Background/Aims: We investigated the histopathological correlates of white matter hyperintensities (WMHs) in participants with Alzheimer's disease (AD) or cerebrovascular disease, and in aged controls. Methods: We reviewed 57 participants who had neuropathology and in whom neuroimaging was done. In addition to AD pathology, cortical microinfarcts, lacunes, and cerebral hemorrhages were assessed. Small-vessel disease included arteriolosclerosis and cerebral amyloid angiopathy. Postmortem brain tissue corresponding to regions of WMHs was investigated in 14 participants. The variables included: demyelination of the deep and periventricular white matter (WM), atrophy of the ventricular ependyma, and thickness of blood vessels. Partial Spearman's rank test and linear regression analysis, adjusted for age at the clinical evaluation and the duration to death, were performed. Results: The severity of arteriosclerosis was correlated with the volume of periventricular hyperintensity (PVH) estimated by magnetic resonance imaging. Deep white matter hyperintensity (DWMH) volume was correlated with the presence of cortical microinfarcts and cerebral hemorrhages. The severity of the breakdown of the ventricular lining was correlated with PVHs, and DWMHs correlated with the severity of deep WM demyelination. The diameter of small blood vessels was not associated with WMHs. Conclusion: WMHs are consistent with small-vessel disease and increase the tissue water content. We found no association between WMHs and the thickness of small blood vessels. © 2014 S. Karger AG, Basel

Background: Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods: Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimer’s disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results: The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The ‘time orientation’ and ‘3-word recall’ score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions: The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.

The mini-mental state examination (MMSE) was adapted by individual countries according to their languages and cultures, though it has not been systematically compared. The objective of this study was to compare the linguistic and cultural variations of the MMSE used in various Asian countries. With this, we can analyze the strengths and weaknesses of the MMSE and consider using a common version in future international clinical studies in Asia. We collected the MMSEs used in 11 Asian nations. After translating those into English, we compared them to understand the differences in the questionnaires with regard to cultural aspects. Many items may be applicable or comparable with a little modification, for Asian countries. However, attention and calculation and repetition may be incomparable. There were some differences in the contents and the ways to administer. The lack of consideration of the cultural differences and their influences on the interpretation of the same cognitive test makes cross-cultural studies difficult. Some items of MMSE tasks need readjusting for, if any, multi-national studies. This study might serve as a first step in the development of a standardized cross-cultural cognitive instrument, especially in Asia.

A definite diagnosis of Alzheimer's disease (AD) can only be made at autopsy. Even at expert research centers, diagnostic accuracy is relatively low. We conducted this study to examine the accuracy of clinical diagnosis of AD and present a list of clinical and neuropsychological findings that could render the clinical diagnosis difficult. Using the National Alzheimer's Coordinating Center database, the records of 533 patients who had been diagnosed clinically with AD, and later underwent autopsy, were reviewed retrospectively. Since the pathologic results of 119 subjects did not meet the criteria for definite AD, we labeled them as Alzheimer “mimics”. The neuropathological diagnoses of Alzheimer mimics consisted of dementia with Lewy bodies (n = 35, 29%), insufficient AD (n = 22, 18%), vascular disease (n = 15, 13%), frontotemporal lobar degeneration (n = 14, 12%), and hippocampal sclerosis (n = 10, 8%). History of pacemaker insertion (10.92% versus 4.11%, p = 0.005), congestive heart failure (13.45% versus 6.04%, p = 0.007), hypertension (56.30% versus 47.83%, p = 0.037), and resting tremor (14.29% versus 10.87%, p = 0.170) was more prevalent in Alzheimer mimics. Clinical Dementia Rating score and frequency of Neuropsychiatric Inventory Questionnaire items reflecting delusions, agitation, depression, and motor disturbance were more severe in confirmed AD. In addition to Mini-Mental State Examination (16.97 ± 8.29 versus 12.74 ± 15.26, p < 0.001), Logical Memory, Animal Fluency, Boston Naming Test, and Digit Span scores showed more severe impairment in confirmed AD. Continuing systematic comparisons of the current criteria for the clinical and pathological dementia diagnoses are essential to clinical practice and research, and may also lead to further improvement of the diagnostic procedure.

Park KH, et al. Dement Neurocogn Disord. 2024 Oct;23(4):165-187. https://doi.org/10.12779/dnd.2024.23.4.165