Callosal circularity as an early marker for Alzheimer's disease

Altered Callosal Morphology and Connectivity in Asymptomatic Carotid Stenosis

BACKGROUND

Carotid stenosis, even in the clinically asymptomatic stage, causes cognitive impairment, silent lesions, and hemispheric changes. The corpus callosum (CC) is crucial for hemispheric cortical integration and specialization.

PURPOSE

To examine if CC morphology and connectivity relate to cognitive decline and lesion burden in asymptomatic carotid stenosis (ACS).

STUDY TYPE

Retrospective, cross-sectional.

POPULATION

33 patients with unilaterally severe (70%) ACS and 28 demographically and comorbidity-matched controls. A publicly available healthy adult lifespan (ages between 18 and 80; n = 483) MRI dataset was also included.

FIELD STRENGTH/SEQUENCE

A 3.0 T; T1 MPRAGE and diffusion weighted gradient echo-planar imaging sequences.

ASSESSMENT

Structural MRI and multidomain cognitive data were obtained. Midsagittal CC area, circularity, thickness, integrity, and probabilistic tractography were calculated and correlated with cognitive tests and white matter hyperintensity. Fractional anisotropy, mean diffusivity (MD), and radial diffusivity were determined from DTI.

STATISTICAL TESTS

Independent two-sample t-tests, χ2 tests, Mann-Whitney U, locally weighted scatterplot smoothing (LOWESS) curve fit, and Pearson correlation. A P value < 0.05 was considered statistically significant.

RESULTS

Patients with ACS demonstrated significant reductions in callosal area, circularity, and thickness compared to controls. The callosal atrophy was significantly correlated with white matter hyperintensity size (r = -0.629, P < 0.001). Voxel-wise analysis of diffusion measures in the volumetric CC showed that ACS patients exhibited significantly lower fractional anisotropy and higher MD and radial diffusivity in the genu and splenium of the CC than controls. Further lifespan trajectory analysis showed that although the midsagittal callosal area, circularity, and thickness exhibited age-related decreases, the values in the ACS patients were significantly lower in all age groups.

DATA CONCLUSION

Midsagittal callosal atrophy and connectivity reflect the load of silent lesions and the severity of cognitive decline, respectively, suggesting that CC degeneration has potential to serve as an early marker in ACS.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Bridging Reduced Grip Strength and Altered Executive Function: Specific Brain White Matter Structural Changes in Patients with Alzheimer's Disease

Objective

To investigate the correlation between specific fiber tracts and grip strength and cognitive function in patients with Alzheimer's disease (AD) by fixel-based analysis (FBA).

Methods

AD patients were divided into AD with low grip strength (AD-LGS, n=29) and AD without low grip strength (AD-nLGS, n=25), along with 31 normal controls (NC). General data, neuropsychological tests, grip strength and cranial magnetic resonance imaging (MRI) scans were collected. FBA evaluated white matter (WM) fiber metrics, including fiber density (FD), fiber cross-sectional (FC), and fiber density and cross-sectional area (FDC). The mean fiber indicators of the fiber tracts of interest (TOI) were extracted in cerebral region of significant statistical differences in FBA to further compare the differences between groups and analyze the correlation between fiber properties and neuropsychological test scores.

Results

Compared to AD-nLGS group, AD-LGS group showed significant reductions in FDC in several cerebral regions. In AD patients, FDC values of bilateral uncinate fasciculus and left superior longitudinal fasciculus were positively correlated with Clock Drawing Test scores, while FDC of splenium of corpus callosum, bilateral anterior cingulate tracts, forceps major, and bilateral inferior longitudinal fasciculus were positively correlated with the Executive Factor Score of Memory and Executive Screening scale scores.

Conclusion

Reduced grip strength in AD patients is associated with extensive impairment of WM structural integrity. Changes in FDC of specific WM fiber tracts related to executive function play a significant mediating role in the reduction of grip strength in AD patients.

Structural irregularities in MR corpus callosal images and their association with cerebrospinal fluid biomarkers in Mild Cognitive Impairments

In this study, irregularity measures from MR images of corpus callosal brain structures in healthy and Mild Cognitive Impairment (MCI) conditions are extracted and their association with Cerebrospinal Fluid (CSF) biomarkers are analyzed. For this, MR images of healthy controls, Early MCI (EMCI) and Late MCI (LMCI) subjects are considered from a public database. The considered images are preprocessed and corpus callosal structure is segmented. Structural irregularity measures are extracted from the segmented regions using Fourier analysis. Statistical tests are performed to identify the significant features which can characterize the MCI stages. Association of these measures with CSF amyloid beta and tau concentrations are further investigated. Results demonstrate that Fourier spectral analysis is able to characterize the non-periodic variations in the corpus callosal structures of healthy, EMCI and LMCI MR images. The callosal irregularity measures increase as the disease progresses from healthy to LMCI. Phosphorylated tau concentrations in CSF demonstrate a positive correlation with irregularity measures across the diagnostic groups. Significant association of callosal measures and amyloid beta levels are found to be absent in MCI stages. As corpus callosal structural irregularities due to early MCI condition and their association with CSF markers remain uncharacterized in the literature, this study seems to be clinically significant for the timely intervention of pre-symptomatic MCI stages.

Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease

The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ₄₂ ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ₄₂ alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ₄₂ , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.

Altered structural and functional homotopic connectivity associated with the progression from mild cognitive impairment to Alzheimer's disease

The progressive mild cognitive impairment (pMCI) is associated with an increased risk of Alzheimer's disease (AD). Many studies have reported the disrupted brain alteration during the imminent conversion from pMCI to AD. However, the subtle difference of structural and functional of inter-hemispheric between pMCI and stable mild cognitive impairment (sMCI) remains unknown. In the present study, we scanned the multimodal magnetic resonance imaging of 38 sMCI, 26 pMCI, and 50 healthy controls (HC) and assessed the cognitive function. The voxel-mirrored homotopic connectivity (VMHC) and volume of corpus callosum were calculated. A structural equation modeling (SEM) was established to determine the relationships between the corpus callosum, the inter-hemispheric connectivity, and cognitive assessment. Compared to sMCI, pMCI exhibited decreased VMHC in insular and thalamus, and reduced volume of corpus callosum. SEM results showed that decreased inter-hemispheric connectivity was directly associated with cognitive impairment and corpus callosum atrophy, and corpus callosum atrophy indirectly caused cognitive impairment by mediating inter-hemispheric connectivity in pMCI. In conclusion, the destruction of homotopic connectivity is related to cognitive impairment, and the corpus callosum atrophy partially mediates the association between the homotopic connectivity and cognitive impairment in pMCI.

Individual variability in the nonlinear development of the corpus callosum during infancy and toddlerhood: a longitudinal MRI analysis

The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.

A biocompatible and injectable hydrogel to boost the efficacy of stem cells in neurodegenerative diseases treatment

AIMS

Stem cell therapies emerged as treatment modalities with potential to cure neurodegenerative diseases (NDs). However, despite high expectations, their clinical use is still limited. Critical issues in treatment outcomes may be related to stem cells formulation and administration route. We develop a hydrogel as a cell carrier, consisting of compounds (phospholipids and hyaluronic acid-HA) naturally present in the central nervous system (CNS). The HA-based hydrogel physically crosslinked with liposomes is designed for direct injection into the CNS to significantly increase the bone marrow mesenchymal stem cells (BMSCs) bioavailability.

MATERIALS AND METHODS

Hydrogel compatibility is confirmed in vitro with BMSCs and in vivo through its intracerebroventricular injection in rats. To assess its efficacy, the main cause of chronic neurologic disability in young adults is selected, namely multiple sclerosis (MS). The efficacy of the developed formulation containing a lower number of cells than previously reported is demonstrated using an experimental autoimmune encephalomyelitis (EAE) rat model.

KEY FINDINGS

The distribution of the engineered hydrogel into corpus callosum can be ideal for NDs treatment, since damage of this white matter structure is responsible for important neuronal deficits. Moreover, the BMSCs-laden hydrogel significantly decreases disease severity and maximum clinical score and eliminated the relapse.

SIGNIFICANCE

The engineering of advanced therapies using this natural carrier can result in efficacious treatments for MS and related debilitating conditions.

The Differential Diagnostic Value of the Callosal Angle and Evans Index in Mild Cognitive Impairment and Alzheimer's Disease

Background

Callosal Angle (CA) and Evans Index (EI) are considered as imaging biomarkers to diagnose normal-pressure hydrocephalus using traditional MR measurement methods.

Objective

The current study aimed to evaluate the differential diagnostic value of CA and EI in Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD).

Methods

Five-hundred and two subjects were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, which included 168 Normal Controls (NC), 233 MCI and 101 AD patients. The structural MR images were interactively applied with multiplanar reconstruction to measure the CA and EI.

Results

CA presented no significant difference among NC, MCI and AD groups (H value = 3.848, P value = 0.146), and EI demonstrated higher value in MCI and AD groups than that in NC groups (P = 0.000 and 0.001, respectively). MCI group had significant larger EI (0.29±0.04) than (0.27±0.03) NC group in 70-75 years old sub-groups. ROC showed that the area under the curve was 0.704±0.045 for NC-MCI in 70-75 years old groups. The correlation analysis indicated that EI was significantly negatively related to MMSE scores of MCI patients (r = -0.131, P = 0.046).

Conclusion

EI might serve as a screening imaging biomarker for MCI in 70-75 years old patients, and show limited differential value for the diagnosis of AD. CA could present no diagnostic value for MCI and AD in the current study.

Structural imaging outcomes in subjective cognitive decline: Community vs. clinical-based samples

Subjective cognitive decline (SCD) has been proposed as a preclinical stage of Alzheimer's disease (AD). Neuroimaging studies have suggested early AD-like structural brain alterations in SCD subjects compared to healthy controls. However, there is substantial heterogeneity in the results, which might depend on whether SCD samples were drawn from the community or from memory clinics. Here we reviewed brain atrophy, assessed through structural magnetic resonance imaging, separately for SCD-community and clinic-based samples. SCD-community samples show a more consistent pattern of atrophy, involving the hippocampus and temporal and parietal cortices. Similarly, in SCD-clinic samples the temporo-parietal cortex showed early vulnerability, however these studies reported a more heterogeneous atrophy pattern. Overall, these studies suggest both commonalities and differences in brain atrophy patterns between SCD clinical and community samples. In SCD-community, the temporal cortex is involved, while SCD-clinical exhibited a more complex pattern of atrophy, which may be related to a more heterogeneous sample reporting neuropsychiatric symptoms along with preclinical AD.

Unsupervised Method Based on Superpixel Segmentation for Corpus Callosum Parcellation in MRI Scans

In this paper, we introduce an unsupervised method for the parcellation of the Corpus Callosum (CC) from MRI images. Since there are no visible landmarks within the structure that explicit its parcels, non-geometric CC parcellation is a challenging task especially that almost of proposed methods are geometric or data-based. In fact, in order to subdivide the CC from brain sagittal MRI scans, we adopt the probabilistic neural network as a clustering technique. Then, we use a cluster validity measure based on the maximum entropy (Vmep) to obtain the optimal number of classes. After that, we obtain the isolated CC that we parcel automatically using SLIC (Simple Linear Iterative Clustering) as superpixel segmentation technique. The obtained results on two challenging public datasets prove the performance of the proposed method against geometric methods from the state of the art. Indeed, as best as we know, it is the first work that investigates the validation of a CC parcellation method on ground-truth datasets using many objective metrics.