Computer-aided extraction of select MRI markers of cerebral small vessel disease: A systematic review

Cerebral small vessel disease (CSVD) is a major vascular contributor to cognitive impairment in ageing, including dementias. Imaging remains the most promising method for in vivo studies of CSVD. To replace the subjective and laborious visual rating approaches, emerging studies have applied state-of-the-art artificial intelligence to extract imaging biomarkers of CSVD from MRI scans. We aimed to summarise published computer-aided methods for the examination of three imaging biomarkers of CSVD, namely cerebral microbleeds (CMB), dilated perivascular spaces (PVS), and lacunes of presumed vascular origin. Seventy classical image processing, classical machine learning, and deep learning studies were identified. Transfer learning and weak supervision techniques have been applied to accommodate the limitations in the training data. While good performance metrics were achieved in local datasets, there have not been generalisable pipelines validated in different research and/or clinical cohorts. Future studies could consider pooling data from multiple sources to increase data size and diversity, and evaluating performance using both image processing metrics and associations with clinical measures

Is intraindividual reaction time variability an independent cognitive predictor of mortality in old age? Findings from the Sydney Memory and Ageing Study

Intraindividual variability of reaction time (IIVRT), a proposed cognitive marker of neurobiological disturbance, increases in old age, and has been associated with dementia and mortality. The extent to which IIVRT is an independent predictor of mortality, however, is unclear. This study investigated the association of IIVRT and all-cause mortality while accounting for cognitive level, incident dementia and biomedical risk factors in 861 participants aged 70–90 from the Sydney Memory and Ageing Study. Participants completed two computerised reaction time (RT) tasks (76 trials in total) at baseline, and comprehensive medical and neuropsychological assessments every 2 years. Composite RT measures were derived from the two tasks—the mean RT and the IIVRT measure computed from the intraindividual standard deviation of the RTs (with age and time-on-task effects partialled out). Consensus dementia diagnoses were made by an expert panel of clinicians using clinical criteria, and mortality data were obtained from a state registry. Cox proportional hazards models estimated the association of IIVRT and mean RT with survival time over 8 years during which 191 (22.2%) participants died. Greater IIVRT but not mean RT significantly predicted survival time after adjusting for age, sex, global cognition score, cardiovascular risk index and apolipoprotein ɛ4 status. After excluding incident dementia cases, the association of IIVRT with mortality changed very little. Our findings suggest that greater IIVRT uniquely predicts shorter time to death and that lower global cognition and prodromal dementia in older individuals do not explain this relationship

Reaction Time Measures Predict Incident Dementia in Community-Living Older Adults: The Sydney Memory and Ageing Study

Objective To examine the utility of intraindividual variability of reaction times (IIVRT) and mean reaction time (RT) as behavioral markers of incident all-cause dementia. Methods A longitudinal cohort study followed biennially for 4 years, the community-based Sydney Memory and Ageing Study, 861 initially nondemented participants aged 70–90. Incident all-cause dementia determined by consensus, RT measures from simple and complex tasks, Mini-Mental State Exam and neuropsychological tests, Geriatric Depression Scale and Goldberg Anxiety Scale, cardiovascular risk score, apolipoprotein ε4 status, and the Bayer ADL Scale were used. Associations of baseline IIVRT and mean RT with time to dementia were evaluated with hazard ratios (HRs) using Cox proportional-hazards models with and without controlling for dementia risk factors. Results Forty-eight cases developed dementia. Greater complex IIVRT predicted a 40% (HR: 1.43) and mean RT a 50%–60% (simple RT: HR 1.53; complex RT: HR 1.59) per standard deviation increased risk of developing dementia, remaining significant after controlling for age, education, sex, general cognitive function, mood, cerebrovascular disease, and genetic susceptibility. Prediction of incident dementia using demographical information and RT measures combined was comparable with several traditional neuropsychological measures (AUC 0.75), although lower than a full neuropsychological battery (AUC 0.90). Prediction of functional decline by RT measures combined was equal to the neuropsychological battery (multiple Rs of .233 and .238, respectively). Conclusion Brief RT measures provided information on risk of imminent dementia and functional decline within 4 years in older adults at a population level, with mean RT the stronger predictor

Systemic Inflammation Predicts Alzheimer Pathology in Community Samples without Dementia

Neuroinflammation and oxidative stress (OS) are implicated in the pathophysiology of Alzheimer’s disease (AD). However, it is unclear at what stage of the disease process inflammation first becomes manifest. The aim of this study was to investigate the associations between specific plasma markers of inflammation and OS, tau, and Amyloid-β 38, 40, and 42 levels in cognitively unimpaired middle-age and older individuals. Associations between inflammatory states identified through principal component analysis and AD biomarkers were investigated in middle-age (52–56 years, n = 335, 52% female) and older-age (72–76 years, n = 351, 46% female) participants without dementia. In middle-age, a component reflecting variation in OS was most strongly associated with tau and to a lesser extent amyloid-β levels. In older-age, a similar component to that observed in middle-age was only associated with tau, while another component reflecting heightened inflammation independent of OS, was associated with all AD biomarkers. In middle and older-age, inflammation and OS states are associated with plasma AD biomarkers

Intraindividual Stepping Reaction Time Variability Predicts Falls in Older Adults With Mild Cognitive Impairment

Background: Reaction time measures have considerable potential to aid neuropsychological assessment in a variety of health care settings. One such measure, the intraindividual reaction time variability (IIV), is of particular interest as it is thought to reflect neurobiological disturbance. IIV is associated with a variety of age-related neurological disorders, as well as gait impairment and future falls in older adults. However, although persons diagnosed with Mild Cognitive Impairment (MCI) are at high risk of falling, the association between IIV and prospective falls is unknown. Methods: We conducted a longitudinal cohort study in cognitively intact (n = 271) and MCI (n = 154) community-dwelling adults aged 70–90 years. IIV was assessed through a variety of measures including simple and choice hand reaction time and choice stepping reaction time tasks (CSRT), the latter administered as a single task and also with a secondary working memory task. Results: Logistic regression did not show an association between IIV on the hand-held tasks and falls. Greater IIV in both CSRT tasks, however, did significantly increase the risk of future falls. This effect was specific to the MCI group, with a stronger effect in persons exhibiting gait, posture, or physiological impairment. Conclusions: The findings suggest that increased stepping IIV may indicate compromised neural circuitry involved in executive function, gait, and posture in persons with MCI increasing their risk of falling. IIV measures have potential to assess neurobiological disturbance underlying physical and cognitive dysfunction in old age, and aid fall risk assessment and routine care in community and health care settings

Biocompatibility and proteomic profiling of DMSA-coated iron nanocubes in a human glioblastoma cell line

Background: Superparamagnetic iron core iron oxide shell nanocubes have previously shown superior performance in magnetic resonance imaging T2 contrast enhancement compared with spherical nanoparticles. Methods: Iron core iron oxide shell nanocubes were synthesized, stabilized with dimercaptosuccinic acid (DMSA-NC) and physicochemically characterized. MRI contrast enhancement and biocompatibility were assessed in vitro. Results: DMSA-NC showed a transverse relaxivity of 122.59 mM-1·s-1 Fe. Treatment with DMSA-NC did not induce cytotoxicity or oxidative stress in U-251 cells, and electron microscopy demonstrated DMSA-NC localization within endosomes and lysosomes in cells following internalization. Global proteomics revealed dysregulation of iron storage, transport, transcription and mRNA processing proteins. Conclusion: DMSA-NC is a promising T2 MRI contrast agent which, in this preliminary investigation, demonstrates favorable biocompatibility with an astrocyte cell model. Plain language summary: MRI is a powerful tool used in the diagnosis of cancer, strokes and other injuries. An MRI scan can be improved with the use of iron oxide nanoparticles, which enhance the contrast of the image. In this study we have developed cube-shaped iron nanoparticles (nanocubes), which have been previously shown to be more effective at inducing contrast. We demonstrated that iron-based nanocubes do not damage or induce stress in cells and work effectively as an MRI contrast agent. We further analyzed how the nanocubes may affect cell functioning by investigating changes to protein levels in the cells. The results of this study are promising steps towards using iron-based nanocubes as a tool to improve the clarity of MRI scans for medical imaging and diagnosis. Future work must determine whether these nanocubes work effectively and safely in an animal model, which is a critical step in progressing to their use in clinical settings

Risk factors for falls in community-dwelling older people with mild cognitive impairment: a prospective one-year study

Objective: Mild cognitive impairment (MCI) is considered an intermediate stage between normal cognitive function and dementia. Fall risk is increased in this group, but there is limited literature exploring specific fall risk factors that may be addressed in fall prevention strategies. The aim of this study was to examine risk factors for falls in older people with MCI, focusing on cognitive, psychological and physical factors. Methods: Participants (n = 266, 45% women) were community-dwelling older people aged 70–90 years who met the criteria for MCI. Cognitive, psychological, sensorimotor and physical assessments, physical activity levels, medication use, general health and disability were ascertained at baseline. Falls were monitored prospectively for 12 months. Results: During follow-up, 106 (40%) participants reported one or more falls. Poorer visual contrast sensitivity, increased postural sway, lower levels of weekly walking activity, higher levels of depressive symptoms and psychotropic medication use were significantly associated with faller status (≥1 falls) in univariable analyses. Of these factors, poor visual contrast sensitivity, increased postural sway and psychotropic medication use were found to be significant independent predictors of falls in multivariable analysis while controlling for age and sex. No measures of cognitive function were associated with falls. Conclusions: Poor visual contrast sensitivity, impaired balance and psychotropic medication use predicted falls in community-dwelling people with MCI. These risk factors may be amenable to intervention, so these factors could be carefully considered in fall prevention programs for this population

Characterising Australian memory clinics: current practice and service needs informing national service guidelines

Background: Memory clinics (MCs) play a key role in accurate and timely diagnoses and treatment of dementia and mild cognitive impairment. However, within Australia, there are little data available on current practices in MCs, which hinder international comparisons for best practice, harmonisation efforts and national coordination. Here, we aimed to characterise current service profiles of Australian MCs. Methods: The ‘Australian Dementia Network Survey of Expert Opinion on Best Practice and the Current Clinical Landscape’ was conducted between August-September 2020 as part of a larger-scale Delphi process deployed to develop national MC guidelines. In this study, we report on the subset of questions pertaining to current practice including wait-times and post-diagnostic care. Results: Responses were received from 100 health professionals representing 60 separate clinics (45 public, 11 private, and 4 university/research clinics). The majority of participants were from clinics in metropolitan areas (79%) and in general were from high socioeconomic areas. While wait-times varied, only 28.3% of clinics were able to offer an appointment within 1-2 weeks for urgent referrals, with significantly more private clinics (58.3%) compared to public clinics (19.5%) being able to do so. Wait-times were less than 8 weeks for 34.5% of non-urgent referrals. Only 20.0 and 30.9% of clinics provided cognitive interventions or post-diagnostic support respectively, with 7.3% offering home-based reablement programs, and only 12.7% offering access to group-based education. Metropolitan clinics utilised neuropsychological assessments for a broader range of cases and were more likely to offer clinical trials and access to research opportunities. Conclusions: In comparison to similar countries with comprehensive government-funded public healthcare systems (i.e., United Kingdom, Ireland and Canada), wait-times for Australian MCs are long, and post-diagnostic support or evidence-based strategies targeting cognition are not common practice. The timely and important results of this study highlight a need for Australian MCs to adopt a more holistic service of multidisciplinary assessment and post-diagnostic support, as well as the need for the number of Australian MCs to be increased to match the rising number of dementia cases

Genetic and environmental influences on fruit and vegetable consumption and depression in older adults

Background: Prior work suggests that higher fruit and vegetable consumption may protect against depression in older adults. Better understanding of the influence of genetic and environmental factors on fruit and vegetable intakes may lead to the design of more effective dietary strategies to increase intakes. In turn this may reduce the occurrence of depression in older adults. Objectives: The primary aim of this study is to estimate the genetic and environmental influences on the consumption of fruit and vegetables in older adults. The secondary aim is an exploratory analysis into possible shared genetic influences on fruit and vegetable intakes and depression. Methods: Analysis of observational data from 374 twins (67.1% female; 208 monozygotic (MZ); 166 dizygotic (DZ)) aged ≥ 65 years drawn from the Older Australian Twins Study. Dietary data were obtained using a validated food frequency questionnaire and depressive symptoms were measured using the 15-item short form Geriatric Depression Scale. The contribution of genetic and environmental influences on fruit and vegetable intake were estimated by comparing MZ and DZ twin intakes using structural equation modelling. A tri-variate twin model was used to estimate the genetic and environmental correlation between total fruit and vegetable intakes and depression. Results: In this study, vegetable intake was moderately influenced by genetics (0.39 95%CI 0.22, 0.54). Heritability was highest for brassica vegetables (0.40 95%CI 0.24, 0.54). Overall fruit intake was not significantly heritable. No significant genetic correlations were detected between fruit and vegetable intake and depressive symptoms. Conclusions: Vegetable consumption, particularly bitter tasting brassica vegetables, was significantly influenced by genetics, although environmental influences were also apparent. Consumption of fruit was only influenced by the environment, with no genetic influence detected, suggesting strategies targeting the food environment may be particularly effective for encouraging fruit consumption

Factors Associated with Participation in a Multidomain Web-Based Dementia Prevention Trial: Evidence from Maintain Your Brain (MYB)

Background: The Maintain Your Brain (MYB) trial aims to prevent cognitive decline and dementia through multidomain, web-based risk-reduction. To facilitate translation, it is important to understand drivers of participation. Objective: To describe characteristics associated with participation in MYB. Methods: This was an observational ancillary study of MYB, a randomized controlled trial nested within the 45 and Up Study in New South Wales, Australia. We linked 45 and Up Study survey and MYB participation data. The study cohort comprised 45 and Up Study participants, aged 55-77 years at 1 January 2018, who were invited to participate in MYB. 45 and Up Study participant characteristics and subsequent MYB consent and participation were examined. Results: Of 98,836 invited, 13,882 (14%) consented to participate and 6,190 participated (6%). Adjusting for age and sex, a wide range of factors were related to participation. Higher educational attainment had the strongest relationship with increased MYB participation (university versus school non-completion; AdjOR = 5.15; 95% CI:4.70-5.64) and lower self-rated quality of life with reduced participation (Poor versus Excellent: AdjOR = 0.19; 95% CI:0.11-0.32). A family history of Alzheimer's disease was related to increased participation but most other dementia risk factors such as diabetes, obesity, stroke, high blood pressure, and current smoking were associated with reduced participation. Conclusion: Higher socio-economic status, particularly educational attainment, is strongly associated with engagement in online dementia prevention research. Increasing population awareness of dementia risk factors, and better understanding the participation barriers in at-risk groups, is necessary to ensure online interventions are optimally designed to promote maximum participation