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Systematic review and meta-analysis of the accuracy of MRI to diagnose appendicitis in the general population.

JOURNAL OF MAGNETIC RESONANCE IMAGING(2015)

Cited 31|Views35
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Abstract
PURPOSE:To perform a systematic review and meta-analysis of all published studies since 2005 that evaluate the accuracy of magnetic resonance imaging (MRI) for the diagnosis of acute appendicitis in the general population presenting to emergency departments. MATERIALS AND METHODS:All retrospective and prospective studies evaluating the accuracy of MRI to diagnose appendicitis published in English and listed in PubMed, Web of Science, Cinahl Plus, and the Cochrane Library since 2005 were included. Excluded studies were those without an explicitly stated reference standard, with insufficient data to calculate the study outcomes, or if the population enrolled was limited to pregnant women or children. Data were abstracted by one investigator and confirmed by another. Data included the number of true positives, true negatives, false positives, false negatives, number of equivocal cases, type of MRI scanner, type of MRI sequence, and demographic data including study setting and gender distribution. Summary test characteristics were calculated. Forest plots and a summary receiver operator characteristic plot were generated. RESULTS:Ten studies met eligibility criteria, representing patients from seven countries. Nine were prospective and two were multicenter studies. A total of 838 subjects were enrolled; 406 (48%) were women. All studies routinely used unenhanced MR images, although two used intravenous contrast-enhancement and three used diffusion-weighted imaging. Using a bivariate random-effects model the summary sensitivity was 96.6% (95% confidence interval [CI]: 92.3%-98.5%) and summary specificity was 95.9% (95% CI: 89.4%-98.4%). CONCLUSION:MRI has a high sensitivity and specificity for the diagnosis of appendicitis, similar to that reported previously for computed tomography. J. Magn. Reson. Imaging 2016;43:1346-1354.
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Key words
diffusion weighted imaging,meta analysis,mri
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