Connie Rees

73 MATERIALS AND METHODS: Study Objective: To develop a multivariate prediction model for adenomyosis diagnosis on histopathology after hysterectomy based on MRI and clinical parameters. Setting: Gynaecological department of a Dutch regional referral teaching hospital. Design: Single centre retrospective observational cohort study Patient Selection and Eligibility: Patients were selected through screening of electronic hospital patient records in Healthcare Information eXchange (HiX) (ChipSoft BV, Amsterdam, the Netherlands), based on electronic search queries in CTcue (CTcue BV, Amsterdam, the Netherlands). Relevant search terms are presented in appendix 3A. Women were eligible for inclusion if they underwent a hysterectomy due to benign pathology in our centre between 2007 and March 2022 and had preoperative pelvic MRI available. Subjects were included regardless of symptoms. Subjects were excluded if: they did not have a pelvic MRI prior to hysterectomy, they had an unsuitable MRI protocol (see appendix 10B for further specification), they were post-menopausal (due to no longer active disease), had a gynaecological malignancy, or if no pathology report was available after hysterectomy. Patients were also excluded if they explicitly stated that they did not want their information to be used for research purposes. Outcomes: The primary outcome assessed in this study is the histopathological diagnosis of adenomyosis after hysterectomy. Secondary outcomes include clinical and MRI parameters of included patients. Histopathology Diagnosis: Adenomyosis was diagnosed based on histopathology if endometrial glands were seen in the myometrium:

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