Magnetization transfer and T2 quantitation in normal appearing cortical gray matter and white matter adjacent to focal abnormality in patients with traumatic brain injury

Traumatic brain injury (TBI) is one of the commonest causes of morbidity and mortality in the developed countries with posttraumatic epilepsy and functional disability being its major sequelae. The purpose of this study was to test the hypothesis whether the normal appearing adjacent gray and white matter regions on T2 and T1 weighted magnetization transfer (MT) weighted images show any abnormality on quantitative imaging in patients with TBI. A total of 51 patients with TBI and 10 normal subjects were included in this study. There were significant differences in T2 and MT ratio values of T2 weighted and T1 weighted MT normal appearing gray matter regions adjacent to focal image abnormality compared to normal gray matter regions in the normal individuals as corresponding contralateral regions of the TBI patient's group (p < 0.05). However the adjoining normal appearing white matter quantitative values did not show any significant change compared to the corresponding contralateral normal white matter values. We conclude that quantitative T2 and MT ratio values provide additional abnormality in patients with TBI that is not discernable on conventional T2 weighted and T1 weighted MT imaging especially in gray matter. This additional information may be of value in overall management of these patients with TBI.     

Alterations in diffusion properties of white matter in Williams syndrome

Diffusion tensor imaging (DTI) was used to investigate the involvement of brain white matter in Williams syndrome (WS), a genetic neurodevelopmental disorder. Whole-brain DTIs were obtained from 16 young adults with WS and 16 normal controls. A voxel-based analysis was performed to compare fractional anisotropy (FA) values between the two groups. A tract-based analysis was also performed to compare FA values between the two groups along two major white matter tracts that pass through the external capsule: the uncinate and inferior fronto-occipital fasciculi. Several regions of both increased and decreased FA were found within major white matter tracts that connect functional regions that have previously been implicated in the cognitive and neurological symptoms of the syndrome. The tract-based analysis provided additional insight into the involvement of specific white matter tracts implicated in the voxel-based analysis within the external capsule. The results from this study support previously reported changes in white matter diffusion properties in WS and demonstrate the potential usefulness for tract-based analysis in future studies of the disorder.     

On- and off-resonance spin-lock MR imaging of normal human brain at 0.1 T: possibilities to modify image contrast

The aim of the present investigation was to determine spin lock (SL) relaxation parameters for the normal brain tissues and thus, to provide basis for optimizing the imaging contrast at 0.1 T. 68 healthy volunteers were included. On-resonance spin lock relaxation time (T_1ρ) and off-resonance spin lock relaxation parameters (T_1ρ^off, M_e/M_o), MT parameters (T_1sat, M_s/M_o), and T₁, T₂ were determined for the cortical gray matter, and for the frontal and parietal white matters. The T_1ρ for the frontal and parietal white matters ranged from 110 to 133 ms and from 122 to 155 ms with locking field strengths from 50 μT to 250 μT, respectively. Accordingly, the values for the gray matter ranged from 127 to 155 ms. With a locking field strength of 50 μT, T_1ρ^off for the frontal and parietal white matters were from 114 to 217 ms and from 126 to 219 ms, and for the gray matter from 136 to 267 ms with the angle between the effective magnetic field (B_eff) and the z-axis (θ) ranging from 60° to 15°, respectively. The T_1ρ of the white and gray matters increased significantly with increasing locking field amplitude (p < 0.001). The T_1ρ^off decreased significantly with increasing θ (p < 0.001). T_1ρ and T_1ρ^off with θ ≥ 30° were statistically significantly shorter in the frontal than in the parietal white matters (p < 0.05). The duration, amplitude and θ of the locking pulse provide additional parameters to optimize contrast in brain SL imaging.     

Biexponential apparent diffusion coefficient parametrization in adult vs newborn brain.

The decay of brain water signal with b-factor in adult and newborn brains has been measured over an extended b-factor range. Measurements of the apparent diffusion coefficient (ADC) decay curves were made at 16 b-factors from 100 to 5000 s/mm(2) along three orthogonal directions using a line scan diffusion imaging (LSDI) sequence to acquire data from 0.09 ml voxels in a mid-brain axial slice. Regions-of-interest (ROIs) in cortical gray (CG) and white matter in the internal capsule (IC) were selected for ADC decay curve analyses using a biexponential fitting model over this extended b-factor range. Measures of the fast and slow ADC component amplitudes and the traces of the fast and slow diffusion coefficients were obtained from CG and IC ROIs in both adults and newborns. The ADC decay curves from the newborn brain regions were found to have a significantly higher fraction of the fast diffusion ADC component than corresponding regions in the adult brain. The results demonstrate that post-natal brain development has a profound affect on the biexponential parameters which characterize the decay of water signal over an extended b-factor range in both gray and white matter.     

In vivo NMR T2 relaxation of experimental brain tumors in the cat: a multiparameter tissue characterization.

Experimental gliomas (F98) were inoculated in cat brain for the systematic study of their in vivo T₂ relaxation time behavior. With a CPMG multi-echo imaging sequence, a train of 16 echoes was evaluated to obtain the transverse relaxation time and the magnetization M(0) at time T = 0. The magnetization decay curves were analyzed for biexponentiality. All tissues showed monoexponential T₂, only that of the ventricular fluid and part of the vital tumor tissue were biexponential. Based on these NMR relaxation parameters the tissues were characterized, their correct assignment being assured by comparison with histological slices. T₂ of normal grey and white matter was 74 ± 6 and 72 ± 6 msec, respectively. These two tissue types were distinguished through M(0) which for white matter was only 0.88 of the intensity of grey matter in full agreement with water content, determined from tissue specimens. At the time of maximal tumor growth and edema spread a tissue differentiation was possible in NMR relaxation parameter images. Separation of the three tissue groups of normal tissue, tumor and edema was based on T₂ with T_2(normal) < T_2(tumor) < T_2(edema). Using M(0) as a second parameter the differentiation was supported, in particular between white matter and tumor or edema. Animals were studied at 1–4 wk after tumor implantation to study tumor development. The magnetization M(0) of both tumor and peritumoral edema went through a maximum between the second and third week of tumor growth. T₂ of edema was maximal at the same time with 133 ± 4 msec, while the relaxation time of tumor continued to increase during the whole growth period, reaching values of 114 ± 12 msec at the fourth week. Thus, a complete characterization of pathological tissues with NMR relaxometry must include a detailed study of the developmental changes of these tissues to assure correct experimental conditions for the goal of optimal contrast between normal and pathological regions in the NMR images.     

Morphometry in temporal lobe epilepsy

We demonstrate a method for quantitating changes in volume and morphology of the temporal lobe in epilepsy. The temporal lobes of 10 neurologically normal subjects and six subjects with well defined left-sided mesial temporal epilepsy were studied. From high resolution T₁-weighted magnetic resonance images, the grey and white matter were manually segmented over a predetermined extent. The volumes of the grey and white matter were determined. Using the segmented images, the grey matter/CSF surface and the white matter/grey matter surface were reconstructed, allowing estimates of the surface area and calculation of indices of curvature for the two surfaces. The index of curvature was calculated for each vertex of a polygonal mesh that was fitted to the surfaces. An index of grey matter thickness (grey matter volume/white matter surface area) was also calculated. There was a significant bilateral decrease in the total volume (p < .01), grey matter volume (p < .001) and grey matter thickness index (p < .05) in epileptic subjects. In addition, there was a bilateral decrease in white matter surface area (p < .05) and a small left-sided decrease in white matter volume (p < .05) in epileptic subjects. The average distributions of indices of curvature for both surfaces differed significantly (p < .05) between normal and epileptic subjects. In the grey matter/CSF surface of normal subjects, a large peak corresponding to surface concavity was present. The amplitude of this peak was significantly lower in epileptic subjects (p < .05 for the right hemisphere; p < .001 for the left hemisphere).     

Non-invasive and low-artifact in vivo brain imaging by using a scanning acoustic-photoacoustic dual mode microscopy

Photoacoustic imaging is a potential candidate for in vivo brain imaging, whereas, its imaging performance could be degraded by inhomogeneous multi-layered media, consisted of scalp and skull. In this work, we propose a low-artifact photoacoustic microscopy (LAPAM) scheme, which combines conventional acoustic-resolution photoacoustic microscopy with scanning acoustic microscopy to suppress the reflection artifacts induced by multi-layers. Based on similar propagation characteristics of photoacoustic signals and ultrasonic echoes, the ultrasonic echoes can be employed as the filters to suppress the reflection artifacts to obtain low-artifact photoacoustic images. Phantom experiment is used to validate the effectiveness of this method. Furthermore, LAPAM is applied for in-vivo imaging mouse brain without removing the scalp and the skull. Experimental results show that the proposed method successfully achieves the low-artifact brain image, which demonstrates the practical applicability of LAPAM. This work might improve the photoacoustic imaging quality in many biomedical applications which involve tissues with complex acoustic properties, such as brain imaging through scalp and skull.     

An automated method for volumetric quantification of magnetization transfer of the brain

Cerebral white matter damages can be detected and characterized using magnetization transfer (MT) imaging. In this study a fully automated method of measuring and analyzing the MT of the whole human brain is presented and assessed. A 3D-FLASH sequence with off-resonance RF pulse was optimized for fast, volumetric MT measurements. The postprocessing software developed for this purpose includes a SPM99-based segmentation algorithm, a visualization tool, and a histogram-based MT parameter analysis. The reproducibility of the method was tested with phantom measures and in studies on nine healthy volunteers. Small variances (0-1.6%) and therefore, a high reproducibility of MT parameter measurements were found in vitro, slightly higher variances in volunteer investigations (0.7-4.0%). With our technique, we expect to be able to better recognize and follow up the progression of white matter diseases. Due to the high reproducibility, this volumetric approach is specifically suitable for longitudinal MT studies.     

Quantitative and qualitative assessment of articular cartilage in the goat knee with magnetization transfer imaging

We investigated the role of collagen in the magnetization transfer (MT) effect in contrast to other macromolecules. By means of phantoms made of collagen, chondroitin sulfate (CS) and albumin, MR parameters have been optimized in order to reduce the acquisition time and improve the sensitivity, as well as to minimize the contributions from CS and albumin to the MT induced signal attenuation. The same method was used to study cartilage ex vivo (bovine articular and nasal cartilage plugs) and in vivo (goat knee femoral chondyle). In phantom samples, the MT signal attenuation depended on the collagen concentration while contributions from the other macromolecules were found to be minimal. In average, analysis of MT images revealed a 25%, 35% and 30% signal attenuation in 10% w/v type I collagen gels, cartilage plugs, and cartilage from the weight-bearing areas of the goat knee, respectively. Biochemical data revealed that treatment of cartilage plugs with bacterial collagenase led to collagen depletion and correspondingly to a decrease of the MT response. In contrast, trypsin-induced proteoglycan loss in cartilage plugs did not alter the MT effect. A significant correlation was observed between the collagen content in these plugs and their respective MT ratios and the rate constant k for the exchange process bound versus free water. Finally, data obtained from in vivo MT measurement of the goat knee demonstrated that intra-articular injection of papain might not only cause degradation of proteoglycans but also a change in collagen integrity in a dose-dependent manner. We conclude that in vivo measurement of MT ratios gives quantitative and qualitative information on the collagen status and may be applied for the routine evaluation of normal and abnormal articular cartilage.     

西洋参-石菖蒲对糖尿病认知障碍大鼠学习记忆相关脑区的影响

本文探究了西洋参-石菖蒲（X-S）药液对糖尿病认知障碍（DACD）大鼠学习记忆相关脑区的影响．腹腔注射链脲佐菌素（STZ）诱导糖尿病大鼠模型,并将动物分为糖尿病组和X-S组,STZ注射7天后给予X-S药,每日1次,连续113天;于STZ注射80天后采用Morris水迷宫方法筛选DACD和非认知障碍（DNCD）大鼠;120天后运用磁共振成像（MRI）技术扫描大鼠全脑,利用感兴趣区（ROI）法和基于体素形态学（VBM）法对各组大鼠大脑灰质和白质进行体积和密度的分析;并通过苏木精-伊红（HE）染色观察大鼠海马神经元的形态结构．ROI分析法显示：与DACD组相比,X-S组大鼠左侧颞叶联合皮质体积减小（p<0.05）;VBM分析法显示：与DACD组相比,X-S组大鼠海马CA1、CA3区及其它脑区的体积和密度或增高或降低（p<0.005）．HE染色结果显示：与DACD组相比,X-S组大鼠海马CA1、CA3区的细胞固缩及排列紊乱减轻．结果表明X-S药液对DACD大鼠与学习记忆相关的海马及其它脑区存在双向调节,从而发挥学习记忆能力的改善作用．     

Magnetic resonance of brain tumors: considerations of imaging contrast on the basis of relaxation measurements

Proton spin-lattice and spin-spin relaxation times have been measured in surgically-removed normal CNS tissues and a variety of tumors of the brain. All measurements were made at 20 MHz and 37 degrees C. Between grey and white matter from autopsy human or canine specimens significant differences in T1 or T2 were observed, with greater differences seen in T1. Such discrimination was reduced in samples obtained from live brain-tumor patients due to lengthening in T1 and T2 of white matter near tumorous lesions. Edematous white matter showed T1 and T2 values higher than those of autopsy disease-free white matter. Compared to normal CNS tissues, most brain tumors examined in this study demonstrated elevated T1 and T2 values. Exceptions, however, did exist. No definitive correlation was indicated on a T1 or T2 basis which allowed a distinction to be made between benign and malignant states. Furthermore, considerable variation in relaxation times occurred from tumor to tumor of the same type, suggesting that within a tumor type there are important differences in physiology, biology, and/or pathologic state. Such variation caused partial overlap in relaxation times among certain tumor types and hence may limit the capability of magnetic resonance imaging (MR) alone for the diagnosis of specific disease. Nonetheless, this study predicts that on the basis of T1 or T2 differences most brain tumors are readily detectable by MR via saturation recovery or inversion recovery with appropriate selections of pulse-spacing parameters. In general, tumors can be discriminated against white matter better than grey matter and contrast between glioma and grey matter is usually superior to that between meningioma and grey matter. This work did not consider tissue-associated proton density which should be addressed together with T1 and T2 for a complete treatment of MR contrast.     

Modeling brain tissue volumes over the lifespan: quantitative analysis of postmortem weights and in vivo MR images

Normative measurements of brain gray matter and white matter tissue volumes across the lifespan have not yet been established. The purpose of this article was to use mathematical modeling and analytical functions to demonstrate the growth trajectory of gray matter and white matter from age 0 to age 90. For each gender, brain weight functions were generated by utilizing existing autopsy data from 4400 subjects. Brain gray matter, white matter and lateral ventricular volumes were measured from 39 MR volumes of normal individuals. These were converted to weight by multiplying the tissue volumes by the specific gravity of that tissue. White matter volumes were described by a saturating exponential function, and the gray matter volume function was calculated by subtracting the white matter weight function from the brain weight function. For each gender, equations were generated for white matter and gray matter volumes as a function of age over the lifespan.     

A modified fuzzy clustering algorithm for operator independent brain tissue classification of dual echo MR images.

Methods for brain tissue classification or segmentation of structural magnetic resonance imaging (MRI) data should ideally be independent of human operators for reasons of reliability and tractability. An algorithm is described for fully automated segmentation of dual echo, fast spin-echo MRI data. The method is used to assign fuzzy-membership values for each of four tissue classes (gray matter, white matter, cerebrospinal fluid and dura) to each voxel based on partition of a two dimensional feature space. Fuzzy clustering is modified for this application in two ways. First, a two component normal mixture model is initially fitted to the thresholded feature space to identify exemplary gray and white matter voxels. These exemplary data protect subsequently estimated cluster means against the tendency of unmodified fuzzy clustering to equalize the number of voxels in each class. Second, fuzzy clustering is implemented in a moving window scheme that accommodates reduced image contrast at the axial extremes of the transmitting/receiving coil. MRI data acquired from 5 normal volunteers were used to identify stable values for three arbitrary parameters of the algorithm: feature space threshold, relative weight of exemplary gray and white matter voxels, and moving window size. The modified algorithm incorporating these parameter values was then used to classify data from simulated images of the brain, validating the use of fuzzy-membership values as estimates of partial volume. Gray:white matter ratios were estimated from 20 twenty normal volunteers (mean age 32.8 years). Processing time for each three-dimensional image was approximately 30 min on a 170 MHz workstation. Mean cerebral gray and white matter volumes estimated from these automatically segmented images were very similar to comparable results previously obtained by operator dependent methods, but without their inherent unreliability.     

Short echo time multislice proton magnetic resonance spectroscopic imaging in human brain: metabolite distributions and reliability.

Multislice proton magnetic resonance spectroscopic imaging (1H MRSI) at 25 ms echo time was used to measure concentrations of myo-inositol (mI), N-acetylaspartate (NAA), and creatine (Cr) and choline (Cho) in ten normal subjects between 22 and 84 years of age (mean age 44 +/- 18 years). By co-analysis with MRI based tissue segmentation results, metabolite distributions were analyzed for each tissue type and for different brain regions. Measurement reliability was evaluated using intraclass correlation coefficients (ICC). Significant differences in metabolite distributions were found for all metabolites. mI of frontal gray matter was 84% of parietal gray matter and 87% of white matter. NAA of frontal gray matter was 86% of parietal gray matter and 85% of white matter. Cho of frontal gray matter was 125% of parietal gray matter and 59% of white matter and Cho of parietal gray matter was 47% of white matter. Cr of parietal gray matter was 113% of white matter. Reliability was relatively high (ICC from.70 to.93) for all metabolites in white matter and for NAA and Cr in gray matter, though limited (ICC less than.63) for mI and Cho in gray matter. These findings indicate that voxel gray/white matter contributions, regional variations in metabolite concentrations, and reliability limitations must be considered when interpreting 1H MR spectra of the brain.     

Diffusion-weighted EPI with magnetization transfer contrast

Capabilities of diffusion-weighted (DW) and magnetization transfer (MT) imaging are well established for tissue characterization in various pathologies individually. However, the effect of suppression of macromolecules on applying MT pulse on signals associated with DW imaging and resulting change in the apparent diffusion coefficient (ADC) of water molecules has not been demonstrated previously. In the present study, we have performed DW echo planar imaging (EPI) with and without MT preparation pulse to see the effect of macromolecular signal suppression on ADC. A total of 10 normal volunteers and 20 patients with different intracranial cystic lesions [abscesses (n=10), cystic tumors (n=5), arachnoid cysts (n=5)] were subjected to DW imaging (b=0 and 1000 s/mm(2)) with and without MT saturation pulse. Analysis of region of interest (ROI) from different areas of white matter in normal volunteers and in the wall and cavity of cystic lesions in patients was carried out for calculating the ADC values. We found a significant increase (P<.05) in the ADC values in brain parenchyma and cavity of those intracranial cystic lesions having considerable amount of proteins after the application of MT preparation pulse except for arachnoid cysts. This is due to the size of the macromolecules present in the normal and abnormal tissue. Our studies suggest that this technique is likely to give a novel image contrast and may be of value in improving the tissue specificity in pathologies associated with variable macromolecular size.     

Establishing norms for age-related changes in proton T1 of human brain tissue in vivo

The goal of this study was to determine the expected normal range of variation in spin-lattice relaxation time (T₁) of brain tissue in vivo, as a function of age. A previously validated precise and accurate inversion recovery method was used to map T₁ transversely, at the level of the basal ganglia, in a study population of 115 healthy subjects (ages 4 to 72; 57 male and 58 female). Least-squares regression analysis shows that T₁ varied as a function of age in pulvinar nucleus (R² = 56%), anterior thalamus (R² = 51%), caudate (R² = 50%), frontal white matter (R² = 47%), optic radiation (R² = 39%), putamen (R² = 36%), genu (R² = 22%), occipital white matter (R² = 20%) (all p < 0.0001), and cortical gray matter (R² = 53%) (p < 0.001). There were no significant differences in T₁ between men and women. T₁ declines throughout adolescence and early adulthood, to achieve a minimum value in the fourth to sixth decade of life, then T₁ begins to increase. Quantitative magnetic resonance imaging provides evidence that brain tissue continues to change throughout the lifespan among healthy subjects with no neurologic deficits. Age-related changes follow a strikingly different schedule in different brain tissues; white matter tracts tend to reach a minimum T₁ value, and to increase again, sooner than do gray matter tracts. Such normative data may prove useful for the early detection of brain pathology in patients.     

Unsupervised MRI segmentation of brain tissues using a local linear model and level set

Real-world magnetic resonance imaging of the brain is affected by intensity nonuniformity (INU) phenomena which makes it difficult to fully automate the segmentation process. This difficult task is accomplished in this work by using a new method with two original features: (1) each brain tissue class is locally modeled using a local linear region representative, which allows us to account for the INU in an implicit way and to more accurately position the region's boundaries; and (2) the region models are embedded in the level set framework, so that the spatial coherence of the segmentation can be controlled in a natural way. Our new method has been tested on the ground-truthed Internet Brain Segmentation Repository (IBSR) database and gave promising results, with Tanimoto indexes ranging from 0.61 to 0.79 for the classification of the white matter and from 0.72 to 0.84 for the gray matter. To our knowledge, this is the first time a region-based level set model has been used to perform the segmentation of real-world MRI brain scans with convincing results.     

Analysis of Brain Tissue by FT-IR Microspectroscopy

Biological specimens contain a vast array of cell types, cell layers, extracellular materials, and other components that are structurally and functionally interrelated. Although the histological relationship of each of these constituents has been documented for most mammalian tissues, the chemical relationships between constituents has largely gone unexplored. Fourier transform infrared (FT-IR) spectroscopy can be a powerful tool for analyzing the chemical composition and molecular interactions of biological materials. Analyses of biological materials, however, have been conducted primarily on homogenized and/or purified samples. As a consequence of these limitations, the distribution and concentration of functional groups within different regions of biological tissues have not been appreciated. Several recent technological developments have enabled an FT-IR spectrometer to be combined with microscope optics. This integrated instrument, called an FT-IR microspectrometer, is capable of collecting good quality spectra from small regions of tissues down to a 10 μm × 10 μm square. Spectra collected along a grid pattern can be combined to generate contour or three-dimensional maps that represent the concentration and distribution of functional groups across a tissue. This is important because it permits a correlation of the spatial concentration of chemical functional groups with tissue histology. Analyses can be performed on normal tissue or tissues with unique properties, i.e., developmental or pathological tissues. This review will focus on FT-IR microspectroscopic investigations of normal biological tissue. Particular attention will be given to one example of FT-IR microspectroscopic analysis: white matter of brain tissue. This region was chosen because its infrared profile is very different from other brain regions, and thus it provides a clear illustration of the information that can be obtained by FT-IR microspectroscopy. This review is intended for the spectroscopist who is interested in applying his or her expertise to biological questions as well as to the biologist who is looking for new ways to obtain chemical information about his or her area of study.     

一种快速提取连续CT脑肿瘤病灶区的算法

脑肿瘤图像提取就是将肿瘤病灶区域(水肿、坏死、癌变)从正常的脑部组织(灰质、白质、脑脊液)分开,精确的脑肿瘤分割对脑瘤的诊断、研究和治疗有重要的临床意义。针对传统脑部CT肿瘤病灶提取的缺点,即需要耗费大量时间并且分割精度不高的问题,提出一种综合了形态学重建、分水岭分割和改进的区域生长算法。先用形态学重建进行去噪,再用结合多尺度梯度分水岭分割提取整个图像的边界,然后在肿瘤病灶区域内选取种子点进行区域生长,提取肿瘤区域轮廓,滤除其他封闭区域,得到的图像作为改进的区域生长法的初始分割区域,使用改进的区域生长法,滤除过分割区域。实验结果显示该算法分割出的结果有效区域大,分割精度高。结论：该算法提高了分割精度,由于不用匹配结构参数,加快了分割速度,具有一定的临床价值。