Frontiers in Medicine (Aug 2024)

Prediction of adenomyosis according to revised definitions of morphological uterus sonographic assessment features

  • Onur Yavuz,
  • Asli Akdöner,
  • Mehmet Eyüphan Özgozen,
  • Begüm Ertan,
  • Sefa Kurt,
  • Emine Cagnur Ulukuş,
  • Mehmet Güney

DOI
https://doi.org/10.3389/fmed.2024.1387515
Journal volume & issue
Vol. 11

Abstract

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ObjectivesThis study aimed to predict the diagnosis of adenomyosis by revised definitions of morphological uterus sonographic assessment (MUSA) features in individuals who had hysterectomy.MethodsThis was retrospective cohort research conducted at a tertiary facility. Between January 2022 and January 2023, 196 individuals who had hysterectomy were analyzed in the research. The revised definitions of MUSA features of the adenomyosis approach were used to record the direct and indirect results of the sonography. The cases were classified as Group 1 (adenomyosis; n = 40, 20.4%) and Group 2 (control; n = 156, 79.6%) according to histopathology reports.ResultsHyperechogenic islands and echogenic subendometrial buds and lines were the most predictive direct features (p = 0.02). Globular uterus and irregular junctional zone were the most predictive indirect features (p = 0.04; p = 0.03, respectively). Among all indirect features, the globular uterus was the most predictive (p = 0.02). Total feature >4 was determined as the significant cutoff value to predict adenomyosis (p < 0.001).ConclusionThis study shows that combinations with a total number of features >4 can be practically used in the evaluation of adenomyosis using the revised definitions of MUSA features.

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