F1000Research (Sep 2023)
Development and validation of sonological classification and scoring system for uterine adenomyosis: A pilot study [version 2; peer review: 2 approved]
Abstract
Background: Adenomyosis is a common disorder in women of reproductive age. The gold standard for diagnosis is histopathological examination of hysterectomy specimen. However, only a small percentage of women undergo surgery as treatment is primarily hormonal. Non-invasive methods of diagnosis include transvaginal sonography and magnetic resonance imaging. Patient management in adenomyosis is often based on ultrasonographic diagnosis alone, highlighting the importance of a uniform, reproducible, clinically relevant and validated sonological classification and scoring system. Although a few investigators have proposed classification and scoring system for diagnosis of adenomyosis, none of those have been validated yet. This study aimed to propose and validate a new sonological classification and scoring system for adenomyosis. Methods: This was a prospective observational pilot study. A new sonological classification and scoring system of adenomyosis was proposed based on topography, type, size and extent, which was validated by comparing the sonological reporting with histopathological reporting. The main outcome measures that were measured were rate of agreement (Cohen’s kappa) between the findings of sonologist and pathologist; and diagnostic accuracy of the sonological classification of adenomyosis. Results: This pilot study included 30 women who underwent hysterectomy over a time period of one year with ultrasonographic diagnosis of adenomyosis. The rate of agreement (Cohen’s kappa) between the findings of sonologist and pathologist showed substantial agreement (0.703) for topography and almost perfect agreement for type (0.896), extent (0.892) and size (0.898). Conclusions: Our newly proposed sonological classification and scoring system for adenomyosis is valid and can be used for clinical application in interpersonal communication between clinicians, to prognosticate patients about the disease severity, to assess the candidates for surgical management and in further studies to correlate with symptoms severity and effectiveness of medical therapies.
