Classification and Reporting Systems for Adenomyosis

Malcolm G. Munro, Munro MG
Journal of Minimally Invasive Gynecology · 2019 · vol. 27(2) , pp. 296–308 · doi:10.1016/j.jmig.2019.11.013 · PMID:31785418 · W2991226005
review OA: closed CC0 ⤵ 85 in-corpus citations
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This paper reviews current classification and reporting systems for adenomyosis, discussing their strengths, limitations, and implications for research and clinical practice.

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Abstract

ObjectiveTo conduct a review of the available histologic and image-based classification systems to determine which of these systems, if any, provide clinical utility for prognosis or the selection of appropriate therapeutic interventions.Data sourcesPubMed in addition to the bibliographies of identified publications.Methods of study selectionOne investigator searched PubMed using Medical Subject Headings terms that included "Adenomyosis," "Classification," "Ultrasound Classification," "MRI Classification," and "Diagnosis," TABULATION, INTEGRATION AND RESULTS: Search results were tabulated in a Microsoft Excel workbook that facilitated the identification of duplicate entries. Publications were allocated into separate categories that included histopathologic, ultrasound, and MRI classifications. Identified systems associated with clinical outcomes were separately tabulated. Abstracts of 1669 articles were reviewed and 278 were identified for review of full text. Twenty-five were considered potentially relevant from the PubMed review and an additional 17 were found in bibliographies. In the 42 full-text articles that were reviewed in detail, 9 histologic classifications were identified, 4 of which were accompanied by an attempt at clinical correlation, 1 of which described a correlation with the outcome of medical, procedural, or surgical intervention. There were 9 image-based reporting or classification systems, 2 using transvaginal ultrasound and 7 using MRI, 3 of which included correlations with intervention outcomes, although these were surrogate (imaging) and not clinical outcomes.ConclusionThere is inconsistency in histopathologic definitions, and there is no uniformly accepted or validated system of image-based reporting or classification that can inform clinical decision making. There exists a need for harmonized classification systems for both ultrasound and MRI that agree with the histopathologic features of the disorder.

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Condition tags

adenomyosis

MeSH descriptors

Adenomyosis Adenomyosis Diagnostic Imaging Image Interpretation, Computer-Assisted Image Interpretation, Computer-Assisted Image Interpretation, Computer-Assisted Adenomyosis Adenomyosis Adenomyosis Data Interpretation, Statistical Diagnostic Imaging Diagnostic Imaging Diagnostic Imaging Female Humans Magnetic Resonance Imaging Research Design Research Design Ultrasonography

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (80)

Cited by (50)

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License: CC0 · commercial use OK