Objectives: Amyloid-lowering immunotherapies can cause amyloid-related imaging abnormalities (ARIA), requiring brain MRI for detection and monitoring. The European Society of Neuroradiology (ESNR)/European Academy of Neurology (EAN) ARIA Working Group conducted a survey to assess European clinicians’ readiness for this logistical challenge and need for further education on ARIA. Materials and methods: An online questionnaire with 32 items (multiple choice, single best choice, and free text) was distributed to ESNR and EAN members. Between June and July 2024, we collected 422 responses from 41 European countries, including 47% neurologists and 51% (neuro)radiologists; 15% were residents, and 58% worked in academic hospitals. Results: Of respondents, 69% were familiar with the concept of ARIA, and 60% reportedly understood its risk factors. Confidence in evaluating ARIA-E (edema/effusion) and ARIA-H (hemorrhage) subtypes was reported by 60% and 69%, respectively, with (neuro)radiologists more confident than neurologists. However, 34% of respondents felt poorly equipped to meet logistical demands, and 82% lacked a dedicated ARIA imaging protocol. Key barriers included limited organizational adaptability and radiology expertise. Notably, 72% saw potential in having support by artificial intelligence approaches, and 93% expressed the wish for further training on how to monitor ARIA. Conclusions: Despite the current unavailability of amyloid-lowering therapies, European neurologists and (neuro)radiologists report reasonable ARIA awareness. There is a clear need for additional practical preparation and training in ARIA assessment, which can inform future ESNR/EAN educational initiatives. Key Points: Question Are neurologists and neuroradiologists ready for ARIA monitoring? Findings Neurologists and neuroradiologists were moderately familiar with the concept of ARIA, its risk factors, and its identification on MRI, but felt poorly equipped to meet the logistical demands. Clinical relevance With the potential introduction of amyloid-lowering therapies in European countries, identifying key barriers, such as limited organizational adaptability and radiology expertise, highlights the need for further practical preparation by clinical departments and additional training in ARIA assessment.

INTRODUCTION: Cognitive resilience refers to maintaining cognitive function despite Alzheimer's disease (AD) pathophysiology. METHODS: We analyzed amyloid-positive individuals across clinical stages of AD in two cohorts: the Amsterdam Dementia Cohort (ADC, N = 1036) and Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 685). Cognitive resilience was conceptualized from a canonical correlation analysis of magnetic resonance imaging and neuropsychological data in each cohort separately. Model validation involved education as a resilience proxy and key genetic factors (apolipoprotein E [APOE] ε4 and APOE ε2) of AD. We explored associations between 83 AD risk loci and cognitive resilience. RESULTS: Resilience was correlated with education (ADC: β = 0.144, p < 0.001; ADNI: β = 0.149, p < 0.001) and APOE ε4 (β_{meta-analysis}= –0.052, p = 0.014). Exploratory single nucleotide polymorphism meta-analysis identified potential involvement of genetic variants around genes UNC5CL, USP6NL, and TPCN1 in lower, and genes COX7C and MINDY2 in higher resilience. DISCUSSION: Our novel resilience approach showed conceptual validity and potential for future discovery of resilience-related genetic variants. Highlights: ·We define a novel approach to resilience using canonical correlation analysis (CCA). ·Apolipoprotein E ε4 is linked to lower resilience, suggesting increased vulnerability. ·Genetic loci around COX7C and MINDY2 are potentially involved in higher resilience. ·This novel approach may be used for multi-cohort studies such as genome-wide association studies in the future.

Computer-aided methods have shown added value for diagnosing and predicting brain disorders and can thus support decision making in clinical care and treatment planning. This chapter will provide insight into the type of methods, their working, their input data –such as cognitive tests, imaging, and genetic data– and the types of output they provide. We will focus on specific use cases for diagnosis, i.e., estimating the current “condition” of the patient, such as early detection and diagnosis of dementia, differential diagnosis of brain tumors, and decision making in stroke. Regarding prediction, i.e., estimation of the future “condition” of the patient, we will zoom in on use cases such as predicting the disease course in multiple sclerosis and predicting patient outcomes after treatment in brain cancer. Furthermore, based on these use cases, we will assess the current state-of-the-art methodology and highlight current efforts on benchmarking of these methods and the importance of open science therein. Finally, we assess the current clinical impact of computer-aided methods and discuss the required next steps to increase clinical impact.

There is evidence for a beneficial effect of aerobic exercise on cognition, but underlying mechanisms are unclear. In this study, we test the hypothesis that aerobic exercise increases cerebral blood flow (CBF) in patients with vascular cognitive impairment (VCI). This study is a multicenter single-blind randomized controlled trial among 80 patients with VCI. Most important inclusion criteria are a diagnosis of VCI with Mini-Mental State Examination ≥22 and Clinical Dementia Rating ≤0.5. Participants are randomized into an aerobic exercise group or a control group. The aerobic exercise program aims to improve cardiorespiratory fitness and takes 14 weeks, with a frequency of three times a week. Participants are provided with a bicycle ergometer at home. The control group receives two information meetings. Primary outcome measure is change in CBF. We expect this study to provide insight into the potential mechanism by which aerobic exercise improves hemodynamic status.