A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood.

Cross-sectional analysis of longitudinal anatomical magnetic resonance imaging (MRI) data may be suboptimal as each dataset is analyzed independently. In this study, we evaluate how much variability can be reduced by analyzing structural volume changes in longitudinal data using longitudinal analysis. We propose a two-part pipeline that consists of longitudinal registration and longitudinal classification. The longitudinal registration step includes the creation of subject-specific linear and nonlinear templates that are then registered to a population template. The longitudinal classification step comprises a four-dimensional expectation-maximization algorithm, using a priori classes computed by averaging the tissue classes of all time points obtained cross-sectionally. To study the impact of these two steps, we apply the framework completely ("LL method": Longitudinal registration and Longitudinal classification) and partially ("LC method": Longitudinal registration and Cross-sectional classification) and compare these with a standard cross-sectional framework ("CC method": Cross-sectional registration and Cross-sectional classification). The three methods are applied to (1) a scan-rescan database to analyze reliability and (2) the NIH pediatric population to compare gray matter growth trajectories evaluated with a linear mixed model. The LL method, and the LC method to a lesser extent, significantly reduced the variability in the measurements in the scan-rescan study and gave the best-fitted gray matter growth model with the NIH pediatric MRI database. The results confirm that both steps of the longitudinal framework reduce variability and improve accuracy in comparison with the cross-sectional framework, with longitudinal classification yielding the greatest impact. Using the improved method to analyze longitudinal data, we study the growth trajectories of anatomical brain structures in childhood using the NIH pediatric MRI database. We report age- and gender-related growth trajectories of specific regions of the brain during childhood that could be used as a reference in studying the impact of neurological disorders on brain development.

Reduced head and brain size for age and disproportionately smaller thalami in child-onset MS.

OBJECTIVE: Whole brain and regional volume measurement methods were used to quantify white matter, gray matter, and deep gray matter structure volumes in a population of patients with pediatric-onset multiple sclerosis (MS). METHODS: Subjects included 38 patients (mean age 15.2 ± 2.4 years) and 33 age- and sex-matched healthy control (HC) participants. MRI measures included intracranial volume, normalized brain volume, normalized white and gray matter volume, and volumes of the thalamus, globus pallidus, putamen, and caudate. Because these volumes vary across age and sex in children, we normalized the volume measurements for MS and control groups by computing z scores using normative values obtained from healthy children enrolled in the MRI Study of Normal Brain Development. RESULTS: The intracranial volume z score was significantly lower in the patients with MS (-0.45 ± 1.16; mean ± SD) compared with the HC participants (+0.25 ± 0.98; p = 0.01). Patients with MS also demonstrated significant decreases in normalized brain volume z scores (-1.09 ± 1.49 vs -0.05 ± 1.22; p = 0.002). After correction for global brain volume, thalamic volumes in the MS population remained lower than those of HCs (-0.68 ± 1.72 vs 0.15 ± 1.35; p = 0.02), indicating an even greater loss of thalamic tissue relative to more global brain measures. Moderate correlations were found between T2-weighted lesion load and normalized thalamic volumes (r = -0.44, p < 0.01) and normalized brain volume (r = -0.47, p < 0.01) and between disease duration and normalized thalamic volume (r = -0.58, p < 0.001) and normalized brain volume (r = -0.46, p < 0.01). CONCLUSIONS: When compared with age- and sex-matched control subjects, the onset of MS during childhood is associated with a smaller overall head size, brain volume, and an even smaller thalamic volume.

MRI correlates of cognitive impairment in childhood-onset multiple sclerosis.

OBJECTIVE: Brain MRI measures were correlated with neuropsychological function in 35 pediatric-onset multiple sclerosis (MS) patients and 33 age- and sex-matched healthy controls. METHOD: Mean age of MS patients was 16.3 ± 2.3 years with average disease duration of 4.3 ± 3.1 years. Cortical gray matter, thalamic, and global brain volumes were calculated for all participants using a scaling factor computed using normalization of atrophy method to normalize total and regional brain volumes for head size. T1- and T2-weighted lesion volumes were calculated for MS patients. RESULTS: Cognitive impairment (CI) was identified in 29% of the MS cohort. Cognitive deficits predominantly involved attention and processing speed, expressive language, and visuomotor integration. Relative to controls, the MS group showed significantly lower thalamic volume (p < .001), total brain volume (p < .008), and gray matter volume (p < .015). Corpus callosum area and thalamic volume differentiated patients identified as having CI from those without CI (p < .05). Regression models controlling for disease duration and age indicated that thalamic volume accounted for significant incremental variance in predicting global IQ, processing speed, and expressive vocabulary (ΔR2 ranging from .43 to .60) and was the most robust MRI predictor of cognition relative to other MRI metrics. CONCLUSIONS: The robust association between cognitive function and reduced size of thalamus and global brain volume in pediatric-onset MS patients implicate neurodegenerative processes early in the disease course, and suggest that plasticity of an immature central nervous system is not sufficient to protect patients from the deleterious consequences of MS on cognitive neural networks. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

Regional brain atrophy in children with multiple sclerosis.

We used cross-sectional tensor-based morphometry to visualize reduced volume in the whole brains of pediatric patients with multiple sclerosis, relative to healthy controls. As a marker of local volume difference, we used the Jacobian determinant of the deformation field that maps each subject to a standard space. To properly assess abnormal differences in volume in this age group, it is necessary to account for the normal, age-related differences in brain volume. This was accomplished by computing normalized z-score Jacobian determinant values at each voxel to represent the local volume difference (in standard deviations) between an individual subject and an age- and sex-matched healthy normal population. Compared with healthy controls, pediatric patients with multiple sclerosis exhibited significantly reduced volumes within the thalamus and the splenium of the corpus callosum and significant expansions in the ventricles. While T2-weighted lesion volume was correlated with reduced splenium volume, no correlation was found between T2-weighted lesion volume and reduced thalamic volume. Reduced volumes of the optic pathways, including that of the optic tracts and optic radiations, correlated with disease duration. Our results suggest that focal inflammatory lesions may play an important role in tract degeneration, including transsynaptic degeneration.

Human brain myelination from birth to 4.5 years.

The myelination of white matter from birth through the first years of life has been studied qualitatively and it is well know the myelination occurs in a orderly and predictable manner, proceeding in a caudocranial direction, from deep to superficial and from posterior to anterior. Even if the myelination is a continuous process, it is useful to characterize myelination evolution in normal brain development in order to better study demyelinating diseases. The quantification of myelination has only been studied for neonates. The original contribution of this study is to develop a method to characterize and visualize the myelination pattern using MRI data from a group of normal subjects from birth to just over 4 years of age. The method includes brain extraction and tissue classification in addition to the analysis of T2 relaxation times to attempt to separate myelinated and unmyelinated white matter. The results agree previously published qualitative observations.

Detection of inter-hemispheric asymmetries of brain perfusion in SPECT.

Technetium-99m HMPAO and technetium-99m ECD single photon emission computed tomography (SPECT) imaging is commonly used to highlight brain regions with altered perfusion. It is particularly useful in the investigation of intractable partial epilepsy. However, SPECT suffers from poor spatial resolution that makes interpretation difficult. In this context, we propose an unsupervised voxel neighbourhood based method to assist the detection of significant functional inter-hemispheric asymmetries in brain SPECT, using anatomical information from MRI. For each MRI voxel, the anatomically homologous voxel in the contralateral hemisphere is identified. Both homologous voxel coordinates are then mapped into the SPECT volume using SPECT-MRI registration. Neighbourhoods are then defined around each SPECT voxel and compared to obtain a volume of inter-hemispheric differences. A volume including only the statistically significant inter-hemispheric differences is deduced from this volume using a non-parametric approach. The method was validated using realistic analytical simulated SPECT data including known asymmetries (in size and amplitude) as ground truth (gold standard). Detection performance was assessed using an ROC (receiver operating characteristic) approach based on the measures of the overlap between known and detected asymmetries. Validation with computer-simulated data demonstrates the ability to detect asymmetric zones with relatively small extension and amplitude. The registration of these detected functional asymmetries on the MRI enables good anatomical localization to be achieved.