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The purpose of this study is to compare ultrasonographic ovarian mass scoring systems in pregnant women.This multicenter study included women with an ovarian mass during pregnancy who were evaluated using ultrasound and underwent surgery in 11 referral hospitals. The ovarian mass was evaluated and scored using three different scoring systems(International Ovarian Tumor Analysis Assessment of Different NEoplasias in the adnexa[IOTA ADNEX], Sassone, and Lerner). The final diagnosis was made histopathologically. Receiver operating characteristic(ROC) curves were generated for each scoring system.During the study period, 236 pregnant women underwent surgery for an ovarian mass, including 223 women(94.5%) with a benign ovarian mass and 13 women(5.5%) with a malignant ovarian mass. Among 10 ultrasound image findings, six findings were different between benign and ovarian masses(maximal diameter of mass, maximal diameter of solid mass, wall thickness of mass, inner wall structure, thickness of septations, and papillarity). In all three scoring systems, the ovarian mass scores were significantly higher in malignant masses than in benign masses, with the highest area under the ROC curve(AUROC) in the Sassone scoring system(AUROC: 0.831 for Sassone, 0.710 for Lerner vs 0.709 for IOTA ADNEX; p 0.05, between the Sassone and Lerner/ IOTA ADNEX). A combined model was developed with the six different ultrasound findings, and the AUROC of the combined model was 0.883(p = not significant between the combined model and Sassone).In pregnant women, malignant ovarian tumors can be predicted with high accuracy using either the Sassone scoring system or the combined model.

Objectives: The objectives of this study were to evaluate ovarian masses across multiple imaging models in series and in parallel with a second-generation multivariate index assay (MIA2G), and to develop a reliable protocol for ovarian malignancy risk stratification. Methods: This is an ongoing randomized controlled trial in Filipino women with ovarian masses in the University of the Philippines - Philippine General Hospital. A comprehensive analysis was performed between various imaging risk classifier methods: IOTA (International Ovarian Tumor Analysis) - Simple Rules, IOTA - LR1, IOTA LR - 2, IOTA-Adnex, Sassone, and Lerner; and a biochemical algorithm: MIA2G (OVERA). The sensitivity, specificity, positive and negative predictive values, and correct classification rate in classifying benign or malignant lesions were computed, as well as their interval estimates. The histopathologic findings served as the ‘gold’ standard or variable that represented ‘true’ presence of disease. Individual screening performances were assessed using parallel testing between the MIA2G (with conventional cut-off at 5.0) and various imaging risk classifier methods. However, based on previous local data, a higher cut-off at 7.0 was observed such that an additional analysis with the adjusted cut-off was also computed. Similarly, these diagnostic criteria were evaluated in series with the imaging tests followed by the MIA2G at both cut offs (5.0 and 7.0). Download : Download high-res image (657KB) Download : Download full-size image Results: There were 410 tumors identified from 343 women included in the study. Around 20% (67/343) had bilateral masses and only 72% (246/343) of women had histopathologic findings available. The observed study prevalence of women with confirmed malignancy was 31.5% (108/343, 26.6 to 36.7%) and much higher than the expected prevalence of the general population. The MIA2G was noted to be high-risk in 73% (251/343) of all the evaluable subjects using the traditional cut-off at greater than 5.0; but at a higher cut-off of 7.0, this resulted in only 40% (138/343) being classified as high-risk. The individual imaging test sensitivity, specificity, and predictive values calculated showed that the optimal imaging methods were IOTA-LR1, IOTA-LR2 and IOTA-Simple Rules, but the latter had a significant number of inconclusive results. When combined with imaging models in parallel, the conventional MIA2G cut-off (5.0), was noted to perform poorer than the adjusted cut-off (7.0). On the other hand, serial testing showed higher accuracy for imaging tests combined with the conventional MIA2G cut off (5.0). Conclusions: In this investigation, ultrasound imaging models and MIA2G are complementary and when used in combination, these provide a better understanding of the malignant potential of an ovarian tumor. MIA2G combined with IOTA-LR2 was the most reliable combination. For parallel testing, an adjusted MIA2G cut-off (7.0) increased overall test accuracy and sensitivity. In serial testing, the conventional MIA2G cut-off (5.0) resulted in overall higher test accuracy and specificity. Applied to our local setting, where the choice of imaging model used for pre-operative evaluation will vary according to the health provider's experience in performing such tests and where there are no standard protocols on the use of biochemical assays, inclusion of such findings in practice guidelines will significantly affect malignancy risk stratification and clinical outcome.

Objectives To evaluate the diagnostic performance of the IOTA (International Ovarian Tumor Analysis group) (clinically oriented three-step strategy for preoperative characterization of ovarian masses when ultrasonography is performed by examiners with different background training and experience. Methods A 27-month prospective multicenter cross-sectional study was performed. 36 level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardized approach. Step one uses simple descriptors (SD), step two ultrasound simple rules (SR) and step three subjective assessment of ultrasound images (SA) by examiners. The final outcome was findings at surgery and the histological diagnosis of surgically removed masses. Results 1165 women with adnexal masses underwent transvaginal ultrasonography, 301 had surgery. Prevalence of malignancy was 31% (n=92). SD were able to classify 46% of the masses into benign or malignant (step one), with a sensitivity of 93% and specificity of 97%. Applying SD followed by SR to residual unclassified masses by SD enabled 89% of all masses (n=268) to be classified with a sensitivity 95% of and specificity of 95%. SA was then used to evaluate the rest of the masses. Compared to the risk of malignancy index (RMI), the sensitivity and specificity for the three-step (SD+SR+SA) strategy were 93% (95% CI: 86–97%) and 92% (95% CI: 87–95%) vs. 72% (95% CI: 62–80%) and 95% (95% CI: 91–97%) for RMI, respectively. Conclusion The IOTA three-step strategy shows good test performance on external validation in the hands of ultrasonography examiners with different background training and experience. This performance is considerably better than the RMI.