In Search of an Imaging Classification of Adenomyosis: A Role for Elastography?

Sun‐Wei Guo, Giuseppe Benagiano, Marc Bazot
Journal of clinical medicine · 2022 · vol. 12(1) , pp. 287 · doi:10.3390/jcm12010287 · PMID:36615089 · PMC9821156 · W4313361154
review OA: gold CC0 ⤵ 10 in-corpus citations
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This paper proposes a new imaging classification for adenomyosis incorporating elastographic findings to better correlate imaging with disease severity and histopathology.

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Abstract

Adenomyosis is a complex and poorly understood gynecological disease. It used to be diagnosed exclusively by histology after hysterectomy; today its diagnosis is carried out increasingly by imaging techniques, including transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI). However, the lack of a consensus on a classification system hampers relating imaging findings with disease severity or with the histopathological features of the disease, making it difficult to properly inform patients and clinicians regarding prognosis and appropriate management, as well as to compare different studies. Capitalizing on our grasp of key features of lesional natural history, here we propose adding elastographic findings into a new imaging classification of adenomyosis, incorporating affected area, pattern, the stiffest value of adenomyotic lesions as well as the neighboring tissues, and other pathologies. We argue that the tissue stiffness as measured by elastography, which has a wider dynamic detection range, quantitates a fundamental biologic property that directs cell function and fate in tissues, and correlates with the extent of lesional fibrosis, a proxy for lesional "age" known to correlate with vascularity and hormonal receptor activity. With this new addition, we believe that the resulting classification system could better inform patients and clinicians regarding prognosis and the most appropriate treatment modality, thus filling a void.

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adenomyosis

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