on biochemistry and metabolism of the brain in health and disease. MRI uses high intensity magnetic fields and radiofrequency pulses to provide structural and functional information on tissues and organs in intact or diseased individuals, including the evaluation of white matter integrity, grey matter thickness and brain perfusion. The aim of this article is to review the most recent advances in neuroimaging research in common neurological disorders such as movement disorders, dementia, epilepsy, traumatic brain injury and multiple sclerosis, and to evaluate their contribution in the diagnosis and management of patients.

Traumatic white matter injury and glial activation: from basic science to clinics

An improved understanding and characterization of glial activation and its relationship with white matter injury will likely serve as a novel treatment target to curb post injury inflammation and promote axonal remyelination after brain trauma. Traumatic brain injury (TBI) is a significant public healthcare burden and a leading cause of death and disability in the United States. Particularly, traumatic white matter (WM) injury or traumatic axonal injury has been reported as being associated with patients' poor outcomes. However, there is very limited data reporting the importance of glial activation after TBI and its interaction with WM injury. This article presents a systematic review of traumatic WM injury and the associated glial activation, from basic science to clinical diagnosis and prognosis, from advanced neuroimaging perspective. It concludes that there is a disconnection between WM injury research and the essential role of glia which serve to restore a healthy environment for axonal regeneration following WM injury. Particularly, there is a significant lack of non-invasive means to characterize the complex pathophysiology of WM injury and glial activation in both animal models and in humans. An improved understanding and characterization of the relationship between glia and WM injury will likely serve as a novel treatment target to curb post injury inflammation and promote axonal remyelination.