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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Post-mortem magnetic resonance imaging in patients with suspected prion disease: Pathological confirmation,
Lorna M Gibson1,2, Francesca M Chappell3, David Summers4
1Department of Clinical Radiology, New Royal Infirmary of Edinburgh, Edinburgh, United Kingdom.
Abstract:
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.
Insights
Magnetic resonance imaging (MRI) features can help diagnose Creutzfeldt-Jakob Disease (CJD). Combining MRI findings with clinical data improves diagnostic accuracy, though autopsy remains essential for confirmation.
Area of Science:
- Neurology
- Radiology
- Pathology
Background:
- The diagnostic accuracy of magnetic resonance imaging (MRI) in suspected Creutzfeldt-Jakob Disease (CJD) requires further clarification.
- Identifying reliable MRI biomarkers and their correlation with disease progression is crucial for early diagnosis.
Purpose of the Study:
- To evaluate the diagnostic performance of specific in vivo MRI features for Creutzfeldt-Jakob Disease (CJD).
- To assess the reliability of MRI feature detection and their variation with disease duration.
- To determine if combining clinical and imaging data enhances CJD diagnostic accuracy.
Main Methods:
- Prospective study of 200 patients with suspected CJD, comparing MRI findings with post-mortem histopathology.
- Independent neuroradiologist assessment of MRI for atrophy, white matter hyperintensities, and basal ganglia/thalamic signals.
- Logistic regression models used to analyze associations between MRI features, clinical variables, and CJD diagnosis.
Main Results:
- A logistic regression model incorporating age, disease duration, atrophy, white matter hyperintensities, caudate signal, and pulvinar sign achieved 81% accuracy in classifying CJD.
- Neuroradiologists showed highest agreement on the presence/absence of atrophy (84.5%).
- No single imaging feature, including the pulvinar sign, independently predicted CJD after adjusting for other factors; no imaging feature correlated significantly with disease duration.
Conclusions:
- Combining specific MRI features (atrophy, white matter hyperintensities, caudate/pulvinar signals) with clinical data (age, disease duration) offers good diagnostic accuracy for CJD.
- While MRI is valuable, autopsy remains the definitive diagnostic method.
- Further research is needed to investigate the pulvinar sign's association with specific CJD subtypes due to data limitations.
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