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The relationship between magnetic resonance imaging (MRI) and clinical variables in patients suspected to have Creutzfeldt-Jakob Disease (CJD) is uncertain. We aimed to determine which MRI features of CJD (positive or negative), previously described in vivo, accurately identify CJD, are most reliably detected, vary with disease duration, and whether combined clinical and imaging features increase diagnostic accuracy for CJD. Prospective patients suspected of having CJD were referred to the National CJD Research and Surveillance Unit between 1994–2004; post-mortem, brains were sent for MRI and histopathology. Two neuroradiologists independently assessed MRI for atrophy, white matter hyperintensities, and caudate, lentiform and pulvinar signals, blind to histopathological diagnosis and clinical details. We examined differences in variable frequencies using Fisher’s exact tests, and associations between variables and CJD in logistic regression models. Amongst 200 cases, 118 (59%) with a histopathological diagnosis of CJD and 82 (41%) with histopathological diagnoses other than CJD, a logistic regression model including age, disease duration at death, atrophy, white matter hyperintensities, bright or possibly bright caudate, and present pulvinar sign correctly classified 81% of cases as CJD versus not CJD. Pulvinar sign alone was not independently associated with an increased likelihood of histopathologically-confirmed CJD (of any subtype) or sporadic CJD after adjustment for age at death, disease duration, atrophy, white matter hyperintensities or caudate signal; despite the large sample, data sparsity precluded investigation of the association of pulvinar sign with variant CJD. No imaging feature varied significantly with disease duration. Of the positive CJD signs, neuroradiologists most frequently agreed on the presence or absence of atrophy (agreements in 169/200 cases [84.5%]). Combining patient age, and disease duration, with absence of atrophy and white matter hyperintensities and presence of increased caudate signal and pulvinar sign predicts CJD with good accuracy. Autopsy remains essential. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]