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BACKGROUND AND PURPOSE: To date, damage of the cerebral cortex neurons in ALS was investigated by using conventional MR imaging and proton MR spectroscopy. We explored the capability of MTI to map the microstructural changes in cerebral motor and extramotor cortices of patients with ALS. MATERIALS AND METHODS: Twenty patients with ALS and 17 age-matched healthy controls were enrolled. A high-resolution 3D SPGR sequence with and without MT saturation pulses was obtained on a 1.5T scanner to compute MTR values. Using the FMRIB Software Library tools, we automatically computed the MTR of the cerebral cortex GM in 48 regions of the entire cerebral cortex derived from the standard Harvard-Oxford cortical atlas. RESULTS: The MTR values were significantly lower in patients with ALS than in healthy controls in the primary motor cortex (precentral gyrus), nonprimary motor areas (superior and middle frontal gyri and superior parietal lobe), and some extramotor areas (frontal pole, planum temporale, and planum polare). No correlation was found between regional MTR values and the severity of clinical deficits or disease duration. CONCLUSIONS: MTI analysis can detect the distributed pattern of microstructural changes of the GM in the cerebral cortex of patients with ALS with involvement of both the motor and extramotor areas.

Diffusion tensor imaging (DTI) is highly sensitive to noise and improvement of radiofrequency coil technology represents a straightforward way for augmenting signal-to-noise ratio (SNR) performance in magnetic resonance imaging (MRI) scanners. The aim of this study was to characterize the dependence of DTI measurements of fractional anisotropy (FA) and mean diffusivity (MD) on the choice of head coil, comparing two head coils with different functional designs and sensitivities.Fourteen healthy subjects underwent DTI acquisitions at 1.5 T. Every subject was scanned twice, using a standard quadrature birdcage head coil (coil-A) and an eight-channel array head coil (coil-B). FA and MD maps, estimated using both the linear least squares (LLS) and nonlinear least squares (NLLS) methods, were nonlinearly normalized into a standard space. Then, volumetric regions of interest encompassing typical white and gray matter structures [splenium of the corpus callosum (SCC), internal capsule (IC), cerebral peduncles (CP), middle cerebellar peduncles (MCP), globus pallidus (GP), thalamus (TH), caudate (CA), and putamen (PU)] were analyzed. Significant differences and trends of variation in DTI measurements were assessed by the Wilcoxon test for paired samples with and without Bonferroni correction for multiple comparisons, respectively.The overall SNR of coil-B was 30% higher than that of coil-A. When comparing DTI measurements (coil-B versus coil-A), mean FA values (SCC, IC, and TH), mean MD values (IC, CP, GP, and TH), FA standard deviation (CP, MCP, GP, and CA), and MD standard deviation (IC, CP, TH, and PU) resulted decreased (significant difference, p(cor)0.05, or trend of variation, P(uncor)0.05) in several gray and white matter regions of the human brain. With the exception of CP, the results in terms of revealed significant difference or trend of variation were independent of the method (LLS and NLLS) used for estimating the diffusion tensor.In various gray and white matter structures, the eight-channel array head coil yielded more precise and accurate measurements of DTI derived indices compared to the standard quadrature birdcage head coil.

Background Post-traumatic cerebral infarction (PTCI) is common after traumatic brain injury (TBI). It is unclear what the occurrence of a PTCI is, how it impacts the long-term outcome, and whether it adds incremental prognostic value to established outcome predictors. Methods This was a prospective multicenter cohort study of moderate and severe TBI patients. The primary objective was to evaluate if PTCI was an independent risk factor for the 6-month outcome assessed with the Glasgow Outcome Scale (GOS). We also assessed the PTCI occurrence and if it adds incremental value to the International Mission for Prognosis and Clinical Trial design in TBI (IMPACT) core and extended models. Results We enrolled 143 patients, of whom 47 (32.9%) developed a PTCI. In the multiple ordered logistic regression, PTCI was retained in both the core and extended IMPACT models as an independent predictor of the GOS. The predictive performances increased significantly when PTCI was added to the IMPACT core model (AUC = 0.73, 95% C.I. 0.66–0.82; increased to AUC = 0.79, 95% CI 0.71–0.83, p = 0.0007) and extended model (AUC = 0.74, 95% C.I. 0.65–0.81 increased to AUC = 0.80, 95% C.I. 0.69–0.85; p = 0.00008). Patients with PTCI showed higher ICU mortality and 6-month mortality, whereas hospital mortality did not differ between the two groups. Conclusions PTCI is a common complication in patients suffering from a moderate or severe TBI and is an independent risk factor for long-term disability. The addition of PTCI to the IMPACT core and extended predictive models significantly increased their performance in predicting the GOS. Trial registration The present study was registered in ClinicalTrial.gov with the ID number NCT02430324.

The structural and functional data gathered with Magnetic Resonance Imaging (MRI) techniques about the brain cortical motor damage in Amyotrophic Lateral Sclerosis (ALS) are controversial. In fact some structural MRI studies showed foci of gray matter (GM) atrophy in the precentral gyrus, even in the early stage, while others did not. Most functional MRI (fMRI) studies in ALS reported hyperactivation of extra-primary motor cortices, while contradictory results were obtained on the activation of the primary motor cortex. We aimed to investigate the cortical motor circuitries in ALS patients by a combined structural and functional approach. Twenty patients with definite ALS and 16 healthy subjects underwent a structural examination with acquisition of a 3D T1-weighted sequence and fMRI examination during a maximal force handgrip task executed with the right-hand, the left-hand and with both hands simultaneously. The T1-weighted images were analyzed with Voxel-Based Morphometry (VBM) that showed several clusters of reduced cortical GM in ALS patients compared to controls including the pre and postcentral gyri, the superior, middle and inferior frontal gyri, the supplementary motor area, the superior and inferior parietal cortices and the temporal lobe, bilaterally but more extensive on the right side. In ALS patients a significant hypoactivation of the primary sensory motor cortex and frontal dorsal premotor areas as compared to controls was observed. The hypoactivated areas matched with foci of cortical atrophy demonstrated by VBM. The fMRI analysis also showed an enhanced activation in the ventral premotor frontal areas and in the parietal cortex pertaining to the fronto-parietal motor circuit which paralleled with disease progression rate and matched with cortical regions of atrophy. The hyperactivation of the fronto-parietal circuit was asymmetric and prevalent in the left hemisphere. VBM and fMRI identified structural and functional markers of an extended cortical damage within the motor circuit of ALS patients. The functional changes in non-primary motor cortices pertaining to fronto-parietal circuit suggest an over-recruitment of a pre-existing physiological sensory-motor network. However, the concomitant fronto-parietal cortical atrophy arises the possibility that such a hyper-activation reflects cortical hyper-excitability due to loss of inhibitory inter-neurons.

Monitoring devices enable control of the correct execution of a given task during functional magnetic resonance imaging (fMRI) acquisitions and analysis of behavioral features that can influence brain activation patterns. In this report, we describe and validate a low-cost device for monitoring hand tracing and writing tasks during fMRI. The subject holds a light-emitting pen whose light spot is recorded by a fixed camera aligned with the tracing plane. Pen trajectories are extracted by a blob detection algorithm through Laplacian of Gaussian filtering applied to the camera recordings. Following phantom and in vivo experiments which demonstrated MR compatibility, the device was applied to monitor the particular case of the task of continuous and self-paced writing of an “8” figure in 10 healthy subjects. They underwent fMRI examinations during the task under three conditions: spontaneous frequency and figure size, “low” frequency and “small” figure size. The task recordings were analyzed with a dedicated algorithm that computed both frequency and area of the figures “8” writing. The device was judged comfortable by all subjects. fMRI data analysis showed that task frequency influenced the activation within primary sensory motor and premotor frontal cortices, while figure size interfered with the activation in posterior parietal cortex. Both frequency and size parameters modulated activation in the inferior cerebellum. By monitoring writing-tasks executions, this device is expected to broaden the spectrum of applications of fMRI. Indeed, it could allow the investigation of patients suffering from neurological disorders affecting handwriting, such as apraxic disorders, cerebellar disorders, or parkinsonisms. © 2010 Wiley Periodicals, Inc. Concepts Magn Reson Part A 36A: 139–152, 2010.

Resting-state functional magnetic resonance imaging (RS-fMRI) is a technique used to investigate the spontaneous correlations of blood-oxygen-level-dependent signals across different regions of the brain. Using functional connectivity tools, it is possible to investigate a specific RS-fMRI network, referred to as "default-mode" (DM) network, that involves cortical regions deactivated in fMRI experiments with cognitive tasks. Previous works have reported a significant effect of aging on DM regions activity. Independent component analysis (ICA) is Often Used for generating spatially distributed DM Functional connectivity patterns front RS-fMRI data without the need for a reference region. This aspect and the relatively easy setup of an RS-fMRI experiment even in clinical trials have boosted the combined use of RS-fMRI and ICA-based DM analysis for noninvasive research of brain disorders, In this work, we considered different strategies for combining ICA results from individual-level and population-level analyses and used them to evaluate and predict the effect of aging on the DM component. Using RS-fMRI data from 20 normal subjects and a previously developed group-level ICA methodology, we generated group DM maps and showed that the overall ICA-DM connectivity is negatively correlated with age. A negative correlation of the ICA voxel weights with age existed in all DM regions at it variable degree. As an alternative approach, we generated a distributed DIM spatial template and evaluated the correlation of each individual DM component fit to this template with age. Using a "leave-one-out" procedure, we discuss the importance of removing the bias from the DM template-generation process.