20–24 October 2018, Singapore Oral communication abstracts Czech Republic; 11 Centre of Obstetrics and Gynecology, Vil- nius University Hospital, Santariskiu Clinic, Vilnius, Lithua- nia; 12 Obstetrics and Gynecology, University of Navarra, Pamplona, Spain; 13 Department of Obstetrics and Gynecol- ogy, University of Cagliari, Cagliari, Italy; 14 Department of Pathology, Karolinska University Hospital, Stockholm, Swe- den; 15 Obstetrics and Gynecology, Lund University, Malm ¨ o, Sweden; 16 Obstetrics and Gynecology, University Hospital Leuven, Leuven, Belgium; 17 Department of Women and Chil- dren’s Health, Karolinska University Hospital, Stockholm, Sweden; 18 Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University, Prague, Czech Repub- lic; 19 Department of Development and Regeneration, KU Leuven, Leuven, Belgium Objectives: To estimate and validate cut-offs for objective measure- ments to predict deep myometrial invasion (MI), cervical stromal invasion (CSI). To validate the subjective and objective 2-step model to identify high risk cancer. Methods: Prospective multicentre study in 1714 women with endometrial cancer undergoing standardised expert transvaginal ultrasound examination: MI/CSI were evaluated subjectively and compared to objective measurements (at optimal and published cut-offs) to predict MI: Tumour/Uterine AP ratio and CSI: distance from outer-cervical-os to lower margin of tumour (Dist-OCO). We also validated a 2-step strategy to predict high risk cancer. First step: biopsy grade 3/non-endometrioid cancer classified as high-risk cancer. Second step: mathematical model with biopsy grade 1-2 and subjective assessment of MI/CSI (subjective model) or grade 1-2 & minimal-tumour-free margin (objective model). Histological assessment from hysterectomy was used as gold standard. Results: After exclusions, 1538 women were available for analysis. In this series, the optimal cut-off for MI for tumour/uterine AP ratio was 0.52 (accuracy 71%, AUC 0.77), for CSI for Dist-OCO was 23mm (accuracy 70%, AUC 0.77). When validated, the published cut-off for Tumour/Uterine AP ratio; 0.53 and Dist-OCO; 21 mm showed similar performance (accuracy 71%, AUC 0.77 and 70%, 0.72) as in the original paper on 144 patients (74%, AUC 0.80 and 65%, AUC 0.75). Subjective impression and grade had an accuracy of 80% to predict high risk cancer. The subjective model was slightly superior to objective model (AUC 0.76 versus 0.75), in line with the original series (accuracy of 80% (AUC 0.76) versus 74% (AUC of 0.75). Conclusions: Tumour/uterine AP ratio at the 0.52-0.53 cut-off and dist-OCO of 21-23mm had an accuracy of 70-74% and 65-70% to predict MI and CSI, respectively. High risk disease was best identified by subjective impression or by the subjective 2-step strategy at an accuracy of 80%. OC12.07 * Development of a clinical prediction model for diagnosing adenomyosis T. Tellum 1,2 , S. Nygaard 3 , E.K. Skovholt 4 , E. Qvigstad 1,2 , M. Lieng 1,2 1 Department of Gynecology, Oslo University Hospital, Ulle- val, Oslo, Norway; 2 Faculty of Clinical Medicine, University of Oslo, Oslo, Norway; 3 Department of Informatics, Univer- sity of Oslo, Oslo, Norway; 4 Department of Pathology, Oslo University Hospital, Oslo, Norway Objectives: To develop a multivariate prediction model for diag- nosing adenomyosis using predictors available through transvaginal ultrasonography (TVUS) and clinical examinations. * This presentation is eligible for the Young Investigator award (to be presented in the closing plenary). Methods: Prospective observational single-centre study at a Nor- wegian teaching university hospital. One hundred premenopausal women aged 30 – 50 years; undergoing hysterectomy due to a benign condition and not using hormonal treatment were consecutively enrolled. Preoperative 2D and 3D TVUS investigations were per- formed and the results were documented in a standardised form. Clinical information was collected using a questionnaire. The diag- nostic performance (sensitivity, specificity, area under the curve) of a multivariate prediction model for adenomyosis was evaluated. The independent diagnostic performance of single predictors and their quantitative effect (β) in the final model was assessed. Results: The final model showed a good test quality [AUC=0.86 (95% CI=0.79–0.94), optimal cut-off 0.56, sensitivity of 85%, specificity of 78%]. The following nine predictors were included [(sensitivity, specificity, β) or (AUC, β)]: presence of myometrial cysts (51%, 86%, β=0.86), fan-shaped echo (36%, 92%, β=0.54), hyperechoic islets (51%, 78%, β=0.62), globular uterus (61%, 83%, β=0.2), normal uterine shape (83%, 61%, β=–0.75), thick- est/thinnest ratio for uterine wall (0.61, β=0.26), maximum width of the junctional zone (JZ) in sagittal plane (0.71, β=0.1), regular appearance of JZ (31%, 92%, β=– 1.0), and grade of dysmenorrhea measured on a verbal numerical rating scale (0.61, β=0.08). Conclusions: We present the development of a multivariate model for diagnosing adenomyosis that weights the predictors based on their diagnostic significance. The reported findings could aid clinicians who are interpreting the heterogeneous appearance of adenomyosis in ultrasonography. OC12.08 High-intensity focused ultrasound of uterine fibroids: the role histogram parameters of quantitative T1 perfusion in predicting treatment outcome H.Q. Huy 1 , N.M. Duc 1 , C. Li 2 , B. Keserci 1 , N.Q. Dung 3 , P.M. Thong 1 1 Radiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh, Vietnam; 2 Radiology, First Afilliated Hospital of Xi’an Jiaotong University, Shannxi, China; 3 Radiology, Huu Nghi Hospital, Ha Noi, Vietnam Objectives: To investigate the role of histogram parameters derived from dynamic contrast-enhanced MRI in predicting magnetic resonance guided high-intensity focused ultrasound outcome of uterine fibroids defined as non-perfused volume (NPV) ratio ≥ 80%. Methods: 28 leiomyoma patients were divided into 2 groups: group 1 with NPV ratio ≥ 80% (n = 8) and group 2 with NPV ratio < 80% (n = 20). Mann Whitney test was utilised to compare histogram parameters: median, mean, skewness and kurtosis between two groups. Logistic regression was accessed independent factors in predicting NPV ratio ≥ 80%. Results: Mean NPV ratio was 94.8% for group 1 and 54.4 % for group 2 (p< 0.05). Median and mean histogram parameters of group 1 were significantly lower than group 2 (p < 0.05). Multiple logistic regression manifested that there was only median parameter had effect on NPV ratio ≥ 80%. Conclusions: Mean and median histogram parameters represented the whole tumour perfusion of group 1 were significant lower than group 2. Median parameter of histogram was an independent factor for NPV ratio ≥ 80%.  The Authors 2018  Ultrasound in Obstetrics & Gynecology 2018; 52 (Suppl. 1): 1–65. 29