998 research outputs found

    A comparison of location of acute symptomatic vs. 'silent' small vessel lesions

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    Background: Acute lacunar ischaemic stroke, white matter hyperintensities, and lacunes are all features of cerebral small vessel disease. It is unclear why some small vessel disease lesions present with acute stroke symptoms, whereas others typically do not. Aim: To test if lesion location could be one reason why some small vessel disease lesions present with acute stroke, whereas others accumulate covertly. Methods: We identified prospectively patients who presented with acute lacunar stroke symptoms with a recent small subcortical infarct confirmed on magnetic resonance diffusion imaging. We compared the distribution of the acute infarcts with that of white matter hyperintensity and lacunes using computational image mapping methods. Results: In 188 patients, mean age 67 ± standard deviation 12 years, the lesions that presented with acute lacunar ischaemic stroke were located in or near the main motor and sensory tracts in (descending order): posterior limb of the internal capsule (probability density 0·2/mm3), centrum semiovale (probability density = 0·15/mm3), medial lentiform nucleus/lateral thalamus (probability density = 0·09/mm3), and pons (probability density = 0·02/mm3). Most lacunes were in the lentiform nucleus (probability density = 0·01–0·04/mm3) or external capsule (probability density = 0·05/mm3). Most white matter hyperintensities were in centrum semiovale (except for the area affected by the acute symptomatic infarcts), external capsules, basal ganglia, and brainstem, with little overlap with the acute symptomatic infarcts (analysis of variance, P < 0·01). Conclusions: Lesions that present with acute lacunar ischaemic stroke symptoms may be more likely noticed by the patient through affecting the main motor and sensory tracts, whereas white matter hyperintensity and asymptomatic lacunes mainly affect other areas. Brain location could at least partly explain the symptomatic vs. covert development of small vessel disease

    A Large Web-Based Observer Reliability Study of Early Ischaemic Signs on Computed Tomography. The Acute Cerebral CT Evaluation of Stroke Study (ACCESS)

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    BACKGROUND: Early signs of ischaemic stroke on computerised tomography (CT) scanning are subtle but CT is the most widely available diagnostic test for stroke. Scoring methods that code for the extent of brain ischaemia may improve stroke diagnosis and quantification of the impact of ischaemia. METHODOLOGY AND PRINCIPAL FINDINGS: We showed CT scans from patients with acute ischaemic stroke (n = 32, with different patient characteristics and ischaemia signs) to doctors in stroke-related specialties world-wide over the web. CT scans were shown twice, randomly and blindly. Observers entered their scan readings, including early ischaemic signs by three scoring methods, into the web database. We compared observers' scorings to a reference standard neuroradiologist using area under receiver operator characteristic curve (AUC) analysis, Cronbach's alpha and logistic regression to determine the effect of scales, patient, scan and observer variables on detection of early ischaemic changes. Amongst 258 readers representing 33 nationalities and six specialties, the AUCs comparing readers with the reference standard detection of ischaemic signs were similar for all scales and both occasions. Being a neuroradiologist, slower scan reading, more pronounced ischaemic signs and later time to CT all improved detection of early ischaemic signs and agreement on the rating scales. Scan quality, stroke severity and number of years of training did not affect agreement. CONCLUSIONS: Large-scale observer reliability studies are possible using web-based tools and inform routine practice. Slower scan reading and use of CT infarct rating scales improve detection of acute ischaemic signs and should be encouraged to improve stroke diagnosis

    Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing

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    Abstract Background Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies. Methods We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss. Results The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data. Conclusions Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage
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