Study Objective: Development of a prediction tool for histopathological
adenomyosis diagnosis after hysterectomy based on MRI and clinical
parameters. Design: Single-centre retrospective cohort study Setting:
Gynaecological department of a referral hospital from 2007-2022.
Population: 296 women undergoing hysterectomy with preoperative pelvic
MRI Methods: MRI’s were retrospectively assessed for adenomyosis markers
(junctional zone (JZ) parameters, high signal intensity foci (HSI) foci)
in a blinded fashion. A multivariate regression model for
histopathological adenomyosis diagnosis was developed based on MRI and
clinical variables from univariate analysis with p>0.10 and
factors deemed clinically relevant. Results: 131/296 women (44.3%) had
histopathological adenomyosis. Patients were of comparable age at
hysterectomy, BMI and clinical symptoms, p>0.05.
Adenomyosis patients more often had undergone a curettage (22.1% vs.
8.9%, p=0.002), a higher mean JZ thickness (9.40 vs. 8.35mm, p
<.001), maximal JZ thickness (16.00 vs. 13.40mm,
p<.001), mean JZ/myometrium ratio (0.56 vs. 0.49, p=.040), and
JZ differential (8.60 vs. 8.15mm, p=.003). Presence of HSI foci was a
strong predictor for adenomyosis (39.7% vs. 8.9%, p<.001).
Based on the parameters age and BMI, history of curettage,
dysmenorrhoea, abnormal uterine bleeding (AUB), mean JZ, JZ Differential
5mm, JZ/myometrium ratio >.40, and presence of HSI Foci,
a predictive model was created with a good Area Under the Curve (AUC) of
.776. Conclusions: This is the first study to create a diagnostic tool
based on MRI and clinical parameters for adenomyosis diagnosis. After
sufficient external validation, this model could function as a useful
clinical-decision making tool in women with suspected adenomyosis.