Antonio Giorgio

Age-related changes in grey and white matter structure throughout adulthood.

Normal ageing is associated with gradual brain atrophy. Determining spatial and temporal patterns of change can help shed light on underlying mechanisms. Neuroimaging provides various measures of brain structure that can be used to assess such age-related change but studies to date have typically considered single imaging measures. Although there is consensus on the notion that brain structure deteriorates with age, evidence on the precise time course and spatial distribution of changes is mixed. We assessed grey matter (GM) and white matter (WM) structure in a group of 66 adults aged between 23 and 81. Multimodal imaging measures included voxel-based morphometry (VBM)-style analysis of GM and WM volume and diffusion tensor imaging (DTI) metrics of WM microstructure. We found widespread reductions in GM volume from middle age onwards but earlier reductions in GM were detected in frontal cortex. Widespread age-related deterioration in WM microstructure was detected from young adulthood onwards. WM decline was detected earlier and more sensitively using DTI-based measures of microstructure than using markers of WM volume derived from conventional T1-weighted imaging.

Changes in white matter microstructure during adolescence.

Postmortem histological studies have demonstrated that myelination in human brain white matter (WM) continues throughout adolescence and well into adulthood. We used in vivo diffusion-weighted magnetic resonance imaging to test for age-related WM changes in 42 adolescents and 20 young adults. Tract-Based Spatial Statistics (TBSS) analysis of the adolescent data identified widespread age-related increases in fractional anisotropy (FA) that were most significant in clusters including the body of the corpus callosum and right superior corona radiata. These changes were driven by changes in perpendicular, rather than parallel, diffusivity. These WM clusters were used as seeds for probabilistic tractography, allowing us to identify the regions as belonging to callosal, corticospinal, and prefrontal tracts. We also performed voxel-based morphometry-style analysis of conventional T1-weighted images to test for age-related changes in grey matter (GM). We identified a cluster including right middle frontal and precentral gyri that showed an age-related decrease in GM density through adolescence and connected with the tracts showing age-related WM FA increases. The GM density decrease was highly significantly correlated with the WM FA increase in the connected cluster. Age-related changes in FA were much less prominent in the young adult group, but we did find a significant age-related increase in FA in the right superior longitudinal fascicle, suggesting that structural development of this pathway continues into adulthood. Our results suggest that significant microstructural changes in WM continue throughout adolescence and are associated with corresponding age-related changes in cortical GM regions.

Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes

Objective: To assess the time course of brain atrophy and the difference across clinical subtypes in multiple sclerosis (MS). Methods: The percent brain volume change (PBVC) was computed on existing longitudinal (2 time points) T1-weighted MRI from untreated (trial and nontrial) patients with MS. Patients (n = 963) were classified as clinically isolated syndromes suggestive of MS (CIS, 16%), relapsing-remitting (RR, 60%), secondary progressive (SP, 15%), and primary progressive (9%) MS. The median length of follow-up was 14 months (range 12–68). Results: There was marked heterogeneity of the annualized PBVC (PBVC/y) across MS subtypes (p = 0.003), with higher PBVC/y in SP than in CIS (p = 0.003). However, this heterogeneity disappeared when data were corrected for the baseline normalized brain volume. When the MS population was divided into trial and nontrial subjects, the heterogeneity of PBVC/y across MS subtypes was present only in the second group, due to the higher PBVC/y values found in trial data in CIS (p = 0.01) and RR (p < 0.001). The estimation of the sample sizes required for demonstrating a reduction of brain atrophy in patients in a placebo-controlled trial showed that this was larger in patients with early MS than in those with the progressive forms of the disease. Conclusions: This first large study in untreated patients with multiple sclerosis (MS) with different disease subtypes shows that brain atrophy proceeds relentlessly throughout the course of MS, with a rate that seems largely independent of the MS subtype, when adjusting for baseline brain volume.

Brain atrophy and lesion load predict long term disability in multiple sclerosis

Objective To determine whether brain atrophy and lesion volumes predict subsequent 10 year clinical evolution in multiple sclerosis (MS). Design From eight MAGNIMS (MAGNetic resonance Imaging in MS) centres, we retrospectively included 261 MS patients with MR imaging at baseline and after 1–2 years, and Expanded Disability Status Scale (EDSS) scoring at baseline and after 10 years. Annualised whole brain atrophy, central brain atrophy rates and T2 lesion volumes were calculated. Patients were categorised by baseline diagnosis as primary progressive MS (n=77), clinically isolated syndromes (n=18), relapsing–remitting MS (n=97) and secondary progressive MS (n=69). Relapse onset patients were classified as minimally impaired (EDSS=0–3.5, n=111) or moderately impaired (EDSS=4–6, n=55) according to their baseline disability (and regardless of disease type). Linear regression models tested whether whole brain and central atrophy, lesion volumes at baseline, follow-up and lesion volume change predicted 10 year EDSS and MS Severity Scale scores. Results In the whole patient group, whole brain and central atrophy predicted EDSS at 10 years, corrected for imaging protocol, baseline EDSS and disease modifying treatment. The combined model with central atrophy and lesion volume change as MRI predictors predicted 10 year EDSS with R2=0.74 in the whole group and R2=0.72 in the relapse onset group. In subgroups, central atrophy was predictive in the minimally impaired relapse onset patients (R2=0.68), lesion volumes in moderately impaired relapse onset patients (R2=0.21) and whole brain atrophy in primary progressive MS (R2=0.34). Conclusions This large multicentre study points to the complementary predictive value of atrophy and lesion volumes for predicting long term disability in MS.

White Matter Development in Adolescence: Diffusion Tensor Imaging and Meta-Analytic Results

BACKGROUND In light of the evidence for brain white matter (WM) abnormalities in schizophrenia, study of normal WM maturation in adolescence may provide critical insights relevant to the neurodevelopment of the disorder. Voxel-wise diffusion tensor imaging (DTI) studies have consistently demonstrated increases in fractional anisotropy (FA), a putative measure of WM integrity, from childhood into adolescence. However, the WM tracts that show FA increases have been variable across studies. Here, we aimed to assess which WM tracts show the most pronounced changes across adolescence. METHODS DTI was performed in 78 healthy subjects aged 8-21 years, and voxel-wise analysis conducted using tract-based spatial statistics (TBSS). In addition, we performed the first meta-analysis of TBSS studies on WM development in adolescence. RESULTS In our sample, we observed bilateral increases in FA with age, which were most significant in the left superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and anterior thalamic radiation. These findings were confirmed by the meta-analysis, and FA increase in the bilateral SLF was the most consistent finding across studies. Moreover, in our sample, FA of the bilateral SLF showed a positive association with verbal working memory performance and partially mediated increases in verbal fluency as a function of increasing age. CONCLUSIONS These data highlight increasing connectivity in the SLF during adolescence. In light of evidence for compromised SLF integrity in high-risk and first-episode patients, these data suggest that abnormal maturation of the SLF during adolescence may be a key target in the neurodevelopment of schizophrenia.

Distinction of seropositive NMO spectrum disorder and MS brain lesion distribution

Objective: Neuromyelitis optica and its spectrum disorder (NMOSD) can present similarly to relapsing-remitting multiple sclerosis (RRMS). Using a quantitative lesion mapping approach, this research aimed to identify differences in MRI brain lesion distribution between aquaporin-4 antibody–positive NMOSD and RRMS, and to test their diagnostic potential. Methods: Clinical brain MRI sequences for 44 patients with aquaporin-4 antibody–positive NMOSD and 50 patients with RRMS were examined for the distribution and morphology of brain lesions. T2 lesion maps were created for each subject allowing the quantitative comparison of the 2 conditions with lesion probability and voxel-wise analysis. Results: Sixty-three percent of patients with NMOSD had brain lesions and of these 27% were diagnostic of multiple sclerosis. Patients with RRMS were significantly more likely to have lesions adjacent to the body of the lateral ventricle than patients with NMOSD. Direct comparison of the probability distributions and the morphologic attributes of the lesions in each group identified criteria of “at least 1 lesion adjacent to the body of the lateral ventricle and in the inferior temporal lobe; or the presence of a subcortical U-fiber lesion; or a Dawsons finger-type lesion,” which could distinguish patients with multiple sclerosis from those with NMOSD with 92% sensitivity, 96% specificity, 98% positive predictive value, and 86% negative predictive value. Conclusion: Careful inspection of the distribution and morphology of MRI brain lesions can distinguish RRMS and NMOSD.

Cognitive assessment and quantitative magnetic resonance metrics can help to identify benign multiple sclerosis.

Background: The definition of benign multiple sclerosis (B-MS) is still controversial. This mainly takes into account the subject’s motor ability, with little or no relevance to other important features such as cognition. Moreover, no paraclinical markers are currently available to reliably identify patients who will remain benign in the long term. Objectives: To assess, by using quantitative magnetic resonance (MR) metrics, differences in tissue damage between B-MS patients after dividing them into two groups on the basis of their cognitive performance. Methods: Forty-seven B-MS patients (Expanded Disability Status Scale score ≤3.0 and disease duration ≥15 years) underwent neuropsychological assessment through the Rao Brief Repeatable Battery and the Stroop Test. At that time, B-MS patients underwent conventional brain MR and magnetization transfer (MT) imaging. White matter lesion load, global and regional brain volumes, and MT ratio (MTr) in lesions and normal-appearing brain were measured. Quantitative MR measures were compared in cognitively impaired (CI-MS) and cognitively preserved (CP-MS) patients and in 24 demographically matched healthy controls. Test performance was correlated with MR changes in specific cortical regions. Results: Eleven patients were classified as CI-MS, and 36 were classified as CP-MS. Both T2-weighted and T1-weighted lesion loads were higher (p = 0.05 and 0.001) in CI-MS than in CP-MS patients. Furthermore, CI-MS patients were characterized by more pronounced decrease in neocortical volume (p = 0.005) and cortical MTr (p = 0.02) values than CP-MS patients. Finally, test performance correlated significantly with MR changes in relevant cortical regions. Conclusions: Cognitive assessment and quantitative magnetic resonance can help to reliably identify benign multiple sclerosis patients.

Association of MRI metrics and cognitive impairment in radiologically isolated syndromes

Objective: To evaluate cognitive changes in a cohort of radiologically isolated syndromes (RIS) suggestive of multiple sclerosis (MS) and to assess their relationship with quantitative magnetic resonance (MR) measures such as white matter (WM), lesion loads, and cerebral atrophy. Methods: We assessed the cognitive performance in a group of 29 subjects with RIS recruited from 5 Italian MS centers and in a group of 26 patients with relapsing-remitting MS (RRMS). A subgroup of 19 subjects with RIS, 26 patients with RRMS, and 21 healthy control (HC) subjects also underwent quantitative MR assessments, which included WM T1 and T2 lesion volumes and global and cortical brain volumes. Results: Cognitive impairment of the same profile as that of RRMS was found in 27.6% of our subjects with RIS. On MR scans, we found comparable levels of lesion loads and brain atrophy in subjects with RIS and well-established RRMS. In subjects with RIS, high T1 lesion volume (ρ = 0.526, p = 0.025) and low cortical volume (ρ = −0.481, p = 0.043) were associated with worse cognitive performance. Conclusions: These findings emphasize the importance of including accurate neuropsychological testing and quantitative MR metrics in subjects with RIS suggestive of MS. They can provide a better characterization of these asymptomatic subjects, potentially useful for diagnostic and therapeutic decisions.

Cognitive reserve and cortical atrophy in multiple sclerosis A longitudinal study

Objective: To test the cognitive reserve (CR) hypothesis in the model of multiple sclerosis (MS) by assessing the interactions among CR, brain atrophy, and cognitive efficiency in patients with relapsing-remitting MS. Methods: A Cognitive Reserve Index was calculated including education, premorbid leisure activities, and IQ. Brain atrophy was assessed through magnetic resonance quantitative parameters of normalized total brain volume and normalized cortical volume. Cognitive function was measured using Raos Brief Repeatable Battery. Results: Fifty-two patients with relapsing-remitting MS were evaluated at baseline and 35 of them were reassessed after a 1.6-year follow-up period. At baseline, higher CR predicted better performance on most of the Brief Repeatable Battery tests, independent of brain atrophy and clinical and demographic characteristics (p ≤ 0.021). An interaction between CRI and normalized cortical volume predicted better cognitive performance on tasks of verbal memory and attention/information processing speed (p < 0.005). However, at the follow-up examination, progressing cortical atrophy (β = 0.45; p = 0.008) and older age (β = −0.33; p = 0.044) were the only predictors of deteriorating cognitive performance. Conclusions: Our findings suggest that higher CR in individuals with MS may mediate between cognitive performance and brain pathology. CR-related compensation may, however, fail with progression of damage. The time window of opportunity for therapeutic approaches aimed at intellectual enhancement most likely lies in the earliest disease stages.

Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis

Objective To assess whether it is feasible to establish specific cut-off values able to discriminate ‘physiological’ or ‘pathological’ brain volume rates in patients with multiple sclerosis (MS). Methods The study was based on the analysis of longitudinal MRI data sets of patients with MS (n=206, 87% relapsing–remitting, 7% secondary progressive and 6% primary progressive) and healthy controls (HC; n=35). Brain atrophy rates were computed over a mean follow-up of 7.5 years (range 1–12) for patients with MS and 6.3 years (range 1–12.5) for HC with the SIENA software and expressed as annualised per cent brain volume change (PBVC/y). A weighted (on the follow-up length) receiver operating characteristic analysis and the area under the curve (AUC) were used for statistics. Results The weighted PBVC/y was −0.51±0.27% in patients with MS and −0.27±0.15% in HC (p<0.0001). There was a significant age-related difference in PBVC/y between HC older and younger than 35 years of age (p=0.02), but not in patients with MS (p=0.8). The cut-off of PBVC/y, as measured by SIENA that could maximise the accuracy in discriminating patients with MS from HC, was −0.37%, with 67% sensitivity and 80% specificity. According to the observed distribution, values of PBVC/y as measured by SIENA that could define a pathological range were above −0.52% with 95% specificity, above −0.46% with 90% specificity and above −0.40% with 80% specificity. Conclusions Our evidence-based criteria provide values able to discriminate the presence or absence of ‘pathological’ brain volume loss in MS with high specificity. Such results could be of great value in a clinical setting, particularly in assessing treatment efficacy in MS.