AI, Robotics, and Clinical Research for Innovative Dementia Interventions: A Japanese-German Collaboration

After a successful international workshop in Karlsruhe, Germany in June 2023, transformative initiative is underway involving major institutions: the RIKEN Cognitive Behavioral Assistive Technology (CB-AT) Team in Japan, the Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Rostock/Greifswald, Rostock, the Forschungszentrum Informatik (FZI) and the Karlsruhe Institute of Technology, Institute for Information Processing Technology as well as the Institute for Entrepreneurship, Technology Management and Innovation. The unique strengths of these institutions unite in an interdisciplinary collaboration focusing on novel dementia interventions. This consortium envisions the future of dementia care and the prevention of its progress – a model that brings together the strengths of AI, robotics, digital platforms, and clinical research, not just targeting patients but considering dyadic interventions that support both patients and caregivers. The KIT and FZI from Karlsruhe bring to the table expertise in software and AI engineering, and experience in research transfer. Particularly crucial is the role of the METIS platform, which supports multi-stage treatment processes for neurodegenerative diseases in an outpatient setting, integrating modern wearables and AI personalization of treatment strategies. RIKEN CB-AT complements this with robotics and system integration capabilities, including access to robots ready for integration into care regimens. The institute is renowned for its speech intervention strategies in dementia prevention, fostering the idea of using robots to aid caregivers and patients alike. Ultimately, the robots could serve as a base station, actively engaging with caregivers, assessing their stress levels, and providing mitigation strategies while simultaneously collecting crucial data. DZNE Rostock/Greifswald rounds out the partnership with a robust clinical background and access to well-defined clinical cohorts. Their research provides valuable insights into patient needs. Furthermore, their proficiency in qualitative research and dyadic interventions adds an essential layer of complexity to the project. In this alliance, a shared ethos of participatory approach, modern digital and wearable technology adoption, and individualized intervention strategies enable a unified research vision. The potential outcomes are manifold: they include technologies for outpatient measurements of intervention, prevention and care, robots aiding caregivers and patients, digitalization of care pathways, stress mitigation, and more. All partners strive to establish bi-lateral connections between existing technology and new integrations, enabling data insights from a variety of sources, including smartwatches, smartphones, robots, novel technology, and caregiver-patient interactions. These insights can be used for the personalization of intervention and care, medication, early detection of emergency situations, and strategies to empower patients and enhance the resilience of caregivers. Once addressed, the opportunity for transformative early prevention of dementia progression are immense. The expected outcomes span joint research projects, scientific publications, societal impact, and entrepreneurial initiatives. In conclusion, this collaborative venture aspires to make strides in dementia care and intervention through the integrative use of platform-based AI, robotics, and clinical research, fostering an enhanced care ecosystem that values patients and caregivers

IC‐P‐127: CSF parameters of neurodestruction and atrophy of the basal forebrain cholinergic system in mild cognitive impairment

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Implementation and evaluation of participatory advisory boards in mental health research: a research protocol of the ‘PART-Beirat’ project

Background The use of participatory research approaches in the field of dementia and forensic mental health research has been on the rise. Advisory board structures, involving people with lived experience (PWLE), have frequently been used for guiding and leading research. Yet, there has been limited guidance on the establishment, retention and use of advisory boards in the field of dementia and forensic mental health research. Objective This project outlined in this research protocol will investigate the benefits and challenges of establishing three patient advisory boards, involving PWLE, practitioners and researchers with the purpose to guide research. Data will be used to develop guidelines for best practice in involving PWLE in dementia and forensic mental health research through advisory boards. Methods The research project will be divided into three phases: Phase I will involve two topic-specific systematic reviews on the use of participatory research with PWLE, followed by an initial study exploring PWLE’s, practitioners’ and researchers’ expectations on research involvement. Phase II will consist of the establishment of three advisory boards, one focusing on dementia, one on forensic mental health and one overarching coordinating advisory board, which will involve PWLE from both fields. Phase III, will consist of interviews and focus groups with advisory board members, exploring any challenges and benefits of involving PWLE and practitioners in advisory boards for guiding research. To capture the impact of involving PWLE in different research phases and tasks, interviews and focus groups will be conducted at four different points of time (0, 6, 12, 18 months). Reflexive thematic analysis will be used for the analysis of data. Discussion The project aims to explore the involvement of PWLE and practitioners in guiding research and aims to develop guidelines for best practice in establishing and using patient advisory boards in dementia and forensic mental health research and involving PWLE and practitioners in research

Fronto-striatal alterations correlate with apathy severity in behavioral variant frontotemporal dementia

Structural and functional changes in cortical and subcortical regions have been reported in behavioral variant frontotemporal dementia (bvFTD), however, a multimodal approach may provide deeper insights into the neural correlates of neuropsychiatric symptoms. In this multicenter study, we measured cortical thickness (CTh) and subcortical volumes to identify structural abnormalities in 37 bvFTD patients, and 37 age- and sex-matched healthy controls. For seed regions with significant structural changes, whole-brain functional connectivity (FC) was examined in a sub-cohort of N = 22 bvFTD and N = 22 matched control subjects to detect complementary alterations in brain network organization. To explore the functional significance of the observed structural and functional deviations, correlations with clinical and neuropsychological outcomes were tested where available. Significantly decreased CTh was observed in the bvFTD group in caudal middle frontal gyrus, left pars opercularis, bilateral superior frontal and bilateral middle temporal gyrus along with subcortical volume reductions in bilateral basal ganglia, thalamus, hippocampus, and amygdala. Resting-state functional magnetic resonance imaging showed decreased FC in bvFTD between: dorsal striatum and left caudal middle frontal gyrus;putamen and fronto-parietal regions;pallidum and cerebellum. Conversely, bvFTD showed increased FC between: left middle temporal gyrus and paracingulate gyrus;caudate nucleus and insula;amygdala and parahippocampal gyrus. Additionally, cortical thickness in caudal, lateral and superior frontal regions as well as caudate nucleus volume correlated negatively with apathy severity scores of the Neuropsychiatry Inventory Questionnaire. In conclusion, multimodal structural and functional imaging indicates that fronto-striatal regions have a considerable influence on the severity of apathy in bvFTD

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy:A Bayesian Approach

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer’s disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid

Fornix fractional anisotropy mediates the association between Mediterranean diet adherence and memory four years later in older adults without dementia

Here, we investigated whether fractional anisotropy (FA) of hippocampus-relevant white-matter tracts mediates the association between baseline Mediterranean diet adherence (MeDiAd) and verbal episodic memory over four years. Participants were healthy older adults with and without subjective cognitive decline and patients with amnestic mild cognitive impairment from the DELCODE cohort study (n = 376; age: 71.47 ± 6.09 years; 48.7 % female). MeDiAd and diffusion data were obtained at baseline. Verbal episodic memory was assessed at baseline and four yearly follow-ups. The associations between baseline MeDiAd and white matter, and verbal episodic memory's mean and rate of change over four years were tested with latent growth curve modeling. Baseline MeDiAd was associated with verbal episodic memory four years later (95 % confidence interval, CI [0.01, 0.32]) but not with its rate of change over this period. Baseline Fornix FA mediated - and, thus, explained - that association (95 % CI [0.002, 0.09]). Fornix FA may be an appropriate response biomarker of Mediterranean diet interventions on verbal memory in older adults.</p

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe

INTRODUCTION Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline

peer reviewed[en] BACKGROUND AND OBJECTIVES: To determine the relevance of minor neuropsychological deficits (MNPD) in patients with subjective cognitive decline (SCD) with regard to CSF levels of Alzheimer disease (AD) biomarkers, cognitive decline, and clinical progression to mild cognitive impairment (MCI). METHODS: This study included patients with clinical SCD and SCD-free, healthy control (HC) participants with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia study. We defined MNPD as a performance of at least 0.5SD below the mean on a demographically adjusted total score derived from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery. We compared SCD patients with MNPD and those without MNPD with regard to CSF amyloid-β (Aβ)42/Aβ40, phosphorylated tau (p-tau181), total tau and Aβ42/p-tau181 levels, longitudinal cognitive composite trajectories, and risk of clinical progression to incident MCI (follow-up M ± SD: 40.6 ± 23.7 months). In addition, we explored group differences between SCD and HC in those without MNPD. RESULTS: In our sample (N = 672, mean age: 70.7 ± 5.9 years, 50% female), SCD patients with MNPD (n = 55, 12.5% of SCD group) showed significantly more abnormal CSF biomarker levels, increased cognitive decline, and a higher risk of progression to incident MCI (HR: 4.07, 95% CI 2.46-6.74) compared with SCD patients without MNPD (n = 384). MNPD had a positive predictive value of 57.0% (95% CI 38.5-75.4) and a negative predictive value of 86.0% (95% CI 81.9-90.1) for the progression of SCD to MCI within 3 years. SCD patients without MNPD showed increased cognitive decline and a higher risk of incident MCI compared with HC participants without MNPD (n = 215; HR: 4.09, 95% CI 2.07-8.09), while AD biomarker levels did not differ significantly between these groups. DISCUSSION: Our results suggest that MNPD are a risk factor for AD-related clinical progression in cognitively normal patients seeking medical counseling because of SCD. As such, the assessment of MNPD could be useful for individual clinical prediction and for AD risk stratification in clinical trials. However, SCD remains a risk factor for future cognitive decline even in the absence of MNPD