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.     

Relaxo-volumetric multispectral quantitative magnetic resonance imaging of the brain over the human lifespan: global and regional aging patterns

The objective of this study was to determine the T1, T2 and secular-T2 relaxo-volumetric brain aging patterns using multispectral quantitative magnetic resonance imaging, both globally and regionally, and covering an age range approaching the full human lifespan. Fifty-one subjects (28 males, 23 females; age range: 0.5–87 years) were studied consisting of 18 healthy volunteers and 33 patients. Patients were selected after carefully reviewing their radiology reports to have either normal-by-MRI findings (25 patient subjects) or small focal pathology less than 6 mm in size (eight patient subjects). All subjects were MR imaged at 1.5 T with the mixed turbo spin echo pulse sequence. The soft tissues inside the cranial vault, termed intracranial matter (ICM), were segmented using a dual-clustering segmentation algorithm. ICM segments were further divided into six subsegments: bilateral anterior cerebral, posterior cerebral and cerebellar subsegments. T1, T2 and secular-T2 relaxation time histograms of all segments were generated and modeled with Gaussian functions. For each segment, the volumes of white matter, gray matter and cerebrospinal fluid were calculated from the T1 histograms. The age-related tendencies of three quantitative MRI parameters (T1, T2 and secular-T2) and the fractional tissue volumes showed four distinct periods of life, specifically a maturation period (0–2 years), a development period (2–20 years), an adulthood period (20–60 years) and a senescence period (60 years and older). For all ages, the anterior cerebral subsegment exhibited consistently longer gray matter T1s and shorter white matter T1s than the posterior cerebral and cerebellar subsegments. Volumetric age-related changes of the cerebellar subsegment were more gradual than in the cerebral subsegments. This study shows that relaxometric and volumetric age-related changes are synchronized and define the same four periods of brain evolution both globally and regionally.     

Effects of echo time variation on perfusion assessment using dynamic susceptibility contrast MR imaging at 3 tesla

The implications of changing the echo time of a gradient-echo echo planar imaging sequence applied to dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for perfusion imaging at 3T were investigated. Four echo times in the range of 21 to 45 ms were examined in a total of 17 patients who received a dose of 0.1 mmol/kg bodyweight Gadobutrol (Gadovist, 1.0 mmol/ml). As the primary optimization parameter, the concentration-to-noise ratio (SNRc) was selected as it takes effects of variations in baseline as well as in signal drop into account. In an analysis of gray matter, white matter and arterial regions of interest, SNRc showed the highest values for the shortest applied echo time in all cases. Maps of regional cerebral blood volume (rCBV) and blood flow (rCBF) were calculated using deconvolution based on singular value decomposition. The quality of rCBF and rCBV images was judged to be good or excellent in all cases, independent of the echo time. Calculated gray matter/white matter ratios of rCBF and rCBV displayed no significant dependence on the applied echo time. Considering the better SNRc and arterial signal saturation aspects, we found that the shortest investigated echo time was the superior one. We thus suggest that short echo times should be applied, taking technical limitations and clinical demands into consideration.     

Graded image segmentation of brain tissue in the presence of inhomogeneous radio frequency fields

Image segmentation is used increasingly to interpret MR spectroscopic data of the brain, using image contrast to identify gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF). T(1)- or T(2)-weighted images are typically used, but poor shimming, susceptibility effects, and small variations in B(1) and receptivity cause difficulties in tissue identification. Quantitative imaging of T(1) can reduce many of these difficulties but is still subject to complications when B(1) has large variations like those observed with the surface coils often used for spectroscopy. In this study, B(1) imaging was implemented to support quantitative imaging of T(1) with either a surface coil or a volume coil. The T(1) observed by this method is a continuous function across mixtures of WM/GM and GM/CSF, and this function was measured and used to convert the images of T(1) to maps of percent GM, WM, and CSF.     

Unbiased segmentation of diffusion-weighted magnetic resonance images of the brain using iterative clustering

Segmentation of diffusion-weighted echo-planar imaging (DW-EPI) is challenging because of concerns regarding spatial resolution and distortion. Methods commonly used require manual input and often need thresholding measures to segment white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). This may introduce operator bias and misclassification error. When comparing patients with a diffuse disease process-such as multiple sclerosis (MS)--with healthy controls, although information from all images may be biased due to disease effect, this is more so if the data set employed to perform segmentation is also used as a measured outcome for the study, for example, fractional anisotropy maps. Presented in this work is an unbiased method for segmenting DW-EPI data sets using the b=0 and single-shot inversion recovery EPI into WM, GM and CSF. The method employs an iterative clustering technique to account for partial volume effects and signal variation caused by radiofrequency inhomogeneity. The technique is evaluated with both real and synthetic brain data and results compared with statistical parametric mapping (SPM02). With synthetic brain data, where a gold standard of segmentation exists, the presented method showed less misclassification compared to SPM02. The unbiased method proposed may provide a more accurate methodology of segmentation in the analysis of DWI-EPI images in conditions such as MS.     

A technique for single-channel MR brain tissue segmentation: Application to a pediatric sample

A segmentation method is presented for gray matter, white matter, and cerebrospinal fluid (CSF) in thinsliced single-channel brain magnetic resonance (MR) scans. The method is based on probabilistic modeling of intensity distributions and on a region growing technique. Interrater and intrarater reliabilities for the method were high, and comparison with phantom studies and hand-traced results from an experienced rater indicated good validity. The method was designed to account for spatially dependent image intensity inhomogeneities. Segmentation of MR brain scans of 105 (56 male and 49 female) healthy children and adolescents showed that although the total brain volume was stable over age 4–18, white matter increased and gray matter decreased significantly. There were no sex differences in total gray and white matter growth after correction for total brain volume. White matter volume increased the most in superior and posterior regions and laterality effects were seen in hemisphere tissue volumes. These findings are consistent with other reports, and further validate the segmentation technique.     

Measurement of relative cerebral blood volume using BOLD contrast and mild hypoxic hypoxia

Relative cerebral blood volume (CBV) was estimated using a mild hypoxic challenge in humans, combined with BOLD contrast gradient-echo imaging at 3 T. Subjects breathed 16% inspired oxygen, eliciting mild arterial desaturation. The fractional BOLD signal change induced by mild hypoxia is expected to be proportional to CBV under conditions in which there are negligible changes in cerebral perfusion. By comparing the regional BOLD signal changes arising with the transition between normoxia and mild hypoxia, we calculated CBV ratios of 1.5±0.2 (mean±S.D.) for cortical gray matter to white matter and 1.0±0.3 for cortical gray matter to deep gray matter.     

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.     

Three dimension double inversion recovery gray matter imaging using compressed sensing

The double inversion recovery (DIR) imaging technique has various applications such as black blood magnetic resonance imaging and gray/white matter imaging. Recent clinical studies show the promise of DIR for high resolution three dimensional (3D) gray matter imaging. One drawback in this case however is the long data acquisition time needed to obtain the fully sampled 3D spatial frequency domain (k-space) data. In this paper, we propose a method to solve this problem using the compressed sensing (CS) algorithm with contourlet transform. The contourlet transform is an effective sparsifying transform especially for images with smooth contours. Therefore, we applied this algorithm to undersampled DIR images and compared with a CS algorithm using wavelet transform by evaluating the reconstruction performance of each algorithm for undersampled k-space data. The results show that the proposed CS algorithm achieves a more accurate reconstruction in terms of the mean structural similarity index and root mean square error than the CS algorithm using wavelet transform.     

Cortex-based independent component analysis of fMRI time series

The cerebral cortex is the main target of analysis in many functional magnetic resonance imaging (fMRI) studies. Since only about 20% of the voxels of a typical fMRI data set lie within the cortex, statistical analysis can be restricted to the subset of the voxels obtained after cortex segmentation. While such restriction does not influence conventional univariate statistical tests, it may have a substantial effect on the performance of multivariate methods.

Here, we describe a novel approach for data-driven analysis of single-subject fMRI time series that combines techniques for the segmentation and reconstruction of the cortical surface of the brain and the spatial independent component analysis (sICA) of the functional time courses (TCs). We use the mesh of the white matter/gray matter boundary, automatically reconstructed from high-spatial-resolution anatomical MR images, to limit the sICA decomposition of a coregistered functional time series to those voxels which are within a specified region with respect to the cortical sheet (cortex-based ICA, or cbICA). We illustrate our analysis method in the context of fMRI blocked and event-related experimental designs and in an fMRI experiment with perceptually ambiguous stimulation, in which an a priori specification of the stimulation protocol is not possible.

A comparison between cbICA and conventional hypothesis-driven statistical methods shows that cortical surface maps and component TCs blindly obtained with cbICA reliably reflect task-related spatiotemporal activation patterns. Furthermore, the advantages of using cbICA when the specification of a temporal model of the expected hemodynamic response is not straightforward are illustrated and discussed. A comparison between cbICA and anatomically unconstrained ICA reveals that — beside reducing computational demand — the cortex-based approach improves the fitting of the ICA model in the gray matter voxels, the separation of cortical components and the estimation of their TCs, particularly in the case of fMRI data sets with a complex spatiotemporal statistical structure.     

Human cranial CSF volumes measured by MRI: Sex and age influences

Accurate measurements of CSF volumes would assist in the diagnosis of several important neurological conditions. Using Magnetic Resonance Imaging (MRI) we have devised a method to measure both total intracranial CSF volume and ventricular volume. This initial study, in normal humans, provides an answer to two longstanding questions: first, do these volumes differ between the sexes; second, do both total and ventricular CSF volumes increase with normal aging? We found that the total cranial CSF volume and skull size of males were significantly greater than those of females, but that there was not a statistically significant difference between the ventricular volumes of the sexes. Total cranial CSF volume increased steeply with age in both sexes but although there was an increase in ventricular volume with age in males, no significant increase with age could be demonstrated in females.     

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).     

Atlas-based and DTI-guided quantification of human brain cerebral blood flow: Feasibility,quality assurance,spatial heterogeneity and age effects

Accurate and noninvasive quantification of regional cerebral blood perfusion (CBF) of the human brain tissue would advance the study of the complex interplay between human brain structure and function, in both health and disease. Despite the plethora of works on CBF in gray matter, a detailed quantitative white matter perfusion atlas has not been presented on healthy adults using the International Consortium for Brain Mapping atlases. In this study, we present a host of assurance measures such as temporal stability, spatial heterogeneity and age effects of regional and global CBF in selected deep, cortical gray matter and white matter tracts identified and quantified using diffusion tensor imaging (DTI). We utilized whole brain high-resolution DTI combined with arterial spin labeling to quantify regional CBF on 15 healthy adults aged 23.2–57.1 years. We present total brain and regional CBF, corresponding volume, mean diffusivity and fractional anisotropy spatial heterogeneity, and dependence on age as additional quality assurance measures to compare with published trends using both MRI and nuclear medicine methods. Total CBF showed a steady decrease with age in gray matter (r=?0.58; P= .03), whereas total CBF of white matter did not significantly change with age (r= 0.11; P= .7). This quantitative report offers a preliminary baseline of CBF, volume and DTI measurements for the design of future multicenter and clinical studies utilizing noninvasive perfusion and DT-MRI.     

Segmentation of the brain using direction-averaged signal of DWI images

Segmentation of brain tissue in diffusion MRI image space has some unique advantages. A novel segmentation method using the direction-averaged diffusion weighted imaging (DWI) signal is proposed. Two images can be obtained from the fitting of the direction-averaged DWI signal as a function of b-value: one with superior contrast between the gray matter and white matter; one with prominent CSF contrast. A pseudo T1 weighted image can be constructed and standard segmentation tools can be applied. The method was tested on the HCP dataset using SPM12, and showed good agreement with segmentation using the T1 weighted image with the same resolution. The Dice score was all greater than 0.88 for GM or WM with full DWI data and very stable against subsampling of the DWI data in number of diffusion directions, number of shells, and spatial resolution.     

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.     

Magnetization transfer of water T(2) relaxation components in human brain: implications for T(2)-based segmentation of spectroscopic volumes

Biexponential T(2) relaxation of the localized water signal can be used for segmentation of spectroscopic volumes. To assess the specificity of the components an iterative relaxation measurement of the localized water signal (STEAM, 12 echo times, geometric spacing from 30 ms to 2000 ms) was combined with magnetization transfer (MT) saturation (40 single lobe pulses, 12 ms duration, 1440 degrees nominal flip angle, 1 kHz offset, repeated every 30 ms). Voxels including CSF were examined in parietal cortex and periventricular parietal white matter (10 each), as well as 13 voxels in central white matter and 16 T(1)-hypointense non-enhancing multiple sclerosis lesions without CSF inclusion. Biexponential models (excluding myelin water) were fitted to the relaxation data. In periventricular VOIs the component of long T(2) (1736 +/- 168 ms) that is attributed to CSF was not affected by MT. In cortical VOIs this component had markedly shorter T(2)'s (961 +/- 239 ms) and showed both attenuation and prolongation with MT, indicating contributions from tissue. MS lesions and central WM showed a second tissue component of intermediate T(2) (160-410 ms). In white matter similar MT attenuation indicated strong exchange between the two tissue components, prohibiting segmentation. In MS lesions, however, markedly less MT of the intermediate component was found, which is consistent with decreased cellularity and exchange in a region that is large compared to diffusion motion.     

MR assessment of the brain maturation during the perinatal period: quantitative T2 MR study in premature newborns

The purpose of our study is to trace in vivo and during the perinatal period, the brain maturation process with exhaustive measures of the T2 relaxation time values. We also compared regional myelination progress with variations of the relaxation time values and of brain signal. T2 relaxation times were measured in 7 healthy premature newborns at the post-conceptional age of 37 weeks, using a Carr-Purcell-Meiboom-Gill sequence (echo time 60 to 150 ms), on a 2.35 Tesla Spectro-Imaging MR system. A total of 62 measures were defined for each subject within the brain stem, the basal ganglia and the hemispheric gray and white matter. The mean and standard deviation of the T2 values were calculated for each location. Regional T2 values changes and brain signal variations were studied. In comparison to the adult ones, the T2 relaxation time values of both gray and white matter were highly prolonged and a reversed ratio between gray and white matter was found. The maturational phenomena might be regionally correlated with a T2 value shortening. Significant T2 variations in the brainstem (p < 0.02), the mesencephalon (p < 0.05), the thalami (p < 0.01), the lentiform nuclei (p < 0.01) and the caudate nuclei (p < 0.02) were observed at an earlier time than they were visible on T2-weighted images. In the cerebral hemispheres, T2 values increased from the occipital white matter to parietal, temporal and frontal white matter (p < 0.05) and in the frontal and occipital areas from periventricular to subcortical white matter (p < 0.01). Maturational progress was earlier and better displayed with T2 measurements and T2 mapping. During the perinatal period, the measurements and analysis of T2 values revealed brain regional differences not discernible with T2-weighted images. It might be a more sensitive indicator for assessment of brain maturation.     

T1 and proton density at 7 T in patients with multiple sclerosis: an initial study

Magnetic resonance imaging of cortical lesions due to multiple sclerosis (MS) has been hampered by the lesions' small size and low contrast to adjacent, normal-appearing tissue. Knowing cortical lesion T1 and proton density (PD) would be highly beneficial for the process of developing and optimizing dedicated magnetic resonance (MR) sequences through computer modeling of MR tissue responses. Eight patients and seven healthy control subjects were scanned at 7 T using a series of inversion recovery turbo field echo scans with varying inversion times. Regions of interest were drawn in white matter, gray matter, cortical lesions, white matter lesions and cerebrospinal fluid. White matter and gray matter T1s were significantly higher in MS patients than in controls. Cortical and white matter lesion T1 and PD are also presented for the first time. The advantages of ultrahigh field MR imaging will be important for future investigations in MS research and sequence optimization for the detection of cortical lesions.     

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T(1)-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement.