Recent developments in classification criteria and diagnosis guidelines for idiopathic inflammatory myopathies

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Abstract

Purpose of review

The aim of this review was to summarize key developments in classification and diagnosis of the idiopathic inflammatory myopathies (IIMs).

Recent findings

The recently published European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria for the IIMs provide a comprehensive, accurate and data-driven approach to identification of IIM cases appropriate for inclusion in research studies. Further, recent studies have advanced understanding of clinical manifestations of the IIMs and delineated the role of imaging, particularly magnetic resonance.

Summary

The recent publication of the EULAR/ACR classification criteria will potentially greatly improve IIM research through more accurate case identification and standardization across studies.

Future inclusion of newly recognized clinical associations with the MSAs may further improve the criteria's accuracy and utility. Clear and comprehensive understanding of associations between clinical manifestations, prognosis and multisystem involvement can aid diagnostic assessment; recent advances include delineation of such associations and expansion of the role of imaging.

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Most cited references 22

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119th ENMC international workshop: trial design in adult idiopathic inflammatory myopathies, with the exception of inclusion body myositis, 10-12 October 2003, Naarden, The Netherlands.

Jessica E Hoogendijk, Anthony Amato, Bryan R Lecky … (2004)

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Thigh muscle MRI in immune-mediated necrotising myopathy: extensive oedema, early muscle damage and role of anti-SRP autoantibodies as a marker of severity.

Iago Pinal-Fernández, Maria Casal-Dominguez, John A Carrino … (2017)

The aims of this study were to define the pattern of muscle involvement in patients with immune-mediated necrotising myopathy (IMNM) relative to those with other inflammatory myopathies and to compare patients with IMNM with different autoantibodies.

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Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods

Philippe M Burlina, Seth Billings, Neil Joshi … (2017)

Objective To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Methods Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and “engineered” features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. Results The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). Conclusions This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

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Author and article information

Journal

Journal ID (nlm-ta): Curr Opin Rheumatol

Journal ID (iso-abbrev): Curr Opin Rheumatol

Journal ID (publisher-id): CORHE

Title: Current Opinion in Rheumatology

Publisher: Lippincott Williams And Wilkins

ISSN (Print): 1040-8711

ISSN (Electronic): 1531-6963

Publication date (Print): November 2018

Publication date (Electronic): 28 September 2018

Volume: 30

Issue: 6

Pages: 606-613

Affiliations

[a ]NIHR Manchester Musculoskeletal Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre

[b ]Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester

[c ]Rheumatology Department, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford, UK

Author notes

Correspondence to Alexander Oldroyd, Arthritis Research UK Centre for Epidemiology, School of Biological Sciences, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. Tel: +44 161 27 51 614; e-mail: Alexander.oldroyd@ 123456manchester.ac.uk

Article

Publisher ID: BOR300607 Accession ID: 00013

DOI: 10.1097/BOR.0000000000000549

PMC ID: 6170146

PubMed ID: 30138132

SO-VID: 999f3260-1518-4c96-ab6e-5ddaaf358500

License:

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0

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Keywords: classification,dermatomyositis,diagnosis,myositis,polymyositis

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Keywords: classification, dermatomyositis, diagnosis, myositis, polymyositis

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Recent developments in classification criteria and diagnosis guidelines for idiopathic inflammatory myopathies

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Abstract

Purpose of review

Recent findings

Summary

Related collections

Hematology and Oncology Discovery

Most cited references 22

119th ENMC international workshop: trial design in adult idiopathic inflammatory myopathies, with the exception of inclusion body myositis, 10-12 October 2003, Naarden, The Netherlands.

Thigh muscle MRI in immune-mediated necrotising myopathy: extensive oedema, early muscle damage and role of anti-SRP autoantibodies as a marker of severity.

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods

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Cited by 7

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