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Background: Neuropsychiatric symptoms could form part of an early cerebral small vessel disease prodrome that is detectable before stroke or dementia onset. We aimed to identify whether apathy, depression, anxiety, and subjective memory complaints associate with longitudinal white matter hyperintensity (WMH) progression. Methods: Community-dwelling older adults from the observational Lothian Birth Cohort 1936 attended three visits at mean ages 73, 76, and 79 years, repeating MRI, Mini-Mental State Examination, neuropsychiatric (Dimensional Apathy Scale, Hospital Anxiety and Depression Scale), and subjective memory symptoms. We ran regression and mixed-effects models for symptoms and normalised WMH volumes (cube root of WMH:ICV x 10). Results: At age 73, 76, and 79, m = 672, n = 476, and n = 382 participants attended MRI respectively. Worse apathy at age 79 was associated with WMH volume increase (β = 0.27, p = 0.04) in the preceding 6 years. A 1SD increase in apathy score at age 79 associated with a 0.17 increase in WMH (β = 0.17 normalised WMH percent ICV, p = 0.009). In apathy subscales, executive (β = 0.13, p = 0.05) and emotional (β = 0.13, p = 0.04) scores associated with increasing WMH more than initiation scores (β = 0.11, p = 0.08). Increasing WMH also associated with age (β = 0.40, p = 0.002) but not higher depression (β = -0.01, p = 0.78), anxiety (β = 0.05, p = 0.13) scores, or subjective memory complaints (β = 1.12, p = 0.75). Conclusions: Apathy independently associates with preceding longitudinal WMH progression, while depression, anxiety, and subjective memory complaints do not. Patients with apathy should be considered for enrolment to small vessel disease trials. [ABSTRACT FROM AUTHOR]

Purpose: Dynamic contrast‐enhanced (DCE) ‐MRI with Patlak model analysis is increasingly used to quantify low‐level blood‐brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability‐surface area product PS and blood plasma volume vp, and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. Methods: Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and vp quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and B1+ error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and B1+ correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. Results: Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10−4 min−1). However, these were reduced (≤0.56 × 10−4 min−1) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in‐vivo normal‐appearing white matter PS estimation (absolute change ≤ 0.45 × 10−4 min−1). Conclusion: Measuring subtle BBB leakage with DCE‐MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown. [ABSTRACT FROM AUTHOR]