Cognitive Profiles and Atrophy Ratings on MRI in Senior Patients With Mild Cognitive Impairment

The impact of medial temporal and parietal atrophy on cognitive function in dementia

Although medial temporal atrophy (MTA) and parietal atrophy (Koedam score) have been used to diagnose Alzheimer's disease (AD), early detection of other dementia types remains elusive. The study aims to investigate the association between these brain imaging markers and cognitive function in dementia. This cross-sectional study collected data from the Memory Clinic of Dr. Sardjito General Hospital Yogyakarta, Indonesia from January 2020 until December 2022. The cut-off value of MTA and Koedam score was set with Receiver Operating Curve. Multivariate analysis was performed to investigate the association between MTA and Koedam score with cognitive function. Of 61 patients, 22.95% had probable AD, 59.01% vascular dementia, and 18.03% mixed dementia. Correlation test showed that MTA and Koedam score were negatively associated with Montreal Cognitive Assessment-Indonesian Version (MoCA-INA) score. MTA score ≥ 3 (AUC 0.69) and Koedam score ≥ 2 (AUC 0.67) were independently associated with higher risk of poor cognitive function (OR 13.54, 95% CI 1.77-103.43, p = 0.01 and OR 5.52, 95% CI 1.08-28.19, p = 0.04). Higher MTA and Koedam score indicate worse cognitive function in dementia. Future study is needed to delineate these findings as prognostic markers of dementia severity.

Combining visual rating scales to identify prodromal Alzheimer's disease and Alzheimer's disease dementia in a population from a low and middle-income country

Background

Many low- and middle-income countries, including Latin America, lack access to biomarkers for the diagnosis of prodromal Alzheimer's Disease (AD; mild cognitive impairment due to AD) and AD dementia. MRI visual rating scales may serve as an ancillary diagnostic tool for identifying prodromal AD or AD in Latin America. We investigated the ability of brain MRI visual rating scales to distinguish between cognitively healthy controls, prodromal AD and AD.

Methods

A cross-sectional study was conducted from a multidisciplinary neurology clinic in Lima, Peru using neuropsychological assessments, brain MRI and cerebrospinal fluid amyloid and tau levels. Medial temporal lobe atrophy (MTA), posterior atrophy (PA), white matter hyperintensity (WMH), and MTA+PA composite MRI scores were compared. Sensitivity, specificity, and area under the curve (AUC) were determined.

Results

Fifty-three patients with prodromal AD, 69 with AD, and 63 cognitively healthy elderly individuals were enrolled. The median age was 75 (8) and 42.7% were men. Neither sex, mean age, nor years of education were significantly different between groups. The MTA was higher in patients with AD (p < 0.0001) compared with prodromal AD and controls, and MTA scores adjusted by age range (p < 0.0001) and PA scores (p < 0.0001) were each significantly associated with AD diagnosis (p < 0.0001) but not the WMH score (p=0.426). The MTA had better performance among ages <75 years (AUC 0.90 [0.85-0.95]), while adjusted MTA+PA scores performed better among ages>75 years (AUC 0.85 [0.79-0.92]). For AD diagnosis, MTA+PA had the best performance (AUC 1.00) for all age groups.

Conclusions

Combining MTA and PA scores demonstrates greater discriminative ability to differentiate controls from prodromal AD and AD, highlighting the diagnostic value of visual rating scales in daily clinical practice, particularly in Latin America where access to advanced neuroimaging and CSF biomarkers is limited in the clinical setting.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

Diagnostic performance of the medial temporal lobe atrophy scale in patients with Alzheimer's disease: a systematic review and meta-analysis

OBJECTIVE

To evaluate the diagnostic performance and reliability of the medial temporal lobe atrophy (MTA) scale in patients with Alzheimer's disease.

METHODS

A systematic literature search of MEDLINE and EMBASE databases was performed to select studies that evaluated the diagnostic performance or reliability of MTA scale, published up to January 21, 2021. Pooled estimates of sensitivity and specificity were calculated using a bivariate random-effects model. Pooled correlation coefficients for intra- and interobserver agreements were calculated using the random-effects model based on Fisher's Z transformation of correlations. Meta-regression was performed to explain the study heterogeneity. Subgroup analysis was performed to compare the diagnostic performance of the MTA scale and hippocampal volumetry.

RESULTS

Twenty-one original articles were included. The pooled sensitivity and specificity of the MTA scale in differentiating Alzheimer's disease from healthy control were 74% (95% CI, 68-79%) and 88% (95% CI, 83-91%), respectively. The area under the curve of the MTA scale was 0.88 (95% CI, 0.84-0.90). Meta-regression demonstrated that the difference in the method of rating the MTA scale was significantly associated with study heterogeneity (p = 0.04). No significant difference was observed in five studies regarding the diagnostic performance between MTA scale and hippocampal volumetry (p = 0.40). The pooled correlation coefficients for intra- and interobserver agreements were 0.85 (95% CI, 0.69-0.93) and 0.83 (95% CI, 0.66-0.92), respectively.

CONCLUSIONS

Our meta-analysis demonstrated a good diagnostic performance and reliability of the MTA scale in Alzheimer's disease.

KEY POINTS

• The pooled sensitivity and specificity of the MTA scale in differentiating Alzheimer's disease from healthy control were 74% and 88%, respectively. • There was no significant difference in the diagnostic performance between MTA scale and hippocampal volumetry. • The reliability of MTA scale was excellent based on the pooled correlation coefficient for intra- and interobserver agreements.

Relationship between cerebral atrophy and number of present teeth in elderly individuals with cognitive decline

BACKGROUND AND AIM

Recent shifts in the distribution of Japan's population towards older ages, have meant that the chance of encountering patients with dementia in dental clinics is increasing. Many studies have shown that the brain volume decreases along with the progression of dementia. Although previous studies have reported a relationship between tooth loss or periodontitis and the onset of dementia, the pathological mechanisms underlying this association have not been elucidated. In this study, we aimed to examine the relationship between the oral condition and brain atrophy and to discuss how to adequately deal with patients with dementia.

PARTICIPANTS AND METHODS

This cross-sectional study included 15 participants who underwent brain magnetic resonance imaging (MRI). The participants were 60 years or older and presented with cognitive decline, including Alzheimer's disease (AD) and mild cognitive impairment (MCI), diagnosed by a neurologist. We obtained information on the oral condition, lifestyle, cognitive function, and brain atrophy. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). MR images of each patient were analyzed using the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) to provide a quantitative measure of the degree of brain atrophy.

RESULTS

The study population included 4 male and 11 female patients. The mean age and mean number of present teeth were 75.9 years (SD 6.7) and 15.0 (SD 11.1), respectively. The median MMSE score was 25.6 (SD 3.7). The degree of atrophy of the whole brain was significantly correlated with the number of present teeth (ρ = -0.72, p < 0.05) and the presence of a daily exercise habit (ρ = -0.66, p < 0.05).

CONCLUSION

This study demonstrated that the number of present teeth could be an indicator of the progress of dementia. Preserving the teeth as well as the acquisition of a regular exercise habit might be important for preventing progression of dementia. Further research examining a larger study population and analyzing a greater number of factors is warranted.

Reduced Capacity of Cognitive Control in Older Adults with Mild Cognitive Impairment

Cognitive control for the coordination of mental operations is essential in normal cognitive functioning of daily life. Although the decline of cognitive control in older adults with mild cognitive impairment (MCI) has been demonstrated, whether this decline is a core deficit in MCI remains unclear. In this study, we employed a perceptual decision-making task to estimate the capacity of cognitive control (CCC) in older adults with MCI (n = 55) and the age-, sex-, and education-matched healthy controls (HC, n = 55) selected based on a commonly used battery of ten neuropsychological tests in five cognitive domains. We found that the CCC was significantly correlated to the neuropsychological measures of the battery. The mean CCC was significantly lower in the MCI group (3.06 bps) than in the HC group (3.59 bps) and significantly lower in the amnestic MCI subgroup (2.90 bps) than in the nonamnestic MCI subgroup (3.22 bps). In detecting and classifying MCI using machine learning, the classifier with the CCC as the input feature outperformed the overall classification with neuropsychological measures in a single cognitive domain. The classification performance was significantly increased when the CCC was included as a feature in addition to measures in a single domain, and the CCC served as a key feature in optimal classifiers with inputs from multiple domains. These results support the hypothesis that the decline in cognitive control is a core deficit in MCI and suggest that the CCC may serve as a key index in the diagnosis of MCI.