Automatic quantification of multiple sclerosis lesion volume using stereotaxic space

Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network

Objective

The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network.

Methods

Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen–Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels K = 0.10‐0.36), asymmetry indexes of these graph metrics were derived.

Results

Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of K = 0.10–0.36. Between-group comparisons (female versus male) of asymmetry indexes revealed opposite directionality of asymmetries (leftward versus rightward) for global metrics of normalized clustering coefficient, normalized characteristic path length, and global efficiency (all p < 0.05). For the local graph metrics, larger rightward asymmetries of cingulate-superior parietal gyri for nodal efficiency in male compared to female, larger leftward asymmetry of temporal pole for degree centrality in female compared to male, and opposite directionality of interhemispheric asymmetry of rectal gyrus for degree centrality between female (rightward) and male (leftward) were shown (all p < 0.05).

Conclusion

Patterns of interhemispheric asymmetries for cingulate, superior parietal gyrus, temporal pole, and rectal gyrus are different between male and female for the similarities of the cortical thickness distribution with other brain regions. Accordingly, possible effect of gender-by-hemispheric interaction has to be considered in future studies of brain morphology and brain structural covariance networks.

Frontal-executive dysfunction affects dementia conversion in patients with amnestic mild cognitive impairment

Among mild cognitive impairment (MCI) patients, those with memory impairment (amnestic MCI, aMCI) are at a high risk of dementia. However, the precise cognitive domain, beside memory, that predicts dementia conversion is unclear. Therefore, we investigated the cognitive domain that predicts dementia conversion in a longitudinal aMCI cohort. We collected data of 482 aMCI patients who underwent neuropsychological tests and magnetic resonance imaging at baseline and were followed for at least 1 year. The patients were categorized according to number (1-4) and type of impaired cognitive domains (memory, language, visuospatial, and frontal-executive function). We evaluated dementia conversion risk in each group when compared to single-domain aMCI after controlling for age, education, diabetes and dyslipidemia. Baseline cortical thickness of each group was compared to that of 410 cognitively normal controls (NCs) after controlling for age, intracranial volume, diabetes and dyslipidemia. Compared to single-domain aMCI, aMCI patients with frontal-executive dysfunction at baseline had a higher risk of dementia conversion than aMCI patients with visuospatial or language dysfunction. Compared to NCs, aMCI patients with frontal-executive dysfunction had overall cortical thinning including frontal areas. Our findings suggest that aMCI patients with frontal-executive dysfunction have poor prognosis and,thus, should be considered for intervention therapy with a higher priority among aMCI patients.

Frontal atrophy as a marker for dementia conversion in Parkinson's disease with mild cognitive impairment

This study aimed to investigate the cortical neural correlates of dementia conversion in Parkinson's disease with mild cognitive impairment (PD-MCI). We classified 112 patients with drug-naïve early stage PD meeting criteria for PD-MCI into either PD with dementia (PDD) converters (n = 34) or nonconverters (n = 78), depending on whether they developed dementia within 4 years of PD diagnosis. Cortical thickness analyses were performed in 34 PDD converters and 34 matched nonconverters. Additionally, a linear discriminant analysis was performed to distinguish PDD converters from nonconverters using cortical thickness of the regions that differed between the two groups. The PDD converters had higher frequencies of multiple domain MCI and amnestic MCI with storage failure, and poorer cognitive performances on frontal/executive, memory, and language function domains than did the nonconverters. Cortical thinning extending from the posterior cortical area into the frontal region was observed in PDD converters relative to nonconverters. The discriminant analysis showed that the prediction model with two cortical thickness variables in the right medial superior frontal and left olfactory cortices optimally distinguished PDD converters from nonconverters. Our data suggest that cortical thinning in the frontal areas including the olfactory cortex is a marker for early dementia conversion in PD-MCI.

Brain structural changes after multi-strategic metamemory training in older adults with subjective memory complaints: A randomized controlled trial

BACKGROUND

Metamemory is the process of monitoring and controlling one's memory. Improving metamemory may reduce the memory problem in old age. We hypothesized that metamemory training (MMT) would improve cognition in older adults with subjective memory complaints and change the brain region related to metacognition.

METHOD

We recruited and randomized older adults to the multi-strategic memory training of 10 weekly 90-min sessions, based on the metamemory concept or usual care. Cognitive tests including the Elderly Verbal Learning Test, Simple Rey Figure Test, Digit Span, Spatial Span, Categorical Fluency, and the Boston Naming Test were done in 201 participants, together with magnetic resonance imaging (MRI) in 49 participants before and after training.

RESULTS

A total of 112 in the training group and 89 in the control group participated. The training group had a significant increase in long-term delayed free recall, categorical fluency, and the Boston Naming test. In MRI, the mean diffusivity of the bundles of axon tracts passing from the frontal lobe to the posterior end of the lateral sulcus decreased in the training group.

CONCLUSION

These results indicate that the MMT program has a positive impact on enhancing older people' cognitive performance. Improved white matter integrity in the anterior and posterior cerebrum and increased cortical thickness of prefrontal regions, which related to metacognition, possibly suggest that the effects of the MMT would be induced via the enhancement of cognitive control.

Multimodal imaging analyses in patients with genetic and sporadic forms of small vessel disease

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is thought to be a pure genetic form of subcortical vascular cognitive impairment (SVCI). The aim of this study was to compare white matter integrity and cortical thickness between typical CADASIL, a genetic form, and two sporadic forms of SVCI (with NOTCH3 and without NOTCH3 variants). We enrolled typical CADASIL patients (N = 11) and SVCI patients [with NOTCH3 variants (N = 15), without NOTCH3 variants (N = 101)]. To adjust the age difference, which reflects the known difference in clinical and radiologic courses between typical CADASIL patients and SVCI patients, we constructed a W-score of measurement for diffusion tensor image and cortical thickness. Typical CADASIL patients showed more frequent white matter hyperintensities in the bilateral posterior temporal region compared to SVCI patients (p < 0.001, uncorrected). We found that SVCI patients, regardless of the presence of NOTCH3 variants, showed significantly greater microstructural alterations (W-score, p < 0.05, FWE-corrected) and cortical thinning (W-score, p < 0.05, FDR-corrected) than typical CADASIL patients. In this study, typical CADASIL and SVCI showed distinct anatomic vulnerabilities in the cortical and subcortical structures. However, there was no difference between SVCI with NOTCH3 variants and SVCI without NOTCH3 variants.

Association of Nutritional Status with Cognitive Stage in the Elderly Korean Population: The Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease

Background and Purpose

Epidemiological studies have suggested the presence of strong correlations among diet, lifestyle, and dementia onset. However, these studies have unfortunately had major limitations due to their inability to fully control the various potential confounders affecting the nutritional status. The purpose of the current study was to determine the nutritional status of participants in the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) and to identify clinical risk factors for being at risk of malnutrition or being malnourished.

Methods

Baseline data from 212 participants [119 cognitively unimpaired (CU), 56 with mild cognitive impairment (MCI), and 37 with dementia] included in the KBASE database were analyzed. All participants underwent a comprehensive cognitive test and MRI at baseline. The presence of malnutrition at baseline was measured by the Mini Nutritional Assessment score. We examined the cross-sectional relationships of clinical findings with nutritional status using multiple logistic regression applied to variables for which p<0.2 in the univariate analysis. Differences in cortical thickness according to the nutritional status were also investigated.

Results

After adjustment for demographic, nutritional, and neuropsychological factors, participants with dementia had a significantly higher odds ratio (OR) for being at risk of malnutrition or being malnourished than CU participants [OR=5.98, 95% CI=1.20–32.97] whereas participants with MCI did not (OR=0.62, 95% CI=0.20–1.83). Cortical thinning in the at-risk/malnutrition group was observed in the left temporal area.

Conclusions

Dementia was found to be an independent predictor for the risk of malnutrition compared with CU participants. Our findings further suggest that cortical thinning in left temporal regions is related to the nutritional status.

The cholinergic contribution to the resting-state functional network in non-demented Parkinson's disease

The cholinergic system arising from the basal forebrain plays an important role in cognitive performance in Parkinson's disease (PD). Here, we analyzed cholinergic status-dependent cortical and subcortical resting-state functional connectivity in PD. A total of 61 drug-naïve PD patients were divided into tertiles based on normalized substantia innominata (SI) volumes. We compared the resting-state network from seed region of interest in the caudate, posterior cingulate cortex (PCC), and SI between the lowest (PD-L) and highest tertile (PD-H) groups. Correlation analysis of the functional networks was also performed in all subjects. The functional network analysis showed that PD-L subjects displayed decreased striato-cortical functional connectivity compared with PD-H subjects. Selecting the PCC as a seed, the PD-L patients displayed decreased functional connectivity compared to PD-H patients. Meanwhile, PD-L subjects had significantly increased cortical functional connectivity with the SI compared with PD-H subjects. Correlation analysis revealed that SI volume had a positive correlation with functional connectivity from the right caudate and PCC. The present study demonstrated that PD patients exhibited unique functional connectivity from the caudate and the PCC that may be closely associated with cholinergic status, suggesting an important role for the cholinergic system in PD-associated cognition.

Protective effects of APOE e2 against disease progression in subcortical vascular mild cognitive impairment patients: A three-year longitudinal study

Although the association between apolipoprotein E (APOE) genotype and disease progression is well characterized in patients with Alzheimer's disease, such a relationship is unknown in patients with subcortical vascular cognitive impairment. We evaluated whether APOE genotype is associated with disease progression in subcortical vascular mild cognitive impairment (svMCI) patients. We prospectively recruited 72 svMCI patients (19 APOE4 carriers, 42 APOE3 homozygotes, and 11 APOE2 carriers). Patients were annually followed-up with brain MRI and neuropsychological tests for three years and underwent a second Pittsburgh compound B (PiB)-PET at a mean interval of 32.3 months. Amyloid-ß burden was quantified by PiB standardized uptake value ratio (SUVR), and the amount of small vessel disease was quantified by number of lacune and small vessel disease score on MRI. We also measured cortical thickness. During the three years of follow-up, compared to the APOE3 homozygotes, there was less increase in PiB SUVR among APOE2 carriers (p = 0.023), while the APOE genotype did not show significant effects on small vessel disease progression. APOE2 carriers also showed less cortical thinning (p = 0.023) and a slower rate of cognitive decline (p = 0.009) compared to those with APOE3 homozygotes. Our findings suggest that, in svMCI patients, APOE2 has protective effects against amyloid-ß accumulation, cortical thinning, and cognitive decline.

Functional organization of the human posterior cingulate cortex, revealed by multiple connectivity-based parcellation methods

Based on cytoarchitecture, the posterior cingulate cortex (PCC) is thought to be comprised of two distinct functional subregions: the dorsal and ventral PCC (dPCC and vPCC). However, functional subregions do not completely match anatomical boundaries in the human brain. To understand the relationship between the functional organization of regions and anatomical features, it is necessary to apply parcellation algorithms based on functional properties. We therefore defined functionally informed subregions in the human PCC by parcellation of regions with similar patterns of functional connectivity in the resting brain. We used various patterns of functional connectivity, namely local, whole-brain and diffuse functional connections of the PCC, and various clustering methods, namely hierarchical, spectral, and k-means clustering to investigate the subregions of the PCC. Overall, the approximate anatomical boundaries and predicted functional regions were highly overlapped to each other. Using hierarchical clustering, the PCC could be clearly separated into two anatomical subregions, namely the dPCC and vPCC, and further divided into four subregions segregated by local functional connectivity patterns. We show that the PCC could be separated into two (dPCC and vPCC) or four subregions based on local functional connections and hierarchical clustering, and that subregions of PCC display differential global functional connectivity, particularly along the dorsal-ventral axis. These results suggest that differences in functional connectivity between dPCC and vPCC may be due to differences in local connectivity between these functionally hierarchical subregions of the PCC. Hum Brain Mapp 38:2808-2818, 2017. © 2017 Wiley Periodicals, Inc.

Impaired growth of the cerebellum in pediatric-onset acquired CNS demyelinating disease

Background:

Acquired demyelinating syndromes (ADS) have the potential to negatively impact cerebellar growth, given the proclivity for infratentorial lesions in pediatric-onset multiple sclerosis (MS) and ADS.

Objective:

To investigate cerebellar growth longitudinally in pediatric ADS.

Methods:

Cerebellar volumes from 472 magnetic resonance imaging (MRI) scans of 98 patients with monophasic ADS (monoADS), monophasic acute disseminated encephalomyelitis (ADEM), and MS (49 girls; mean age: 11.4 years at first scan, mean follow-up: 3.1 years) imaged serially from onset and 897 MRI scans of 418 healthy children (223 girls, mean age: 11.3 years, mean follow-up: 2.9 years) were segmented automatically, analyzed with mixed-effect models, and compared with cerebral volume.

Results:

Cerebellar developmental trajectories followed a U-shaped curve, showing larger volumes in boys ( p < 0.001). Cerebellar volumes in all three patient groups failed to reach age-expected trajectories, leading to significantly smaller volumes, notably in the posterior lobes. Cerebellar volume reductions were of a similar magnitude to cerebral volume reductions. Cerebellar white matter volume declined in MS and ADEM patients over time, while in monoADS patients it remained similar to controls. Cerebellar volumes did not correlate either with lesion volumes at onset or with physical disability.

Conclusion:

MonoADS, ADEM, and MS in childhood lead to impaired age-expected growth of the cerebellum.

Multicenter, randomized, placebo-controlled, double-blind clinical trial of escitalopram on the progression-delaying effects in Alzheimer's disease

OBJECTIVES

A series of preclinical studies have suggested that selective serotonin reuptake inhibitor antidepressants not only stimulate neurogenesis but also have neuroprotective effects. The present study primarily aimed to investigate whether escitalopram would decelerate the brain atrophy of patients with mild-to-moderate Alzheimer's disease (AD). We also assessed the effects of escitalopram on the cognitive function and neuropsychiatric symptoms of these participants.

METHODS

Seventy-four probable AD patients without major depression were recruited from four dementia clinics of university hospitals and randomly assigned in a 1:1 ratio. Each group received 20 mg/day of escitalopram or placebo for 52 weeks. The primary outcome measures were the change rates of hippocampal and whole brain volume on magnetic resonance imaging for 52 weeks. The Alzheimer's Disease Assessment Scale-cognitive subscale, Mini-Mental State Examination, Neuropsychiatric Inventory, and Cornell Scale for Depression in Dementia (CSDD) were also applied.

RESULTS

We did not find any significant differences in the changes of hippocampal or whole brain volume between the groups. Escitalopram showed significant beneficial effects on the CSDD score at 28 weeks compared with placebo (t = -2.17, df = 50.42, p = 0.035), but this finding did not persist throughout the study.

CONCLUSION

The findings of the present study do not support the role of escitalopram as a progression-delaying treatment for AD. However, the negative results of the present trial should be interpreted cautiously because of the relatively small sample size. Further large-scale escitalopram trials targeting the earlier stages of AD, even prodromal AD, are still needed. Copyright © 2015 John Wiley & Sons, Ltd.

Albuminuria, Cerebrovascular Disease and Cortical Atrophy: among Cognitively Normal Elderly Individuals

We tested the hypothesis that decreased glomerular filtration rate and albuminuria have different roles in brain structure alterations. We enrolled 1,215 cognitively normal individuals, all of whom underwent high-resolution T1-weighted volumetric magnetic resonance imaging scans. The cerebral small vessel disease burdens were assessed with white matter hyperintensities (WMH), lacunes, and microbleeds. Subjects were considered to have an abnormally elevated urine albumin creatinine ratio if the value was ≥17 mg/g for men and ≥25 mg/g for women. Albuminuria, but not estimated glomerular filtration rate (eGFR), was associated with increased WMH burdens (p = 0.002). The data was analyzed after adjusting for age, sex, education, history of hypertension, diabetes mellitus, hyperlipidemia, ischemic heart disease, stroke, total cholesterol level, body mass index, status of smoking and alcohol drinking, and intracranial volume. Albuminuria was also associated with cortical thinning, predominantly in the frontal and occipital regions (both p < 0.01) in multiple linear regression analysis. However, eGFR was not associated with cortical thickness. Furthermore, path analysis for cortical thickness showed that albuminuria was associated with frontal thinning partially mediated by WMH burdens. The assessment of albuminuria is needed to improve our ability to identify individuals with high risk for cognitive impairments, and further institute appropriate preventive measures.

Decreased hemoglobin levels, cerebral small-vessel disease, and cortical atrophy: among cognitively normal elderly women and men

BACKGROUND

Decreased hemoglobin levels increase the risk of developing dementia among the elderly. However, the underlying mechanisms that link decreased hemoglobin levels to incident dementia still remain unclear, possibly due to the fact that few studies have reported on the relationship between low hemoglobin levels and neuroimaging markers. We, therefore, investigated the relationships between decreased hemoglobin levels, cerebral small-vessel disease (CSVD), and cortical atrophy in cognitively healthy women and men.

METHODS

Cognitively normal women (n = 1,022) and men (n = 1,018) who underwent medical check-ups and magnetic resonance imaging (MRI) were enrolled at a health promotion center. We measured hemoglobin levels, white matter hyperintensities (WMH) scales, lacunes, and microbleeds. Cortical thickness was automatically measured using surface based methods. Multivariate regression analyses were performed after controlling for possible confounders.

RESULTS

Decreased hemoglobin levels were not associated with the presence of WMH, lacunes, or microbleeds in women and men. Among women, decreased hemoglobin levels were associated with decreased cortical thickness in the frontal (Estimates, 95% confidence interval, -0.007, (-0.013, -0.001)), temporal (-0.010, (-0.018, -0.002)), parietal (-0.009, (-0.015, -0.003)), and occipital regions (-0.011, (-0.019, -0.003)). Among men, however, no associations were observed between hemoglobin levels and cortical thickness.

CONCLUSION

Our findings suggested that decreased hemoglobin levels affected cortical atrophy, but not increased CSVD, among women, although the association is modest. Given the paucity of modifiable risk factors for age-related cognitive decline, our results have important public health implications.

The neural correlates of motor intentional disorders in patients with subcortical vascular cognitive impairment

Subcortical vascular cognitive impairment (SVCI) refers to cognitive impairment associated with small vessel disease. Motor intentional disorders (MID) have been reported in patients with SVCI. However, there are no studies exploring the neuroanatomical regions related to MID in SVCI patients. The aim of this study, therefore, was to investigate the neural correlates of MID in SVCI patients. Thirty-one patients with SVCI as well as 10 healthy match control participants were included. A "Pinch-Grip" apparatus was used to quantify the force control capabilities of the index finger in four different movement phases including initiation, development, maintenance, and termination. All participants underwent magnetic resonance imaging (MRI). Topographical cortical areas and white matter tracts correlated with the performances of the four different movement phases were assessed by the surface-based morphometry and tract-based spatial statistics analyses. Poorer performance in the maintenance task was related to cortical thinning in bilateral dorsolateral prefrontal, orbitofrontal and parietal cortices, while poorer performance in the termination task was associated with the disruption of fronto-parietal cortical areas as well as the white matter tracts including splenium and association fibers such as superior longitudinal fasciculus. Our study demonstrates that cortical areas and underlying white matter tracts associated with fronto-parietal attentional system play an important role in motor impersistence and perseveration in SVCI patients.

Impact of smoking on neurodegeneration and cerebrovascular disease markers in cognitively normal men

BACKGROUND AND PURPOSE

Smoking is a major risk factor for cognitive decline and dementia. However, the exact pathobiology of smoking remains unknown. The effects of smoking on cortical thickness as a biomarker of neurodegeneration or white matter hyperintensities and lacunes as biomarkers of cerebrovascular burden were concurrently evaluated.

METHODS

Our study included 977 cognitively normal men who visited a health promotion centre and underwent medical check-ups, including 3.0 T magnetic resonance imaging. Participants were categorized into never smoker, past smoker or current smoker groups and pack-years and the years of smoking cessation were used as continuous variables.

RESULTS

The current smoker group exhibited cortical thinning in frontal and temporo-parietal regions compared with the never smoker group. These effects were particularly prominent in smokers with a high cumulative exposure to smoking in the current smoker group. However, there was no association between smoking and the severity of white matter hyperintensity or number of lacunes.

CONCLUSION

Our findings indicate that smoking might impact on neurodegeneration rather than cerebrovascular burdens in cognitively normal men, suggesting that smoking might be an important modifiable risk factor for the development of Alzheimer's disease.

Patterns of Neuropsychological Profile and Cortical Thinning in Parkinson's Disease with Punding

BACKGROUND

Punding, one of dopamine replacement treatment related complications, refers to aimless and stereotyped behaviors. To identify possible neural correlates of punding behavior in patients with Parkinson's disease (PD), we investigated the patterns of cognitive profiles and cortical thinning.

METHODS

Of the 186 subjects with PD screened during the study period, we prospectively enrolled 10 PD patients with punding and 43 without punding on the basis of a structured interview. We performed comprehensive neuropsychological tests and voxel-based and regions-of-interest (ROIs)-based cortical thickness analysis between PD patients with and without punding.

RESULTS

The prevalence of punding in patients with PD was 5.4%. Punding behaviors were closely related to previous occupations or hobbies and showed a temporal relationship to changes of levodopa-equivalent dose (LED). Significant predisposing factors were a long duration of PD and intake of medications of PD, high total daily LED, dyskinesia, and impulse control disorder. Punding severity was correlated with LED (p = 0.029). The neurocognitive assessment revealed that PD patients with punding showed more severe cognitive deficits in the color Stroop task than did those without punding (p = 0.022). Voxel-based analysis showed that PD-punders had significant cortical thinning in the dorsolateral prefrontal area relative to controls. Additionally, ROI-based analysis revealed that cortical thinning in PD-punders relative to PD-nonpunders was localized in the prefrontal cortices, extending into orbitofrontal area.

CONCLUSIONS

We demonstrated that PD patients with punding performed poorly on cognitive tasks in frontal executive functions and showed severe cortical thinning in the dorsolateral prefrontal and orbitofrontal areas. These findings suggest that prefrontal modulation may be an essential component in the development of punding behavior in patients with PD.

Contribution of the cerebellum to cognitive performance in children and adolescents with multiple sclerosis

Background:

Posterior fossa lesions are common in pediatric-onset multiple sclerosis (MS), which is of concern, given the known role of the cerebellum in cognition.

Objectives:

To investigate the relationship between cerebellar pathology and cognitive function in youth with pediatric-onset MS.

Methods:

Twenty-eight pediatric-onset relapsing–remitting MS patients (21 girls; mean age 16.2 years; mean disease duration 4.3 years, median Expanded Disability Status Scale 1.25) were compared to 33 age- and sex-matched healthy controls. Participants underwent structural magnetic resonance imaging (MRI) and neuropsychological evaluation to assess intelligence, attention, processing speed, language, visuo-motor integration, and fine-motor dexterity. Associations between cognitive outcomes and cerebellar volume independent of cerebral volume were examined.

Results:

Cognitive and motor performance of the MS group was reduced relative to controls (all p<0.003). While cerebellar volumes did not differ between groups, cerebellar posterior lobe volume and infratentorial lesion volume accounted for extra variance on measures of information processing ( R2=0.43; p=0.02) and vocabulary ( R2=0.56; p=0.04) in patients (controlling for cerebral volume and sex), but not in controls.

Conclusion:

Smaller cerebellar posterior lobe volume, a known region for cognitive processing, and increased lesion burden in the posterior fossa adversely impact cognitive function, an important functional consequence of MS onset during childhood.

Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach

Objective

To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls.

Methods

Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness.

Results

Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected).

Conclusion

The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.

Assessment of Functional Characteristics of Amnestic Mild Cognitive Impairment and Alzheimer's Disease Using Various Methods of Resting-State FMRI Analysis

Resting-state functional magnetic resonance imaging (RS FMRI) has been widely used to analyze functional alterations in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) patients. Although many clinical studies of aMCI and AD patients using RS FMRI have been undertaken, conducting a meta-analysis has not been easy because of seed selection bias by the investigators. The purpose of our study was to investigate the functional differences in aMCI and AD patients compared with healthy subjects in a meta-analysis. Thus, a multimethod approach using regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and global brain connectivity was used to investigate differences between three groups based on previously published data. According to the choice of RS FMRI approach used, the patterns of functional alteration were slightly different. Nevertheless, patients with aMCI and AD displayed consistently decreased functional characteristics with all approaches. All approaches showed that the functional characteristics in the left parahippocampal gyrus were decreased in AD patients compared with healthy subjects. Although some regions were slightly different according to the different RS FMRI approaches, patients with aMCI and AD showed a consistent pattern of decreased functional characteristics with all approaches.

Olfactory performance and resting state functional connectivity in non-demented drug naïve patients with Parkinson's disease

Olfactory performance in Parkinson's disease (PD) is closely associated with subsequent cognitive decline. In the present study, we analyzed the olfaction-dependent functional connectivity with a hypothesis that olfactory performance would influence functional connectivity within key brain areas of PD. A total of 110 nondemented drug-naïve patients with PD were subdivided into three groups of high score (PD-H, n = 23), middle score (PD-M, n = 64), and low score (PD-L, n = 23) based on olfactory performance. We performed the resting-state functional connectivity with seed region of interest in the posterior cingulate cortex (PCC) and caudate. An analysis of functional connectivity revealed that PD-L patients exhibited a significant attenuation of cortical functional connectivity with the PCC in the bilateral primary sensory areas, right frontal areas, and right parietal areas compared to PD-H or PD-M patients. Meanwhile, PD-L patients exhibited a significant enhancement of striatocortical functional connectivity in the bilateral occipital areas and right frontal areas compared to PD-H or PD-M patients. In the voxel-wise correlation analysis, olfactory performance was positively associated with cortical functional connectivity with the PCC in similar areas of attenuated cortical connectivity in PD-L patients relative to PD-H patients. On the other hand, the cortical functional connectivity with the caudate was negatively correlated with olfactory performance in similar areas of increased connectivity in PD-L patients relative to PD-H patients. The present study demonstrated that resting state functional connectivity exhibits a distinctive pattern depending on olfactory performance, which might shed light on a meaningful relationship between olfactory impairment and cognitive dysfunction in PD.

Dopaminergic modulation of resting-state functional connectivity in de novo patients with Parkinson's disease

Parkinson's disease (PD) is characterized by degenerative changes of nigral dopamine neurons, resulting in the dopaminergic denervation of the striatum. Resting state networks studies have demonstrated that dopamine modulates distinct network connectivity patterns in both a linear and a nonlinear fashion, but quantitative analyses of dopamine-dependent functional connectivity secondary to PD pathology were less informative. In the present study, we performed a correlation analysis between striatal dopamine levels assessed quantitatively by FP-CIT positron emission tomography imaging and resting-state functional connectivity in 23 drug naïve de novo patients with PD to elucidate dopamine-dependent functional networks. The major finding is that the patterns of dopamine-dependent positive functional connectivity varied depending on the location of striatal seeds. Dopamine-dependent functional connectivity with the caudate predominantly overlay pericentral cortical areas, whereas dopamine-dependent structures functionally connected with the posterior putamen predominantly involved cerebellar areas. The dorsolateral frontal area overlapped as a dopamine-dependent cortical region that was positively connected with the anterior and posterior putamen. On the other hand, cortical areas where functional connectivity from the posterior cingulate was negatively correlated with dopaminergic status in the posterior putamen were localized in the left anterior prefrontal area and the parietal area. Additionally, functional connectivity between the anterior putamen and mesiofrontal areas was negatively coupled with striatal dopamine levels. The present study demonstrated that dopamine-dependent functional network connectivity secondary to PD pathology mainly exhibits a consistent pattern, albeit with some variation. These patterns may reflect the diverse effects of dopaminergic medication on parkinsonian-related motor and cognitive performance.

Mesenchymal stem cells can modulate longitudinal changes in cortical thickness and its related cognitive decline in patients with multiple system atrophy

Multiple system atrophy (MSA) is an adult-onset, sporadic neurodegenerative disease. Because the prognosis of MSA is fatal, neuroprotective or regenerative strategies may be invaluable in MSA treatment. Previously, we obtained clinical and imaging evidence that mesenchymal stem cell (MSC) treatment could have a neuroprotective role in MSA patients. In the present study, we evaluated the effects of MSC therapy on longitudinal changes in subcortical deep gray matter volumes and cortical thickness and their association with cognitive performance. Clinical and imaging data were obtained from our previous randomized trial of autologous MSC in MSA patients. During 1-year follow-up, we assessed longitudinal differences in automatic segmentation-based subcortical deep gray matter volumes and vertex-wise cortical thickness between placebo (n = 15) and MSC groups (n = 11). Next, we performed correlation analysis between the changes in cortical thickness and changes in the Korean version of the Montreal Cognitive Assessment (MoCA) scores and cognitive performance of each cognitive subdomain using a multiple, comparison correction. There were no significant differences in age at baseline, age at disease onset, gender ratio, disease duration, clinical severity, MoCA score, or education level between the groups. The automated subcortical volumetric analysis revealed that the changes in subcortical deep gray matter volumes of the caudate, putamen, and thalamus did not differ significantly between the groups. The areas of cortical thinning over time in the placebo group were more extensive, including the frontal, temporal, and parietal areas, whereas these areas in the MSC group were less extensive. Correlation analysis indicated that declines in MoCA scores and phonemic fluency during the follow-up period were significantly correlated with cortical thinning of the frontal and posterior temporal areas and anterior temporal areas in MSA patients, respectively. In contrast, no significant correlations were observed in the MSC group. These results suggest that MSC treatment in patients with MSA may modulate cortical thinning over time and related cognitive performance, inferring a future therapeutic candidate for cognitive disorders.

Improved explanation of human intelligence using cortical features with second order moments and regression

BACKGROUND

Cortical features derived from magnetic resonance imaging (MRI) provide important information to account for human intelligence. Cortical thickness, surface area, sulcal depth, and mean curvature were considered to explain human intelligence. One region of interest (ROI) of a cortical structure consisting of thousands of vertices contained thousands of measurements, and typically, one mean value (first order moment), was used to represent a chosen ROI, which led to a potentially significant loss of information.

METHODS

We proposed a technological improvement to account for human intelligence in which a second moment (variance) in addition to the mean value was adopted to represent a chosen ROI, so that the loss of information would be less severe. Two computed moments for the chosen ROIs were analyzed with partial least squares regression (PLSR). Cortical features for 78 adults were measured and analyzed in conjunction with the full-scale intelligence quotient (FSIQ).

RESULTS

Our results showed that 45% of the variance of the FSIQ could be explained using the combination of four cortical features using two moments per chosen ROI. Our results showed improvement over using a mean value for each ROI, which explained 37% of the variance of FSIQ using the same set of cortical measurements.

DISCUSSION

Our results suggest that using additional second order moments is potentially better than using mean values of chosen ROIs for regression analysis to account for human intelligence.

Prediction for human intelligence using morphometric characteristics of cortical surface: partial least square analysis

A number of imaging studies have reported neuroanatomical correlates of human intelligence with various morphological characteristics of the cerebral cortex. However, it is not yet clear whether these morphological properties of the cerebral cortex account for human intelligence. We assumed that the complex structure of the cerebral cortex could be explained effectively considering cortical thickness, surface area, sulcal depth and absolute mean curvature together. In 78 young healthy adults (age range: 17-27, male/female: 39/39), we used the full-scale intelligence quotient (FSIQ) and the cortical measurements calculated in native space from each subject to determine how much combining various cortical measures explained human intelligence. Since each cortical measure is thought to be not independent but highly inter-related, we applied partial least square (PLS) regression, which is one of the most promising multivariate analysis approaches, to overcome multicollinearity among cortical measures. Our results showed that 30% of FSIQ was explained by the first latent variable extracted from PLS regression analysis. Although it is difficult to relate the first derived latent variable with specific anatomy, we found that cortical thickness measures had a substantial impact on the PLS model supporting the most significant factor accounting for FSIQ. Our results presented here strongly suggest that the new predictor combining different morphometric properties of complex cortical structure is well suited for predicting human intelligence.

Cortical thinning in vascular mild cognitive impairment and vascular dementia of subcortical type

BACKGROUND AND PURPOSE

Amnestic mild cognitive impairment (MCI) is known to be a preclinical stage of Alzheimer's disease (AD). Similarly, MCI associated with small-vessel disease (svMCI), might be a forme froste of subcortical vascular dementia (SVaD). Patterns of cortical thinning in addition to the ischemia rating on MRI may further elucidate the clinical characteristics and pathogenesis of SVaD and svMCI. We tried to determine if svMCI differs from SVaD in the distribution of cortical atrophy, which may help understand the hierarchy between svMCI and SVaD and possibly also how svMCI evolves into SVaD.

METHODS

Twenty patients with SVaD, 34 patients with svMCI, 115 patients with AD, and 96 individuals with normal-cognition (NC) were imaged with magnetic resonance imaging (MRI) including 3-dimensional volumetric images for cortical thickness analysis across the entire brain.

RESULTS

Compared to NC, svMCI patients showed cortical thinning in inferior frontal and orbitofrontal gyri, anterior cingulate, insula, superior temporal gyrus, and lingual gyrus, while cortical thinning in SVaD patients involved all these areas plus dorsolateral prefrontal and temporal cortices.

CONCLUSION

Our findings suggest the presence of hierarchy between svMCI and SVaD, and that the cognitive decline from svMCI to SVaD is associated with lesions in dorsolateral prefrontal and temporal cortices.

Sulcal morphology changes and their relationship with cortical thickness and gyral white matter volume in mild cognitive impairment and Alzheimer's disease

We investigated the changes of sulcal shape (average mean curvature in folded regions and sulcal depth) in mild cognitive impairment (MCI) and Alzheimer's disease (AD) using quantitative surface-based methods in a large sample of magnetic resonance imaging data. Moreover, we observed their relationships with cortical thickness and gyral white matter (WM) volume, while considering age effect. This study involved 85 normal controls (n [men/women]: 36/49, age [mean+/-SD]: 71.1+/-4.9 years), and 100 MCI (44/56, 71.8+/-6.5) and 145 AD subjects (53/92, 72.7+/-7.3). We found significantly lower average mean curvature (greater sulcal widening) and shallower sulcal depth with disease progression from controls to MCI and MCI to AD. The most remarkable change in MCI and AD was sulcal widening observed in the temporal lobe (average mean curvature, control [mean]: 0.564, MCI: 0.534 (5.3% decrease from control), AD: 0.486 (13.8% and 9.0% decrease from control and MCI respectively)). Of the four measurements, the sulcal widening measurement showed the highest sensitivity in revealing group differences between control and MCI, which might be useful for detecting early dementia. Significant reductions in cortical thickness and gyral WM volume also occurred in MCI and AD. Multiple regression analysis demonstrated that a wider and shallower sulcal shape was primarily associated with decreased cortical thickness and gyral WM volume in each group. Age-related trends for the sulcal shape were not strongly found when cortical thickness and gyral WM volume were considered.

Fractal dimension in human cortical surface: multiple regression analysis with cortical thickness, sulcal depth, and folding area

Fractal dimension (FD) has been widely used to provide a quantitative description of structural complexity in the cerebral cortex. FD is an extremely compact measure of shape complexity, condensing all details into a single numeric value. We interpreted the variation of the FD in the cortical surface of normal controls through multiple regression analysis with cortical thickness, sulcal depth, and folding area related to cortical complexity. We used a cortical surface showing a reliable representation of folded gyri and manually parcellated it into frontal, parietal, temporal, and occipital regions for regional analysis. In both hemispheres the mean cortical thickness and folding area showed significant combination effects on cortical complexity and accounted for about 50% of its variance. The folding area was significant in accounting for the FD of the cortical surface, with positive coefficients in both hemispheres and several lobe regions, while sulcal depth was significant only in the left temporal region. The results may suggest that human cortex develops a complex structure through the thinning of cortical thickness and by increasing the frequency of folds and the convolution of gyral shape rather than by deepening sulcal regions. Through correlation analysis of FD with IQ and the number of years of education, the results showed that a complex shape of the cortical surface has a significant relationship with intelligence and education. Our findings may indicate the structural characteristics that are revealed in the cerebral cortex when the FD in human brain is increased, and provide important information about brain development.

Asymmetries of the planum temporale and Heschl's gyrus: relationship to language lateralization

Morphological asymmetries favouring the left hemisphere in the planum temporale (PT) and Heschl's gyrus (HG) have both been presumed to relate to the typical left-hemisphere dominance for language functions. However, a direct link between structure and function has not been clearly established. The present study investigates this issue by measuring the volume of the PT and HG on the MRI scans of epilepsy patients classified into three groups: left speech group (LSG; n = 20), right speech group (RSG; n = 11) and bilateral speech group (BSG; n = 13), as assessed by the intracarotid Sodium Amytal procedure. Additionally, an automatic voxel-based morphometry (VBM) analysis was performed to explore collateral structural asymmetries. Although leftward structural asymmetries were found in the PT, consistent with the literature, they did not relate to language lateralization. For HG we also replicated asymmetries favouring the left side; interestingly, three of the individuals within the RSG showed a strongly reversed asymmetry, but as a whole the structure-function relationship for HG was not obligatory. The VBM analysis revealed a grey-matter concentration difference in the posterior part of the inferior frontal gyrus (pars opercularis, corresponding functionally to Broca's area), which favoured the left hemisphere in the LSG, and the right hemisphere in the RSG. The findings suggest that this frontal cortical region bears a direct relationship to language lateralization, which may be related to use-dependent plasticity in patients with language reorganization.

The morphometry of auditory cortex in the congenitally deaf measured using MRI

The study of congenitally deaf individuals provides a unique opportunity to understand the organization and potential for reorganization of human auditory cortex. We used magnetic resonance imaging (MRI) to examine the structural organization of two auditory cortical regions, Heschl's gyrus (HG) and the planum temporale (PT), in deaf and hearing subjects. The results show preservation of cortical volume in HG and PT of deaf subjects deprived of auditory input since birth. Measurements of grey and white matter, as well as the location and extent of these regions in the deaf showed complete overlap both with matched controls and with previous samples of hearing subjects. The results of the manual volume measures were supported by findings from voxel-based morphometry analyses that showed increased grey-matter density in the left motor hand area of the deaf, but no differences between the groups in any auditory cortical region. This increased cortical density in motor cortex may be related to more active use of the dominant hand in signed languages. Most importantly, expected interhemispheric asymmetries in HG and PT thought to be related to auditory language processing were preserved in these deaf subjects. These findings suggest a strong genetic component in the development and maintenance of auditory cortical asymmetries that does not depend on auditory language experience. Preservation of cortical volume in the deaf suggests plasticity in the input and output of auditory cortex that could include language-specific or more general-purpose information from other sensory modalities.

Statistical mapping analysis of lesion location and neurological disability in multiple sclerosis: application to 452 patient data sets

In multiple sclerosis (MS), the correlation between disability and the volume of white matter lesions on magnetic resonance imaging (MRI) is usually weak. This may be because lesion location also influences the extent and type of functional disability. We applied an automatic lesion-detection algorithm to 452 MRI scans of patients with relapsing-remitting MS to identify the regions preferentially responsible for different types of clinical deficits. Statistical parametric maps were generated by performing voxel-wise linear regressions between lesion probability and different clinical disability scores. There was a clear distinction between lesion locations causing physical and cognitive disability. Lesion likelihood correlated with the Expanded Disability Status Scale (EDSS) in the left internal capsule and in periventricular white matter mostly in the left hemisphere. Pyramidal deficits correlated with only one area in the left internal capsule that was also present in the EDSS correlation. Cognitive dysfunction correlated with lesion location at the grey-white junction of associative, limbic, and prefrontal cortex. Coordination impairment correlated with areas in interhemispheric and pyramidal periventricular white matter tracts, and in the inferior and superior longitudinal fascicles. Bowel and bladder scores correlated with lesions in the medial frontal lobes, cerebellum, insula, dorsal midbrain, and pons, areas known to be involved in the control of micturition. This study demonstrates for the first time a relationship between the site of lesions and the type of disability in large scale MRI data set in MS.

Computer-assisted imaging to assess brain structure in healthy and diseased brains

Neuroanatomical structures may be profoundly or subtly affected by the interplay of genetic and environmental factors, age, and disease. Such effects are particularly true in healthy ageing individuals and in those who have neurodegenerative diseases. The ability to use imaging to identify structural brain changes associated with different neurodegenerative disease states would be useful for diagnosis and treatment. However, early in the progression of such diseases, neuroanatomical changes may be too mild, diffuse, or topologically complex to be detected by simple visual inspection or manually traced measurements of regions of interest. Computerised methods are being developed that can capture the extraordinary morphological variability of the human brain. These methods use mathematical models sensitive to subtle changes in the size, position, shape, and tissue characteristics of brain structures affected by neurodegenerative diseases. Neuroanatomical features can be compared within and between groups of individuals, taking into account age, sex, genetic background, and disease state, to assess the structural basis of normality and disease. In this review, we describe the strengths and limitations of algorithms of existing computer-assisted tools at the most advanced stage of development, together with available and foreseeable evidence of their usefulness at the clinical and research level.

A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)

Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem tissue to determine the probabilistic distribution of microscopic cyto- and chemoarchitectural regions in the human brain. This, combined with macroscopic information about structure and function derived from subjects in vivo, provides the first large scale opportunity to gain meaningful insights into the concordance or discordance in micro- and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behaviour will allow for the first assessment of cerebral genotype-phenotype-behavioural correlations in humans to take place in a population this large. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.

Automated segmentation of multiple sclerosis lesions by model outlier detection

This paper presents a fully automated algorithm for segmentation of multiple sclerosis (MS) lesions from multispectral magnetic resonance (MR) images. The method performs intensity-based tissue classification using a stochastic model for normal brain images and simultaneously detects MS lesions as outliers that are not well explained by the model. It corrects for MR field inhomogeneities, estimates tissue-specific intensity models from the data itself, and incorporates contextual information in the classification using a Markov random field. The results of the automated method are compared with lesion delineations by human experts, showing a high total lesion load correlation. When the degree of spatial correspondence between segmentations is taken into account, considerable disagreement is found, both between expert segmentations, and between expert and automatic measurements.

Measurement of cortical thickness using an automated 3-D algorithm: a validation study

A validation study was conducted to assess the accuracy of the algorithm developed by MacDonald et al. (1999) for measuring cortical thickness. This algorithm automatically determines the cortical thickness by 3-D extraction of the inner and outer surfaces of the cerebral cortex from an MRI scan. A manual method of tagging the grey-csf and grey-white interface was used on 20 regions (10 cortical areas found in each hemisphere) in 40 MRIs of the brain to validate the algorithm. The regions were chosen throughout the cortex to get broad assessment of the algorithm's performance. Accuracy was determined by an anatomist tagging the csf-grey and grey-white borders of selected gyri and by allowing the algorithm to determine the csf-grey and grey-white borders and the corresponding cortical thickness of the same region. Results from the manual and automatic methods were statistically compared using overall ANOVA and paired t tests for each region. The manual and automatic methods were in agreement for all but 4 of the 20 regions tested. The four regions where there were significant differences between the two methods were the insula left and right, the right cuneus, and the right parahippocampus. We conclude that the automatic algorithm is valid for most of the cortex and provides a viable alternative to manual methods of determining cortical thickness in vivo. However, caution should be taken when measuring the regions mentioned previously where the results of the algorithm can be biased by surrounding grey structures.

Exploring the discrimination power of the time domain for segmentation and characterization of active lesions in serial MR data

This paper presents a new method for the automatic segmentation and characterization of object changes in time series of three-dimensional data sets. The technique was inspired by procedures developed for analysis of functional MRI data sets. After precise registration of serial volume data sets to 4-D data, we applied a time series analysis taking into account the characteristic time function of variable lesions. The images were preprocessed with a correction of image field inhomogeneities and a normalization of the brightness over the whole time series. Thus, static regions remain unchanged over time, whereas changes in tissue characteristics produce typical intensity variations in the voxel's time series. A set of features was derived from the time series, expressing probabilities for membership to the sought structures. These multiple sources of uncertain evidence were combined to a single evidence value using Dempster-Shafer's theory. The project was driven by the objective of improving the segmentation and characterization of white matter lesions in serial MR data of multiple sclerosis patients. Pharmaceutical research and patient follow-up requires efficient and robust methods with a high degree of automation. The new approach replaces conventional segmentation of series of 3-D data sets by a 1-D processing of the temporal change at each voxel in the 4-D image data set. The new method has been applied to a total of 11 time series from different patient studies, covering time resolutions of 12 and 24 data sets over a period of about 1 year. The results demonstrate that time evolution is a highly sensitive feature for detection of fluctuating structures.

MRI simulation-based evaluation of image-processing and classification methods

With the increased interest in computer-aided image analysis methods, there is a greater need for objective methods of algorithm evaluation. Validation of in vivo MRI studies is complicated by a lack of reference data and the difficulty of constructing anatomically realistic physical phantoms. We present here an extensible MRI simulator that efficiently generates realistic three-dimensional (3-D) brain images using a hybrid Bloch equation and tissue template simulation that accounts for image contrast, partial volume, and noise. This allows image analysis methods to be evaluated with controlled degradations of image data.

Automated extraction and variability analysis of sulcal neuroanatomy

Systematic mapping of the variability in cortical sulcal anatomy is an area of increasing interest which presents numerous methodological challenges. To address these issues, we have implemented sulcal extraction and assisted labeling (SEAL) to automatically extract the two-dimensional (2-D) surface ribbons that represent the median axis of cerebral sulci and to neuroanatomically label these entities. To encode the extracted three-dimensional (3-D) cortical sulcal schematic topography (CSST) we define a relational graph structure composed of two main features: vertices (representing sulci) and arcs (representing the relationships between sulci). Vertices contain a parametric representation of the surface ribbon buried within the sulcus. Points on this surface are expressed in stereotaxic coordinates (i.e., with respect to a standardized brain coordinate system). For each of these vertices, we store length, depth, and orientation as well as anatomical attributes (e.g., hemisphere, lobe, sulcus type, etc.). Each arc stores the 3-D location of the junction between sulci as well as a list of its connecting sulci. Sulcal labeling is performed semiautomatically by selecting a sulcal entity in the CSST and selecting from a menu of candidate sulcus names. In order to help the user in the labeling task, the menu is restricted to the most likely candidates by using priors for the expected sulcal spatial distribution. These priors, i.e., sulcal probabilistic maps, were created from the spatial distribution of 34 sulci traced manually on 36 different subjects. Given these spatial probability maps, the user is provided with the likelihood that the selected entity belongs to a particular sulcus. The cortical structure representation obtained by SEAL is suitable to extract statistical information about both the spatial and the structural composition of the cerebral cortical topography. This methodology allows for the iterative construction of a successively more complete statistical models of the cerebral topography containing spatial distributions of the most important structures, their morphometrics, and their structural components.

A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI

Quantitative assessment of Magnetic Resonance Imaging (MRI) lesion load of patients with multiple sclerosis (MS) is the most objective approach for a better understanding of the history of the pathology, either natural or modified by therapies. To achieve an accurate and reproducible quantification of MS lesions in conventional brain MRI, an automatic segmentation algorithm based on a multiresolution approach using pyramidal data structures is proposed. The systematic pyramidal decomposition in the frequency domain provides a robust and flexible low level tool for MR image analysis. Context-dependent rules regarding MRI findings in MS are used as high level considerations for automatic lesion detection.