Table_1_The Diagnostic Value of MRI Pattern Recognition in Distal Myopathies.DOCX (733.24 kB)
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Table_1_The Diagnostic Value of MRI Pattern Recognition in Distal Myopathies.DOCX

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posted on 26.06.2018, 04:16 by Enrico Bugiardini, Jasper M. Morrow, Sachit Shah, Claire L. Wood, David S. Lynch, Alan M. Pitmann, Mary M. Reilly, Henry Houlden, Emma Matthews, Matt Parton, Michael G. Hanna, Volker Straub, Tarek A. Yousry

Objective: Distal myopathies are a diagnostically challenging group of diseases. We wanted to understand the value of MRI in the current clinical setting and explore the potential for optimizing its clinical application.

Methods: We retrospectively audited the diagnostic workup in a distal myopathy patient cohort, reassessing the diagnosis, whilst documenting the usage of MRI. We established a literature based distal myopathies MRI pattern template and assessed its diagnostic utility in terms of sensitivity, specificity, and potential impact on the diagnostic workup.

Results: Fifty-five patients were included; in 38 with a comprehensive set of data the diagnostic work-up was audited. The median time from symptoms onset to diagnosis was 12.1 years. The initial genetic diagnostic rate was 39%; 18% were misdiagnosed as neuropathies and 13% as inclusion body myositis (IBM). Based on 21 publications we established a MRI pattern template. Its overall sensitivity (50%) and specificity (32%) were low. However in some diseases (e.g., MYOT-related myopathy, TTN-HMERF) MRI correctly identified the causative gene. The number of genes suggested by MRI pattern analysis was smaller compared to clinical work up (median 1 vs. 9, p < 0.0001) but fewer genes were correctly predicted (5/10 vs. 7/10). MRI analysis ruled out IBM in all cases.

Conclusion: In the diagnostic work-up of distal myopathies, MRI is useful in assisting genetic testing and avoiding misdiagnosis (IBM). The overall low sensitivity and specificity limits its generalized use when traditional single gene test methods are applied. However, in the context of next generation sequencing MRI may represent a valuable tool for interpreting complex genetic results.