Correlation between white matter damage and gray matter lesions in multiple sclerosis patients

We observed the characteristics of white matter fibers and gray matter in multiple sclerosis patients, to identify changes in diffusion tensor imaging fractional anisotropy values following white matter fiber injury. We analyzed the correlation between fractional anisotropy values and changes in whole-brain gray matter volume. The participants included 20 patients with relapsing-remitting multiple sclerosis and 20 healthy volunteers as controls. All subjects underwent head magnetic resonance imaging and diffusion tensor imaging. Our results revealed that fractional anisotropy values decreased and gray matter volumes were reduced in the genu and splenium of corpus callosum, left anterior thalamic radiation, hippocampus, uncinate fasciculus, right corticospinal tract, bilateral cingulate gyri, and inferior longitudinal fasciculus in multiple sclerosis patients. Gray matter volumes were significantly different between the two groups in the right frontal lobe（superior frontal, middle frontal, precentral, and orbital gyri）, right parietal lobe（postcentral and inferior parietal gyri）, right temporal lobe（caudate nucleus）, right occipital lobe（middle occipital gyrus）, right insula, right parahippocampal gyrus, and left cingulate gyrus. The voxel sizes of atrophic gray matter positively correlated with fractional anisotropy values in white matter association fibers in the patient group. These findings suggest that white matter fiber bundles are extensively injured in multiple sclerosis patients. The main areas of gray matter atrophy in multiple sclerosis are the frontal lobe, parietal lobe, caudate nucleus, parahippocampal gyrus, and cingulate gyrus. Gray matter atrophy is strongly associated with white matter injury in multiple sclerosis patients, particularly with injury to association fibers.

Compression analysis of the gray and white matter of the spinal cord

The spinal cord is composed of gray matter and white matter.It is well known that the properties of these two tissues differ considerably.Spinal diseases often present with symptoms that are caused by spinal cord compression.Understanding the mechanical properties of gray and white matter would allow us to gain a deep understanding of the injuries caused to the spinal cord and provide information on the pathological changes to these distinct tissues in several disorders.Previous studies have reported on the physical properties of gray and white matter,however,these were focused on longitudinal tension tests.Little is known about the differences between gray and white matter in terms of their response to compression.We therefore performed mechanical compression test of the gray and white matter of spinal cords harvested from cows and analyzed the differences between them in response to compression.We conducted compression testing of gray matter and white matter to detect possible differences in the collapse rate.We found that increased compression(especially more than 50%compression)resulted in more severe injuries to both the gray and white matter.The present results on the mechanical differences between gray and white matter in response to compression will be useful when interpreting findings from medical imaging in patients with spinal conditions.

Computerized White Matter and Gray Matter Extraction from MRI of Brain Image

Automated segmentation of white matter (WM) and gray matter (GM) is a very important task for detecting multiple diseases. The paper proposed a simple method for WM and GM extraction form magnetic resonance imaging (MRI) of brain. The proposed methods based on binarization, wavelet decomposition, and convexhull produce very effective results in the context of visual inspection and as well as quantifiably. It tested on three different (Transvers, Sagittal, Coronal) types of MRI of brain image and the validation of experiment indicate accurate detection and segmentation of the interesting structures or particular region of MRI of brain image.

β-Estradiol 17-acetate enhances the in vitro vitality of endothelial cells isolated from the brain of patients subjected to neurosurgery

In the current landscape of endothelial cell isolation for building in vitro models of the blood-brain barrier,our work moves towards reproducing the features of the neurovascular unit to achieve glial compliance through an innovative biomimetic coating technology for brain chronic implants.We hypothesized that the autologous origin of human brain mic rovascular endothelial cells(hBMECs)is the first requirement for the suitable coating to prevent the glial inflammato ry response trigge red by foreign neuroprosthetics.Therefo re,this study established a new procedure to preserve the in vitro viability of hBMECs isolated from gray and white matter specimens taken from neurosurge ry patients.Culturing adult hBMECs is generally considered a challenging task due to the difficult survival ex vivo and progressive reduction in proliferation of these cells.The addition of 10 nMβ-estradiol 17-acetate to the hBMEC culture medium was found to be an essential and discriminating factor promoting adhesion and proliferation both after isolation and thawing,suppo rting the well-known protective role played by estrogens on microvessels.In particular,β-estradiol 17-acetate was critical for both freshly isolated and thawed female-derived hBMECs,while it was not necessary for freshly isolated male-derived hBMECs;however,it did countera ct the decay in the viability of the latter after thawing.The tumo r-free hBMECs were thus cultured for up to 2 months and their growth efficiency was assessed befo re and after two periods of cryopreservation.Des pite the thermal stress,the hBMECs remained viable and suitable for re-freezing and storage for several months.This approach increasing in vitro viability of hBMECs opens new perspectives for the use of cryopreserved autologous hBMECs as biomimetic therapeutic tools,offering the potential to avoid additional surgical sampling for each patient.

Atlas-based deep gray matter and white matter analysis in Alzheimer's disease: diffusion abnormality and correlation with cognitive function

Objective To identify the diffusion alterations of deep gray matter(GM)and white matter(WM)among Alzheimer’s disease(AD),mild cognitive impairment(MCI)and healthy people by atlas-based analysis(ABA),and to investigate the respective relationship with cognitive function.Methods Twenty-one AD patients(AD group),8 MCI patients(MCI group)and

Alteration of functional connectivity in patients with Alzheimer’s disease revealed by resting-state functional magnetic resonance imaging

The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.

Dynamic correlation of diffusion tensor imaging and neurological function scores in beagles with spinal cord injury

Exploring the relationship between different structure of the spinal cord and functional assessment after spinal cord injury is important. Quantitative diffusion tensor imaging can provide information about the microstructure of nerve tissue and can quantify the pathological damage of spinal cord white matter and gray matter. In this study, a custom-designed spinal cord contusion-impactor was used to damage the T_（10） spinal cord of beagles. Diffusion tensor imaging was used to observe changes in the whole spinal cord, white matter, and gray matter, and the Texas Spinal Cord Injury Score was used to assess changes in neurological function at 3 hours, 24 hours, 6 weeks, and 12 weeks after injury. With time, fractional anisotropy values after spinal cord injury showed a downward trend, and the apparent diffusion coefficient, mean diffusivity, and radial diffusivity first decreased and then increased. The apparent diffusion-coefficient value was highly associated with the Texas Spinal Cord Injury Score for the whole spinal cord（R = 0.919, P = 0.027）, white matter（R = 0.932, P = 0.021）, and gray matter（R = 0.882, P = 0.048）. Additionally, the other parameters had almost no correlation with the score（P 〉 0.05）. In conclusion, the highest and most significant correlation between diffusion parameters and neurological function was the apparent diffusion-coefficient value for white matter, indicating that it could be used to predict the recovery of neurological function accurately after spinal cord injury.

Pulsed arterial spin labeling effectively and dynamically observes changes in cerebral blood flow after mild traumatic brain injury

Cerebral blood flow is strongly associated with brain function, and is the main symptom and diagnostic basis for a variety of encephalopathies. However, changes in cerebral blood flow after mild traumatic brain injury remain poorly understood. This study sought to observe changes in cerebral blood flow in different regions after mild traumatic brain injury using pulsed arterial spin labeling. Our results demonstrate maximal cerebral blood flow in gray matter and minimal in the white matter of patients with mild traumatic brain injury. At the acute and subacute stages, cerebral blood flow was reduced in the occipital lobe, parietal lobe, central region, subcutaneous region, and frontal lobe. Cerebral blood flow was restored at the chronic stage. At the acute, subacute, and chronic stages, changes in cerebral blood flow were not apparent in the insula. Cerebral blood flow in the temporal lobe and limbic lobe diminished at the acute and subacute stages, but was restored at the chronic stage. These findings suggest that pulsed arterial spin labeling can precisely measure cerebral blood flow in various brain regions, and may play a reference role in evaluating a patient＇s condition and judging prognosis after traumatic brain injury.

Monte Carlo and phantom study in the brain edema models

Because the brain edema has a crucial impact on morbidity and mortality,it is important to develop a noninvasive method to monitor the process of the brain edema effectively.When the brain edema occurs,the optical properties of the brain will change.The goal of this study is to access the feasibility and reliability of using noninvasive near-infrared spectroscopy(NIRS)monitoring method to measure the brain edema.Specifically,three models,including the water content changes in the cerebrospinal fuid(CSF),gray matter and white matter,were explored.Moreover,these models were numerically simulated by the Monte Carlo studies.Then,the phantom experiments were performed to investigate the light intensity which was measured at different detecting radius on the tissue surface.The results indicated that the light intensity correlated well with the conditions of the brain edema and the detecting radius.Briefly,at the detect ing radius of 3.0 cm and 4.0 cm,the light intensity has a high response to the change of tissue parameters and optical properties.Thus,it is possible to monitor the brain edema noninvasively by NIRS method and the light intensity is a reliable and simple parameter to assess the brain edema.

Diffusion tensor imaging of spinal microstructure in healthy adults： improved resolution with the readout segmentation of long variable echo-trains

Diffusion tensor imaging plays an important role in the accurate diagnosis and prognosis of spinal cord diseases. However, because of technical limitations, the imaging sequences used in this technique cannot reveal the fine structure of the spinal cord with precision. We used the readout segmentation of long variable echo-trains（RESOLVE） sequence in this cross-sectional study of 45 healthy volunteers aged 20 to 63 years. We found that the RESOLVE sequence significantly increased the resolution of the diffusion images and improved the median signal-to-noise ratio of the middle（C4–6） and lower（C7–T1） cervical segments to the level of the upper cervical segment. In addition, the values of fractional anisotropy and radial diffusivity were significantly higher in white matter than in gray matter. Our study verified that the RESOLVE sequence could improve resolution of diffusion tensor imaging in clinical applications and provide accurate baseline data for the diagnosis and treatment of cervical spinal cord diseases.

FEM Based Study of Concentration of Proliferating Cell in Brain Tumor

In this chapter we have developed a deterministic model of growth of abnormal cell concentration in a human subject at different positions. The diffusion-reaction Equation has been applied to satisfy growth dynamics .The whole tumor region is divided into layers which, with the growth of tumor form necrotic, quiescent and region of proliferating of tumor cells. Finite element method for one dimension has been employed for solving the Equations. Here we have taken into account the cellular motility along with proliferative growth ,which is particularly required in case of some of the brain tumors, where motility of gliomas cells differ widely in gray and white matter.