Whole-brain voxel-based morphometry of white matter in mild cognitive impairment

The impact of breast milk feeding on early brain development in preterm infants in China: An observational study

BACKGROUND

The prevailing consensus from large epidemiological studies is that breastfeeding is associated with improved IQ and cognitive functioning in later childhood and adolescence. Current research is exploring the association between breastfeeding and early brain development in preterm infants.

OBJECTIVE

To explore the differences in brain gray matter between breastmilk-fed and formula-fed preterm infants using structural and functional magnetic resonance imaging.

METHODS

A convenience sample of breastmilk-fed preterm infants(n = 34) and formula-fed infants (n = 22) aged approximately 32 weeks. At near term-equivalent age, MR scanning was performed. Gray matter structural and functional differences between the two groups were assessed using MATLAB software for voxel-based morphometry (VBM) and amplitude of low-frequency fluctuation (ALFF) analysis.

RESULTS

Maternal and neonatal demographic characteristics showed no significant difference between the two groups. Breastmilk-fed infants had greater regional gray matter volume on MRI than formula-fed infants in multiple brain regions, including the bilateral frontal lobe (BA11, BA46), right temporal lobe (BA37), and left caudate nucleus, at a statistical threshold of p<0.01 (AlphaSim corrected) with a cluster size of >40 voxels. Compared with formula-fed infants, breastmilk-fed infants showed increased brain activation on fMRI in the right superior temporal gyrus (BA41).

CONCLUSION

Breastmilk-fed infants had greater regional gray matter development and increased regional gray matter function compared with formula-fed infants at near term-equivalent age, suggesting breastmilk feeding in the early period after birth may have some degree of influence on early brain development in preterm infants.

Differential Impact of Cognitive Impairment in MCI Patients: A Case-Based Report

Mild cognitive impairment (MCI) traditionally refers to an intermediate stage between healthy individuals and early Alzheimer disease. Evidence shows grey and white matter volume changes and decrease in several executive functions, albeit the relation between cognitive performance and brain volume remains unclear. Here, we discuss 3 individual cases of MCI by investigating their MRI scans and cognitive test performance. We also recruited age-matched healthy older adults serving as gold standard for both grey and white matter volume and cognitive test outcomes. Our results show the impact of cognitive impairment on cognitive test performance and grey and white matter volumes, and the role played by cognitive and brain reserve on mitigating cognitive decline. Furthermore, we add evidence to previous studies by showing an increase in white matter volume compared to healthy controls, in all 3 patients. This pattern of increased white matter volume might help us to better understand the pathological mechanisms underlying MCI which in turn could contribute to future investigations.

Distinct Components in the Right Extended Frontal Aslant Tract Mediate Language and Working Memory Performance: A Tractography-Informed VBM Study

The extended frontal aslant tract (exFAT) is a tractography-based extension of the frontal aslant tract (FAT) which has been shown to be related with language and working memory performance in healthy human adults, but whether those functional implications map to structurally separate regions along its trajectory is still an open question. We present a tractography-informed Voxel-Based Morphometry procedure capable of detecting local tract-specific structural differences in white matter regions and apply it in two maximum variation sampling studies by comparing local differences in diffusion-derived microstructural parameters and fiber density along the exFAT territory between top performers and bottom performers in language and working memory tasks. In the right hemisphere we were able to detect, without prior constraints, a vertical frontal aslant component approximating the original FAT trajectory whose fiber density was significantly correlated with language (but not working memory) performance and an anterior cluster component corresponding to a distinct anterior frontal aslant component whose fiber density was significantly correlated with working memory (but not language) performance. The reported sub-division of the exFAT territory describes a set of frontal connections that are compatible with previously reported results on the Broca’s territory and frontal cortex hierarchical organization along an anterior-posterior gradient, suggesting that the exFAT could be part of a common neuroanatomical scaffold where language and working memory functions are integrated in the healthy human brain.

Volumetric Magnetic Resonance Imaging Study of Brain and Cerebellum in Children with Cerebral Palsy

Introduction. Quantitative magnetic resonance imaging (MRI) studies are rarely used in the diagnosis of patients with cerebral palsy. The aim of present study was to assess the relationships between the volumetric MRI and clinical findings in children with cerebral palsy compared to control subjects. Materials and Methods. Eighty-two children with cerebral palsy and 90 age- and sex-matched healthy controls were collected. Results. The dominant changes identified on MRI scans in children with cerebral palsy were periventricular leukomalacia (42%) and posthemorrhagic hydrocephalus (21%). The total brain and cerebellum volumes in children with cerebral palsy were significantly reduced in comparison to controls. Significant grey matter volume reduction was found in the total brain in children with cerebral palsy compared with the control subjects. Positive correlations between the age of the children of both groups and the grey matter volumes in the total brain were found. Negative relationship between width of third ventricle and speech development was found in the patients. Positive correlations were noted between the ventricles enlargement and motor dysfunction and mental retardation in children with cerebral palsy. Conclusions. By using the voxel-based morphometry, the total brain, cerebellum, and grey matter volumes were significantly reduced in children with cerebral palsy.

Impaired and preserved aspects of feedback learning in aMCI: contributions of structural connectivity

Distinct lines of research demonstrated that patients with amnestic mild cognitive impairment (aMCI), a potential precursor of Alzheimer disease (AD), are particularly impaired in remembering relations between items and that the use of emotional targets can facilitate memory in patients with AD. We link these findings by examining learning through positive and negative feedback in patients with aMCI, and explore its anatomic underpinnings with diffusion tensor imaging and tractography. Compared to healthy controls, patients with single-domain aMCI were impaired in learning from positive feedback, while learning from negative outcomes was preserved. Among pathways within the brain circuit involved in feedback learning, abnormal white matter microstructure was observed in tracts, which connect left-hemispheric amygdala with hippocampus and entorhinal cortex. In all participants, reduced white matter integrity in this left fiber tract was specifically associated with learning from positive outcomes. Microstructure of right-hemispheric tracts between amygdala and entorhinal cortex was related to learning from negative feedback, and was not compromised in aMCI patients. Our results provide new insight into how anatomical connections might contribute to impaired and preserved aspects of learning behaviors in the early AD process and indicate potential compensatory mechanisms.

Interhemispheric Functional and Structural Disconnection in Alzheimer's Disease: A Combined Resting-State fMRI and DTI Study

Neuroimaging studies have demonstrated that patients with Alzheimer's disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI) to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI), as well as 16 cognitive normal healthy subjects (CN). The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC) method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of AD<MCI<CN. Increased VMHC was observed in MCI subjects in posterior brain regions with patterns of AD/CN < MCI (sensorimotor cortex) and AD < CN/MCI (occipital gyrus). DTI analysis showed the most significant difference among the three cohorts was the fractional anisotropy in the genu of corpus callosum, which was positively associated with the VMHC of prefrontal and subcortical regions. Across all the three cohorts, the diffusion parameters in the genu of corpus callosum and VMHC in the above brain regions had significant correlation with the cognitive performance. These results demonstrate that there are specific patterns of interhemispheric functional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.

Spatial patterns of whole brain grey and white matter injury in patients with occult spastic diplegic cerebral palsy

Spastic diplegic cerebral palsy(SDCP)is a common type of cerebral palsy (CP), which presents as a group of motor-impairment syndromes. Previous conventional MRI studies have reported abnormal structural changes in SDCP, such as periventricular leucomalacia. However, there are roughly 27.8% SDCP patients presenting normal appearance in conventional MRI, which were considered as occult SDCP. In this study, sixteen patients with occult SDCP and 16 age- and sex-matched healthy control subjects were collected and the data were acquired on a 3T MR system. We applied voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) analysis to investigate whole brain grey and white matter injury in occult SDCP. By using VBM method, the grey matter volume reduction was revealed in the bilateral basal ganglia regions, thalamus, insula, and left cerebral peduncle, whereas the white matter atrophy was found to be located in the posterior part of corpus callosum and right posterior corona radiata in the occult SDCP patients. By using TBSS, reduced fractional anisotropy (FA) values were detected in multiple white matter regions, including bilateral white matter tracts in prefrontal lobe, temporal lobe, internal and external capsule, corpus callosum, cingulum, thalamus, brainstem and cerebellum. Additionally, several regions of white matter tracts injury were found to be significantly correlated with motor dysfunction. These results collectively revealed the spatial patterns of whole brain grey and white matter injury in occult SDCP.

Predicting dementia development in Parkinson's disease using Bayesian network classifiers

Parkinson's disease (PD) has broadly been associated with mild cognitive impairment (PDMCI) and dementia (PDD). Researchers have studied surrogate, neuroanatomic biomarkers provided by magnetic resonance imaging (MRI) that may help in the early diagnosis of this condition. In this article, four classification models (naïve Bayes, multivariate filter-based naïve Bayes, filter selective naïve Bayes and support vector machines, SVM) have been applied to evaluate their capacity to discriminate between cognitively intact patients with Parkinson's disease (PDCI), PDMCI and PDD. For this purpose, the MRI studies of 45 subjects (16 PDCI, 15 PDMCI and 14 PDD) were acquired and post-processed with Freesurfer, obtaining 112 variables (volumes of subcortical structures and thickness of cortical parcels) per subject. A multivariate filter-based naïve Bayes model was found to be the best classifier, having the highest cross-validated sensitivity, specificity and accuracy. Additionally, the most relevant variables related to dementia in PD, as predicted by our classifiers, were cerebral white matter, and volumes of the lateral ventricles and hippocampi.