Detecting amyloid-ß positivity using regions of interest from structural magnetic resonance imaging.

BACKGROUND AND PURPOSE: Alzheimer disease (AD) is the most common type of dementia. Amyloid-ß (Aß) positivity is the main diagnostic marker for AD. Aß positron emission tomography and cerebrospinal fluid are widely used in the clinical diagnosis of AD. However, these methods only assess the concentrations of Aß, and the accessibility of these methods is thus relatively limited compared with structural magnetic resonance imaging (sMRI). METHODS: We investigated whether regions of interest (ROIs) in sMRIs can be used to predict Aß positivity for samples with normal cognition (NC), mild cognitive impairment (MCI), and dementia. We obtained 846 Aß negative (Aß-) and 865 Aß positive (Aß+) samples from the Alzheimer's Disease Neuroimaging Initiative database. To predict which samples are Aß+, we built five machine learning models using ROIs and apolipoprotein E (APOE) genotypes as features. To test the performance of the machine learning models, we constructed a new cohort containing 97 Aß- and 81 Aß+ samples. RESULTS: The best performing machine learning model combining ROIs and APOE had an accuracy of 0.798, indicating that it can help predict Aß+. Furthermore, we searched ROIs that could aid our prediction and discovered that an average left entorhinal cortical region (L-ERC) thickness is an important feature. We also noted significant differences in L-ERC thickness between the Aß- and Aß+ samples even in the same diagnosis of NC, MCI, and dementia. CONCLUSIONS: Our findings indicate that ROIs from sMRIs along with APOE can be used as an initial screening tool in the early diagnosis of AD.

Predicting superagers by machine learning classification based on the functional brain connectome using resting-state functional magnetic resonance imaging.

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology underlying successful aging. We aimed to investigate the unique patterns of functional brain connectome of superagers and develop predictive models to differentiate superagers from typical agers based on machine learning methods. We obtained resting-state functional magnetic resonance imaging (rsfMRI) data and cognitive measures from 32 superagers and 58 typical agers. The accuracies of three machine learning methods including the linear support vector machine classifier (SV), the random forest classifier (RF), and the logistic regression classifier (LR) in predicting superagers were comparable (SV = 0.944, RF = 0.944, LR = 0.944); however, RF achieved the highest area under the curve (AUC; 0.979). An ensemble learning method combining the three classifiers achieved the highest AUC (0.986). The most discriminative nodes for predicting superagers encompassed areas in the precuneus; posterior cingulate gyrus; insular cortex; and superior, middle, and inferior frontal gyrus, which were located in default, salient, and multiple-demand networks. Thus, rsfMRI data can provide high accuracy for predicting superagers, thereby capturing and describing the unique characteristics of their functional brain connectome.

Predicting cognitive stage transition using p-tau181, Centiloid, and other measures.

BACKGROUND: A combination of plasma phospho-tau (p-tau), amyloid beta (Aß)-positron emission tomography (PET), brain magnetic resonance imaging, cognitive function tests, and other biomarkers might predict future cognitive decline. This study aimed to investigate the efficacy of combining these biomarkers in predicting future cognitive stage transitions within 3 years. METHODS: Among the participants in the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE-V) study, 49 mild cognitive impairment (MCI) and 113 cognitively unimpaired (CU) participants with Aß-PET and brain imaging data were analyzed. RESULTS: Older age, increased plasma p-tau181, Aß-PET positivity, and decreased semantic fluency were independently associated with cognitive stage transitions. Combining age, p-tau181, the Centiloid scale, semantic fluency, and hippocampal volume produced high predictive value in predicting future cognitive stage transition (area under the curve = 0.879). CONCLUSIONS: Plasma p-tau181 and Centiloid scale alone or in combination with other biomarkers, might predict future cognitive stage transition in non-dementia patients. HIGHLIGHTS: -Plasma p-tau181 and Centiloid scale might predict future cognitive stage transition. -Combining them or adding other biomarkers increased the predictive value. -Factors that independently associated with cognitive stage transition were demonstrated.

Radiological protection in human research ethics using a case study: toward update of the ICRP Publication 62.

The benefits of biomedical research involving humans are well recognised, along with the need for conformity to international standards of science and ethics. When human research involves radiation imaging procedures or radiotherapy, an extra level of expert review should be provided from the point of view of radiological protection. The relevant publication of the International Commission for Radiological Protection (ICRP) is now three decades old and is currently undergoing an update. This paper aims to provoke discussions on how the risks of radiation dose and the benefits of research should be assessed, using a case study of diagnostic radiology involving volunteers for whom there is no direct benefit. Further, the paper provides the current understanding of key concepts being considered for review and revision-such as the dose constraint and the novel research methods on the horizon, including radiation biology and epidemiology. The analysis revisits the perspectives described in the ICRP Publication 62, and considers the recent progress in both radiological protection ethics and medical research ethics.

Cilostazol Versus Aspirin on White Matter Changes in Cerebral Small Vessel Disease: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Cerebral small vessel disease is characterized by progressive cerebral white matter changes (WMCs). This study aimed to compare the effects of cilostazol and aspirin on changes in WMC volume in patients with cerebral small vessel disease. METHODS: In a multicenter, double-blind, randomized controlled trial, participants with moderate or severe WMCs and at least one lacunar infarction detected on brain magnetic resonance imaging were randomly assigned to the cilostazol and aspirin groups in a 1:1 ratio. Cilostazol slow release (200 mg) or aspirin (100 mg) capsules were administered once daily for 2 years. The primary outcome was the change in WMC volume on magnetic resonance images from baseline to 2 years. Secondary imaging outcomes include changes in the number of lacunes or cerebral microbleeds, fractional anisotropy, and mean diffusivity on diffusion tensor images, and brain atrophy. Secondary clinical outcomes include all ischemic strokes, all ischemic vascular events, and changes in cognition, motor function, mood, urinary symptoms, and disability. RESULTS: Between July 2013 and August 2016, 256 participants were randomly assigned to the cilostazol (n=127) and aspirin (n=129) groups. Over 2 years, the percentage of WMC volume to total WM volume and the percentage of WMC volume to intracranial volume increased in both groups, but neither analysis showed significant differences between the groups. The peak height of the mean diffusivity histogram in normal-appearing WMs was significantly reduced in the aspirin group compared with the cilostazol group. Cilostazol significantly reduced the risk of ischemic vascular event compared with aspirin (0.5 versus 4.5 cases per 100 person-years; hazard ratio, 0.11 [95% CI, 0.02-0.89]). CONCLUSIONS: There was no significant difference between the effects of cilostazol and aspirin on WMC progression in patients with cerebral small vessel disease. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01932203.

Subtle Cognitive Deficits Are Associated with Amyloid-ß Positivity, but Not Severity of Self-Reported Decline: Results from the CoSCo Study.

INTRODUCTION: Subjective cognitive decline (SCD) can be considered as the preclinical manifestation of Alzheimer's disease (AD). The National Institute on Aging and the Alzheimer's Association criteria for preclinical AD proposed that subtle cognitive changes appear along with AD biomarkers in the late stage of preclinical AD. The objective of this study was to explore whether subtle cognitive impairment (SCI) in individuals with SCD is associated with brain amyloid-ß (Aß) status and SCD severity. METHODS: One hundred twenty individuals with SCD (mean age: 70.87 ± 6.10 years) were included in this study. SCI was defined as performance ≤ -1.0 SD on at least two neuropsychological tests. Participants underwent an amyloid positron emission tomography, which was assessed visually and quantitatively using standardized uptake value ratio (SUVR). The severity of SCD was assessed using two self-reported questionnaires: the SCD questionnaire based on the SCD-plus features and the Korean-Everyday Cognition (K-ECog) scale. RESULTS: SCD individuals with SCI (n = 25) had more Aß positivity than the SCD only group (n = 95) (44% vs. 15.79%; p = 0.002). In addition, the SCI group had a higher global SUVR than the SCD only group (p = 0.048). For self-reported questionnaires, there were no differences in SCD questionnaire total scores and K-ECog global and cognitive domain-specific scores between two groups. CONCLUSIONS: In SCD individuals, SCI was associated with higher Aß positivity, but not with the severity of self-reported cognitive decline, compared to the SCD only group. These results suggest that the recognition of objectively defined subtle cognitive deficits may contribute to the early identification of AD in SCD.

The Effect of Hearing Loss on Cognitive Function in Subjective Cognitive Decline.

INTRODUCTION: Subjective cognitive decline (SCD) is a self-reported cognitive decline without objective cognitive impairment. The relationship between audiometric hearing loss (HL) and cognitive function has not been reported in SCD. The purpose of this study was to investigate whether HL affects cognition-related indexes in SCD individuals. METHODS: This is a cross-sectional study that used the baseline data of a multicenter cohort study that monitors clinical progression from SCD to dementia. Individuals aged ≥60 years who reported cognitive decline but had no objective cognitive impairment on comprehensive neuropsychological tests were recruited. Participants were grouped into the normal-hearing (NH) and bilateral HL groups. The demographics, clinical characteristics, dementia biomarkers, global cognition, questionnaire scores, neuropsychological test scores, and segmental brain volumes from MRI were compared between the groups. RESULTS: Of a total of 120 participants, one hundred and two had NH (n = 57) or bilateral HL (n = 45). There were no group differences in the demographic and clinical data except the age. The biomarkers, global cognition, and questionnaire scores were not different between the groups. The HL group performed worse (the z-score of -0.06) in the Stroop Color Word Test than the NH group (0.27) (p = 0.025). Brain volumetric analysis revealed that the HL group had reduced gray matter volumes in four brain subregions: left temporal pole, left caudal middle frontal gyrus, left hippocampus, and right isthmus of the cingulate gyrus. CONCLUSION: In SCD, HL exerted an adverse effect on cognitive function, primarily frontal executive function tested in the Stroop task. HL was also related to gray matter volume reductions in brain subregions, although causality needs further investigation. This study may provide evidence for a potential link between hearing and cognition in SCD, an emerging clinical entity.

The Moderating Role of Sleep Quality on the Association between Neuroticism and Frontal Executive Function in Older Adults.

OBJECTIVE/BACKGROUND: Personality traits are regarded as risk factors for cognitive impairment in older adults, while sleep disturbance and physical inactivity are also considered as modifiable risk factors. Therefore, it could be beneficial to investigate the effects of those modifiable risk factors on the relationship between personality traits and cognitive functions, to prepare appropriate strategies for mitigating cognitive impairment. PARTICIPANTS: A total of 155 cognitively unimpaired older adults were included. METHODS: All participants underwent cognitive function tests using the Seoul Neuropsychological Screening Battery and examinations for personality traits using the Big Five Inventory. Individual physical activity and sleep quality were assessed using the International Physical Activity Questionnaire and Pittsburgh Sleep Quality Index, respectively. A hierarchical linear multiple regression analysis was performed to demonstrate the direct association between personality traits and cognitive functions, and the multiple moderator analysis was used to analyze the moderating effects of lifestyle factors on this association. RESULTS: Among the five personality traits, only neuroticism was negatively associated with the frontal executive and visuospatial functions after controlling age, sex, and years of education. Interestingly, the negative relationship between neuroticism and frontal executive function was alleviated in older adults with higher sleep quality. CONCLUSIONS: Our findings demonstrated that higher sleep quality has significant moderating effects on the negative association between neuroticism and frontal executive functions in older adults, which suggests intervention for improving sleep quality such as cognitive behavioral therapy can be considered in older adults who have personality traits associated with a high risk of cognitive impairment.

Language treatment effects on communicative abilities and working memory in Korean-speaking agrammatic Broca's aphasia caused by moyamoya disease: Phase II evidence from a case study.

The present study reports on the language treatment outcomes from sentence- and story-level linguistic facilitation and its generalization effect on communicative abilities, working memory, and sentence processing in the case of an adult with Moyamoya Disease (MMD). After treatment,the patient's overall performance, including the Aphasia Quotient, and sentence processing ability as measured by language testing, were improved. Furthermore, the treatment effects were generalizable to working memory abilities. Our case study conveys clinically meaningful implications since it is the first report on the effects of language treatment on linguistic and cognitive domains for an individual with MMD-induced agrammatic Broca's aphasia.

Self- and informant-reported cognitive functioning and awareness in subjective cognitive decline, mild cognitive impairment, and very mild Alzheimer disease.

OBJECTIVES: The present study examined self-reports and informant reports of cognitive function and discrepancies between the two reporting methods in healthy controls (HC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and very mild Alzheimer disease (AD) using three questionnaires. METHODS: The study included a total of 300 individuals (mean age: 74.4 ± 5.7 y), including 130 HC, 70 SCD, 51 MCI, and 49 very mild AD patients. Self-ratings and informant ratings of cognitive function were assessed using the Korean Dementia Screening Questionnaire-Cognition (KDSQ-C), AD8, and Subjective Memory Complaints Questionnaire (SMCQ). Awareness of cognitive functioning was measured on the basis of the discrepancy scores between self-reports and informant reports. RESULTS: Group comparisons on questionnaire scores adjusting for age, education, and depressive symptoms showed that self-reports were lowest in HC than other groups, with no differences between SCD and MCI groups. Informant reports were lower in SCD than in MCI, while discrepancy scores were higher in SCD than in MCI (P < .001 for KDSQ-C and SMCQ; P = .076 for AD8). There were no differences in self-reports, informant reports, and discrepancy scores between MCI and AD groups. CONCLUSIONS: These results support the usefulness of informant-reported cognitive functioning to classify MCI among elderly with subjective cognitive complaints. In addition, discrepancies between self-reports and informant reports demonstrate that overestimation and underestimation of cognitive function may serve as a clinical indicator of SCD and MCI across the cognitive continuum, respectively.