Giovanni Giulietti

Cognitive profile and brain morphological changes in obstructive sleep apnea

Obstructive sleep apnea (OSA) is accompanied by neurocognitive impairment, likely mediated by injury to various brain regions. We evaluated brain morphological changes in patients with OSA and their relationship to neuropsychological and oximetric data. Sixteen patients affected by moderate-severe OSA (age: 55.8±6.7 years, 13 males) and fourteen control subjects (age: 57.6±5.1 years, 9 males) underwent 3.0 Tesla brain magnetic resonance imaging (MRI) and neuropsychological testing evaluating short- and long-term memory, executive functions, language, attention, praxia and non-verbal learning. Volumetric segmentation of cortical and subcortical structures and voxel-based morphometry (VBM) were performed. Patients and controls differed significantly in Rey Auditory-Verbal Learning test (immediate and delayed recall), Stroop test and Digit span backward scores. Volumes of cortical gray matter (GM), right hippocampus, right and left caudate were smaller in patients compared to controls, with also brain parenchymal fraction (a normalized measure of cerebral atrophy) approaching statistical significance. Differences remained significant after controlling for comorbidities (hypertension, diabetes, smoking, hypercholesterolemia). VBM analysis showed regions of decreased GM volume in right and left hippocampus and within more lateral temporal areas in patients with OSA. Our findings indicate that the significant cognitive impairment seen in patients with moderate-severe OSA is associated with brain tissue damage in regions involved in several cognitive tasks. We conclude that OSA can increase brain susceptibility to the effects of aging and other clinical and pathological occurrences.

Quantitative magnetization transfer provides information complementary to grey matter atrophy in Alzheimer's disease brains

Preliminary studies, based on a region-of-interest approach, suggest that quantitative magnetization transfer (qMT), an extension of magnetization transfer imaging, provides complementary information to conventional magnetic resonance imaging (MRI) in the characterisation of Alzheimers disease (AD). The aim of this study was to extend these findings to the whole brain, using a voxel-wise approach. We recruited 19AD patients and 11 healthy subjects (HS). All subjects had an MRI acquisition at 3.0T including a T(1)-weighted volume, 12 MT-weighted volumes for qMT, and data for computing T(1) and B(1) maps. The T(1)-weighted volumes were processed to yield grey matter (GM) volumetric maps, while the other sequences were used to compute qMT parametric maps of the whole brain. qMT maps were warped to standard space and smoothed, and subsequently compared between groups. Of all the qMT parameters considered, only the forward exchange rate, RM(0)(B), showed significant group differences. These images were therefore retained for the multimodal statistical analysis, designed to locate brain regions of RM(0)(B) differences between AD and HS groups, adjusting for local GM atrophy. Widespread areas of reduced RM(0)(B) were found in AD patients, mainly located in the hippocampus, in the temporal lobe, in the posterior cingulate and in the parietal cortex. These results indicate that, among qMT parameters, RM(0)(B) is the most sensitive to AD pathology. This quantity is altered in the hippocampus of patients with AD (as found by previous works) but also in other brain areas, that PET studies have highlighted as involved with both, reduced glucose metabolism and amyloid β deposition. RM(0)(B) might reflect, through the measurement of the efficiency of MT exchange, some information with a specific pathological counterpart. Given previous evidence of a strict relationship between RM(0)(B) and intracellular pH, an intriguing speculation is that our findings might reflect metabolic changes related to mitochondrial dysfunction, which has been proposed as a contributor to neurodegeneration in AD.

Anatomical brain connectivity can assess cognitive dysfunction in multiple sclerosis

Background: Brain disconnection plays a major role in determining cognitive disabilities in multiple sclerosis (MS). We recently developed a novel diffusion-weighted magnetic resonance imaging (DW-MRI) tractography approach, namely anatomical connectivitity mapping (ACM), that quantifies structural brain connectivity. Objective: Use of ACM to assess structural connectivity modifications in MS brains and ascertain their relationship with the patients’ Paced-Auditory-Serial-Addition-Test (PASAT) scores. Methods: Relapsing–remitting MS (RRMS) patients (n = 25) and controls (n = 25) underwent MRI at 3T, including conventional images, T1-weighted volumes and DW-MRI. Volumetric scans were coregistered to fractional anisotropy (FA) images, to obtain parenchymal FA maps for both white and grey matter. We initiated probabilistic tractography from all parenchymal voxels, obtaining ACM maps by counting the number of streamlines passing through each voxel, then normalizing by the total number of streamlines initiated. The ACM maps were transformed into standard space, for statistical use. Results: RRMS patients had reduced grey matter volume and FA, consistent with previous literature. Also, we showed reduced ACM in the thalamus and in the head of the caudate nucleus, bilaterally. In our RRMS patients, ACM was associated with PASAT scores in the corpus callosum, right hippocampus and cerebellum. Conclusions: ACM opens a new perspective, clarifying the contribution of anatomical brain disconnection to clinical disabilities in MS.

Longitudinal Changes in Functional Brain Connectivity Predicts Conversion to Alzheimer’s Disease

This longitudinal study investigates the modifications in structure and function occurring to typical Alzheimers disease (AD) brains over a 2-year follow-up, from pre-dementia stages of disease, with the aim of identifying biomarkers of prognostic value. Thirty-one patients with amnestic mild cognitive impairment were recruited and followed-up with clinical, neuropsychological, and MRI assessments. Patients were retrospectively classified as AD Converters or Non-Converters, and the data compared between groups. Cross-sectional MRI data at baseline, assessing volume and functional connectivity abnormalities, confirmed previous findings, showing a more severe pattern of regional grey matter atrophy and default-mode network disconnection in Converters than in Non-Converters. Longitudinally, Converters showed more grey matter atrophy in the frontotemporal areas, accompanied by increased connectivity in the precuneus. Discriminant analysis revealed that functional connectivity of the precuneus within the default mode network at baseline is the parameter able to correctly classify patients in Converters and Non-Converters with high sensitivity, specificity, and accuracy.

Connectivity-based parcellation of the thalamus explains specific cognitive and behavioural symptoms in patients with bilateral thalamic infarct

A novel approach based on diffusion tractography was used here to characterise the cortico-thalamic connectivity in two patients, both presenting with an isolated bilateral infarct in the thalamus, but exhibiting partially different cognitive and behavioural profiles. Both patients (G.P. and R.F.) had a pervasive deficit in episodic memory, but only one of them (R.F.) suffered also from a dysexecutive syndrome. Both patients had an MRI scan at 3T, including a T1-weighted volume. Their lesions were manually segmented. T1-volumes were normalised to standard space, and the same transformations were applied to the lesion masks. Nineteen healthy controls underwent a diffusion-tensor imaging (DTI) scan. Their DTI data were normalised to standard space and averaged. An atlas of Brodmann areas was used to parcellate the prefrontal cortex. Probabilistic tractography was used to assess the probability of connection between each voxel of the thalamus and a set of prefrontal areas. The resulting map of corticothalamic connections was superimposed onto the patients’ lesion masks, to assess whether the location of the thalamic lesions in R.F. (but not in G. P.) implied connections with prefrontal areas involved in dysexecutive syndromes. In G.P., the lesion fell within areas of the thalamus poorly connected with prefrontal areas, showing only a modest probability of connection with the anterior cingulate cortex (ACC). Conversely, R.F.’s lesion fell within thalamic areas extensively connected with the ACC bilaterally, with the right dorsolateral prefrontal cortex, and with the left supplementary motor area. Despite a similar, bilateral involvement of the thalamus, the use of connectivity-based segmentation clarified that R.F.’s lesions only were located within nuclei highly connected with the prefrontal cortical areas, thus explaining the patient’s frontal syndrome. This study confirms that DTI tractography is a useful tool to examine in vivo the effect of focal lesions on interconnectivity brain patterns.

Characterization of the functional response in the human spinal cord: Impulse-response function and linearity

Functional magnetic resonance imaging (fMRI) has emerged during the last decade as the main non-invasive technique for the investigation of human brain function. More recently, fMRI was also proposed for functional studies of the human spinal cord, but with controversial results. In fact, the functional contrast is not well-characterized, and even its origin has been challenged. In the present work, we characterized the temporal features of the functional signal evoked in the human spinal cord by a motor task, studied with an approach based on time-locked averaging of functional time series of different durations. Based on the results here reported, we defined an impulse-response function (irf) able to explain the functional response for motor tasks in the interval of 15-42 s of duration, thus suggesting the linearity of the phenomenon in this interval. Conversely, with stimulation durations ranging between 3 and 9 s, the functional signal was not detectable, and was under the level predicted by a linear behavior, suggesting deviation from linearity during short stimulations. The impulse-response function appeared slower than in the brain, peaking at about 9 s after its beginning. The observed contrast was generally larger than in the brain, on the order of about 5.4% of baseline signal at 1.5 T. The findings further suggested that the physiological origin of T(2) weighted functional imaging is similar in the spinal cord and in the brain.

Characterizing axonal myelination within the healthy population: a tract-by-tract mapping of effects of age and gender on the fiber g-ratio

The g-ratio, equal to the ratio of the inner-to-outer diameter of a myelinated axon, is associated with the speed of conduction, and thus reflects axonal function and integrity. It is now possible to estimate an “aggregate” g-ratio in vivo using MRI. The aim of this study was to assess the variation of the MRI-derived fiber g-ratio in the brain of healthy individuals, and to characterize its variation across the lifespan. Thirty-eight healthy participants, aged between 20 and 76, were recruited. Whole-brain g-ratio maps were computed and analyzed voxel-wise. Median tract g-ratio values were also extracted. No significant effect of gender was found, whereas age was found to be significantly associated with the g-ratio within the white matter. The tract-specific analysis showed this relationship to follow a nearly-linear increase, although the slope appears to slow down slightly after the 6th decade of life. The most likely interpretation is a subtle but consistent reduction in myelin throughout adulthood, with the density of axons beginning to decrease between the 4th and 5th decade.

Brain tissue modifications induced by cholinergic therapy in Alzheimer's disease.

A previous preliminary investigation based on a novel MRI approach to map anatomical connectivity revealed areas of increased connectivity in Alzheimers disease (AD) but not in mild cognitive impairment patients. This prompted the hypothesis tested here, that these areas might reflect phenomena of brain plasticity driven by acetylcholinesterase inhibitors (AChEIs). Thirty‐eight patients with probable AD (19 under medication with AChEIs and 19 drug‐naïve) were recruited together with 11 healthy controls. All subjects had MRI scanning at 3T, including volumetric and diffusion‐weighted scans. Probabilistic tractography was used to initiate streamlines from all parenchymal voxels, and anatomical connectivity maps (ACMs) were obtained by counting, among the total number of streamlines initiated, the fraction passing through each brain voxel. After normalization into standard space, ACMs were used to test for between‐group comparisons, and for interactions between the exposure to AChEIs and global level of cognition. Patients with AD had reduced ACM values in the fornix, cingulum, and supramarginal gyri. The ACM value was strongly associated with the AChEI dosage‐x‐duration product in the anterior limb (non‐motor pathway) of the internal capsule. Tractography from this region identified the anterior thalamic radiation as the main white matter (WM) tract passing through it. The reduced connectivity in WM bundles connecting the hippocampi with the rest of the brain (fornix/cingulum) suggests a possible mechanism for the spread of AD pathology. An intriguing explanation for the interaction between AChEIs and ACM is related to the mechanisms of brain plasticity, partially driven by neurotrophic properties of acetylcholine replacement. Hum Brain Mapp 34:3158–3167, 2013.

fMRI study of motor cortex activity modulation in early Parkinson's disease

Parkinsons disease is a neurological disorder associated with the disfunction of dopaminergic pathways of the basal ganglia, mainly resulting in a progressive alteration in the execution of voluntary movements. We present a functional magnetic resonance imaging (fMRI) study on cortical activations during simple motor task performance, in six early-stage hemiparkinsonian patients and seven healthy volunteers. We acquired data in three sessions, during which subjects performed the task with right or left hand, or bimanually. We observed consistent bilateral activations in cingulate cortex and dorsolateral prefrontal cortex of Parkinsonian subjects during the execution of the task with the affected hand. In addition, patients showed both larger and stronger activations in motor cortex of the affected hemisphere with respect to the healthy hemisphere. Compared with the control group, patients showed a hyperactivation of the dorsolateral prefrontal cortex of the affected hemisphere. We concluded that a presymptomatic reorganization of the motor system is likely to occur in Parkinsons disease at earlier stages than previously hypothesized. Moreover, our results support fMRI as a sensitive technique for revealing the initial involvement of motor cortex areas at the debut of this degenerative disorder.

Semiautomated segmentation of the human spine based on echoplanar images

The number of functional magnetic resonance imaging (fMRI) studies performed on the human spinal cord (SC) has considerably increased in recent years. The lack of a validated processing pipeline is, however, a significant obstacle to the spread of SC fMRI. One component likely to be involved in any such pipeline is the process of SC masking, analogous to brain extraction in cerebral fMRI. In general, SC masking has been performed manually, with the incumbent costs of being very time consuming and operator dependent. To overcome these drawbacks, we have developed a tailored semiautomatic method for segmenting echoplanar images (EPI) of human spine that is able to identify the spinal canal and the SC. The method exploits both temporal and spatial features of the EPI series and was tested and optimized on EPI images of cervical spine acquired at 3 T. The dependence of algorithm performance on the degree of EPI image distortion was assessed by computing the displacement warping field that best matched the EPI to the corresponding high-resolution T(2) images. Segmentation accuracy was above 80%, a significant improvement over values obtained with similar approaches, but not exploiting temporal information. Geometric distortion was found to explain about 50% of the variance of algorithm classification efficiency.