The brief repeatable battery of neuropsychological tests (BRB-N) version a: update of Italian normative data from the Italian Neuroimaging Network Initiative (INNI).

BACKGROUND: Cognitive impairment is a common clinical manifestation in people with multiple sclerosis (PwMS) and significantly impacts patients' quality life. Cognitive assessment is crucial for treatment decisions and understanding disease progression. Several neuropsychological batteries are used in MS, including the Brief Repeatable Battery of Neuropsychological Tests (BRB-N), Minimal Assessment of Cognitive Function in MS (MACFIMS), and Brief International Cognitive Assessment for MS (BICAMS). However, normative data for BRB-N version A in Italy are outdated. OBJECTIVES: To revise and update normative data for the BRB-N version A in the Italian population. METHODS: From the Italian Neuroimaging Network Initiative (INNI) database, we retrospectively selected 342 healthy subjects (172 males and 170 females) evaluated at four Italian INNI-affiliated sites (Milan, Siena, Rome, Naples). The subjects underwent neuropsychological assessment using the BRB-N version A. Regression-based method relying on scaled scores was used to calculate demographic correction procedures. RESULTS: No significant differences were found in age, education, and sex distribution among the four sites (p ≥ 0.055). Regression analysis provided normative data to calculate demographically adjusted z-scores for each BRB-N version A test. DISCUSSION: This study provides updated normative data for the BRB-N version A in the Italian population. The use of a regression-based method and scaled scores ensures consistency with other neuropsychological batteries commonly used in Italy, namely MACFIMS and BICAMS. The availability of updated normative data increases reliability of neuropsychological assessment of cognitive function in Italian PwMS and other clinical populations using BRB-N version A, providing valuable insights for both clinical and research applications.

Cognitive phenotypes in multiple sclerosis: mapping the spectrum of impairment.

BACKGROUND: Available criteria for cognitive phenotypes in multiple sclerosis (MS) do not consider the severity of impairment. OBJECTIVES: To identify cognitive phenotypes with varying degrees of impairment in MS patients and describe their demographic, clinical and MRI characteristics. METHODS: Two hundred and forty-three MS patients and 158 healthy controls underwent neuropsychological tests to assess memory, attention, and executive function. For each domain, mild impairment was defined as performing 1.5 standard deviations below the normative mean on two tests, while the threshold for significant impairment was 2 standard deviations. Patients were classified into cognitive phenotypes based on severity of the impairment (mild/significant) and number of domains affected (one/more). RESULTS: Five cognitive phenotypes emerged: Preserved cognition (PC; 56%), Mild Single-Domain Impairment (MSD; 15%), Mild Multi-Domain Impairment (MMD; 9%), Significant Single-Domain Impairment (SSD; 12%), Significant Multi-Domain Impairment (SMD; 8%). Compared with PC, MSD patients were older, had longer disease duration (DD) and higher T2-hyperintense lesion volume (LV; all p ≤ 0.02); MMD patients were older, had longer DD, higher disability, higher T2 LV and lower thalamic volume (all p ≤ 0.01); SSD patients had longer DD and lower gray matter cortical volume, thalamic, caudate, putamen and accumbens volumes (all p ≤ 0.04); and SMD patients were older, had longer DD, higher disability and more extensive structural damage in all brain regions explored (all p ≤ 0.03), except white matter and amygdala volumes. CONCLUSIONS: We identified five cognitive phenotypes with graded levels of impairment. These phenotypes were characterized by distinct demographic, clinical and MRI features, indicating potential variations in the neural substrates of dysfunction throughout disease stages.

Functional correlates of cognitive abilities vary with age in pediatric multiple sclerosis.

BACKGROUND: Pediatric multiple sclerosis (PedMS) can hamper brain maturation. Aim of this study was to assess the neuropsychological profile of PedMS patients and their resting-state functional connectivity (RS FC). METHODS: We assessed intelligence quotient (IQ), executive speed, and language in 76 PedMS patients. On a 3.0T scanner RS FC of brain networks was estimated with a seed-based analysis (subset of 58 right-handed PedMS patients and 22 matched healthy controls). Comparisons were run between controls and PedMS (whole cohort and by age). RESULTS: Ninety-five% of patients had normal IQ. The highest rate of failure was observed in executive speed. PedMS showed reduced RS FC in all networks than controls, especially in the basal ganglia. In younger patients (<16-year-old, n = 32) reduced RS FC in the basal ganglia, language, and sensorimotor networks associated with poorer cognitive performance (p < 0.05; r range: 0.39; 0.56). Older patients (≥16-year-old, n = 26) showed increased RS FC in the basal ganglia, default-mode, sensorimotor, executive, and language networks, associated with poorer performance in executive speed and language abilities (p < 0.05; r range: -0.40; -0.59). In both groups, lower RS FC of the caudate nucleus associated with poorer executive speed. CONCLUSIONS: The effect of PedMS on RS FC is clinically relevant and differs according to patients' age.

Functional and structural brain MRI changes associated with cognitive worsening in multiple sclerosis: a 3-year longitudinal study.

BACKGROUND: Heterogeneous processes may contribute to cognitive impairment in multiple sclerosis (MS). OBJECTIVE: To apply a longitudinal multiparametric MRI approach to identify mechanisms associated with cognitive worsening in MS patients. METHODS: 3 T brain functional and structural MRI scans were acquired at baseline and after a median follow-up of 3.4 years in 35 MS patients and 22 healthy controls (HC). Associations between cognitive worsening (reliable change index score < - 1.25 at the Rao's battery) and longitudinal changes in regional T2-hyperintense white matter (WM) lesions, diffusion tensor microstructural WM damage, gray matter (GM) atrophy and resting state (RS) functional connectivity (FC) were explored. RESULTS: At follow-up, HC showed no clusters of significant microstructural WM damage progression, GM atrophy or changes in RS FC. At follow-up, 10 MS patients (29%) showed cognitive worsening. Compared to cognitively stable, cognitively worsened MS patients showed more severe GM atrophy of the right anterior cingulate cortex and bilateral supplementary motor area (p < 0.001). Cognitively worsened vs cognitively stable MS patients showed also decreased RS FC in the right hippocampus of the right working memory network and in the right insula of the default mode network. Increased RS FC in the left insula of the executive control network was found in the opposite comparison (p < 0.001). No significant regional accumulation of focal WM lesions nor microstructural WM abnormalities occurred in both patients' groups. CONCLUSIONS: GM atrophy progression in cognitively relevant brain regions combined with functional impoverishment in networks involved in cognitive functions may represent the substrates underlying cognitive worsening in MS.

Regional white matter and gray matter damage and cognitive performances in multiple sclerosis according to sex.

In this study, we investigated whether regional distribution of white matter (WM) lesions, normal-appearing [NA] WM microstructural abnormalities and gray matter (GM) atrophy may differently contribute to cognitive performance in multiple sclerosis (MS) patients according to sex. Using the same scanner, brain 3.0T MRI was acquired for 287 MS patients (females = 173; mean age = 42.1 [standard deviation, SD = 12.7] years; relapsing-remitting = 196, progressive = 91; median Expanded Disability Status Scale = 2.5 [interquartile range, IQR = 1.5-5.0]; median disease duration = 12.1 [IQR = 6.3-19.0] years; treatment: none = 70, first-line = 130, second-line = 87) and 172 healthy controls (HC) (females = 92; mean age = 39.3 [SD = 14.8] years). MS patients underwent also Rao's neuropsychological battery. Using voxel-wise analyses, we investigated in patients sex-related differences in the association of cognitive performances with WM lesions, NAWM fractional anisotropy (FA) and GM volumes (p < 0.01, family-wise error [FWE]). Sixty-six female (38%) and 48 male (42%) MS patients were cognitively impaired, with no significant between-group difference (p = 0.704). However, verbal memory performance was worse in males (p = 0.001), whereas verbal fluency performance was worse in females (p = 0.004). In both sexes, a higher T2-hyperintense lesion prevalence in cognitively-relevant WM tracts was significantly associated with worse cognitive performance (p ≤ 0.006), with stronger associations in females than males in global cognition (p ≤ 0.004). Compared to sex-matched HC, male and female MS patients had widespread lower NAWM FA and GM volume (p < 0.01). In both sexes, worse cognitive performance was associated with widespread reduced NAWM FA (p < 0.01), with stronger associations in females than males in global cognition and verbal memory (p ≤ 0.009). Worse cognitive performance was significantly associated with clusters of cortical GM atrophy in males (p ≤ 0.007) and mainly with deep GM atrophy in females (p ≤ 0.006). In this study, only limited differences in cognitive performances were found between male and female MS patients. A disconnection syndrome due to focal WM lesions and diffuse NAWM microstructural abnormalities seems to be more relevant in female MS patients to explain cognitive impairment.

Correspondence among gray matter atrophy and atlas-based neurotransmitter maps is clinically relevant in multiple sclerosis.

In multiple sclerosis (MS), gray matter (GM) atrophy progresses in a non-random manner, possibly in regions with a high distribution of specific neurotransmitters involved in several relevant central nervous system functions. We investigated the associations among regional GM atrophy, atlas-based neurotransmitter distributions and clinical manifestations in a large MS patients' group. Brain 3 T MRI scans, neurological examinations and neuropsychological evaluations were obtained from 286 MS patients and 172 healthy controls (HC). Spatial correlations among regional GM volume differences and atlas-based nuclear imaging-derived neurotransmitter maps, and their associations with MS clinical features were investigated using voxel-based morphometry and JuSpace toolbox. Compared to HC, MS patients showed widespread GM atrophy being spatially correlated with the majority of neurotransmitter maps (false discovery rate [FDR]-p ≤ 0.004). Patients with a disease duration ≥ 5 vs < 5 years had significant cortical, subcortical and cerebellar atrophy, being spatially correlated with a higher distribution of serotoninergic and dopaminergic receptors (FDR-p ≤ 0.03). Compared to mildly-disabled patients, those with Expanded Disability Status Scale ≥ 3.0 or ≥ 4.0 had significant cortical, subcortical and cerebellar atrophy being associated with serotonergic, dopaminergic, opioid and cholinergic maps (FDR-p ≤ 0.04). Cognitively impaired vs cognitively preserved patients had widespread GM atrophy being spatially associated with serotonergic, dopaminergic, noradrenergic, cholinergic and glutamatergic maps (FDR-p ≤ 0.04). Fatigued vs non-fatigued MS patients had significant cortical, subcortical and cerebellar atrophy, not associated with neurotransmitter maps. No significant association between GM atrophy and neurotransmitter maps was found for depression. Regional GM atrophy with specific neurotransmitter systems may explain part of MS clinical manifestations, including locomotor disability, cognitive impairment and fatigue.

Current perspectives on the diagnosis and management of fatigue in multiple sclerosis.

INTRODUCTION: Fatigue is a common and debilitating symptom among multiple sclerosis (MS) patients with a prevalence up to 81% and with a considerable impact on quality of life. However, its subjective nature makes it difficult to define and quantify in clinical practice. Research aimed at a more precise definition and knowledge of this construct is thus continuously growing. AREAS COVERED: This review summarizes the most relevant updates available on PubMed up to 1 July 2022 regarding: the assessment methods that aim to measure the concept of fatigue (as opposed to fatigability), the possible treatment pathways currently available to clinicians, interconnection with the pathophysiological substrates and with the common comorbidities of MS, such as depression and mood disorders. EXPERT OPINION: The in-depth study of fatigue can help to better understand its actual impact on MS patients and can stimulate clinicians toward a more valid approach, through a targeted analysis of this symptom. Considering fatigue from a multidimensional perspective allows the use of patient-tailored methods for its identification and subsequent treatment by different professional figures. Better identification of methods and treatment pathways would reduce the extremely negative impact of fatigue on MS patients' quality of life.

A Deep Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging.

OBJECTIVES: Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring of disease course in multiple sclerosis (MS). However, its prognostic value for predicting disease worsening is still being debated. The aim of this study was to propose a deep learning algorithm to predict disease worsening at 2 years of follow-up on a multicenter cohort of MS patients collected from the Italian Neuroimaging Network Initiative using baseline MRI, and compare it with 2 expert physicians. MATERIALS AND METHODS: For 373 MS patients, baseline T2-weighted and T1-weighted brain MRI scans, as well as baseline and 2-year clinical and cognitive assessments, were collected from the Italian Neuroimaging Network Initiative repository. A deep learning architecture based on convolutional neural networks was implemented to predict: (1) clinical worsening (Expanded Disability Status Scale [EDSS]-based model), (2) cognitive deterioration (Symbol Digit Modalities Test [SDMT]-based model), or (3) both (EDSS + SDMT-based model). The method was tested on an independent data set and compared with the performance of 2 expert physicians. RESULTS: For the test set, the convolutional neural network model showed high predictive accuracy for clinical (83.3%) and cognitive (67.7%) worsening, although the highest accuracy was reached when training the algorithm using both EDSS and SDMT information (85.7%). Artificial intelligence classification performance exceeded that of 2 expert physicians (70% of accuracy for the human raters). CONCLUSIONS: We developed a robust and accurate model for predicting clinical and cognitive worsening of MS patients after 2 years, based on conventional T2-weighted and T1-weighted brain MRI scans obtained at baseline. This algorithm may be valuable for supporting physicians in their clinical practice for the earlier identification of MS patients at risk of disease worsening.

Unraveling the substrates of cognitive impairment in multiple sclerosis: A multiparametric structural and functional magnetic resonance imaging study.

BACKGROUND: Cognitive impairment frequently affects multiple sclerosis (MS) patients. However, its neuroanatomical correlates still need to be fully explored. We investigated the contribution of structural and functional magnetic resonance imaging (MRI) abnormalities in explaining cognitive impairment in MS. METHODS: Brain dual-echo, diffusion tensor, 3D T1-weighted and resting-state (RS) MRI sequences were acquired from 276 MS patients and 102 healthy controls. Using random forest analysis, the contribution of regional white matter (WM) lesions, WM fractional anisotropy (FA) abnormalities, gray matter (GM) atrophy and RS functional connectivity (FC) alterations to cognitive impairment in MS patients was investigated. RESULTS: Eighty-four MS patients (30.4%) were cognitively impaired. The best MRI predictors of cognitive impairment (relative importance [%]) (out-of-bag area under the curve [AUC] = 0.795) were (a) WM lesions in the right superior longitudinal fasciculus (100%), left anterior thalamic radiation (93.4%), left posterior corona radiata (78.5%), left medial lemniscus (74.2%), left inferior longitudinal fasciculus (70.4%), left optic radiation (68.7%), right middle cerebellar peduncle (60.6%) and right optic radiation (53.5%); (b) decreased FA in the splenium of the corpus callosum (64.3%), left optic radiation (61.0%), body of the corpus callosum (51.9%) and fornix (50.9%); and (c) atrophy of the left precuneus (91.4%), right cerebellum crus I (84.4%), right caudate nucleus (78.6%), left thalamus (76.2%) and left supplementary motor area (59.8%). The relevance of these MRI measures in explaining cognitive impairment was confirmed in a cross-validation analysis (AUC =0.765). CONCLUSION: Structural damage in strategic WM and GM regions explains cognitive impairment in MS patients more than RS FC abnormalities.

Effect of cognitive reserve on structural and functional MRI measures in healthy subjects: a multiparametric assessment.

BACKGROUND: Cognitive reserve (CR) contributes to inter-individual variability of cognitive performance and to preserve cognitive functioning facing aging and brain damage. However, brain anatomical and functional substrates of CR still need to be fully explored in young healthy subjects (HS). By evaluating a relatively large cohort of young HS, we investigated the associations between CR and structural and functional magnetic resonance imaging (MRI) measures in early adulthood. METHODS: A global Cognitive Reserve Index (CRI), combining intelligence quotient, leisure activities and education, was measured from 77 HS and its brain anatomical and functional substrates were evaluated through a multiparametric MRI approach. Substrates of the three subdomains (cognitive/social/physical) of leisure activities were also explored. RESULTS: Higher global and subdomain CRIs were associated with higher gray matter volume of brain regions involved in motor and cognitive functions, such as the right (R) supplementary motor area, left (L) middle frontal gyrus and L cerebellum. No correlation with measures of white matter (WM) integrity was found. Higher global and subdomains CRIs were associated with lower resting-state functional connectivity (RS FC) of L postcentral gyrus and R insula in sensorimotor network, L postcentral gyrus in salience network and R cerebellum in the executive-control network. Moreover, several CRIs were also associated with higher RS FC of R cuneus in default-mode network. CONCLUSIONS: CR modulates structure and function of several brain motor and cognitive networks responsible for complex cognitive functioning already in young HS. CR could promote optimization of the recruitment of brain networks.