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Abstract The cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we test this hypothesis in the continuum from cognitively normal to at-risk stages for Alzheimer’s Disease (AD) to AD dementia using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function is measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis, we identify a CR-related activity pattern underlying successful memory encoding that moderates the detrimental effect of AD pathological load on cognitive performance. CR is mainly represented by a more pronounced expression of the task-active network encompassing deactivation of the default mode network (DMN) and activation of inferior temporal regions including the fusiform gyrus. We devise personalized fMRI-based CR scores that moderate the impact of AD pathology on cognitive performance and are positively associated with years of education. Furthermore, higher CR scores attenuate the effect of AD pathology on cognitive decline over time. Our findings primarily provide evidence for the maintenance of core cognitive circuits including the DMN as the neural basis of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.

Abstract Background Perivascular space (PVS) enlargement in ageing and Alzheimer’s disease (AD) and the drivers of such a structural change in humans require longitudinal investigation. Elucidating the effects of demographic factors, hypertension, cerebrovascular dysfunction, and AD pathology on PVS dynamics could inform the role of PVS in brain health function as well as the complex pathophysiology of AD. Methods We studied PVS in centrum semiovale (CSO) and basal ganglia (BG) computationally over three to four annual visits in 503 participants (255 females; meanage = 70.78 ± 5.78) of the ongoing observational multicentre “DZNE Longitudinal Cognitive Impairment and Dementia Study” (DELCODE) cohort. We analysed data from subjects who were cognitively unimpaired (n = 401), had amnestic mild cognitive impairment (n = 71), or had AD (n = 31). We used linear mixed-effects modelling to test for changes of PVS volumes in relation to cross-sectional and longitudinal age, as well as sex, years of education, hypertension, white matter hyperintensities, AD diagnosis, and cerebrospinal-fluid-derived amyloid (A) and tau (T) status (available for 46.71%; A-T-/A + T-/A + T + n = 143/48/39). Results PVS volumes increased significantly over follow-ups (CSO: B = 0.03 [0.02, 0.05], p A-T-, p FDR = 0.004) or who were amyloid positive but tau negative (A + T + > A + T-, p FDR = 0.07). CSO-PVS volumes increased at a faster rate with amyloid positivity as compared to amyloid negativity (A + T-/A + T + > A-T-, p FDR = 0.021). Conclusion Our longitudinal evidence supports the relevance of PVS enlargement in presumably healthy ageing as well as in AD pathology. We further discuss the region-specific involvement of white matter hyperintensities and neurotoxic waste accumulation in PVS enlargement and the possibility of additional factors contributing to PVS progression. A comprehensive understanding of PVS dynamics could facilitate the understanding of pathological cascades and might inform targeted treatment strategies. Trial registration German Clinical Trials Register DRKS00007966. Registered 04.05.2015 – retrospectively registered, https://drks.de/search/en/trial/DRKS00007966 .

Abstract Background For over three decades, the concomitance of cortical neurodegeneration and white matter hyperintensities (WMH) has sparked discussions about their coupled temporal dynamics. Longitudinal studies supporting this hypothesis nonetheless remain scarce. Methods We applied global and regional bivariate latent growth curve modelling to determine the extent to which WMH and cortical thickness were interrelated over a four-year period. For this purpose, we leveraged longitudinal MRI data from 451 cognitively unimpaired participants (DELCODE; median age 69.71 [IQR 65.51, 75.50] years; 52.32% female). Participants underwent MRI sessions annually over a four-year period (1815 sessions in total, with roughly four MRI sessions per participant). We adjusted all models for demographics and cardiovascular risk. Results Our findings were three-fold. First, larger WMH volumes were linked to lower cortical thickness (σ = -0.165, SE = 0.047, Z = -3.515, P

Abstract Background While several studies in cerebral amyloid angiopathy (CAA) focus on cognitive function, data on neuropsychiatric symptoms (NPS) and lifelong mental activities in these patients are scarce. Since NPS are associated with functional impairment, faster cognitive decline and faster progression to death, replication studies in more diverse settings and samples are warranted. Methods We prospectively recruited n = 69 CAA patients and n = 18 cognitively normal controls (NC). The number and severity of NPS were assessed using the Alzheimer’s Disease (AD) Assessment Scale’s (ADAS) noncognitive subscale. We applied different regression models exploring associations between NPS number or severity and group status (CAA vs. NC), CAA severity assessed with magnetic resonance imaging (MRI) or cognitive function (Mini-Mental State Examination (MMSE), ADAS cognitive subscale), adjusting for age, sex, years of education, arterial hypertension, AD pathology, and apolipoprotein E status. Mediation analyses were performed to test indirect effects of lifelong mental activities on CAA severity and NPS. Results Patients with CAA had 4.86 times (95% CI 2.20-10.73) more NPS and 3.56 units (95% CI 1.94–5.19) higher expected NPS severity than NC. Higher total CAA severity on MRI predicted 1.14 times (95% CI 1.01.-1.27) more NPS and 0.57 units (95% CI 0.19–0.95) higher expected NPS severity. More severe white matter hyperintensities were associated with 1.21 times more NPS (95% CI 1.05–1.39) and 0.63 units (95% CI 0.19–1.08) more severe NPS. NPS number (MMSE mean difference − 1.15, 95% CI -1.67 to -0.63; ADAS cognitive mean difference 1.91, 95% CI 1.26–2.56) and severity (MMSE − 0.55, 95% CI -0.80 to -0.30; ADAS cognitive mean difference 0.89, 95% CI 0.57–1.21) predicted lower cognitive function. Greater lifelong mental activities partially mediated the relationship between CAA severity and NPS (indirect effect 0.05, 95% CI 0.0007-0.13), and greater lifelong mental activities led to less pronounced CAA severity and thus to less NPS (indirect effect − 0.08, 95% CI -0.22 to -0.002). Discussion This study suggests that NPS are common in CAA, and that this relationship may be driven by CAA severity. Furthermore, NPS seem to be tied to lower cognitive function. However, lifelong mental activities might mitigate the impact of NPS in CAA.

Abstract Background White matter hyperintensities (WMH) in subjects across the Alzheimer’s disease (AD) spectrum with minimal vascular pathology suggests that amyloid pathology—not just arterial hypertension—impacts WMH, which in turn adversely influences cognition. Here we seek to determine the effect of both hypertension and Aβ positivity on WMH, and their impact on cognition. Methods We analysed data from subjects with a low vascular profile and normal cognition (NC), subjective cognitive decline (SCD), and amnestic mild cognitive impairment (MCI) enrolled in the ongoing observational multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (n = 375, median age 70.0 [IQR 66.0, 74.4] years; 178 female; NC/SCD/MCI 127/162/86). All subjects underwent a rich neuropsychological assessment. We focused on baseline memory and executive function—derived from multiple neuropsychological tests using confirmatory factor analysis—, baseline preclinical Alzheimer’s cognitive composite 5 (PACC5) scores, and changes in PACC5 scores over the course of three years (ΔPACC5). Results Subjects with hypertension or Aβ positivity presented the largest WMH volumes (p FDR

Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer’s disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aβ42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05–3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57–2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00–1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26–0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid β beyond age.

IntroductionThe role of systolic blood pressure (SBP) variability in the pathogenesis of cerebral amyloid angiopathy (CAA) as an underlying cause of intracerebral hemorrhage (ICH) is unknown. We studied SBP variability before ICH according to CAA severity at autopsy.MethodsWe collected office (primary care or hospital clinic) BP readings during 10 years before first-ever ICH onset in adults who died and had brain research autopsy in the Lothian IntraCerebral Hemorrhage, Pathology, Imaging, and Neurological Outcome (LINCHPIN), prospective, population-based, inception cohort study. A neuropathologist assessed CAA severity using a histopathological rating scale, masked to BP readings. Functional principal component analysis was used to model SBP levels by time before ICH, and logistic regression models assessed associations of SBP variability indices with CAA severity (moderate-severe vs. absent-mild) adjusted for age, gender, and mean SBP.ResultsAmong 72 adults (median age 81 [interquartile range 76–86], 56% female, median number of SBP readings 11 [3–19]), patients with moderate-severe CAA had similar mean SBP (143 vs. 145 mmHg, P = 0.588) but lower SBP variability (SBP standard deviation [SD] 14 vs. 17 mmHg, P = 0.033) compared with patients with absent-mild CAA, and their SBP trajectories seemed to differ over 10 years before ICH. The odds of moderate-severe CAA were higher with lower maximum SBP (adjusted OR per 10 mmHg lower: 1.53, 95% confidence interval [CI] 1.09–2.15; P = 0.015) and lower SBP range (1.29 [1.03–1.61]; P = 0.028), but not SBP SD (1.95 [0.87–4.38]; P = 0.11).DiscussionCompared with absent-mild autopsy-verified CAA, moderate-severe CAA is associated with lower maximum and range of pre-morbid SBP.

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

Neuropsychiatric symptoms, such as executive dysfunction, fatigue and depression, are highly prevalent and severely incapacitating among Long- and Post-COVID patients (Schou et al., 2021), to the point where some are unable to resume their jobs and even their daily lives. While the prognosis of these patients remains elusive, cognition worsens over time in many of them (Lu et al., 2020). Perivascular inflammation in the brain, as a consequence of the blood-brain barrier damage caused by SARS-CoV-2 (Yang et al., 2020), is one of the mechanisms of ongoing systemic and intracerebral inflammation proposed to contribute to these long-lasting symptoms. We thus investigated two surrogate measurements of glymphatics, enlarged perivascular spaces in T1-w magnetic resonance imaging and three-dimensional propagation of cardiorespiratory pulsations in ultrafast magnetic resonance encephalography (Barghoorn et al., 2021), in 60 neuropsychiatric long-COVID patients, 30 healthy COVID-19 survivors and 30 never-infected healthy controls. We provide evidence of EPVS burden being associated with cognitive impairment and cardiorespiratory pulsations slightly varying among these groups. We hypothesize glymphatic clearance dysfunction might be a way for post-COVID to transition into a neurodegenerative disorder.

ABSTRACT: Stress urinary incontinence (SUI) is a common complication after radical prostatectomy. Placement of artificial urinary sphincter (AUS) is the current gold-standard treatment. Slings are considered as a therapeutic option for stress urinary incontinence, while non-adjustable slings may be considered for mild incontinence. On the other hand, adjustable Transobturator Male System (ATOMS®) consists of a sling that has an adjustable cushion compressing the bulbar urethra ventrally to achieve dryness. ATOMS® achieves continence rates between 64 and 88%, with major complications in only around 3% of the cases. Its market value is around 40% less than AUS.The objective is to show a step-by-step ATOMS® surgery putting forward a standard technique in a challenging preoperative decision-making scenario. For this, we describe a case of a 70-year-old man with right hemiparesis and severe stress incontinence after an open radical prostatectomy, using 6 wet pads per day, who was able to straighten his penis for self-catheterization under supervision while unable to deactivate an AUS pump during a preoperative trial. He underwent an ATOMS® procedure. No intraoperative complications occurred and the patient was discharged 24 h postoperatively. After 3 months, the patient reported using 0 pads per day, and had only occasional small losses of urine with a full bladder. At the 6-month follow-up, he reported being very satisfied with the surgical results, still using 0 pads daily, with no leakages and no storage or voiding symptoms. In conclusion, ATOMS® male adjustable sling may be effective for male stress incontinence, even in severe cases when AUS is not suitable, making it a good alternative in this scenario. Surgical steps shown in this video might be of help to achieve better outcomes.

Brain vascular health appears to be critical for preventing the development of amyotrophic lateral sclerosis (ALS) and slowing its progression. ALS patients often demonstrate cardiovascular risk factors and commonly suffer from cerebrovascular disease, with evidence of pathological alterations in their small cerebral blood vessels. Impaired vascular brain health has detrimental effects on motor neurons: vascular endothelial growth factor levels are lowered in ALS, which can compromise endothelial cell formation and the integrity of the blood–brain barrier. Increased turnover of neurovascular unit cells precedes their senescence, which, together with pericyte alterations, further fosters the failure of toxic metabolite removal. We here provide a comprehensive overview of the pathogenesis of impaired brain vascular health in ALS and how novel magnetic resonance imaging techniques can aid its detection. In particular, we discuss vascular patterns of blood supply to the motor cortex with the number of branches from the anterior and middle cerebral arteries acting as a novel marker of resistance and resilience against downstream effects of vascular risk and events in ALS. We outline how certain interventions adapted to patient needs and capabilities have the potential to mechanistically target the brain microvasculature towards favorable motor cortex blood supply patterns. Through this strategy, we aim to guide novel approaches to ALS management and a better understanding of ALS pathophysiology.

Although it is widely assumed that Artificial Intelligence (AI) will revolutionise healthcare in the near future, considerable progress must yet be made in order to gain the trust of healthcare professionals and patients. Improving AI transparency is a promising avenue for addressing such trust issues. However, transparency still lacks maturation and definitions. We seek to answer what challenges do experts and professionals in computing and healthcare identify concerning transparency of AI in healthcare? Here, we examine AI transparency in healthcare from five angles: interpretability, privacy, security, equity, and intellectual property. We respond to this question based on recent literature discussing the transparency of AI in healthcare and on an international online survey we sent to professionals working in computing and healthcare and potentially within AI. We collected responses from 40 professionals around the world. Overall, the survey results and current state of the art suggest key problems are a generalised lack of information available to the general public, a lack of understanding of transparency aspects covered in this work, and a lack of involvement of all stakeholders in the development of AI systems. We propose a set of recommendations, the implementation of which can enhance the transparency of AI in healthcare.

Accurate brain tissue segmentation in magnetic resonance imaging (MRI) has attracted the attention of medical doctors and researchers since variations in tissue volume and shape permit diagnosing and monitoring neurological diseases. Several proposals have been designed throughout the years comprising conventional machine learning strategies as well as convolutional neural networks (CNNs) approaches. In particular, in this paper, we analyze a sub-group of deep learning methods producing dense predictions. This branch, referred in the literature as fully CNN (FCNN), is of interest as these architectures can process an input volume in less time than CNNs. Our study focuses on understanding the architectural strengths and weaknesses of literature-like approaches. We implement eight FCNN architectures inspired by robust state-of-the-art methods on brain segmentation related tasks and use them within a standard pipeline. We evaluate them using the IBSR18, MICCAI2012, and iSeg2017 datasets as they contain infant and adult data and exhibit different voxel spacing, image quality, number of scans, and available imaging modalities. The discussion is driven in four directions: comparison between 2D and 3D approaches, the relevance of multiple imaging sequences, the effect of patch size, and the impact of patch overlap as a sampling strategy for training and testing models. Besides the aforementioned analysis, we show that the methods under evaluation can yield top performance on the three data collections. A public version is accessible to download from our research website to encourage other researchers to explore the evaluation framework.

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.

Purpose: We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW) for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase), a granular tabu search is applied during the improvement phase (second phase). Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.

Atrophy quantification is fundamental for understanding brain development and diagnosing and monitoring brain diseases. FSL-SIENA is a well-known fully automated method that has been widely used in brain magnetic resonance imaging studies. However, intensity variations arising during image acquisition may compromise evaluation, analysis and even diagnosis. In this work, we studied whether intensity standardisation could improve longitudinal atrophy quantification using FSL-SIENA. We evaluated the effect of six intensity standardisation methods—z-score, fuzzy c-means, Gaussian mixture model, kernel density estimation, histogram matching and WhiteStripe—on atrophy detected by FSL-SIENA. First, we evaluated scan–rescan repeatability using scans taken during the same session from OASIS (n=122). Except for WhiteStripe, intensity standardisation did not compromise the scan–rescan repeatability of FSL-SIENA. Second, we compared the mean annual atrophy for Alzheimer’s and control subjects from OASIS (n=122) and ADNI (n=147) yielded by FSL-SIENA with and without intensity standardisation, after adjusting for covariates. Our findings were threefold: First, the use of histogram matching was counterproductive, primarily as its assumption of equal tissue proportions does not necessarily hold in longitudinal studies. Second, standardising with z-score and WhiteStripe before registration affected the registration performance, thus leading to erroneous estimates. Third, z-score was the only method that consistently led to increased effect sizes compared to when omitted (no standardisation: 0.39 and 0.43 for OASIS and ADNI; z-score: 0.45 for both datasets). Overall, we found that incorporating z-score right after registration led to reduced inter-subject inter-scan intensity variability and benefited FSL-SIENA. Our work evinces the relevance of appropriate intensity standardisation in longitudinal cerebral atrophy assessments using FSL-SIENA.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to examine the distribution of an intravenous contrast agent within the brain. Computational methods have been devised to analyse the contrast uptake/washout over time as reflections of cerebrovascular dysfunction. However, there have been few direct comparisons of their relative strengths and weaknesses. In this paper, we compare five semiquantitative methods comprising the slope and area under the enhancement-time curve, the slope and area under the concentration-time curve ( S l o p e C o n and A U C C o n ), and changes in the power spectrum over time. We studied them in cerebrospinal fluid, normal tissues, stroke lesions, and white matter hyperintensities (WMH) using DCE-MRI scans from a cohort of patients with small vessel disease (SVD) who presented mild stroke. The total SVD score was associated with A U C C o n in WMH ( p < 0.05 ), but not with the other four methods. In WMH, we found higher A U C C o n was associated with younger age ( p < 0.001 ) and fewer WMH ( p < 0.001 ), whereas S l o p e C o n increased with younger age ( p > 0.05 ) and WMH burden ( p > 0.05 ). Our results show the potential of different measures extracted from concentration-time curves extracted from the same DCE examination to demonstrate cerebrovascular dysfunction better than those extracted from enhancement-time curves.

Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.