Cortical Complexity Analyses and Their Cognitive Correlate in Alzheimer's Disease and Frontotemporal Dementia

Accurate identification of individuals with subjective cognitive decline using 3D regional fractal dimensions on structural magnetic resonance imaging

BACKGROUND AND OBJECTIVE

Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD.

METHODS

This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions.

RESULTS

The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations.

CONCLUSION

Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.

Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study

BACKGROUND AND PURPOSE

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities.

METHODS

We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy.

RESULTS

Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p = .04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p = .09). GM volumes of the frontal cortex (r = 0.54, p = .01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p = .02), thalamus (r = 0.48, p = .03), and posterior cingulate cortex (PCC) (r = 0.47, p = .03).

CONCLUSIONS

Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

Relationship between Neuroimaging and Cognition in Frontotemporal Dementia: A [18 F]FDG PET and Structural MRI Study

Background

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous condition with a prevalence comparable to Alzheimer's Disease for patients under sixty-five years of age. Gray matter (GM) atrophy and glucose hypometabolism are important biomarkers for the diagnosis and evaluation of disease progression in FTD. However, limited studies have systematically examined the association between cognition and neuroimaging in FTD using different imaging modalities in the same patient group.

Methods

We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both GM volume and glucose metabolism using structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography scanning ([18F]FDG PET) in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for [18F]FDG PET. Partial volume correction was applied to PET data to account for disease-related atrophy.

Results

Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.461, p = 0.035). The association between whole-cortex [18F]FDG SUVR and MoCA scores was not Significant (r = 0.374, p = 0.094). GM volumes of the frontal cortex (r = 0.540, p = 0.011), caudate (r = 0.616, p = 0.002), and insula (r = 0.568, p = 0.007) were also Significantly correlated with MoCA, as were SUVR values of the insula (r = 0.508, p = 0.018), thalamus (r = 0.478, p = 0.028), and posterior cingulate cortex (PCC) (r = 0.472, p = 0.030).

Discussion

Whole-cortex atrophy is associated with cognitive dysfunction, and this effect is larger than for cortical hypometabolism as measured with [18F]FDG PET. At the regional level, focal atrophy and/or hypometabolism in the frontal lobe, insula, PCC, thalamus, and caudate seem to imply the importance of these regions for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways. Our findings provide insight into the relationships between structural, metabolic, and cognitive changes due to FTD.

Fractal Dimension Studies of the Brain Shape in Aging and Neurodegenerative Diseases

The fractal dimension is a morphometric measure that has been used to investigate the changes of brain shape complexity in aging and neurodegenerative diseases. This chapter reviews fractal dimension studies in aging and neurodegenerative disorders in the literature. Research has shown that the fractal dimension of the left cerebral hemisphere increases until adolescence and then decreases with aging, while the fractal dimension of the right hemisphere continues to increase until adulthood. Studies in neurodegenerative diseases demonstrated a decline in the fractal dimension of the gray matter and white matter in Alzheimer's disease, amyotrophic lateral sclerosis, and spinocerebellar ataxia. In multiple sclerosis, the white matter fractal dimension decreases, but conversely, the fractal dimension of the gray matter increases at specific stages of disease. There is also a decline in the gray matter fractal dimension in frontotemporal dementia and multiple system atrophy of the cerebellar type and in the white matter fractal dimension in epilepsy and stroke. Region-specific changes in fractal dimension have also been found in Huntington's disease and Parkinson's disease. Associations were found between the fractal dimension and clinical scores, showing the potential of the fractal dimension as a marker to monitor brain shape changes in normal or pathological processes and predict cognitive or motor function.

Fractal Dimension Analysis in Neurological Disorders: An Overview

Fractal analysis has emerged as a powerful tool for characterizing irregular and complex patterns found in the nervous system. This characterization is typically applied by estimating the fractal dimension (FD), a scalar index that describes the topological complexity of the irregular components of the nervous system, both at the macroscopic and microscopic levels, that may be viewed as geometric fractals. Moreover, temporal properties of neurophysiological signals can also be interpreted as dynamic fractals. Given its sensitivity for detecting changes in brain morphology, FD has been explored as a clinically relevant marker of brain damage in several neuropsychiatric conditions as well as in normal and pathological cerebral aging. In this sense, evidence is accumulating for decreases in FD in Alzheimer's disease, frontotemporal dementia, Parkinson's disease, multiple sclerosis, and many other neurological disorders. In addition, it is becoming increasingly clear that fractal analysis in the field of clinical neurology opens the possibility of detecting structural alterations in the early stages of the disease, which highlights FD as a potential diagnostic and prognostic tool in clinical practice.

Alzheimer's disease cortical morphological phenotypes are associated with TOMM40'523-APOE haplotypes

Both the APOE ε4 and TOMM40 rs10524523 ("523") genes have been associated with risk for Alzheimer's disease (AD) and neuroimaging biomarkers of AD. No studies have investigated the relationship of TOMM40'523-APOE ε4 on the structural complexity of the brain in AD individuals. We quantified brain morphology and multiple cortical attributes in individuals with mild cognitive impairment (MCI) and AD, then tested whether APOE ε4 or TOMM40 poly-T genotypes were related to AD morphological biomarkers in cognitively unimpaired (CU) and MCI/AD individuals. We identified several AD-specific phenotypes in brain morphology and found that TOMM40 poly-T short alleles are associated with early, AD-specific brain morphological differences in healthy aging. We observed decreased cortical thickness, sulcal depth, and fractal dimension in CU individuals with the poly-T short alleles. Moreover, in MCI/AD participants, the APOE ε4 (TOMM40 L) individuals had a higher rate of gene-related morphological markers indicative of AD. Our data suggest that TOMM40'523 is associated with early brain structure variations in the precuneus, temporal, and limbic cortices.

Brain Complexity and Psychiatric Disorders

Objective: In recent years, researchers and neuroscientists have begun to use a variety of nonlinear techniques for analyzing neurophysiologic signals derived from fMRI, MEG, and EEG in order to describe the complex dynamical aspects of neural mechanisms. In this work, we first attempted to describe different algorithms to estimate neural complexity in a simple manner understandable for psychiatrists, psychologists, and neuroscientists. Then, we reviewed the findings of the brain complexity analysis in psychiatric disorders and their clinical implications. Method : A non-systematic comprehensive literature search was conducted for original studies on the complexity analysis of neurophysiological signals such as electroencephalogram, magnetoencephalogram, and blood-oxygen-level-dependent obtained from functional magnetic resonance imaging or functional near infrared spectroscopy. The search encompassed online scientific databases such as PubMed and Google Scholar. Results: Complexity measures mainly include entropy-based methods, the correlation dimension, fractal dimension, Lempel-Ziv complexity, and the Lyapunov exponent. There are important differences in the physical notions between these measures. Our literature review shows that dementia, autism, and adult ADHD exhibit less complexity in their neurophysiologic signals than healthy controls. However, children with ADHD, drug-naïve young schizophrenic patients with positive symptoms, and patients with mood disorders (i.e., depression and bipolar disorder) exhibit higher complexity in their neurophysiologic signals compared to healthy controls. In addition, contradictory findings still exist in some psychiatric disorders such as schizophrenia regarding brain complexity, which can be due to technical issues, large heterogeneity in psychiatric disorders, and interference of typical factors. Conclusion: In summary, complexity analysis may present a new dimension to understanding psychiatric disorders. While complexity analysis is still far from having practical applications in routine clinical settings, complexity science can play an important role in comprehending the system dynamics of psychiatric disorders.

Cortical signature of depressive symptoms in frontotemporal dementia: A surface-based analysis

BACKGROUND AND OBJECTIVES

Depressive symptoms are frequently reported in patients affected by frontotemporal dementia (FTD). At structural MRI, cortical features of depressed FTD patients have been poorly described. Our objective was to investigate correlations between cortical measures and depression severity in FTD patients.

METHODS

Data were obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) database. We included 98 controls and 92 FTD patients, n = 38 behavioral variant FTD (bvFTD), n = 26 non-fluent variant Primary Progressive Aphasia (nfvPPA), and n = 28 semantic variant Primary Progressive Aphasia (svPPA). Patients underwent clinical and cognitive evaluations, as well as a 3D T1-weighted MRI on a 3 Tesla scanner (Siemens, Trio Tim system). Depression was evaluated by means of Geriatric Depression Scale (GDS). Surface-based analysis was performed on T1-weighted images to evaluate cortical thickness, a measure of gray matter integrity, and local gyrification index (lGI), a quantitative metric of cortical folding.

RESULTS

Patients affected by svPPA were more depressed than controls at NPI and depression severity at GDS was higher in svPPA and bvFTD. Severity of depression correlated with a decrease in lGI in left precentral and superior frontal gyrus, supramarginal and postcentral gyrus and right precentral, supramarginal, superior parietal and superior frontal gyri. Furthermore, depression severity correlated positively with cortical thickness in the left medial orbitofrontal cortex.

DISCUSSION

We found that lGI was associated with depressive symptoms over brain regions involved in the pathophysiology of major depressive disorder. This finding provides novel insights into the mechanisms underlying psychiatric symptoms in FTD.

Cortical morphological changes in multiple sclerosis patients: a study of cortical thickness, sulcal depth, and local gyrification index

PURPOSE

Multiple sclerosis (MS) is a disease that progresses not only with demyelination but also with neurodegeneration. One of the goals of drug treatment in MS is to prevent neurodegeneration. Cortical thickness (CT), sulcal depth (SD), and local gyrification index (LGI) are indicators related to neurodegeneration. The aim of this study is to investigate changes in CT, SD, and LGI in patients with relapsing-remitting MS (RRMS).

METHODS

T1 images of 74 RRMS patients and 65 healthy controls were used. T1 hypointense areas in RRMS patients were corrected using fully automated methods. CT, SD, and LGI were calculated for each patient.

RESULTS

RRMS patients showed widespread cortical thinning, especially in bilateral temporoparietal areas, decreased SD in bilateral supramarginal gyrus, superior temporal gyrus, postcentral gyrus, and transverse temporal gyrus, and decreased LGI, especially in the left posterior cingulate gyrus and insula. The decrease in cortical thickness was associated with the number of attacks and lesion volume. EDSS was related to CT in the right lingual, inferior temporal, and fusiform gyrus. The LGI was correlated with T2 lesion volume in bilateral insula, with EDSS in the right insula and transverse and superior temporal gyri, and with the number of attacks in the right paracentral gyrus and pre-cuneus. However, SD did not show any correlation with EDSS, T2 lesion volume, or the number of attacks.

CONCLUSION

Our results demonstrate widespread cortical thinning, decreased sulcal depth in local areas, and decreased gyrification in folds in RRMS patients, which are related to clinical parameters.

Voxel-Based and Surface-Based Morphometry Analysis in Patients with Pathologically Confirmed Argyrophilic Grain Disease and Alzheimer’s Disease

Background: Due to clinicoradiological similarities, including amnestic cognitive impairment and limbic atrophy, differentiation of argyrophilic grain disease (AGD) from Alzheimer’s disease (AD) is often challenging. Minimally invasive biomarkers, especially magnetic resonance imaging (MRI), are valuable in routine clinical practice. Although it is necessary to explore radiological clues, morphometry analyses using new automated analytical methods, including whole-brain voxel-based morphometry (VBM) and surface-based morphometry (SBM), have not been sufficiently investigated in patients with pathologically confirmed AGD and AD. Objective: This study aimed to determine the volumetric differences in VBM and SBM analyses between patients with pathologically confirmed AGD and AD. Methods: Eight patients with pathologically confirmed AGD with a lower Braak neurofibrillary tangle stage (<III), 11 patients with pathologically confirmed AD without comorbid AGD, and 10 healthy controls (HC) were investigated. Gray matter volumetric changes in VBM and cortical thickness changes in SBM were compared between the two patient groups (i.e., AGD and AD) and the HC group. Results: In contrast to widespread gray matter volume or cortical thickness loss in the bilateral limbic, temporoparietal, and frontal lobes of the AD group, these were limited, especially in the limbic lobes, in the AGD group, compared with that of the HC group. Although bilateral posterior dominant gray matter volume loss was identified in the AD group compared with the AGD group on VBM, there was no significant cluster between these patient groups on SBM. Conclusion: VBM and SBM analyses both showed a different distribution of atrophic changes between AGD and AD.

Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is associated with marked brain atrophy. While commonly used structural MRI imaging methods do not account for the complexity of human brain morphology, little is known about the longitudinal changes of cortical geometry and their relationship with cognitive decline in subjects with AD.

METHODS

Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to perform two-sample t-tests to investigate longitudinal changes of cortical thickness (CTh) and three surface-based morphometry measures: fractal dimension (i.e. cortical complexity; FD), gyrification index (GI), and sulcal depth (SD) in subjects with AD, amnestic mild cognitive impairment (aMCI) in comparison to cognitively unimpaired controls (CU) in baseline and 2-year follow-up sMRI scans. In addition, correlations of the morphological measures with two-year cognitive decline as assessed by the modified AD Assessment Scale-Cognitive Subscale (ADAS-Cog 11) were calculated via regression analyses.

RESULTS

Compared to CU, both AD and aMCI showed marked decreases in CTh. In contrast, analyses of FD and GI yielded a more nuanced decline of the respective measures with some areas showing increases in FD and GI. Overall changes in FD and GI were more pronounced in AD as compared to aMCI. Analyses of SD yielded widespread decreases. Interestingly, cognitive decline corresponded well with CTh declines in aMCI but not AD, whereas changes in FD corresponded with AD only but not aMCI, whereas GI and SD were associated with cognitive decline in aMCI and AD.

CONCLUSION

Patterns of longitudinal changes in FD, GI and SD were only partially overlapping with CTh reductions. In AD, surface-based morphometry measures for brain-surface complexity showed better correspondence than CTh with cognitive decline over a two-year period of time. Being drawn from measures reflecting changes in more intricate aspects of human brain morphology, these data provide new insight into the complexity of AD-related brain atrophy and its relationship with cognitive decline.

Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration

BACKGROUND

Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park-).

METHODS

Thirty FTD patients (12 Park+, 18 Park-) and 30 healthy controls were enrolled and underwent 3T MRI scanning. MRI analyses included: (1) surface-based morphometry; (2) basal ganglia and thalamic volumetry; (3) diffusion-based probabilistic tractography of fiber tracts connecting the supplementary motor area (SMA) and primary motor cortex (M1) to the putamen, globus pallidus, and thalamus; and (4) resting-state functional connectivity (RSFC) between the aforementioned regions.

RESULTS

Patients in Park+ and Park- groups showed comparable patterns of cortical thinning in frontotemporal regions and reduced thalamic volume with respect to controls. Only Park+ patients showed reduced putaminal volume and reduced fractional anisotropy of the fibers connecting the SMA to the globus pallidus, putamen, and thalamus, with respect to controls. Park+ patients also showed decreased RSFC between the SMA and putamen with respect to both Park- patients and controls.

CONCLUSIONS

The present findings support the hypothesis that FTD patients with parkinsonism are characterized by neurodegenerative processes in specific corticobasal ganglia-thalamocortical motor loops.

Altered cortical gyrification, sulcal depth, and fractal dimension in the autism spectrum disorder comorbid attention-deficit/hyperactivity disorder than the autism spectrum disorder

Autism spectrum disorder (ASD) frequently occurs accompanied by attention-deficit/hyperactivity disorder (ADHD), which catches increasing attention. The comorbid diagnosis of ASD with ADHD (ASD + ADHD) is permitted in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). However, compared to autism spectrum disorder without other symptoms (ASD-only), the special neural underpinnings in ASD+ADHD remain unclear. Therefore, this study aimed to uncover the differences in cortical complexity between ASD + ADHD and ASD-only patients. A total of 114 ASD participants (i.e. containing 40 ASD + ADHD and 74 ASD-only participants) with T1-weighted magnetic resonance images were collected from the Autism Brain Imaging Data Exchange II. Afterward, a surface-based morphometry method was carried out to compare the cortical complexity (i.e. gyrification index, fractal dimension, and sulcal depth) between the ASD + ADHD and ASD-only cohorts. Results showed the increased fractal dimension in the right fusiform gyrus of the ASD + ADHD cohort in comparison to the ASD-only cohort. Moreover, the ASD + ADHD cohort exhibited increased sulcal depth in the left middle temporal gyrus/inferior temporal gyrus and right middle temporal gyrus compared to the ASD-only cohort. Last but not least, the increased gyrification index in the insula/postcentral gyrus was observed in the ASD + ADHD cohort in comparison to the ASD-only cohort. Overall, the present study contributes to the delineation of particular structural abnormalities in ASD + ADHD than ASD-only, enriching the evidence of the combined phenotype of ASD + ADHD.

Decreased Brain Structural Network Connectivity in Patients with Mild Cognitive Impairment: A Novel Fractal Dimension Analysis

Mild cognitive impairment (MCI) is widely regarded to be the intermediate stage to Alzheimer's disease. Cerebral morphological alteration in cortical subregions can provide an accurate predictor for early recognition of MCI. Thirty patients with MCI and thirty healthy control subjects participated in this study. The Desikan-Killiany cortical atlas was applied to segment participants' cerebral cortex into 68 subregions. A complexity measure termed fractal dimension (FD) was applied to assess morphological changes in cortical subregions of participants. The MCI group revealed significantly decreased FD values in the bilateral temporal lobes, right parietal lobe including the medial temporal, fusiform, para hippocampal, and also the orbitofrontal lobes. We further proposed a novel FD-based brain structural network to compare network parameters, including intra- and inter-lobular connectivity between groups. The control group had five modules, and the MCI group had six modules in their brain networks. The MCI group demonstrated shrinkage of modular sizes with fewer components integrated, and significantly decreased global modularity in the brain network. The MCI group had lower intra- and inter-lobular connectivity in all lobes. Between cerebral lobes, the MCI patients may maintain nodal connections between both hemispheres to reduce connectivity loss in the lateral hemispheres. The method and results presented in this study could be a suitable tool for early detection of MCI.

Alterations of peripheral cytokines, BDNF, and surface-based morphometry indices in T2DM patients without cognitive impairment

Purpose

This study aimed to investigate potential biological mechanisms underlying cognitive function alterations in Type 2 diabetes mellitus (T2DM) patients by integrating cortical morphology with peripheral cytokine levels and brain-derived neurotrophic factor (BDNF) levels, and to offer potential insights for the early detection of T2DM-related cognitive impairment.

Methods

This study included 16 T2DM patients with a Montreal Cognitive Assessment (MoCA) score of at least 26 points, as well as 16 healthy controls with normal cognitive function. The participants also completed the digit span test and digit symbol substitution test. Participants' serum levels of Interleukin 4 (IL-4), IL-6, IL-10, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and BDNF were also examined. Each subject underwent a high-resolution 3T structural brain MRI scan. Based on the aparc. a2009s atlas, we calculated the cortical thickness, sulcus depth, gyrification index, and fractal dimension for each participant using surface-based morphometry (SBM). Correlation analysis between cognitive measures, serum levels of cytokines and BDNF, and SBM indices were further performed.

Results

The levels of IL-4 and BDNF showed significant group differences. In the T2DM group, the sulcus depth exhibited a significant decrease in the left transverse frontopolar gyri and sulci, as well as in the right pole-occipital; the fractal dimension showed a significant increase in the right posterior-dorsal part of the cingulate gyrus; and the gyrification index significantly increased in the left inferior part of the precentral sulcus and right triangular part of the inferior frontal gyrus. Correlation analysis revealed a significant positive correlation between IL-10 levels and the sulcus depth of left transverse frontopolar gyri and sulci; a significant positive correlation between the sulcus depth of the right pole-occipital and the digit span test-forward scores, and a significant negative correlation between the gyrification index of the left inferior part of the precentral sulcus and the digit span test-backward scores among T2DM participants.

Conclusion

T2DM patients without cognitive impairment displayed reductions in IL 4 and BDNF levels, as well as significant alterations in their SBM indices, indicating that prior to the emergence of cognitive impairment, the SBM indices, peripheral cytokines, and BDNF may have altered in T2DM patients. IL-10 may lessen inflammation-related brain edema and preserve sulcus depth in T2DM patients through its anti-inflammatory activity.

A new strategy for the early detection of alzheimer disease stages using multifractal geometry analysis based on K-Nearest Neighbor algorithm

Alzheimer's Disease (AD) is considered one of the most diseases that much prevalent among elderly people all over the world. AD is an incurable neurodegenerative disease affecting cognitive functions and were characterized by progressive and collective functions deteriorating. Remarkably, early detection of AD is essential for the development of new and invented treatment strategies. As Dementia causes irreversible damage to the brain neurons and leads to changes in its structure that can be described adequately within the framework of multifractals. Hence, the present work focus on developing a promising and efficient computing technique to pre-process and classify the AD disease especially in the early stages using multifractal geometry to extract the most changeable features due to AD. Then, A machine learning classification algorithm (K-Nearest Neighbor) has been implemented in order to classify and detect the main four early stages of AD. Two datasets have been used to ensure the validation of the proposed methodology. The proposed technique has achieved 99.4% accuracy and 100% sensitivity. The comparative results show that the proposed classification technique outperforms is recent techniques in terms of performance measures.

Reduced cortical complexity in patients with end-stage kidney disease prior to dialysis initiation

End-stage kidney disease (ESKD) is associated with cognitive impairment (CI) and affects different aspects of cortical morphometry, but where these changes converge remains unclear. Fractal dimension (FD) is used to represent cortical complexity (CC), which describes the structural complexity of the cerebral cortex by integrating different cortical morphological measures. This study aimed to investigate changes in CC in patients with ESKD prior to initiation of dialysis and to evaluate the relationship between changes in CC, cognitive performance, and uremic toxins. Forty-nine patients with ESKD naive to dialysis and 31 healthy controls (HCs) were assessed using structural magnetic resonance imaging (MRI) and cognitive tests, including evaluations of global cognitive function, memory, and executive function. Clinical laboratory blood tests were performed on all patients with ESKD, including measurement of nine uremic toxin-related indices. CC was measured using MRI data to determine regional FD values. We estimated the association between cognitive performance, uremic toxin levels, and CC changes. Compared to HCs, patients with ESKD showed significantly lower CC in the left precuneus (p = 0.006), left middle temporal cortex (p = 0.010), and left isthmus cingulate cortex (p = 0.018). Furthermore, lower CC in the left precuneus was associated with impaired long-term delayed memory (Pearson r = 0.394, p = 0.042) in patients with ESKD. Our study suggests that regional decreases in CC are an additional characteristic of patients with ESKD naive to dialysis, related to impaired long-term memory performance. These findings may help further understand the underlying neurobiological mechanisms between brain structural changes and CI in patients with ESKD.

The Parietal Lobe in Alzheimer’s Disease and Blindness

The progressive aging of the population will notably increase the burden of those diseases which leads to a disabling situation, such as Alzheimer’s disease (AD) and ophthalmological diseases that cause a visual impairment (VI). Eye diseases that cause a VI raise neuroplastic processes in the parietal lobe. Meanwhile, the aforementioned lobe suffers a severe decline throughout AD. From this perspective, diving deeper into the particularities of the parietal lobe is of paramount importance. In this article, we discuss the functions of the parietal lobe, review the parietal anatomical and pathophysiological peculiarities in AD, and also describe some of the changes in the parietal region that occur after VI. Although the alterations in the hippocampus and the temporal lobe have been well documented in AD, the alterations of the parietal lobe have been less thoroughly explored. Recent neuroimaging studies have revealed that some metabolic and perfusion impairments along with a reduction of the white and grey matter could take place in the parietal lobe during AD. Conversely, it has been speculated that blinding ocular diseases induce a remodeling of the parietal region which is observable through the improvement of the integration of multimodal stimuli and in the increase of the volume of this cortical region. Based on current findings concerning the parietal lobe in both pathologies, we hypothesize that the increased activity of the parietal lobe in people with VI may diminish the neurodegeneration of this brain region in those who are visually impaired by oculardiseases.

Cognitive Reserve Modulates Brain Structure and Cortical Architecture in the Alzheimer's Disease

BACKGROUND

Cognitive reserve (CR) explains the individual resilience to neurodegeneration.

OBJECTIVE

The present study investigated the effect of CR in modulating brain cortical architecture.

METHODS

278 individuals [110 Alzheimer's disease (AD), 104 amnestic mild cognitive impairment (aMCI) due to AD, 64 healthy subjects (HS)] underwent a neuropsychological evaluation and 3T-MRI. Cortical thickness (CTh) and fractal dimension (FD) were assessed. Years of formal education were used as an index of CR by which participants were divided into high and low CR (HCR and LCR). Within-group differences in cortical architecture were assessed as a function of CR. Associations between cognitive scores and cortical measures were also evaluated.

RESULTS

aMCI-HCR compared to aMCI-LCR patients showed significant decrease of CTh in the right temporal and in the left prefrontal lobe. Moreover, they showed increased FD in the right temporal and in the left temporo-parietal lobes. Patients with AD-HCR showed reduced CTh in several brain areas and reduced FD in the left temporal cortices when compared with AD-LCR subjects. HS-HCR showed a significant increase of CTh in prefrontal areas bilaterally, and in the right parieto-occipital cortices. Finally, aMCI-HCR showed significant positive associations between brain measures and memory and executive performance.

CONCLUSION

CR modulates the cortical architecture at pre-dementia stage only. Indeed, only patients with aMCI showed both atrophy (likely due to neurodegeneration) alongside richer brain folding (likely due to reserve mechanisms) in temporo-parietal areas. This opposite trend was not observed in AD and HS. Our data confirm the existence of a limited time-window for CR modulation at the aMCI stage.

Longitudinal Effects of Combination Antiretroviral Therapy on Cognition and Neuroimaging Biomarkers in Treatment-Naïve People with HIV

BACKGROUND AND OBJECTIVES

While combination antiretroviral therapy (cART) has dramatically increased the life expectancy of people with HIV (PWH), nearly 50% develop HIV-associated neurocognitive disorders (HAND)¹. This may be due to previously uncontrolled HIV viral replication, immune activation maintained by residual viral replication² or activation from other sources^{3, 4}, or cART-associated neurotoxicity⁵. The aim of this study was to determine the effect of cART on cognition and neuroimaging biomarkers markers in people with HIV (PWH) before and after initiation of cART compared to HIV negative controls (HC) and HIV elite controllers (EC) who remain untreated.

METHODS

We recruited three groups of participants from the University of Rochester, McGovern Medical School and SUNY Upstate Medical University: 1) ART-treatment-naïve PWH; 2) age-matched HC; and 3) EC. Participants underwent brain MRI and clinical and neuropsychological assessments at baseline, one year, and two years. PWH were also assessed 12 weeks after initiating cART. Volumetric analysis and fractal dimensionality (FD) were calculated for cortical and subcortical regions. Mixed effect regressions examined the effect of group and imaging variables on cognition.

RESULTS

We enrolled 47 PWH, 58 HC, and 10 EC. At baseline, PWH had worse cognition and lower cortical volumes than HC. Cognition improved following initiation of cART and remained stable over time. Greater cortical thickness was associated with better cognition at baseline; greater FD of parietal, temporal and occipital lobes was associated with better cognition at baseline and longitudinally. At baseline, EC had worse cognition, lower cortical thickness and lower FD in all four lobes and caudate than PWH and HC. Greater cortical thickness, hippocampal volumes and FD of frontal, temporal and occipital lobes were associated with better cognition longitudinally.

CONCLUSIONS

Initiation of cART in PWH is associated with improvement in brain structure and cognition. However, significant differences persist over time compared to HC. Similar trends in EC suggest that results are due to HIV infection rather than treatment. Stronger associations between cognition and FD suggest this imaging metric may be a more sensitive marker of neuronal injury than cortical thickness and volumetric measures.

Fractal dimension of the brain in neurodegenerative disease and dementia: A systematic review

Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.

Cortical Complexity Estimation Using Fractal Dimension: A Systematic Review of the Literature on Clinical and Nonclinical Samples

Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty‐two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure.

Fractal dimension (FD) is a useful tool for the assessment of cortical complexity. In healthy controls, FD is associated with development, aging and cognition. Alterations in FD have been observed in different neurological and psychiatric disorders.

MDReg‐Net: Multi‐resolution diffeomorphic image registration using fully convolutional networks with deep self‐supervision

We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks (FCNs) under a self‐supervised learning setting. Particularly, a deep neural network is trained to estimate diffeomorphic spatial transformations between pairs of images by maximizing an image‐wise similarity metric between fixed and warped moving images, similar to those adopted in conventional image registration algorithms. The network is implemented in a multi‐resolution image registration framework to optimize and learn spatial transformations at different image resolutions jointly and incrementally with deep self‐supervision in order to better handle large deformation between images. A spatial Gaussian smoothing kernel is integrated with the FCNs to yield sufficiently smooth deformation fields for diffeomorphic image registration. The spatial transformations learned at coarser resolutions are utilized to warp the moving image, which is subsequently used as input to the network for learning incremental transformations at finer resolutions. This procedure proceeds recursively to the full image resolution and the accumulated transformations serve as the final transformation to warp the moving image at the finest resolution. Experimental results for registering high‐resolution 3D structural brain magnetic resonance (MR) images have demonstrated that image registration networks trained by our method obtain robust, diffeomorphic image registration results within seconds with improved accuracy compared with state‐of‐the‐art image registration algorithms.

Aberrant Changes in Cortical Complexity in Right-Onset Versus Left-Onset Parkinson's Disease in Early-Stage

There is increasing evidence to show that motor symptom lateralization in Parkinson’s disease (PD) is linked to non-motor features, progression, and prognosis of the disease. However, few studies have reported the difference in cortical complexity between patients with left-onset of PD (LPD) and right-onset of PD (RPD). This study aimed to investigate the differences in the cortical complexity between early-stage LPD and RPD. High-resolution T1-weighted magnetic resonance images of the brain were acquired in 24 patients with LPD, 34 patients with RPD, and 37 age- and sex-matched healthy controls (HCs). Cortical complexity including gyrification index, fractal dimension (FD), and sulcal depth was analyzed using surface-based morphometry via CAT12/SPM12. Familywise error (FWE) peak-level correction at p < 0.05 was performed for significance testing. In patients with RPD, we found decreased mean FD and mean sulcal depth in the banks of the left superior temporal sulcus (STS) compared with LPD and HCs. The mean FD in the left superior temporal gyrus (STG) was decreased in RPD compared with HCs. However, in patients with LPD, we did not identify significantly abnormal cortical complex change compared with HCs. Moreover, we observed that the mean FD in STG was negatively correlated with the 17-item Hamilton Depression Scale (HAMD) among the three groups. Our findings support the specific influence of asymmetrical motor symptoms in cortical complexity in early-stage PD and reveal that the banks of left STS and left STG might play a crucial role in RPD.

Preoperative Peripheral Nerve Blocks in Orthopaedic Trauma Surgery: A Guide to Diagnosis-Based Treatment

Perioperative pain management remains an important focus of both patient and provider attention in orthopaedic trauma surgery. There is a constant effort to improve pain management while decreasing opioid consumption, and peripheral nerve blocks are a safe and effective way to achieve these two goals. This is particularly relevant because more procedures are being done in outpatient surgery centers, and the need to safely provide analgesia without the systemic risk of opioid medications is paramount. The primary goal of this article was to describe the diagnosis-based approach for the utilization of preoperative peripheral nerve blocks in perioperative care for orthopaedic trauma surgery procedures based on the experience and current practice at our center.

Exploring Signatures of Neurodegeneration in Early-Onset Older-Age Bipolar Disorder and Behavioral Variant Frontotemporal Dementia

Introduction: Older-age bipolar disorder (OABD) may involve neurocognitive decline and behavioral disturbances that could share features with the behavioral variant of frontotemporal dementia (bvFTD), making the differential diagnosis difficult in cases of suspected dementia.

Objective: To compare the neuropsychological profile, brain morphometry, and structural connectivity patterns between patients diagnosed with bvFTD, patients classified as OABD with an early onset of the disease (EO-OABD), and healthy controls (HC).

Methods: bvFTD patients (n = 25, age: 66 ± 7, female: 64%, disease duration: 6 ± 4 years), EO-OABD patients (n = 17, age: 65 ± 9, female: 71%, disease duration: 38 ± 8 years), and HC (n = 28, age: 62 ± 7, female: 64%) were evaluated through neuropsychological tests concerning attention, memory, executive function, praxis, and language. Brain morphometry was analyzed through surface-based morphometry (SBM), while structural brain connectivity was assessed through diffusion tensor imaging (DTI).

Results: Both bvFTD and EO-OABD patients showed lower performance in neuropsychological tests of attention, verbal fluency, working memory, verbal memory, and praxis than HC. Comparisons between EO-OABD and bvFTD showed differences limited to cognitive flexibility delayed recall and intrusion errors in the memory test. SBM analysis demonstrated that several frontal, temporal, and parietal regions were altered in both bvFTD and EO-OABD compared to HC. In contrast, comparisons between bvFTD and EO-OABD evidenced differences exclusively in the right temporal pole and the left entorhinal cortex. DTI analysis showed alterations in association and projection fibers in both EO-OABD and bvFTD patients compared to HC. Commissural fibers were found to be particularly affected in EO-OABD. The middle cerebellar peduncle and the pontine crossing tract were exclusively altered in bvFTD. There were no significant differences in DTI analysis between EO-OABD and bvFTD.

Discussion: EO-OABD and bvFTD may share an overlap in cognitive, brain morphometry, and structural connectivity profiles that could reflect common underlying mechanisms, even though the etiology of each disease can be different and multifactorial.

Cortical structure and the risk for Alzheimer's disease: a bidirectional Mendelian randomization study

Progressive loss of neurons in a specific brain area is one of the manifestations of Alzheimer's disease (AD). Much effort has been devoted to investigating brain atrophy and AD. However, the causal relationship between cortical structure and AD is not clear. We conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationship between cortical structure (surface area and thickness of the whole cortex and 34 cortical regions) and AD risk. Genetic variants used as instruments came from a large genome-wide association meta-analysis of cortical structure (33,992 participants of European ancestry) and AD (AD and AD-by-proxy, 71,880 cases, 383,378 controls). We found suggestive associations of the decreased surface area of the temporal pole (OR (95% CI): 0.95 (0.9, 0.997), p = 0.04), and decreased thickness of cuneus (OR (95% CI): 0.93 (0.89, 0.98), p = 0.006) with higher AD risk. We also found a suggestive association of vulnerability to AD with the decreased surface area of precentral (β (SE): -43.4 (21.3), p = 0.042) and isthmus cingulate (β (SE): -18.5 (7.3), p = 0.011). However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and AD met the threshold. We show suggestive evidence of an association of the atrophy of the temporal pole and cuneus with higher AD risk. In the other direction, there was a suggestive causal relationship between vulnerability to AD and the decreased surface area of the precentral and isthmus cingulate. Our findings shed light on the associations of cortical structure with the occurrence of AD.

Novel Volumetric and Surface-Based Magnetic Resonance Indices of the Aging Brain - Does Male and Female Brain Age in the Same Way?

Introduction: Novel post-processing methods allow not only for assessment of brain volumetry or cortical thickness based on magnetic resonance imaging (MRI) but also for more detailed analysis of cortical shape and complexity using parameters such as sulcal depth, gyrification index, or fractal dimension. The aim of this study was to analyze changes in brain volumetry and other cortical indices during aging in men and women.

Material and Methods: Material consisted of 697 healthy volunteers (aged 38–80 years; M/F, 264/443) who underwent brain MRI using a 1.5-T scanner. Voxel-based volumetry of total gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) was performed followed by assessment of cortical parameters [cortical thickness (CT), sulcal depth (SD), gyrification index (GI), and fractal dimension (FD)] in 150 atlas locations using surface-based morphometry with a region-based approach. All parameters were compared among seven age groups (grouped every 5 years) separately for men and women. Additionally, percentile curves for men and women were provided for total volumes of GM, WM, and CSF.

Results: In men and women, a decrease in GM and WM volumes and an increase in CSF volume seem to progress slowly since the age of 45. In men, significant GM and WM loss as well as CSF increase start above 55 years of age, while in women, significant GM loss starts above 50 and significant WM loss as well as CSF increase above 60. CT was found to significantly decrease with aging in 39% of locations in women and in 36% of locations in men, SD was found to increase in 13.5% of locations in women and in 1.3% of locations in men, GI was decreased in 3.4% of locations in women and in 2.0% of locations in men, and FD was changed in 2.7% of locations in women compared to 2.0% in men.

Conclusions: Male and female brains start aging at the similar age of 45. Compared to men, in women, the cortex is affected earlier and in the more complex pattern regarding not only cortical loss but also other alterations within the cortical shape, with relatively longer sparing of WM volume.

Midlife Cardiovascular Fitness Is Reflected in the Brain's White Matter

Disappointing results from clinical trials designed to delay structural brain decline and the accompanying increase in risk for dementia in older adults have precipitated a shift in testing promising interventions from late in life toward midlife before irreversible damage has accumulated. This shift, however, requires targeting midlife biomarkers that are associated with clinical changes manifesting only in late life. Here we explored possible links between one putative biomarker, distributed integrity of brain white matter, and two intervention targets, cardiovascular fitness and healthy lifestyle behaviors, in midlife. At age 45, fractional anisotropy (FA) derived from diffusion weighted MRI was used to estimate the microstructural integrity of distributed white matter tracts in a population-representative birth cohort. Age-45 cardiovascular fitness (VO₂Max; N = 801) was estimated from heart rates obtained during submaximal exercise tests; age-45 healthy lifestyle behaviors were estimated using the Nyberg Health Index (N = 854). Ten-fold cross-validated elastic net predictive modeling revealed that estimated VO₂Max was modestly associated with distributed FA. In contrast, there was no significant association between Nyberg Health Index scores and FA. Our findings suggest that cardiovascular fitness levels, but not healthy lifestyle behaviors, are associated with the distributed integrity of white matter in the brain in midlife. These patterns could help inform future clinical intervention research targeting ADRDs.