72 INTRODUCTION: The gold standard for diagnosing adenomyosis is histopathological after hysterectomy. Adenomyosis can also be diagnosed using Magnetic Resonance Imaging (MRI) (29,31,181). Accurate diagnosis on MRI remains challenging as a consensus on diagnostic criteria is lacking (19). Clinically, adenomyosis can be suspected based on symptoms (dysmenorrhoea, abnormal uterine bleeding (AUB) and infertility (19,81)), but this can be difficult due to up to a third of patients being asymptomatic (5,19). Ultrasound (TVUS) diagnostic criteria do exist and are the most commonly used noninvasive diagnostic tool(182–184), but are dependent on experienced sonographers (125,185,186). Furthermore, TVUS is less reliable in cases of mild or atypical adenomyosis (24,182). Moreover, in cases with combined pathology (e.g. adenomyosis and fibroids, or adenomyosis and endometriosis) TVUS diagnosis can be extra challenging (182). In cases such as these, MRI can help lead to a more definitive diagnosis. In the frequently associated condition endometriosis (187), reported diagnostic delay is up to nine years (20,21). The diagnostic delay for adenomyosis is unknown. The mental and physical toll on women suffering from either of these conditions is considerable (188). Especially in women of fertile age, there is a need for an accurate diagnostic tool so that appropriate management can be implemented swiftly. Early diagnosis is clinically relevant even in mild cases, due to a potential for reproductive sequelae (81). Such a tool could also be used to predict certain clinical outcomes such as treatment response, or fertility outcomes. There are a wide range of MRI parameters that can be used to characterise adenomyosis, such as junctional zone (JZ) thickness, myometrial signal intensity and uterine size (33,181). Many of them have not been investigated for diagnostic accuracy, and little is likewise known about their correlation with clinical outcomes (32,181). Despite attempts to create (imaging-based) classification systems for adenomyosis (16,17), there exists no clinically applicable tool for prediction of adenomyosis diagnosis on MRI. This study aims to create a multivariate prediction model for histopathological diagnosis of adenomyosis based on a combination of MRI parameters and clinical criteria prior to hysterectomy.
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