Developing precision stroke imaging

Endothelial Shear Stress and Platelet FcγRIIa Expression in Intracranial Atherosclerotic Disease

Intracranial atherosclerotic disease (ICAD) has been characterized by the degree of arterial stenosis and downstream hypoperfusion, yet microscopic derangements of endothelial shear stress at the luminal wall may be key determinants of plaque growth, vascular remodeling and thrombosis that culminate in recurrent stroke. Platelet interactions have similarly been a principal focus of treatment, however, the mechanistic basis of anti-platelet strategies is largely extrapolated rather than directly investigated in ICAD. Platelet FcγRIIa expression has been identified as a potent risk factor in cardiovascular disease, as elevated expression markedly increases the risk of recurrent events. Differential activation of the platelet FcγRIIa receptor may also explain the variable response of individual patients to anti-platelet medications. We review existing data on endothelial shear stress and potential interactions with the platelet FcγRIIa receptor that may alter the evolving impact of ICAD, based on local pathophysiology at the site of arterial stenosis. Current methods for quantification of endothelial shear stress and platelet activation are described, including tools that may be readily adapted to the clinical realm for further understanding of ICAD.

The Use of Deep Learning to Predict Stroke Patient Mortality

The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a stroke improve outcomes. Medical service use and health behavior data are easier to collect than medical imaging data. Here, we used a deep neural network to detect stroke using medical service use and health behavior data; we identified 15,099 patients with stroke. Principal component analysis (PCA) featuring quantile scaling was used to extract relevant background features from medical records; we used these to predict stroke. We compared our method (a scaled PCA/deep neural network [DNN] approach) to five other machine-learning methods. The area under the curve (AUC) value of our method was 83.48%; hence; it can be used by both patients and doctors to prescreen for possible stroke.

Pipeline for Analyzing Lesions After Stroke (PALS)

Lesion analyses are critical for drawing insights about stroke injury and recovery, and their importance is underscored by growing efforts to collect and combine stroke neuroimaging data across research sites. However, while there are numerous processing pipelines for neuroimaging data in general, few can be smoothly applied to stroke data due to complications analyzing the lesioned region. As researchers often use their own tools or manual methods for stroke MRI analysis, this could lead to greater errors and difficulty replicating findings over time and across sites. Rigorous analysis protocols and quality control pipelines are thus urgently needed for stroke neuroimaging. To this end, we created the Pipeline for Analyzing Lesions after Stroke (PALS; DOI: https://doi.org/10.5281/zenodo.1266980), a scalable and user-friendly toolbox to facilitate and ensure quality in stroke research specifically using T1-weighted MRIs. The PALS toolbox offers four modules integrated into a single pipeline, including (1) reorientation to radiological convention, (2) lesion correction for healthy white matter voxels, (3) lesion load calculation, and (4) visual quality control. In the present paper, we discuss each module and provide validation and example cases of our toolbox using multi-site data. Importantly, we also show that lesion correction with PALS significantly improves similarity between manual lesion segmentations by different tracers (z = 3.43, p = 0.0018). PALS can be found online at https://github.com/npnl/PALS. Future work will expand the PALS capabilities to include multimodal stroke imaging. We hope PALS will be a useful tool for the stroke neuroimaging community and foster new clinical insights.

Mapping the collaterome for precision cerebrovascular health: Theranostics in the continuum of stroke and dementia

Precision cerebrovascular health or individualized long-term preservation of the brain and associated blood vessels, is predicated on understanding, diagnosing, and tailoring therapies for people at risk of ischemic injury associated with stroke and vascular dementia. The associated imaging patterns are sculpted by the protective effect of the collaterome, the innate compensatory ability of the brain and vasculature to offset hypoperfusion when antegrade or normal arterial inflow pathways are compromised. Theranostics or rational and synchronous use of diagnostic studies in tandem with specific therapies to optimally guide patient outcomes in ischemic brain disorders may capitalize on the pivotal role of the collaterome. Understanding the functional impact of the collaterome across populations of individuals would advance translational science on the brain, while questions with immediate clinical implications may be prioritized. Big data and systematic analyses are necessary to develop normative standards, multimodal imaging atlases, and delineation of specific patterns to guide clinical management. Large-scale, systematic imaging analyses of the collaterome provide a platform for translational work on cerebral collateral circulation and hemodynamics and a theranostic framework with direct clinical implications. This article frames incipient research objectives to guide precision stroke medicine in coming years, building upon the collaterome concept in brain health.

Collaterals 2016: Translating the collaterome around the globe

Collaterals 2016 (third International Symposium on Collaterals to the Brain) was a multidisciplinary scientific conference focused on collateral circulation in acute ischemic stroke. Decisive challenges include generalizability of optimal triage and selection paradigms based on collateral status for definitive treatment of acute ischemic stroke, rapid dissemination of expert methods, and the urgent need to leverage networking opportunities for stroke science related to the hemodynamics of collaterals. The collaterome, or individual capacity to offset ischemia in the brain, and determination of a favorable collateral profile have become pivotal factors in consideration of the precision medicine of stroke decision-making. The conference convened over 50 invited faculty from around the world to connect on-site participants at a state-of-the-art facility with remote audiences in more than 22 countries and regions. The 2½-day program was structured into 40-min sessions devoted to key issues in translating the collaterome in acute stroke therapy across the globe. This unique forum of expertise emphasized the timely impact of collaterals on a monumental scale, encouraging maximal participation, rapid diffusion and added value of a diverse networking resource. The meeting format established a model geographical framework and innovative videoconferencing platform for future scientific conferences.

Principles of precision medicine in stroke

The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health.

Toward precision medicine in neurological diseases

Technological development has paved the way for accelerated genomic discovery and is bringing precision medicine into view. The goal of precision medicine is to deliver optimally targeted and timed interventions tailored to an individual's molecular drivers of disease. Neurological diseases are promisingly suited models for precision medicine because of the rapidly expanding genetic knowledge base, phenotypic classification, the development of biomarkers and the potential modifying treatments. Moving forward, it is crucial that through these integrated research platforms to provide analysis both for accurate personal genome analysis and gene and drug discovery. Here we describe our vision of how precision medicine can bring greater clarity to the clinical and biological complexity of neurological diseases.

Novel Diagnostic and Monitoring Tools in Stroke: an Individualized Patient-Centered Precision Medicine Approach

Central to the pathogenesis of ischaemic stroke are the normally protective processes of platelet adhesion and activation. Experimental evidence has shown that the ligand-receptor interactions in ischaemic stroke represent a thrombo-inflammatory cascade, which presents research opportunities into new treatment. However, as anti-platelet drugs have the potential to cause severe side effects in ischaemic stroke patients (as well as other vascular disease patients), it is important to carefully monitor the risk of bleeding and risk of thrombus in patients receiving treatment. Because thrombo-embolic ischaemic stroke is a major health issue, we suggest that the answer to adequate treatment is based on an individualized patient-centered approach, inline with the latest NIH precision medicine approach. A combination of viscoelastic methodologies may be used in a personalized patient-centered regime, including thromboelastography (TEG®) and the lesser used scanning electron microscopy approach (SEM). Thromboelastography provides a dynamic measure of clot formation, strength, and lysis, whereas SEM is a visual structural tool to study patient fibrin structure in great detail. Therefore, we consider the evidence for TEG® and SEM as unique means to confirm stroke diagnosis, screen at-risk patients, and monitor treatment efficacy. Here we argue that the current approach to stroke treatment needs to be restructured and new innovative thought patterns need to be applied, as even approved therapies require close patient monitoring to determine efficacy, match treatment regimens to each patient's individual needs, and assess the risk of dangerous adverse effects. TEG® and SEM have the potential to be a useful tool and could potentially alter the clinical approach to managing ischaemic stroke. As envisaged in the NIH precision medicine approach, this will involve a number of role players and innovative new research ideas, with benefits that will ultimately only be realized in a few years. Therefore, with this ultimate goal in mind, we suggest that an individualized patient-orientated approach is now available and therefore already within our ability to use.

Innovative Interventional and Imaging Registries: Precision Medicine in Cerebrovascular Disorders

BACKGROUND

Precision medicine in cerebrovascular disorders may be greatly advanced by the use of innovative interventional and imaging-intensive registries. Registries have remained subsidiary to randomized controlled trials, yet vast opportunities exist to leverage big data in stroke.

SUMMARY

This overview builds upon the rationale for innovative, imaging-intensive interventional registries as a pivotal step in realizing precision medicine for several cerebrovascular disorders. Such enhanced registries may serve as a model for expansion of our translational research pipeline to fully leverage the role of phase IV investigations. The scope and role of registries in precision medicine are considered, followed by a review on the history of stroke and interventional registries, data considerations, critiques or barriers to such initiatives, and the potential modernization of registry methods into efficient, searchable, imaging-intensive resources that simultaneously offer clinical, research and educational added value.

KEY MESSAGES

Recent advances in technology, informatics and endovascular stroke therapies converge to provide an exceptional opportunity for registries to catapult further progress. There is now a tremendous opportunity to deploy registries in acute stroke, intracranial atherosclerotic disease and carotid disease where other clinical trials leave questions unanswered. Unlike prior registries, imaging-intensive and modernized methods may leverage current technological capabilities around the world to efficiently address key objectives and provide added clinical, research and educational value.

Toward a Literature-Driven Definition of Big Data in Healthcare

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.

The Modern Clinical Neuroimager: Leading the Next Generation in Stroke

The recent culmination of imaging-endowed endovascular stroke trials has decisively proven the utility of clinically relevant neuroimaging in improving the outcome of patients with potentially debilitating neurological disorders. These large multicenter trials conducted across several continents notably utilized a variety of multimodal CT/MRI modalities to rapidly identify a favorable collateral profile that presages clinically beneficial revascularization. The modern clinical neuroimager may accelerate complex decision-making through the rational use of a variety of imaging modalities and an active feedback loop of imaging at the bedside. The modern clinical neuroimager is often the initial care provider for a wide range or type of stroke patients from hemorrhage to ischemia, armed with the incredibly important aspects of clinical history and examination findings and best poised to utilize imaging to guide therapy from acute stroke to recovery and prevention. The next generation in stroke should not exclusively focus on whether to order a CT or MRI counting minutes at the bedside, but actively and efficiently integrate the vast wealth of information available when imaging is used in the proper clinical context. The novel endovascular era in stroke provides an ideal venue for the synergistic goals of translating research advances, improving patient outcomes and ongoing education as a modern neuroimager.

Imaging of cerebrovascular disorders: precision medicine and the collaterome

Imaging of stroke and neurovascular disorders has profoundly enhanced clinical practice and related research during the last 40 years since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI) enabled mapping of the brain. We highlight recent advances in neurovascular imaging. We describe how the convergence of readily available data and new clinical trial paradigms will recast our methods for studying the neurovascular patient. The application of a precision medicine approach to the collaterome, a comprehensive synthesis of neurovascular pathophysiology, will entail novel methods for clinical trial randomization, collection of routine and clinical trial imaging results, data archiving, and analysis.

Big and bigger data in endovascular stroke therapy

More than 30 years after initial reports demonstrated the feasibility of intra-arterial or endovascular therapies for the treatment of acute ischemic stroke, big data have finally established requisite evidence for the safety and efficacy of thrombectomy. Cautious enthusiasm for this breakthrough is tempered, as we await the bigger data of these trials to understand the constellation of variables that ensured success. Noninvasive imaging, including multimodal computed tomography and MRI as used in recent endovascular trials, has dramatically advanced since that time, providing snapshots or profiles of the collaterome in a given patient. Data-driven analyses will provide the most potent argument to distinguish comprehensive stroke centers from interventional-ready sites. These trials may provide insight on the future role of telestroke, for intravenous thrombolysis and remote imaging review of multimodal computed tomography or MRI to streamline patient transfer for endovascular therapy. Rather than concluding that recent trials have answered the most important question regarding endovascular therapy, even more data are needed to effectively translate such success and extend such potential benefit to the greatest number of stroke patients encountered on a daily basis.