Quantifying brain health in acute ischemic stroke through effective reserve.

Objective: To quantify brain health using a measure of reserve that incorporates pre-existing pathology.

Methods: We analyzed two retrospective ischemic stroke cohorts (GASROS and SALVO) with neuroimaging and 90-day modified Rankin Scores (mRS) available. White matter hyperintensity (WMHv), brain, and intracranial volumes were automatically extracted, and brain parenchymal fraction (BPF) calculated.

White matter hyperintensity on MRI and plasma Aβ42/40 ratio additively increase the risk of cognitive impairment in hypertensive adults.

Introduction: Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study.

Methods: We analyzed the Systolic Blood Pressure Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aβ)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aβ risk, (3) WMH risk, and (4) combined high risk.

Impact and determinants of door in-door out time for stroke thrombectomy transfers in a large hub-and-spoke network.

Introduction: The mantra "time is brain" cannot be overstated for patients suffering from acute ischemic stroke. This is especially true for those with large vessel occlusions (LVOs) requiring transfer to an endovascular thrombectomy (EVT) capable center. We sought to evaluate the spoke hospital door in-door out (DIDO) times for patients transferred to our hub center for EVT.

Better nanoscience through open, collaborative, and critical discussions.

We aim to foster a discussion of science correction and of how individual researchers can improve the quality and control of scientific production. This is crucial because although the maintenance of rigorous standards and the scrupulous control of research findings and methods are sometimes taken for granted, in practice, we are routinely confronted with articles that contain errors.

Brain volume is a better biomarker of outcomes in ischemic stroke compared to brain atrophy.

Brain parenchymal fraction (BPF) has been used as a surrogate measure of global brain atrophy, and as a biomarker of brain reserve in studies evaluating clinical outcomes after brain injury. Total brain volume at the time of injury has recently been shown to influence functional outcomes, where larger brain volumes are associated with better outcomes. Here, we assess if brain volume at the time of ischemic stroke injury is a better biomarker of functional outcome than BPF.

Characterizing coma in large vessel occlusion stroke.

Background: Coma is an unresponsive state of disordered consciousness characterized by impaired arousal and awareness. The epidemiology and pathophysiology of coma in ischemic stroke has been underexplored. We sought to characterize the incidence and clinical features of coma as a presentation of large vessel occlusion (LVO) stroke.

Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity.

Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 10-10 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller.

Neuroimaging markers of patient-reported outcome measures in acute ischemic stroke.

Objectives: To determine the relationship between patient-reported outcome measures (PROMs) and volumetric imaging markers in acute ischemic stroke (AIS).

Patients And Methods: Patients presenting at Massachusetts General Hospital between February 14, 2017 and February 5, 2020 with a confirmed AIS by MRI were eligible and underwent a telephone interview including PROM-10 questionnaires 3-15 months after stroke. White matter hyperintensity (V) and brain volumes (V) were automatically determined using admission clinical MRI.

Informed consent practices for acute stroke therapy: principles, challenges and emerging opportunities.

Importance: Informed consent (IC) plays a crucial yet underexplored role in acute stroke treatment, particularly in the context of intravenous thrombolysis (IVT) and endovascular thrombectomy (EVT). This narrative review examines data on current IC practices in acute ischemic stroke management, specifically for patients treated with IVT or EVT, with the aim of identifying areas for improvement and strategies to enhance the IC process.

Observations: IC practices for IVT vary significantly among hospitals and physicians with the frequency of always requiring consent ranging from 21 to 37%.

The Brain Health Imperative in the 21st Century-A Call to Action: The AAN Brain Health Platform and Position Statement.

Brain health is crucial to optimizing both the function and well-being of every person at each stage of life and is key to both individual and social progress. As a concept, brain health is complex and requires a multidisciplinary collaborative approach between many professional and public organizations to bring into effect meaningful change. Neurologists are uniquely positioned to serve as specialists in brain health and to advance the newly evolving field of preventive neurology, which aims to identify individuals at high risk of brain disorders and other neurologic conditions and offer strategies to mitigate disease emergence or progression.

Management of Inherited CNS Small Vessel Diseases: The CADASIL Example: A Scientific Statement From the American Heart Association.

Lacunar infarcts and vascular dementia are important phenotypic characteristics of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, the most common inherited cerebral small vessel disease. Individuals with the disease show variability in the nature and onset of symptoms and rates of progression, which are only partially explained by differences in pathogenic mutations in the gene. Recognizing the disease early in its course and securing a molecular diagnosis are important clinical goals, despite the lack of proven disease-modifying treatments.

Mapping Lesion-Related Epilepsy to a Human Brain Network.

Importance: It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions.

Objective: To assess whether lesion locations associated with epilepsy map to specific brain regions and networks.

Spatial-Intensity Transforms for Medical Image-to-Image Translation.

Image-to-image translation has seen major advances in computer vision but can be difficult to apply to medical images, where imaging artifacts and data scarcity degrade the performance of conditional generative adversarial networks. We develop the spatial-intensity transform (SIT) to improve output image quality while closely matching the target domain. SIT constrains the generator to a smooth spatial transform (diffeomorphism) composed with sparse intensity changes.

Neuroimaging standards for research into small vessel disease-advances since 2013.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI.

The role of population-level preventive care for brain health in ageing.

Over the past several decades, a worldwide demographic transition has led to an increasing number of older adults with chronic neurological conditions. These conditions, which have a profound effect on the cognitive function and physical ability of older adults, also have a long preclinical phase. This feature provides a unique opportunity to implement preventive measures for high-risk groups and the population as a whole, and therefore to reduce the burden of neurological diseases.

Cognitive Impairment After Ischemic and Hemorrhagic Stroke: A Scientific Statement From the American Heart Association/American Stroke Association.

Purpose: Cognitive impairment is a common consequence of stroke and has direct implications for poststroke functioning and quality of life, including the ability to maintain a job, live independently, sustain interpersonal relationships, and drive a vehicle. In this scientific statement, we critically appraise the literature on the prevalence, diagnosis, and management of poststroke cognitive impairment (PSCI) and provide a framework for clinical care while highlighting gaps that merit further study.

Methods: We performed a scoping literature review of randomized controlled clinical trials, prospective and retrospective cohort studies, case-control studies, clinical guidelines, review articles, and editorials on the incidence and prevalence, natural history, diagnosis, and management of PSCI.

Bayesian stroke modeling details sex biases in the white matter substrates of aphasia.

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men.

Spoke-administered thrombolysis improves large vessel occlusion early recanalization: the real-world experience of a large academic hub-and-spoke telestroke network.

Introduction: Intravenous thrombolysis (IVT) prior to mechanical thrombectomy (MT) for large vessel occlusion (LVO) stroke is increasingly controversial. Recent trials support MT without IVT for patients presenting directly to MT-capable "hub" centers. However, bypassing IVT has not been evaluated for patients presenting to IVT-capable "spoke" hospitals that require hub transfer for MT.

Multimodal predictions of treatment outcome in major depression: A comparison of data-driven predictors with importance ratings by clinicians.

Background: Reliable prediction models of treatment outcome in Major Depressive Disorder (MDD) are currently lacking in clinical practice. Data-driven outcome definitions, combining data from multiple modalities and incorporating clinician expertise might improve predictions.

Methods: We used unsupervised machine learning to identify treatment outcome classes in 1060 MDD inpatients.