Visual rating method and tensor-based morphometry in the diagnosis of mild cognitive impairment and Alzheimer's disease: a comparative magnetic resonance imaging study

A comprehensive investigation of the associations between tensor-based morphometry indices and executive functions, memory, language, and visuospatial abilities in patients in the Alzheimer's disease continuum

OBJECTIVES

Based on the literature, tensor-based morphometry (TBM) parameters were related to neurocognitive functions such as memory, learning, language ability, and executive functions. The present study aims to evaluate the associations between TBM indices with executive functions, memory, language, and visuospatial abilities and the value of TBM in the clinical diagnosis of Alzheimer's disease (AD) among individuals with Alzheimer's disease continuum and mild cognitive impairment (MCI) from Alzheimer's Disease Neuroimaging Initiative (ADNI).

METHODS

The authors used ADNI-memory (ADNI-MEM), ADNI-executive functions (ADNI-EF), ADNI-language (ADNI-LAN), and ADNI-visuospatial (ADNI-VS) composite scores. TBM parameters, including measure 1, which represents average within a statistically defined region-of-interest inside the temporal lobes and measure 2 which indicates average within an anatomically defined region-of-interest including bilateral temporal lobes were utilized in the current study. Statistical analysis was performed using IBM SPSS Statistics version 26, and Pearson's correlation, Bonferroni's correction, and multiple linear regression were utilized for data analysis. P <0.05 was considered statistically significant.

RESULTS

After screening 800 participants, 270 (151 men, 119 women) were selected for a study with TBM scores and cognition-related assessments at 6, 12, and 24 months. Groups included healthy controls (n=53), MCI (n=158), and Alzheimer's Disease (AD) (n=59). TBM indices correlated with cognitive scores in MCI and AD groups but not healthy controls. Changes in TBM indices and cognitive scores were significantly correlated in MCI and AD groups over 24 months. TBM indices were weak predictors of cognitive decline at all time points.

CONCLUSIONS

TBM can help physicians diagnose MCI and AD early. However, TBM could not strongly predict cognitive functions decline at all time points.

Brain ventricles, CSF and cognition: a narrative review

The brain ventricles are structures that have been related to cognition since antiquity. They are essential components in the development and maintenance of brain functions. The aging process runs with the enlargement of ventricles and is related to a less selective blood-cerebrospinal fluid barrier and then a more toxic cerebrospinal fluid environment. The study of brain ventricles as a biological marker of aging is promissing because they are structures easily identified in neuroimaging studies, present good inter-rater reliability, and measures of them can identify brain atrophy earlier than cortical structures. The ventricular system also plays roles in the development of dementia, since dysfunction in the clearance of beta-amyloid protein is a key mechanism in sporadic Alzheimer's disease. The morphometric and volumetric studies of the brain ventricles can help to distinguish between healthy elderly and persons with mild cognitive impairment (MCI) and dementia. Brain ventricle data may contribute to the appropriate allocation of individuals in groups at higher risk for MCI-dementia progression in clinical trials and to measuring therapeutic responses in these studies, as well as providing differential diagnosis, such as normal pressure hydrocephalus. Here, we reviewed the pathophysiology of healthy aging and cognitive decline, focusing on the role of the choroid plexus and brain ventricles in this process.

Application of GIS and Machine Learning to Predict Flood Areas in Nigeria

Floods are one of the most devastating forces in nature. Several approaches for identifying flood-prone locations have been developed to reduce the overall harmful impacts on humans and the environment. However, due to the increased frequency of flooding and related disasters, coupled with the continuous changes in natural and social-economic conditions, it has become vital to predict areas with the highest probability of flooding to ensure effective measures to mitigate impending disasters. This study predicted the flood susceptible areas in Nigeria based on historical flood records from 1985~2020 and various conditioning factors. To evaluate the link between flood incidence and the fifteen (15) explanatory variables, which include climatic, topographic, land use and proximity information, the artificial neural network (ANN) and logistic regression (LR) models were trained and tested to develop a flood susceptibility map. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to evaluate both model accuracies. The results show that both techniques can model and predict flood-prone areas. However, the ANN model produced a higher performance and prediction rate than the LR model, 76.4% and 62.5%, respectively. In addition, both models highlighted that those areas with the highest susceptibility to flood are the low-lying regions in the southern extremities and around water areas. From the study, we can establish that machine learning techniques can effectively map and predict flood-prone areas and serve as a tool for developing flood mitigation policies and plans.

Combining Visual Rating Scales for Medial Temporal Lobe Atrophy and Posterior Atrophy to Identify Amnestic Mild Cognitive Impairment from Cognitively Normal Older Adults: Evidence Based on Two Cohorts

BACKGROUND

Visual rating scales for medial temporal lobe atrophy (MTA) and posterior atrophy (PA) have been reported to be useful for Alzheimer's disease diagnosis in routine clinical practice.

OBJECTIVE

To investigate the efficacy of combined MTA and PA visual rating scales to discriminate amnestic mild cognitive impairment (aMCI) patients from healthy controls.

METHODS

This study included T1-weighted MRI images from two different cohorts. In the first cohort, we recruited 73 patients with aMCI and 48 group-matched cognitively normal controls for training and validation. Visual assessments of MTA and PA were carried out for each participant. Global gray matter volume and density were estimated using voxel-based morphometry analysis as the objective reference. We investigated the discriminative power of a single visual rating scale and the combination of the MTA and PA rating scales for identifying aMCI. The second cohort, consisting of 33 aMCI patients and 45 controls, was used to verify the reliability of the visual assessments.

RESULTS

Compared with the single visual rating scale, the combination of the MTA and PA exhibited the best discriminative power, with an AUC of 0.818±0.041, which was similar to the diagnostic accuracy of the gray matter volumetric measures. The discriminative power of the combined MTA and PA was verified in the second cohort (AUC 0.824±0.058).

CONCLUSION

The combined MTA and PA rating scales demonstrated practical diagnostic value for distinguishing aMCI patients from controls, suggesting its potential to serve as a convenient and reproducible method to assess the degree of atrophy in clinical settings.

Evaluation of MR Visual Rating Scales in Major Forms of Dementia

Objective  The aim of the study is to visually rate major forms of dementia using global cortical atrophy (GCA), medial temporal lobe atrophy (MTA), and Fazeka’s scales and Koedam’s score using magnetic resonance imaging (MRI). The purpose is to correlate the visual rating scales (VRS) with severity of dementia.

Materials and Methods  Thirty patients fulfilling DSM 5 (Diagnostic and Statistical Manual of Mental Disorders) criteria for Alzheimer’s dementia (AD), vascular dementia (VaD), and frontotemporal dementia (FTD) underwent MRI brain. Cortical atrophy, medial temporal, and parietal lobe atrophy were assessed using GCA and MTA scales and Koedam’s score, respectively. White matter hyperintensities were assessed using Fazeka’s scale. Correlation between VRS and mini-mental state exam (MMSE) scores was done using Pearson correlation coefficient.

Results  70% of patients had Grade 2 GCA. More patients with AD had higher MTA scores as compared with others with 57% of AD patients showing abnormal for age MTA scores. Fazeka’s scale was abnormal for age in 58.33% of VaD and 57% AD patients. Majority (75%) showing severe parietal atrophy (Grade 3 Koedam’s score) were AD patients. Disproportionate frontal lobe atrophy was seen in all four (100%) FTD patients. Significant negative correlation was seen between MMSE and GCA scores of all patients ( p -value = 0.003) as well as between MTA and MMSE scores in AD patients ( p -value = 0.00095).

Conclusion  Visual rating of MTA is a reliable method for detecting AD and correlates strongly with memory scores. Atrophy of specific regions is seen more commonly in some conditions, for instance, where MTA and parietal atrophy are specific for AD while asymmetric frontal lobe and temporal pole atrophy favor FTD.

Visual rating versus volumetry of regional brain atrophy and longitudinal changes over a 5-year period in an elderly population

INTRODUCTION

The purpose of our study was to compare visual rating and volumetry of brain atrophy in an elderly population over a 5-year period and compare findings with cognitive test results.

MATERIALS AND METHODS

Two hundred and one subjects were examined with magnetic resonance imaging (MRI) of the brain. Visual rating and volumetry were performed in all subjects at ages 75 and 80. Cognitive function at both time points was assessed with the Mini-Mental State Examination (MMSE) and Trail Making Tests A and B (TMT-A and TMT-B). Changes in visual rating and volumetry were compared with changes in cognitive test.

RESULTS

A correlation was found between visual rating of medial temporal lobe atrophy (MTA) and hippocampal volumetry at both time points (rs = -.42 and rs = -.49, p < .001, respectively). The correlation between visual rating of posterior atrophy (PA); frontal atrophy (F-GCA) and volumetry of these brain regions was significant only at age 80 (rs = -.16, p = .02 for PA and rpb = .19, p = .006 for F-GCA). Visual rating showed only a minimal progression of regional atrophy at age 80, whereas volumetry showed 2%-5% decrease in volume depending on brain region. Performance in the MMSE, TMT-A, and TMT-B was virtually unchanged between ages 75 and 80.

CONCLUSION

We found a mild age-associated decrease in regional brain volumes in this healthy cohort with well-preserved cognitive functions. Visual assessment may not be sufficient for detecting mild progression of brain atrophy due to normal aging, whereas volumetry is more sensitive to capture these subtle changes.

Association between Deep Gray Matter Changes and Neurocognitive Function in Mild Cognitive Impairment and Alzheimer's Disease: A Tensor-Based Morphometric MRI Study

BACKGROUND

Atrophy of the deep gray matter (DGM) has been associated with a risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and the degree of cognitive impairment. However, specific knowledge of the associations between degenerative DGM changes and neurocognitive functions remains limited.

OBJECTIVE

To examine degenerative DGM changes and evaluate their association with neurocognitive functions.

METHOD

We examined DGM volume changes with tensor-based morphometry (TBM) and analyzed the relationships between DGM changes and neurocognitive functions in control (n = 58), MCI (n = 38), and AD (n = 58) groups with multiple linear regression analyses.

RESULTS

In all DGM areas, the AD group had the largest changes in TBM volume. The differences in TBM volume changes were larger between the control group and the AD group than between the other pairs of groups. In the AD group, volume changes of the right thalamus were significantly associated with episodic memory, learning, and semantic processing. Significant or trend-level associations were identified between bilateral caudate nucleus changes and episodic memory as well as semantic processing. In the control and MCI groups, very few significant associations emerged.

CONCLUSIONS

Atrophy of the DGM structures, especially the thalamus and caudate nucleus, is related to cognitive impairment in AD. DGM atrophy is associated with tests reflecting both subcortical and cortical cognitive functions.

Longitudinal changes in the brain in mild cognitive impairment: a magnetic resonance imaging study using the visual rating method and tensor-based morphometry

Background Brain atrophy is associated with mild cognitive impairment (MCI), and by using volumetric and visual analyzing methods, it is possible to differentiate between individuals with progressive MCI (MCIp) and stable MCI (MCIs). Automated analysis methods detect degenerative changes in the brain earlier and more reliably than visual methods. Purpose To detect and evaluate structural brain changes between and within the MCIs, MCIp, and control groups during a two-year follow-up period. Material and Methods Brain magnetic resonance imaging (MRI) scans of 11 participants with MCIs, 18 participants with MCIp, and 84 controls were analyzed by the visual rating method (VRM) and tensor-based morphometry (TBM). Results At baseline, both VRM and TBM differentiated the whole MCI group (combined MCIs and MCIp) and the MCIp group from the control group, but they did not differentiate the MCIs group from the control group. At follow-up, both methods differentiated the MCIp group from the control group, but minor differences between the MCIs and control groups were only seen by TBM. Neuropsychological tests did not find differences between the MCIs and control groups at follow-up. Neither method revealed relevant signs of brain atrophy progression within or between MCI subgroups during the follow-up time. Conclusion Both methods are equally good in the evaluation of structural brain changes in MCI if the groups are sufficiently large and the disease progresses to AD. Only TBM disclosed minor atrophic changes in the MCIs group compared to controls at follow-up. The results need to be confirmed with a large patient group and longer follow-up time.

Visual Ratings of Medial Temporal Lobe Atrophy Correlate with CSF Tau Indices in Clinical Variants of Early-Onset Alzheimer Disease

BACKGROUND/AIMS

Prior studies of late-onset Alzheimer disease (AD) have reported that cerebrospinal fluid (CSF) tau levels correlate with hippocampal/medial temporal lobe atrophy. These findings suggest that CSF tau indices in AD may reflect tau-related neurodegeneration in the medial temporal lobe. However, it remains uncertain whether elevated CSF tau levels in the clinically heterogeneous subtypes of early-onset AD (EOAD; amnestic, posterior cortical atrophy [PCA], and logopenic progressive aphasia [LPA]) are attributable to similar underlying mechanisms.

METHODS

We identified 41 EOAD patients (18 amnestic, 14 with LPA, and 9 with PCA) with CSF and brain MRI data. Semiquantitative ratings were used to assess medial temporal lobe atrophy and PCA, which were compared to CSF biomarker indices.

RESULTS

Lower CSF tau levels were seen in PCA relative to amnestic EOAD and LPA, but similar ratings for medial temporal lobe atrophy and PCA were seen across the groups. After adjustments for demographics and cognitive performance, both total (p = 0.004) and hyperphosphorylated (p = 0.026) tau levels correlated with medial temporal lobe atrophy across this EOAD cohort.

CONCLUSIONS

These results replicate prior findings in late-onset AD and support the hypothesis that CSF tau levels primarily reflect tau-related neurodegenerative changes in the hippocampus/medial temporal lobe across the clinical subtypes of EOAD.