The ADNEX model to triage adnexal masses: An external validation study and comparison with the IOTA two-step strategy and subjective assessment by an experienced ultrasound operator

ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies

Objectives

To conduct a systematic review of studies externally validating the ADNEX (Assessment of Different Neoplasias in the adnexa) model for diagnosis of ovarian cancer and to present a meta-analysis of its performance.

Design

Systematic review and meta-analysis of external validation studies.

Data sources

Medline, Embase, Web of Science, Scopus, and Europe PMC, from 15 October 2014 to 15 May 2023.

Eligibility criteria for selecting studies

All external validation studies of the performance of ADNEX, with any study design and any study population of patients with an adnexal mass. Two independent reviewers extracted the data. Disagreements were resolved by discussion. Reporting quality of the studies was scored with the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) reporting guideline, and methodological conduct and risk of bias with PROBAST (Prediction model Risk Of Bias Assessment Tool). Random effects meta-analysis of the area under the receiver operating characteristic curve (AUC), sensitivity and specificity at the 10% risk of malignancy threshold, and net benefit and relative utility at the 10% risk of malignancy threshold were performed.

Results

47 studies (17 007 tumours) were included, with a median study sample size of 261 (range 24-4905). On average, 61% of TRIPOD items were reported. Handling of missing data, justification of sample size, and model calibration were rarely described. 91% of validations were at high risk of bias, mainly because of the unexplained exclusion of incomplete cases, small sample size, or no assessment of calibration. The summary AUC to distinguish benign from malignant tumours in patients who underwent surgery was 0.93 (95% confidence interval 0.92 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX with the serum biomarker, cancer antigen 125 (CA125), as a predictor (9202 tumours, 43 centres, 18 countries, and 21 studies) and 0.93 (95% confidence interval 0.91 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX without CA125 (6309 tumours, 31 centres, 13 countries, and 12 studies). The estimated probability that the model has use clinically in a new centre was 95% (with CA125) and 91% (without CA125). When restricting analysis to studies with a low risk of bias, summary AUC values were 0.93 (with CA125) and 0.91 (without CA125), and estimated probabilities that the model has use clinically were 89% (with CA125) and 87% (without CA125).

Conclusions

The results of the meta-analysis indicated that ADNEX performed well in distinguishing between benign and malignant tumours in populations from different countries and settings, regardless of whether the serum biomarker, CA125, was used as a predictor. A key limitation was that calibration was rarely assessed.

Systematic review registration

PROSPERO CRD42022373182.

Ultrasonographic diagnosis of adnexal masses: interobserver agreement in the interpretation of videos, using IOTA terminology

OBJECTIVES

Aim of this study is to estimate interobserver agreement in classifying adnexal tumors using IOTA terms, simple rules and subjective assessment. In addition, we related observers' accuracy with their experience in gynecological ultrasonography and the year of IOTA certification.

METHODS

Eleven observers with three different levels of experience evaluated videoclips of 70 adnexal masses, defining tumor type according to IOTA terms and definitions, classifying the mass using IOTA Simple rules and Subjective assessment as well as providing Color Score evaluation. Sensitivity, specificity and area under the ROC curve were calculated and the year of IOTA certification was related with operators' accuracy through Pearson correlation coefficient. Interobserver agreement was estimated calculating percentage of agreement, Fleiss kappa and Cohen's kappa.

RESULTS

We found a positive correlation between the year of IOTA certification and operators' accuracy (Pearson coefficient 0.694), especially among the observers with the least experience, the residents (p = 0.003). For tumor type classification, identification of papillary projections and classification of tumors using subjective assessment, agreement among all observers was moderate (Fleiss kappa 0.455, 0.552, and 0.476, respectively) and increased with the years of experience. Agreement in the application of Simple Rules was moderate in all examiners with IOTA certification, with Fleiss kappa in the range of (0.403, 0.498). For Color Score assignment interobserver agreement among all observers was fair (Cohen's kappa 0.380).

CONCLUSIONS

Even among expert examiners, the results of adnexal lesion assessment can be inconsistent. Experience impacts on accuracy and agreement in subjective assessment, while the application of Simple Rules can mitigate the role of experience in interobserver agreement. The knowledge of IOTA models among residents seams to improve their diagnostic accuracy, showing the benefits of IOTA terminology for in training sonographers.

Current uptake and barriers to wider use of the International Ovarian Tumor Analysis (IOTA) models in Dutch gynaecological practice

OBJECTIVE

Correct referral of women with an ovarian tumor to an oncology department remains challenging. The International Ovarian Tumor Analysis (IOTA) consortium has developed models with higher diagnostic accuracy than the alternative Risk of Malignancy Index (RMI). This study explores the uptake of the IOTA models in Dutch hospitals and factors that impede or promote implementation. Optimal implementation is crucial to improve pre-operative classification of ovarian tumors, which may lead to better patient referral to the appropriate level of care.

STUDY DESIGN

In February 2021, an electronic questionnaire consisting of 37 questions was sent to all 72 hospitals in the Netherlands. One pre-selected gynaecologist per hospital was asked to respond on behalf of the department.

RESULTS

The study had a response rate of 93% (67/72 hospitals). All respondents (100%) were familiar with the IOTA models with 94% using them in practice. The logistic regression 2 (LR2)-model, Simple ultrasound-based rules (SR) and Assessment of Different NEoplasias in the adneXa (ADNEX) model were used in respectively 40%, 67% and 73% of these hospitals. Respondents rated the models overall with an 8.2 (SD 1.8), 8.3 (SD 1.6) and 8.9 (SD 1.3) respectively for LR2, SR and ADNEX on a scale from 1 to 10. Moreover, 89% indicated to have confidence in the results of the IOTA models. The most important factors to improve further implementation are more training (43%), research on sensitivity, specificity and cost-effectiveness in the Dutch health care system (27%), easier usability (24%) and more consultation time (19%).

CONCLUSION

The IOTA ultrasound models are adopted in the majority of Dutch hospitals with the ADNEX model being used the most. While Dutch gynecologists have a strong familiarity and confidence in the models, the uptake varies in reality. Areas that warrant improvement in the Dutch context are more uniformity, education and more research. These findings can be helpful for other countries considering adopting the IOTA models.

Subjective assessment and IOTA ADNEX model in evaluation of adnexal masses in patients with history of breast cancer

OBJECTIVE

To evaluate the performance of subjective assessment and the Assessment of Different NEoplasias in the adneXa (ADNEX) model in discriminating between benign and malignant adnexal tumors and between metastatic and primary adnexal tumors in patients with a personal history of breast cancer.

METHODS

This was a retrospective single-center study including patients with a history of breast cancer who underwent surgery for an adnexal mass between 2013 and 2020. All patients had been examined with transvaginal or transrectal ultrasound using a standardized examination technique and all ultrasound reports had been stored and were retrieved for the purposes of this study. The specific diagnosis suggested by the original ultrasound examiner in the retrieved report was analyzed. For each mass, the ADNEX model risks were calculated prospectively and the highest relative risk was used to categorize each into one of five categories (benign, borderline, primary Stage I, primary Stages II-IV or metastatic ovarian cancer) for analysis of the ADNEX model in predicting the specific tumor type. The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal tumors and between primary and metastatic adnexal tumors was evaluated, using final histology as the reference standard.

RESULTS

Included in the study were 202 women with a history of breast cancer who underwent surgery for an adnexal mass. At histology, 93/202 (46.0%) masses were benign, 76/202 (37.6%) were primary malignancies (four borderline and 72 invasive tumors) and 33/202 (16.3%) were metastases. The original ultrasound examiner classified correctly 79/93 (84.9%) benign adnexal masses, 72/76 (94.7%) primary adnexal malignancies and 30/33 (90.9%) metastatic tumors. Subjective ultrasound evaluation had a sensitivity of 93.6%, specificity of 84.9% and accuracy of 89.6%, while the ADNEX model had higher sensitivity (98.2%) but lower specificity (78.5%), with similar accuracy (89.1%), in discriminating between benign and malignant ovarian masses. Subjective evaluation had a sensitivity of 51.5%, specificity of 88.8% and accuracy of 82.7% in distinguishing metastatic and primary tumors (including benign, borderline and invasive tumors), and the ADNEX model had a sensitivity of 63.6%, specificity of 84.6% and similar accuracy (81.2%).

CONCLUSIONS

The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal masses in this series of patients with history of breast cancer was relatively similar. Both subjective assessment and the ADNEX model demonstrated good accuracy and specificity in discriminating between metastatic and primary tumors, but the sensitivity was low. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Application of Ultrasound Scores (Subjective Assessment, Simple Rules Risk Assessment, ADNEX Model, O-RADS) to Adnexal Masses of Difficult Classification

BACKGROUND

Ultrasound features help to differentiate benign from malignant masses, and some of them are included in the ultrasound (US) scores. The main aim of this work is to describe the ultrasound features of certain adnexal masses of difficult classification and to analyse them according to the most frequently used US scores.

METHODS

Retrospective studies of adnexal lesions are difficult to classify by US scores in women undergoing surgery. Ultrasound characteristics were analysed, and masses were classified according to the Subjective Assessment of the ultrasonographer (SA) and other US scores (IOTA Simple Rules Risk Assessment-SRRA, ADNEX model with and without CA125 and O-RADS).

RESULTS

A total of 133 adnexal masses were studied (benign: 66.2%, n:88; malignant: 33.8%, n:45) in a sample of women with mean age 56.5 ± 7.8 years. Malignant lesions were identified by SA in all cases. Borderline ovarian tumors (n:13) were not always detected by some US scores (SRRA: 76.9%, ADNEX model without and with CA125: 76.9% and 84.6%) nor were serous carcinoma (n:19) (SRRA: 89.5%), clear cell carcinoma (n:9) (SRRA: 66.7%) or endometrioid carcinoma (n:4) (ADNEX model without CA125: 75.0%). While most teratomas and serous cystadenomas have been correctly differentiated, other benign lesions were misclassified because of the presence of solid areas or papillae. Fibromas (n:13) were better identified by SA (23.1% malignancy), but worse with the other US scores (SRRA: 69.2%, ADNEX model without and with CA125: 84.6% and 69.2%, O-RADS: 53.8%). Cystoadenofibromas (n:10) were difficult to distinguish from malignant masses via all scores except SRRA (SA: 70.0%, SRRA: 20.0%, ADNEX model without and with CA125: 60.0% and 50.0%, O-RADS: 90.0%). Mucinous cystadenomas (n:12) were misdiagnosed as malignant in more than 15% of the cases in all US scores (SA: 33.3%, SRRA: 16.7%, ADNEX model without and with CA125: 16.7% and 16.7%, O-RADS:41.7%). Brenner tumors are also difficult to classify using all scores.

CONCLUSION

Some malignant masses (borderline ovarian tumors, serous carcinoma, clear cell carcinoma, endometrioid carcinomas) are not always detected by US scores. Fibromas, cystoadenofibromas, some mucinous cystadenomas and Brenner tumors may present solid components/papillae that may induce confusion with malignant lesions. Most teratomas and serous cystadenomas are usually correctly classified.

Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort

Importance

Ultrasonography-based risk models can help nonexpert clinicians evaluate adnexal lesions and reduce surgical interventions for benign tumors. Yet, these models have limited uptake in the US, and studies comparing their diagnostic accuracy are lacking.

Objective

To evaluate, in a US cohort, the diagnostic performance of 3 ultrasonography-based risk models for differentiating between benign and malignant adnexal lesions: International Ovarian Tumor Analysis (IOTA) Simple Rules with inconclusive cases reclassified as malignant or reevaluated by an expert, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX), and Ovarian-Adnexal Reporting and Data System (O-RADS).

Design, Setting, and Participants

This retrospective diagnostic study was conducted at a single US academic medical center and included consecutive patients aged 18 to 89 years with adnexal masses that were managed surgically or conservatively between January 2017 and October 2022.

Exposure

Evaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS.

Main Outcomes and Measures

The main outcome was diagnostic performance, including area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Surgery or follow-up were reference standards. Secondary analyses evaluated the models' performances stratified by menopause status and race.

Results

The cohort included 511 female patients with a 15.9% malignant tumor prevalence (81 patients). Mean (SD) ages of patients with benign and malignant adnexal lesions were 44.1 (14.4) and 52.5 (15.2) years, respectively, and 200 (39.1%) were postmenopausal. In the ROC analysis, the AUCs for discriminative performance of the ADNEX and O-RADS models were 0.96 (95% CI, 0.93-0.98) and 0.92 (95% CI, 0.90-0.95), respectively. After converting the ADNEX continuous individualized risk into the discrete ordinal categories of O-RADS, the ADNEX performance was reduced to an AUC of 0.93 (95% CI, 0.90-0.96), which was similar to that for O-RADS. The Simple Rules combined with expert reevaluation had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 91.9% specificity (95% CI, 88.9%-94.3%), and the Simple Rules combined with malignant classification had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 88.1% specificity (95% CI, 84.7%-91.0%). At a 10% risk threshold, ADNEX had 91.4% sensitivity (95% CI, 83.0%-96.5%) and 86.3% specificity (95% CI, 82.7%-89.4%) and O-RADS had 98.8% sensitivity (95% CI, 93.3%-100%) and 74.4% specificity (95% CI, 70.0%-78.5%). The specificities of all models were significantly lower in the postmenopausal group. Subgroup analysis revealed high performances independent of race.

Conclusions and Relevance

In this diagnostic study of a US cohort, the Simple Rules, ADNEX, and O-RADS models performed well in differentiating between benign and malignant adnexal lesions; this outcome has been previously reported primarily in European populations. Risk stratification models can lead to more accurate and consistent evaluations of adnexal masses, especially when used by nonexpert clinicians, and may reduce unnecessary surgeries.

Value of Contrast-Enhanced Ultrasound Parameters in the Evaluation of Adnexal Masses with Ovarian-Adnexal Reporting and Data System Ultrasound

OBJECTIVE

The aim of this study was to determine whether incorporating qualitative parameters of contrast-enhanced ultrasound (CEUS) can increase the accuracy of adnexal lesion assessments with Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound category 4 or 5.

METHODS

Retrospective analysis of patients with adnexal masses who underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations between January and August of 2020. The study investigators reviewed and analyzed the morphological features of each mass before categorizing the US images independently according to the O-RADS system published by the American College of Radiology. In the CEUS analysis, the initial time and intensity of enhancement involving the wall and/or septation of the mass were compared with the uterine myometrium. Internal components of each mass were observed for signs of enhancement. The sensitivity, specificity, and Youden's index were calculated as the contrast variables and O-RADS.

RESULTS

Receiver operating characteristic curve analysis revealed that the best cutoff value was higher than O-RADS 4. When information on the extent of enhancement was applied to selectively upgrade O-RADS category 4 and selectively downgrade O-RADS category 5, the overall sensitivity increased to 90.2%, while the level of specificity (91.3%) remained the same.

CONCLUSION

Incorporating additional information from CEUS with respect to the extent of enhancement helped to improve the sensitivity of O-RADS category 4 and 5 masses without loss of specificity.

Ultrasound Features and Ultrasound Scores in the Differentiation between Benign and Malignant Adnexal Masses

BACKGROUND

Several ultrasound (US) features help ultrasound experts in the classification of benign vs. malignant adnexal masses. US scores serve in this differentiation, but they all have misdiagnoses. The main objective of this study is to evaluate what ultrasound characteristics are associated with malignancy influencing ultrasound scores.

METHODS

This is a retrospective analysis of ultrasound features of adnexal lesions of women managed surgically. Ultrasound characteristics were analyzed, and masses were classified by subjective assessment of the ultrasonographer (SA) and other ultrasound scores (IOTA Simple Rules Risk Assessment SRRA, ADNEX model, and O-RADS).

RESULTS

Of a total of 187 adnexal masses studied, 134 were benign (71.7%) and 53 were malignant (28.3%). SA, IOTA SRRA, ADNEX model with or without CA125 and O-RADS had high levels of sensitivity (93.9%, 81.1%, 94.3%, 88.7%, 98.1%) but lower specificity (80.2%, 82.1%, 82.8%, 77.6%, 73.1%) with similar AUC (0.87, 0.87, 0.92, 0.90, 0.86). Ultrasound features significantly related with malignancy were the presence of irregular contour, absence of acoustic shadowing, vascularized solid areas, ≥1 papillae, vascularized septum, and moderate-severe ascites.

CONCLUSION

IOTA SRRA, ADNEX model, and O-RADS can help in the classification of benign and malignant masses. Certain ultrasound characteristics studied in ultrasound scores are associated with malignancy.

Manifestations of Ovarian Cancer in Relation to Other Pelvic Diseases by MRI

Imaging plays a pivotal role in the diagnostic approach of women with suspected ovarian cancer. MRI is widely used for preoperative characterization and risk stratification of adnexal masses. While epithelial ovarian cancer (EOC) has typical findings on MRI; there are several benign and malignant pelvic conditions that may mimic its appearance on imaging. Knowledge of the origin and imaging characteristics of a pelvic mass will help radiologists diagnose ovarian cancer promptly and accurately. Finally, in special subgroups, including adolescents and gravid population, the prevalence of various ovarian tumors differs from that of the general population and there are conditions which uniquely manifest during these periods of life.

Comparison of Ultrasound Scores in Differentiating between Benign and Malignant Adnexal Masses

Subjective ultrasound assessment by an expert examiner is meant to be the best option for the differentiation between benign and malignant adnexal masses. Different ultrasound scores can help in the classification, but whether one of them is significantly better than others is still a matter of debate. The main aim of this work is to compare the diagnostic performance of some of these scores in the evaluation of adnexal masses in the same set of patients. This is a retrospective study of a consecutive series of women diagnosed as having a persistent adnexal mass and managed surgically. Ultrasound characteristics were analyzed according to IOTA criteria. Masses were classified according to the subjective impression of the sonographer and other ultrasound scores (IOTA simple rules -SR-, IOTA simple rules risk assessment -SRRA-, O-RADS classification, and ADNEX model -with and without CA125 value-). A total of 122 women were included. Sixty-two women were postmenopausal (50.8%). Eighty-one women had a benign mass (66.4%), and 41 (33.6%) had a malignant tumor. The sensitivity of subjective assessment, IOTA SR, IOTA SRRA, and ADNEX model with or without CA125 and O-RADS was 87.8%, 66.7%, 78.1%, 95.1%, 87.8%, and 90.2%, respectively. The specificity for these approaches was 69.1%, 89.2%, 72.8%, 74.1%, 67.9%, and 60.5%, respectively. All methods with similar AUC (0.81, 0.78, 0.80, 0.88, 0.84, and 0.75, respectively). We concluded that IOTA SR, IOTA SRRA, and ADNEX models with or without CA125 and O-RADS can help in the differentiation of benign and malignant masses, and their performance is similar to the subjective assessment of an experienced sonographer.

Performance of IOTA Simple Rules Risks, ADNEX Model, Subjective Assessment Compared to CA125 and HE4 with ROMA Algorithm in Discriminating between Benign, Borderline and Stage I Malignant Adnexal Lesions

BACKGROUND

Borderline ovarian tumors (BOTs) and early clinical stage malignant adnexal masses can make sonographic diagnosis challenging, while the clinical utility of tumor markers, e.g., CA125 and HE4, or the ROMA algorithm, remains controversial in such cases.

OBJECTIVE

To compare the IOTA group Simple Rules Risk (SRR), the ADNEX model and the subjective assessment (SA) with serum CA125, HE4 and the ROMA algorithm in the preoperative discrimination between benign tumors, BOTs and stage I malignant ovarian lesions (MOLs).

METHODS

A multicenter retrospective study was conducted with lesions classified prospectively using subjective assessment and tumor markers with the ROMA. The SRR assessment and ADNEX risk estimation were applied retrospectively. The sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-) were calculated for all tests.

RESULTS

In total, 108 patients (the median age: 48 yrs, 44 postmenopausal) with 62 (79.6%) benign masses, 26 (24.1%) BOTs and 20 (18.5%) stage I MOLs were included. When comparing benign masses with combined BOTs and stage I MOLs, SA correctly identified 76% of benign masses, 69% of BOTs and 80% of stage I MOLs. Significant differences were found for the presence and size of the largest solid component (p = 0.0006), the number of papillary projections (p = 0.01), papillation contour (p = 0.008) and IOTA color score (p = 0.0009). The SRR and ADNEX models were characterized by the highest sensitivity (80% and 70%, respectively), whereas the highest specificity was found for SA (94%). The corresponding likelihood ratios were as follows: LR+ = 3.59 and LR- = 0.43 for the ADNEX; LR+ = 6.40 and LR- = 0.63 for SA and LR+ = 1.85 with LR- = 0.35 for the SRR. The sensitivity and specificity of the ROMA test were 50% and 85%, respectively, with LR+ = 3.44 and LR- = 0.58. Of all the tests, the ADNEX model had the highest diagnostic accuracy of 76%.

CONCLUSIONS

This study demonstrates the limited value of diagnostics based on CA125 and HE4 serum tumor markers and the ROMA algorithm as independent modalities for the detection of BOTs and early stage adnexal malignant tumors in women. SA and IOTA methods based on ultrasound examination may present superior value over tumor marker assessment.

Diagnostic Performance of Ultrasound-Based International Ovarian Tumor Analysis Simple Rules and Assessment of Different NEoplasias in the adneXa Model for Predicting Malignancy in Women with Ovarian Tumors: A Prospective Cohort Study

Background

Comparative performance of various ultrasound models in diagnosing ovarian lesions has not been adequately studied. This study aimed to evaluate the diagnostic performance of the International Ovarian Tumor Analysis (IOTA) simple rules and Assessment of Different NEoplasias in the adneXa (ADNEX) models in women with ovarian lesions.

Methods

Women 18-80 years, with an ovarian lesion planned for surgery were recruited in this prospective observational cohort study. Preoperative risk stratification was done by both IOTA simple rules and the ADNEX model. The diagnostic performance of both models was estimated using histopathology as the gold standard.

Results

A total of 90 women were recruited into the study. The IOTA simple rules were applicable to 77 (85.5%) participants and the ADNEX model on 100% women. Both the simple rules and the ADNEX model had good diagnostic performance. The sensitivity and specificity of the IOTA simple rules for predicting malignancy was 66.6% and 91%, while that of the ADNEXA model was 80% and 94%, respectively. The maximum diagnostic accuracy for prediction of both benign and malignant tumors was obtained when cancer antigen-125 (CA-125) was combined with the IOTA ADNEX model (91.0%), but for Stage I malignancy, the maximum diagnostic accuracy was for ADNEX without CA-125 (91.0%).

Conclusion

Both the IOTA models have a good diagnostic accuracy and are of paramount importance in differentiating benign from malignant tumors and predicting the stage of the malignant disease.

The International Ovarian Tumor Analysis-Assessment of Different Neoplasias in the Adnexa (IOTA-ADNEX) Model Assessment for Risk of Ovarian Malignancy in Adnexal Masses

Ovarian cancers are one of the major leading causes of death across the world. In addition to many challenges to diagnose the disease, it is also hard to predict the type of cancer with effective tools and technology. Many attempts have been made to diagnose ovarian malignancies using ultrasonography, MRI, and CT scans, but seldom will they give the clinician a clear understanding of cancer's type and stage. It is of utmost importance to understand the mass peri-operatively, which will help the clinicians to decide on the course of management mortality. With technological advancements, many predictive models have come into the picture. Many of those were dependent on the Serum CA-125 markers. With ultrasonography machine usage, the International Ovarian Tumor Analysis (IOTA) group has developed a Simple Rules model, Logistic Regression (LR) models, and, most recently, the IOTA-assessment of different neoplasias in the adnexa (IOTA-ADNEX) model. It has been found to be effective and reliable among all the tools developed in the past. The ADNEX predicts the type of cancer (benign or malignant) and stages of cancer (borderline, Stage I, Stages II-IV, and secondary metastatic). These models can be used for people who are coming with persistent adnexal masses in the ovarian region, para ovarian region, or in the tubes and are recommended for the surgeries. The model is developed by a team of clinicians and statisticians, based on ultrasound and clinical data. This article reviews the IOTA-ADNEX model as a tool for predicting ovarian malignancies in people coming with adnexal masses, especially in comparison with other methods and models. It also tests its effectiveness in the hands of experienced technicians and non-expert technicians.

Diagnostic Accuracies of the Ultrasound and Magnetic Resonance Imaging ADNEX Scoring Systems For Ovarian Adnexal Mass: Systematic Review and Meta-Analysis

We conducted a meta-analysis of IOTA (international ovarian tumor analysis) ADNEX (Assessment of Different NEoplasias in the adneXa) as ultrasound system and MRI (magnetic resonance imaging) ADNEX scoring systems as MR system to assess their diagnostic test accuracy for differentiating benign from malignant adnexal masses of the ovary. We performed an electronic search for relevant publications in the English language up to February 2021 using PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, and Google scholar databases and search engines. We computed the pooled sensitivity, pooled specificity, and summary receiver operating characteristics curve (SROC) using the statistical software STATA (Version 13, College Station, TX, StataCorp LP). Based on 11 studies using IOTA-ADNEX, we observed pooled sensitivity, specificity, area under curve, and diagnostic odds ratio were 96% (95% CI, 94% to 97%), 79% (95% CI, 70% to 86 %), 97% (95% CI, 95% to 98%), and 88 (95% CI, 43 to 180). Based on five studies using MR-ADNEX scoring system the pooled sensitivity, specificity, area under curve and diagnostic odds ratio were 91 % (95% CI, 87% to 94 %), 95% (95% CI, 92% to 97 %), 98% (95% CI, 96% to 99%), and 189 (95% CI, 90 to 396) respectively. Our meta-analysis results demonstrate that the MR-ADNEX scoring system had higher specificity however bit lower sensitivity compared to the IOTA-ADNEX scoring system for discriminating benign from malignant ovarian tumors.

Value of Assessment of Different Neoplasias in the Adnexa in the Differential Diagnosis of Malignant Ovarian Tumor and Benign Ovarian Tumor: A Meta-analysis

To evaluate the accuracy of the assessment of different neoplasias in the adnexa (ADNEX) model in the differential diagnosis of malignant and benign ovarian tumors, the optimal cutoff value and the accuracy in diagnosing ovarian tumors at different stages, PubMed, Web of Science and Cochrane Library databases were retrieved to search literature with per-patient analysis until publication of the last study in November 2021. STATA 14.1, Meta-Disc 1.4 and Revman software 5.3 were used in the performance of meta-analysis. To explore sources of heterogeneity, a subgroup analysis was conducted for the ADNEX model. The pooled sensitivity, specificity, diagnostic odds ratio, positive likelihood, negative likelihood ratio and area under the summary receiver operating characteristic curve were 0.91 (95% confidence interval [CI]: 0.89-0.93), 0.84 (95% CI: 0.80-0.88), 55.55 (95% CI: 40.47-76.26), 5.71 (95% CI: 4.49-7.26), 0.10 (95% CI: 0.08-0.13) and 0.94 (95% CI: 0.92-0.96) in differentiating benign and malignant ovarian tumors, respectively. The area under the curve in identifying benign, borderline, stage I and stages II-IV were 0.93, 0.73, 0.27 and 0.92. The ADNEX model had high diagnostic performance was influential in the diagnosis of benign and stage II-IV ovarian tumors.

Adnexal masses: Diagnostic performance of contrast-enhanced ultrasound using the simple rules from the International Ovarian Tumor Analysis group

OBJECTIVE

To evaluate the role of the Simple Rules (SR) from the International Ovarian Tumor Analysis group in contrast-enhanced ultrasound (CEUS) of for the differential diagnosis of benign and malignant adnexal tumors.

METHODS

A total of 180 patients with suspected malignant adnexal masses admitted to Lanzhou University Second Hospital were included, all of whom received conventional ultrasound (US) and CEUS examination before surgery. All masses were assessed using SR in US and SR in CEUS. To compare the diagnostic performance, the sensitivity, specificity, negative and positive predictive values, Youden index, and area under the curves values of SR in US and SR in CEUS were obtained.

RESULTS

Sensitivity, negative predictive values, Youden index, and area under the curves were better for SR in CEUS than SR in US. The specificity and negative predictive value of SR in CEUS were lower than that of SR in US. Compared with SR in US, SR in CEUS significantly reduced the number of uncertain masses (21, 36.7% vs. 66, 11.7%).

CONCLUSION

We concluded that SR in CEUS performed well in the diagnosis of malignant adnexal masses. SR in CEUS is a supplement to SR in US.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumors

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumors, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

Diagnostic Accuracy of the ADNEX Model for Ovarian Cancer at the 15% Cut-Off Value: A Systematic Review and Meta-Analysis

Objectives

To evaluate the diagnostic accuracy of the ADNEX model for ovarian cancer at the 15% cut-off value.

Methods

Studies on the identified diagnosis of the ADNEX model for ovarian cancer published in PubMed, Embase, the Cochrane Library and Web of Science databases from January 1st, 2014 to February 20th, 2021 were searched. Two researchers independently screened the retrieved studies and extracted the basic features and parameter data. The quality of the eligible studies was evaluated by Quality Assessment of Diagnostic Accuracy Studies-2, and the result was summarized by Review Manager 5.3. Meta-Disc 1.4 and STATA 16.0 were used in statistical analysis. Heterogeneity of this meta-analysis was calculated. Meta-regression was performed to investigate the potential sources of heterogeneity. Sensitivity analysis and Deek's funnel plot analysis were conducted to evaluate the stability and publication bias, respectively.

Results

280 studies were initially retrieved through the search strategy, and 10 eligible studies were ultimately included. The random-effects model was selected for data synthesis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and the area under the summary receiver operating characteristic curve were 0.92 (95% CI: 0.89-0.94), 0.82 (95% CI: 0.78-0.86), 5.2 (95% CI: 4.1-6.4), 0.10 (95% CI: 0.07-0.13), 54.0 (95% CI: 37.0-77.0) and 0.95 (95% CI: 0.91-0.95). Meta-regression based on study design, country, enrollment and blind method was not statistically significant. This meta-analysis was stable with no obvious publication bias.

Conclusions

The ADNEX model at the 15% cut-off had high diagnostic accuracy in identifying ovarian cancer.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumours

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumours, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumours and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumours and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

Prediction Models of Adnexal Masses: State-of-the-Art Review

Importance

Several predictive models and scoring systems have been developed to differentiate between benign and malignant ovarian masses, in order to guide effective management. These models use combinations of patient characteristics, ultrasound markers, and biochemical markers.

Objective

The aim of this study was to describe, compare, and prioritize, according to their strengths and qualities, all the adnexal prediction models.

Evidence Acquisition

This was a state-of-the-art review, synthesizing the findings of the current published literature on the available prediction models of adnexal masses.

Results

The existing models include subjective assessment by expert sonographers, the International Ovarian Tumor Analysis models (logistic regression models 1 and 2, Simple Rules, 3-step strategy, and ADNEX [Assessment of Different NEoplasias in the adneXa] model), the Risk of Malignancy Index, the Risk of Malignancy Ovarian Algorithm, the Gynecologic Imaging Reporting and Data System, and the Ovarian-Adnexal Reporting and Data System. Overall, subjective assessment appears to be superior to all prediction models. However, the International Ovarian Tumor Analysis models are probably the best available methods for nonexpert examiners. The Ovarian-Adnexal Reporting and Data System is an international approach that incorporates both the common European and North American approaches, but still needs to be validated.

Conclusions

Many prediction models exist for the assessment of adnexal masses. The adoption of a particular model is based on local guidelines, as well as sonographer's experience. The safety of expectant management of adnexal masses with benign ultrasound morphology is still under investigation.

Sonographic Assessment of Complex Ultrasound Morphology Adnexal Tumors in Pregnant Women with the Use of IOTA Simple Rules Risk and ADNEX Scoring Systems

Background: To evaluate the accuracy of subjective assessment (SA), the International Ovarian Tumor Analysis (IOTA) group Simple Rules Risk (SRR) and the Assessment of Different NEoplasias in the adneXa (ADNEX) model for the preoperative differentiation of adnexal masses in pregnant women. Methods: The study population comprised 36 pregnant women (median age: 28.5 years old, range: 20–42 years old) with a mean gestation age of 13.5 (range: 8–31) weeks at diagnosis. Tumors were prospectively classified by local sonographers as probably benign or probably malignant using SA. Final tumor histological diagnosis was used as the reference standard in all cases. Logistic regression SRR and ADNEX models were used to obtain a risk score for every case. Serum CA125 and human epidydimis protein 4 (HE4) concentrations were also retrieved and the Risk of Ovarian Malignancy Algorithm (ROMA) value was calculated. The calculated predictive values included positive and negative likelihood ratios of ultrasound and biochemical tests. Results: Final histology confirmed 27 benign and 9 malignant (including 2 borderline) masses. The highest sensitivity (89%) and specificity (70%) were found for the subjective tumor assessment. Although no malignancy was classified as benign using the SRR criteria (sensitivity = 100%), the specificity of this scoring system was only 37%. At the cut-off risk level of >20%, the ADNEX model had a sensitivity of 78% and a specificity of 70%. Serum levels of CA125, HE4 and the ROMA risk model correctly identified adnexal malignant tumors with a sensitivity of 67%, 25% and 25%, respectively. Corresponding specificities were 72%, 100% and 100%, respectively. The highest positive and negative likelihood ratios were found for SA (LR+ = 3.0 and LR− = 0.16, respectively). Overall diagnostic accuracy of all predictive methods used in this study were similar (range: 70–75%) except for SRR (53%). Conclusion: Subjective assessment remains the best predictive method in complex adnexal masses found at prenatal ultrasound in pregnant women. For less experienced sonographers, both the SRR and ADNEX scoring systems may be also used for the characterization of such tumors, while serum tumor markers CA125 and HE4, along with the ROMA algorithm appear to be less accurate.