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BACKGROUND AND PURPOSE: In 1948, Paul Yakovlev described an additional limbic circuit located basolateral to James Papez’s circuit (1937) and included orbitofrontal cortex, amygdala and dorsomedial nucleus of thalamus. This circuit is shown to be an important component of subcortical cognitive abilities. We aimed to demonstrate this circuit in a multiple sclerosis (MS) cohort, using diffusion tensor imaging (DTI) and evaluate its role in MS related cognitive impairment (CI). METHODS: We enrolled cognitively intact (n=10) and impaired (n=36) MS patients who underwent a comprehensive cognitive assessment; the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) and structural magnetic resonance imaging (MRI). Correlation analyses between volumetric and DTI derived values of the orbitofrontothalamic (OFT), amygdalothalamic tracts (ATT) and dorsomedial nucleus of thalamus and CI index derived from MACFIMS were computed after adjustment for age, education and lesion load. RESULTS: We observed a consistent trend between CI index and bilateral dorsomedial nucleus’ mean diffusivity (MD) (r=0.316; p: 0.02), left OFT FA (r:−0.302; p:0.02), MD (r=0.380; 0.006), and radial diffusivities (RD) (r=0.432; p:0.002), also with right ATT FA (r=−0.475; p:0.0006) and left ATT FA (r=−0.487; p:0.0005). After Bonferroni correction, correlations of left OFT RD, right and left ATT FA with CI were found to be significant. CONCLUSIONS: Our study provides in vivo DTI delineation of Yakovlev’s historical basolateral limbic circuit and establishes a role in MS related CI. These findings may potentially pave the way for future clinical studies using targeted invasive and non-invasive neurostimulation modalities for cognitive impairment in MS.

A comprehensive analysis of the effect of lesion in-painting on the estimation of cortical thickness using magnetic resonance imaging was performed on a large cohort of 918 relapsing-remitting multiple sclerosis patients who participated in a phase III multicenter clinical trial. An automatic lesion in-painting algorithm was developed and implemented. Cortical thickness was measured using the FreeSurfer pipeline with and without in-painting. The effect of in-painting was evaluated using FreeSurfer's paired analysis pipeline. Multivariate regression analysis was also performed with field strength and lesion load as additional factors. Overall, the estimated cortical thickness was different with in-painting than without. The effect of in-painting was observed to be region dependent, more significant in the left hemisphere compared to the right, was more prominent at 1.5 T relative to 3 T, and was greater at higher lesion volumes. Our results show that even for data acquired at 1.5 T in patients with high lesion load, the mean cortical thickness difference with and without in-painting is ∼2%. Based on these results, it appears that in-painting has only a small effect on the estimated regional and global cortical thickness. Hum Brain Mapp 36:3749-3760, 2015. © 2015 Wiley Periodicals, Inc.

Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology.

Several in vivo quantitative magnetic resonance imaging (qMRI) techniques have been proposed as surrogate measures to map iron content in the human brain. The majority of in vivo qMRI iron mapping methods utilized the age-dependent iron content data based on postmortem data. In this work we fused atlas-based human brain volumetry obtained on a large cohort of healthy adults using FreeSurfer with T2 relaxation time measurements. We provide a brain atlas-based T2 relaxation time map which was subsequently used along with published postmortem iron content data to obtain a map of iron content in subcortical and cortical gray matter. We have also investigated the sensitivity of the linear model relating transverse relaxation rate with published iron content to the number of regions used. Our work highlights the challenges encountered upon using the simple model along with postmortem data to infer iron content in several brain regions where postmortem iron data are scant (e.g. corpus callosum, amygdale).

BACKGROUND AND PURPOSE: High tissue contrast and short acquisition time are desirable when scanning patients. The purpose of this report is to describe the implementation of a new technique for generating high gray matter (GM) and white matter (WM) contrast in a short scan time, make a quantitative evaluation of the contrast efficiency, and explore its potential applications in neuroimaging. METHOD: A fully interleaved T1-weighted inversion recovery (T1IR) sequence with phase-sensitive reconstruction (PS-T1IR) is implemented. This sequence is compared with conventional T1-weighted spin-echo imaging (T1SE) and T1-weighted fluid-attenuated inversion recovery (T1FLAIR). The time efficiency and contrast enhancement have been quantitatively analyzed in normal volunteers. The performance of the sequence is evaluated in >30 patients with neurologic disorders. The sensitivity of PS-T1IR relative to T1SE in detecting gadolinium enhancements is also evaluated. RESULTS: PS-T1IR is more time-efficient than T1SE and generates better GM-WM contrast. It results in the best contrast-to-noise ratio (CNR) efficiency (1.16) compared with T1FLAIR (0.73) and T1SE (0.23). For a typical clinical protocol, PS-T1IR takes only 1:30 minutes versus 2:40 minutes for T1SE imaging for the whole brain coverage. Although gadolinium enhancements are detected with comparable sensitivity on both PS-T1IR and T1SE sequences, in certain instances, the latter sequence appears to be more sensitive in demonstrating gadolinium enhancements within WM. CONCLUSION: PS-T1IR has the highest CNR efficiency compared with T1FLAIR and T1SE. It is a very practical technique for neuroradiologic applications.

The empirical origin of random noise is described, its influence on DTI variables is illustrated by a review of numerical and in vivo studies supplemented by new simulations investigating high noise levels. A stochastic model of noise propagation is presented to structure noise impact in DTI. Finally, basics of voxelwise and spatial denoising procedures are presented. Recent denoising procedures are reviewed and consequences of the stochastic model for convenient denoising strategies are discussed.