Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital

Abstract

Objectives: The aim of this study was to evaluate the accuracy of IOTA Simple Rules (SR), IOTA ADNEX model, Risk of Malignancy Index (RMI), and subjective assessment (SA) which is used for adnexal mass assessment in our institution. Design: Prospective observational study. Participants/Materials, Setting, Methods: We included patients with at least one adnexal mass who needed elective surgical evaluation based on clinical and laboratory findings. Patients admitted to Clinic for Gynecology and Obstetrics, University Clinical Center of Serbia were recruited for the study between January 2019 and June 2021. Level II ultrasonographers performed a gray-scale and Doppler exam for each patient. Preoperative classification of adnexal masses (benign or malignant) was performed by subjective assessment (SA), the International Ovarian Analysis Group (IOTA) Simple Rules (SR), IOTA ADNEX model and Risk of Malignancy Index (RMI). Postoperatively obtained histological findings were used as a reference. Results During the study period, we enrolled 179 premenopausal and 217 postmenopausal patients, representing 396 patients in our sample. Prevalence of malignant disease in pre and postmenopausal groups was 16.2% (29/179) and 41% (89/217), respectively. Malignant disease was diagnosed in 29.8% (118/396) of patients. SA achieved the highest discrimination accuracy between benign and malignant tumors (AUC of 0.928, 95% CI (0.898-0.952)). For SA, the overall diagnostic accuracy, sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were 91.4%, 88.1%, 92.8%, 12.25, and 0.13. The AUC for SR+SA was 0.912 (95% CI (0.880-0.938)). Regarding SR+SA, diagnostic accuracy, sensitivity, specificity, LR+, and LR - were 92.4%, 88.1%, 94.2%, 15.31, and 0.13. The ADNEX model had the AUC of 0.914 (95% CI (0.882-0.940)). Binary classification using the ADNEX model at a cut-off value of 10% for malignancy, had the sensitivity, specificity, LR+ and LR- of 92.4%, 73.0%, 3.42, and 0.10. This resulted in the lowest overall accuracy of 78.8%. The AUC for RMI was 0.854 (95% CI (0.815-0.887)), with overall accuracy, sensitivity, specificity, LR+ and LR- of 82.3%, 73.7%, 86.0%, 5.26, and 0.31. There was no difference in the AUCs of the SA and IOTA models for the whole group, premenopausal, and postmenopausal groups. RMI performed worse compared to SA and the IOTA models. The ADNEX model achieved the highest accuracy at the cut-off value of 35%. Limitations The data generalizability is limited by a single institution-dependent sampling. Conclusions The IOTA Simple Rules and ADNEX model were reliable and comparable with the subjective assessment and performed better than the RMI. The IOTA SR model offers the potential for immediate and reliable diagnosis, even in the hands of less experienced ultrasonographers. Both IOTA models studied can be a valuable adjunct to a clinician’s decision-making process.

The Role of Three-dimensional Power Doppler for Detecting Ovarian Cancer in Adnexal Masses: A Systematic Review and Meta-analysis

“…4 However, when less experienced sonographers evaluate ovarian tumors, the use of IOTA simple rules or the ADNEX model yields comparable diagnostic performance. 5 Despite significant advancements made in the field of ultrasound diagnosis for the majority of adnexal masses, this diagnostic tool still exhibits a considerable rate of false positive results, potentially resulting in a significant number of unnecessary procedures and heightened patient anxiety. 6 Among these advancements, three-dimensional power-Doppler ultrasound was introduced into clinical practice in the late 90's.…”

Prediction model of adnexal masses with complex ultrasound morphology

“…Recently, scholars have proposed various guidelines for the evaluation of ovarian-adnexal masses, including simple rules (SRs) (7), risk of malignancy index (RMI) (7,8), and gynecology imaging reporting and data system (GI-RADS) (9,10). RMI is the most frequently validated model.…”