Giuseppina Caiazzo

Widespread Microstructural White Matter Involvement in Amyotrophic Lateral Sclerosis: A Whole-Brain DTI Study

BACKGROUND AND PURPOSE: The extensive application of advanced MR imaging techniques to the study of ALS has undoubtedly improved our knowledge of disease pathophysiology, even if the actual spread of the neurodegenerative process throughout the central nervous system is not fully understood. The present study aimed to detect WM patterns of microstructural abnormalities to better investigate the pathologic process in ALS, within but also beyond CSTs, in a whole-brain analysis. MATERIALS AND METHODS: DTI was performed in 19 patients with ALS and 20 matched healthy controls, by using whole-brain TBSS and VOI analyses. RESULTS: We observed a significant decrease of FA in the body of CC of the ALS group (P < .05). At the VOI level, both FA decrease and RD increase in the body of CC significantly correlated with the UMN score (P = .003 and P = .02). Additionally, significant voxelwise positive correlations between FA and the ALSFRS-R were detected in the WM tracts underneath the left premotor cortex (P < .05). CONCLUSIONS: The correlations between reduction of FA and increase of RD in the body of CC with the UMN score indicate that the WM degeneration in the CC is strictly related to the ALS pyramidal impairment, while the correlation between FA and ALSFRS-R in the associative tracts underneath the left premotor cortex might reflect the progressive spread of the disease from the motor toward the extramotor areas.

Increased interictal visual network connectivity in patients with migraine with aura

Objective To evaluate the resting-state visual network functional connectivity in patients with migraine with aura and migraine without aura during the interictal period. Population and methods Using resting-state functional magnetic resonance imaging, the resting-state visual network integrity was investigated in 20 patients with migraine with aura, 20 age- and sex-matched patients with migraine without aura and 20 healthy controls. Voxel-based morphometry and diffusion tensor imaging were used to assess whether between-groups differences in functional connectivity were dependent on structural or microstructural changes. Results Resting-state functional magnetic resonance imaging data showed that patients with migraine with aura, compared to both patients with migraine without aura and healthy controls, had a significant increased functional connectivity in the right lingual gyrus within the resting-state visual network (p < 0.05, cluster-level corrected). This abnormal resting-state visual network functional connectivity was observed in the absence of structural or microstructural abnormalities and was not related to migraine severity. Conclusions Our imaging data revealed that patients with migraine with aura exhibit an altered resting-state visual network connectivity. These results support the hypothesis of an extrastriate cortex involvement, centred in the lingual gyrus, a brain region related to mechanisms underlying the initiation and propagation of the migraine aura. This resting-state functional magnetic resonance imaging finding may represent a functional biomarker that could differentiate patients experiencing the aura phenomenon from patients with migraine without aura, even between migraine attacks.

Abnormal Connectivity Within Executive Resting-State Network in Migraine With Aura.

To evaluate the executive control network connectivity integrity in patients with migraine with aura, in the interictal period, in comparison to patients with migraine without aura and healthy controls.

Motor and extramotor neurodegeneration in amyotrophic lateral sclerosis: A 3T high angular resolution diffusion imaging (HARDI) study

Abstract In amyotrophic lateral sclerosis (ALS), diffusion weighted magnetic resonance imaging (DW-MRI) has produced mounting evidence of a widespread white matter (WM) damage within motor and extramotor pathways. To provide novel information about the degenerative process in ALS, overcoming some of the limitations imposed by diffusion tensor imaging (DTI), we performed a high angular resolution diffusion imaging (HARDI) analysis of DW-MRI data. Generalized fractional anisotropy (GFA) was evaluated in 19 patients with ALS and 19 matched control subjects, and was correlated with clinical scores of disability, pyramidal impairment by upper motor neuron (UMN) score and frontal dysfunction by the Frontal Systems Behaviour (FrSBe) scale. Results demonstrated that ALS patients showed a significant decrease of GFA in the WM tracts underneath the left and right precentral gyri and the body of the corpus callosum (p < 0.05, corrected), where GFA was significantly related to UMN scores (p < 0.001, uncorrected); and in the left superior longitudinal fasciculus (p < 0.05, corrected), where GFA was significantly related to FrSBe scale scores (p < 0.01, uncorrected). In conclusion, this study revealed a pattern of motor and extramotor frontal diffusivity abnormalities (probably related to behavioural and cognitive dysfunctions) showing a spatial distribution similar to what was previously described in ALS − frontotemporal dementia continuum.

Fatigue in multiple sclerosis: The contribution of occult white matter damage

Background: A functional cortico-subcortical disconnection has been recognized in fatigued multiple sclerosis (MS) patients. Normal appearing white matter (NAWM) damage might contribute to the abovementioned disconnectivity. Objectives: To assess the relationship between fatigue and microstructural NAWM damage in relapsing-remitting (RR) MS. Methods: Sixty RRMS patients and 29 healthy controls (HC) underwent a magnetic resonance imaging (MRI) protocol including diffusion tensor imaging (DTI). Patients with a mean Fatigue Severity Scale (FSS) score ⩾ 4 were considered fatigued (fatigued MS (F-MS)). Tract-based spatial statistics were applied for voxel-wise analysis of DTI indices. A correlation analysis was performed between FSS score and DTI indices in the entire MS group. Results: Thirty MS patients were F-MS. Compared to HC, F-MS patients showed a more extensive NAWM damage than not fatigued MS (NF-MS) patients, with additional damage in the following tracts: frontal and occipital juxtacortical fibers, external capsule, uncinate fasciculus, forceps minor, superior longitudinal fasciculus, cingulum, and pons. No differences were found between F-MS and NF-MS patients. Fatigue severity correlated to DTI abnormalities of corona radiata, cingulum, corpus callosum, forceps minor, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, thalamus and anterior thalamic radiation, cerebral peduncle, and midbrain. Conclusions: Fatigue is associated to a widespread microstructural NAWM damage, particularly in associative tracts connected to frontal lobes.

Functional connectivity underpinnings of fatigue in "Drug-Naïve" patients with Parkinson's disease.

Fatigue is a common problem in PD either in the early or later stage of the disease. Using resting‐state functional MRI, we investigated the functional correlates of fatigue in a cohort of “drug‐naïve” patients with PD.

Functional interictal changes of pain processing in migraine with ictal cutaneous allodynia

Objective A prospective clinical imaging study has been conducted to investigate pain processing functional pathways during trigeminal heat stimulation (THS) in patients with migraine without aura experiencing ictal cutaneous allodynia (CA) (MwoA CA+). Methods Using whole-brain BOLD-fMRI, functional response to THS at three different intensities (41°, 51° and 53℃) was investigated interictally in 20 adult MwoA CA+ patients compared with 20 MwoA patients without ictal CA (MwoA CA−) and 20 healthy controls (HCs). Secondary analyses evaluated associations between BOLD signal change and clinical features of migraine. Results During moderate-noxious THS (51℃), we observed a significantly greater activation in (a) the anterior cingulate cortex in MwoA CA+ patients compared to HCs and (b) the middle frontal gyrus in MwoA CA+ patients compared to both MwoA CA− patients and HCs. Furthermore, during high-noxious THS (53℃) a significantly decreased activation in the secondary somatosensory cortices was observed in (a) MwoA CA− patients compared to both MwoA CA+ patients and HCs and (b) MwoA CA+ patients compared to HCs. CA severity was positively correlated with the secondary somatosensory cortices activation. Conclusions Our findings suggest that CA may be subtended by both a dysfunctional analgesic compensatory mechanism and an abnormal internal representation of pain in migraine patients.

Microstructural changes across different clinical milestones of disease in amyotrophic lateral sclerosis.

Neurodegenerative process in amyotrophic lateral sclerosis (ALS) has been proven to involve several cortical and subcortical brain regions within and beyond motor areas. However, how ALS pathology spreads progressively during disease evolution is still unknown. In this cross-sectional study we investigated 54 ALS patients, divided into 3 subsets according to the clinical stage, and 18 age and sex-matched healthy controls, by using tract-based spatial statistics (TBSS) diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) analyses. We aimed to identify white (WM) and gray matter (GM) patterns of disease distinctive of each clinical stage, corresponding to specific clinical milestones. ALS cases in stage 2A (i.e., at diagnosis) were characterized by GM and WM impairment of left motor and premotor cortices and brainstem at ponto-mesenchephalic junction. ALS patients in clinical stage 2B (with impairment of two functional regions) exhibited decreased fractional anisotropy (FA) (p<0.001, uncorrected) and increased mean (MD) and radial diffusivity (RD) (p<0.001, uncorrected) in the left cerebellar hemisphere and brainstem precerebellar nuclei, as well as in motor areas, while GM atrophy (p<0.001, uncorrected) was detected only in the left inferior frontal gyrus and right cuneus. Finally, ALS patients in stage 3 (with impairment of three functional regions) exhibited decreased FA and increased MD and RD (p<0.05, corrected) within WM underneath bilateral pre and postcentral gyri, corpus callosum midbody, long associative tracts and midbrain, while no significant clusters of GM atrophy were observed. Our findings reinforce the hypothesis that the neurodegenerative process propagates along the axonal pathways and develops beyond motor areas from early stages, involving progressively several frontotemporal regions and their afferents and efferents, while the detection of GM atrophy in earlier stages and its disappearance in later stages may be the result of reactive gliosis.

Intrinsic brain connectivity predicts impulse control disorders in patients with Parkinson's disease

Background: Impulse control disorders can be triggered by dopamine replacement therapies in patients with PD. Using resting‐state functional MRI, we investigated the intrinsic brain network connectivity at baseline in a cohort of drug‐naive PD patients who successively developed impulse control disorders over a 36‐month follow‐up period compared with patients who did not.

Multi-View Ensemble Classification of Brain Connectivity Images for Neurodegeneration Type Discrimination

Brain connectivity analyses using voxels as features are not robust enough for single-patient classification because of the inter-subject anatomical and functional variability. To construct more robust features, voxels can be aggregated into clusters that are maximally coherent across subjects. Moreover, combining multi-modal neuroimaging and multi-view data integration techniques allows generating multiple independent connectivity features for the same patient. Structural and functional connectivity features were extracted from multi-modal MRI images with a clustering technique, and used for the multi-view classification of different phenotypes of neurodegeneration by an ensemble learning method (random forest). Two different multi-view models (intermediate and late data integration) were trained on, and tested for the classification of, individual whole-brain default-mode network (DMN) and fractional anisotropy (FA) maps, from 41 amyotrophic lateral sclerosis (ALS) patients, 37 Parkinson’s disease (PD) patients and 43 healthy control (HC) subjects. Both multi-view data models exhibited ensemble classification accuracies significantly above chance. In ALS patients, multi-view models exhibited the best performances (intermediate: 82.9%, late: 80.5% correct classification) and were more discriminative than each single-view model. In PD patients and controls, multi-view models’ performances were lower (PD: 59.5%, 62.2%; HC: 56.8%, 59.1%) but higher than at least one single-view model. Training the models only on patients, produced more than 85% patients correctly discriminated as ALS or PD type and maximal performances for multi-view models. These results highlight the potentials of mining complementary information from the integration of multiple data views in the classification of connectivity patterns from multi-modal brain images in the study of neurodegenerative diseases.