4.5 Article

Classification and Reporting Systems for Adenomyosis

Journal

JOURNAL OF MINIMALLY INVASIVE GYNECOLOGY
Volume 27, Issue 2, Pages 296-308

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmig.2019.11.013

Keywords

Adenomyosis; Adenomyosis classification; Adenomyosis imaging; Adenomyosis categorization

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Objective: To 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 Sources: PubMed in addition to the bibliographies of identified publications. Methods of Study Selection: One 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. Conclusion: There 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. (C) 2019 Published by Elsevier Inc. on behalf of AAGL.

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