Performance of the IOTA ADNEX model in preoperative discrimination of adnexal masses in a gynecological oncology center

Performance of International Ovarian Tumor Analysis (IOTA) predictive models in preoperative discrimination between benign and malignant adnexal lesions: preliminary outcomes in a Tertiary Care Hospital in Greece

OBJECTIVES

To apply the International Ovarian Tumor Analysis (IOTA) predictive models, the logistic regression model 2 (LR2) and the IOTA Assessment of Different NEoplasias in the adneXa (ADNEX), in patients with ovarian masses and to compare their performance in preoperative discrimination between benign and malignant adnexal lesions.

METHODS

This was a retrospective diagnostic accuracy study with prospectively collected data, performed between January 2019 and December 2022, in a single tertiary gynecologic oncology center in Greece. The study included women with an adnexal lesion which underwent surgery within 6 months after of using the LR2 and ADNEX protocol to assess the risk of malignancy. Correlation of the ultrasound findings with the postoperative histopathological analysis was performed. Receiver-operating characteristics (ROC) curve analysis was used to determine the diagnostic accuracy of the models to classify tumors; sensitivity and specificity were determined for each model and their performance was compared.

RESULTS

Of the136 participants, 117 (86%) had benign ovarian masses and 19 (14%) had malignant tumors. The area under the ROC curve (AUC) of the LR2 model was 0.84 (95% CI 0.74-0.93), which was significantly higher than the AUC for ADNEX model: 0.78 (95% CI 0.67-0.89). At a cut off > 10%, the LR2 model had the highest sensitivity 89.5% (95% CI 66.9-98.7) and specificity 85.1% (95% CI 76.9-91.2) compared to ADNEX model [sensitivity 84.2% (95% CI 60.4-96.6) and specificity 71.8% (95% CI 62.7-79.7)].

CONCLUSIONS

IOTA LR2 had the highest accuracy in differentiating between benign and malignant ovarian masses. IOTA LR2 and ADNEX models were both useful tools in discriminating between benign and malignant ovarian masses.

Clinical Utility and Diagnostic Accuracy of ROMA, RMI, ADNEX, HE4, and CA125 in the Prediction of Malignancy in Adnexal Masses

OBJECTIVE

We aimed to compare the clinical utility and diagnostic accuracy of the ADNEX model, ROMA score, RMI I, and RMI IV, as well as two serum markers (CA125 and HE4) in preoperative discrimination between benign and malignant adnexal masses (AMs).

METHODS

We conducted a retrospective study extracting all consecutive patients with AMs seen at our Institution between January 2015 and December 2020. Accuracy metrics included sensitivity (SE), specificity (SP), and area under the receiver operating characteristic curve (AUC), and their 95% confidence intervals (CI) were calculated for basic discrimination between AMs. Model performance was evaluated in terms of discrimination ability and clinical utility (net benefit, NB).

RESULTS

A total of 581 women were included; 481 (82.8%) had a benign ovarian tumor and 100 (17.2%) had a malignant tumor. The SE and SP of CA125, HE4, ROMA score, RMI I, RMI IV, and ADNEX model were 0.60 (0.54-0.66) and 0.80 (0.76-0.83); 0.39 (0.30-0.49) and 0.96 (0.94-0.98); 0.59 (0.50-0.68) and 0.92 (0.88-0.95); 0.56 (0.46-0.65) and 0.98 (0.96-0.99); 0.54 (0.44-0.63) and 0.96 (0.94-0.98); 0.82 (0.73-0.88) and 0.91 (0.89-0.94), respectively. The overall AUC was 0.76 (0.74-0.79) for CA125, 0.81 (0.78-0.83) for HE4, 0.82 (0.80-0.85) for ROMA, 0.86 (0.84-0.88) for RMI I, 0.83 (0.81-0.86) for RMI IV, and 0.92 (0.90-0.94) for ADNEX. The NB for ADNEX was higher than other biomarkers and models across all decision thresholds between 5% and 50%.

CONCLUSIONS

The ADNEX model showed a better discrimination ability and clinical utility when differentiating malignant from benign Ams, compared to CA125, HE4, ROMA score, RMI I, and RMI IV.

Prospective external validation of IOTA methods for classifying adnexal masses and retrospective assessment of two-step strategy using benign descriptors and ADNEX model: Portuguese multicenter study

OBJECTIVES

To externally and prospectively validate the International Ovarian Tumor Analysis (IOTA) Simple Rules (SRs), Logistic Regression model 2 (LR2) and Assessment of Different NEoplasias in the adneXa (ADNEX) model in a Portuguese population, comparing these approaches with subjective assessment and the risk-of-malignancy index (RMI), as well as with each other. This study also aimed to retrospectively validate the IOTA two-step strategy, using modified benign simple descriptors (MBDs) followed by the ADNEX model in cases in which MBDs were not applicable.

METHODS

This was a prospective multicenter diagnostic accuracy study conducted between January 2016 and December 2021 of consecutive patients with an ultrasound diagnosis of at least one adnexal tumor, who underwent surgery at one of three tertiary referral centers in Lisbon, Portugal. All ultrasound assessments were performed by Level-II or -III sonologists with IOTA certification. Patient clinical data and serum CA 125 levels were collected from hospital databases. Each adnexal mass was classified as benign or malignant using subjective assessment, RMI, IOTA SRs, LR2 and the ADNEX model (with and without CA 125). The reference standard was histopathological diagnosis. In the second phase, all adnexal tumors were classified retrospectively using the two-step strategy (MBDs + ADNEX). Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios and overall accuracy were determined for all methods. Receiver-operating-characteristics curves were constructed and corresponding areas under the curve (AUC) were determined for RMI, LR2, the ADNEX model and the two-step strategy. The ADNEX model calibration plots were constructed using locally estimated scatterplot smoothing (LOESS).

RESULTS

Of the 571 patients included in the study, 428 had benign disease and 143 had malignant disease (prevalence of malignancy, 25.0%), of which 42 had borderline ovarian tumor, 93 had primary invasive adnexal cancer and eight had metastatic tumors in the adnexa. Subjective assessment had an overall sensitivity of 97.9% and a specificity of 83.6% for distinguishing between benign and malignant lesions. RMI showed high specificity (95.6%) but very low sensitivity (58.7%), with an AUC of 0.913. The IOTA SRs were applicable in 80.0% of patients, with a sensitivity of 94.8% and specificity of 98.6%. The IOTA LR2 had a sensitivity of 84.6%, specificity of 86.9% and an AUC of 0.939, at a malignancy risk cut-off of 10%. At the same cut-off, the sensitivity, specificity and AUC for the ADNEX model with vs without CA 125 were 95.8% vs 98.6%, 82.5% vs 79.7% and 0.962 vs 0.960, respectively. The ADNEX model gave heterogeneous results for distinguishing between benign masses and different subtypes of malignancy, with the highest AUC (0.991) for discriminating benign masses from primary invasive adnexal cancer Stages II-IV, and the lowest AUC (0.696) for discriminating primary invasive adnexal cancer Stage I from metastatic lesion in the adnexa. The calibration plot suggested underestimation of the risk by the ADNEX model compared with the observed proportion of malignancy. The MBDs were applicable in 26.3% (150/571) of cases, of which none was malignant. The two-step strategy using the ADNEX model in the second step only, with and without CA 125, had AUCs of 0.964 and 0.961, respectively, which was similar to applying the ADNEX model in all patients.

CONCLUSIONS

The IOTA methods showed good-to-excellent performance in the Portuguese population, outperforming RMI. The ADNEX model was superior to other methods in terms of accuracy, but interpretation of its ability to distinguish between malignant subtypes was limited by sample size and large differences in the prevalence of tumor subtypes. The IOTA MBDs are reliable in identifying benign disease. The two-step strategy comprising application of MBDs followed by the ADNEX model if MBDs are not applicable, is suitable for daily clinical practice, circumventing the need to calculate the risk of malignancy in all patients. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of the value of the GI-RADS and ADNEX models in the diagnosis of adnexal tumors by junior physicians

Objective

To compare the diagnostic effectiveness of the Gynecologic Imaging Reporting and Data System (GI-RADS) and Neoplasias in the Adnexa (ADNEX) model for the diagnosis of benign and malignant ovarian tumors by junior physicians.

Methods

The sonographic data of 634 patients with ovarian tumors confirmed by pathology in our hospital over 4 years were analyzed retrospectively by junior doctors. The diagnostic efficacy of the GI-RADS and ADNEX models was compared based on pathology.

Results

(1) Regarding the diagnostic efficacy of the GI-RADS and ADNEX models, the sensitivity was 90.15% and 84.85%, the specificity was 87.65% and 85.86%, the accuracy rates were 88.17% and 85.65%, and the Youden Indices were 0.778 and 0.707, respectively. The areas under the receiver operating characteristic (ROC) curves were 0.924 (95% CI: 0.900-0.943) and 0.933 (95% CI: 0.911-0.951), respectively. The GI-RADS classification was equivalent to that of the ADNEX model in the diagnosis of adnexal tumors (P>0.05). These findings were highly consistent with the pathological results (Kappa values were 0.684 and 0.691, respectively). (2) When differentiating between different pathological types of adnexal tumors, the ADNEX model had the best diagnostic value for distinguishing between benign tumors and stage II-IV ovarian cancer (AUC=0.990, 95% CI: 0.978-0.997).

Conclusions

(1) The diagnostic efficacy of the GI-RADS and ADNEX models in the diagnosis of benign and malignant ovarian tumors by junior physicians is excellent and comparable. (2) The ADNEX model shows good value for differentiating ovarian tumors of different pathological types by junior physicians.

Analysis of Diagnostic Efficacy of the International Ovarian Tumor Analysis ADNEX Model and the ACR O-RADS US (Ovarian-Adnexal Reporting and Data System) for Benign and Malignant Ovarian Tumors: A Retrospective Study in a Tumor Center in Northeast China

This study is to analyze and compare the diagnostic efficacy of the ADNEX model and O-RADS in Northeast China for benign and malignant ovarian-adnexal tumors. From July 2020 to February 2022, ultrasound images of 312 ovarian-adnexal masses included in the study were analyzed retrospectively, and the properties of these masses were identified using the ADNEX model and O-RADS. The diagnostic efficiency of the ADNEX model and O-RADS was analyzed using a ROC curve, and the capacities of the two models in differentiating benign and malignant ovarian masses at the optimum cutoff value were compared, as well as the consistency of their diagnosis results was evaluated. The study included 312 ovarian-adnexal masses, including 145 malignant masses and 167 benign masses from 287 patients with an average age of (46.8 ± 11.3) years. The AUC of the ADNEX model was 0.974, and the optimum cutoff value was the risk value > 24.2%, with the corresponding sensitivity and specificity being 97.93 and 86.83, respectively. The AUC of the O-RADS was 0.956, and the optimum cutoff value was > O-RADS 3, with the corresponding sensitivity and specificity being 97.24 and 85.03, respectively. The AUCs of the two models were 0.924 and 0.911 at the optimum cutoff values, with no statistical differences between them (P = 0.284). Consistency analysis: the kappa values of the two models for the determination and pathological results of masses were 0.840 and 0.815, respectively, and that for the diagnostic outcomes was 0.910. Both the ADNEX model and O-RADS had good diagnostic performance in people from Northeast China. Their diagnostic capabilities were similar, and diagnostic results were highly consistent at the optimum cutoff values.

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.

Prediction model of adnexal masses with complex ultrasound morphology

Background

Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.

Methods

In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).

Results

Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.

Conclusion

The risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.

Current and Emerging Strategies for Tubo-Ovarian Cancer Diagnostics

Tubo-ovarian cancer is the most lethal gynaecological cancer. More than 75% of patients are diagnosed at an advanced stage, which is associated with poorer overall survival. Symptoms at presentation are vague and non-specific, contributing to late diagnosis. Multimodal risk models have improved the diagnostic accuracy of adnexal mass assessment based on patient risk factors, coupled with findings on imaging and serum-based biomarker tests. Newly developed ultrasonographic assessment algorithms have standardised documentation and enable stratification of care between local hospitals and cancer centres. So far, no screening test has proven to reduce ovarian cancer mortality in the general population. This review is an update on the evidence behind ovarian cancer diagnostic strategies.

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.

Can the ultrasound microcystic pattern accurately predict borderline ovarian tumors?

OBJECTIVE

To investigate whether the ultrasound microcystic pattern (MCP) can accurately predict borderline ovarian tumors (BOTs).

METHODS

A retrospective collection of 393 patients who met the inclusion criteria was used as the study population. Indicators that could well identify BOT in different pathological types of tumors were derived by multivariate unordered logistic regression analysis. Finally, the correlation between ultrasound MCP and pathological features was analyzed.

RESULTS

(1) MCP was present in 55 of 393 ovarian tumors, including 34 BOTs (34/68, 50.0%), 16 malignant tumors (16/88, 18.2%), and 5 benign tumors (5/237, 2.1%). (2) Univariate screening showed significant differences (P < 0.05) in patient age, CA-125 level, ascites, > 10 cyst locules, a solid component, blood flow, and MCP among BOTs, benign ovarian tumors, and malignant ovarian tumors. (3) Multivariate unordered logistic regression analysis showed that the blood flow, > 10 cyst locules, and MCP were significant factors in identifying BOTs (P < 0.05). (4) The pathology of ovarian tumors with MCP showed "bubble"- or "fork"- like loose tissue structures.

CONCLUSION

MCP can be observed in different pathological types of ovarian tumors and can be used as a novel sonographic marker to differentiate between BOTs, benign tumors and malignant tumors. MCP may arise as a result of anechoic cystic fluid filling the loose tissue gap.

Ovarian Masses: The Value of Acoustic Shadowing on Ultrasound Examination

Adnexal lesions are a common finding in women and pose a clinical challenge since ovarian cancer is a highly lethal disease. However, most adnexal masses are benign, benefiting from a more conservative approach. In preoperative assessment, transvaginal ultrasound plays a key role in evaluating morphologic features that correlate with the risk of malignancy. The acoustic shadow is the loss of echo behind sound-absorbing components, such as calcifications or fibrous tissues, which are predominantly found in benign lesions. However, recognizing the acoustic shadow is a difficult skill to master, and its usefulness may be underappreciated.

Does Combing O-RADS US and CA-125 Improve Diagnostic Accuracy in Assessing Adnexal Malignancy Risk in Women With Different Menopausal Status?

OBJECTIVES

To evaluate the individual and combined performances of the Ovarian-adnexal Reporting and Data System Ultrasound (O-RADS US) and serum cancer antigen 125 (CA-125) in assessing adnexal malignancy risk in women with different menopausal status.

METHODS

This retrospective study included patients with adnexal masses scheduled for surgery based on their preoperative US and histopathology results between January 2018 and January 2020. O-RADS were used to assess adnexal malignancy by two experienced radiologists. The area under the receiver operating characteristic curves (AUCs) were used to compare the accuracy of O-RADS and a combination of O-RADS and CA-125. The weighted κ index was used to evaluate the inter-reviewer agreement.

RESULTS

Overall, the data of 443 lesions in 443 patients were included, involving 312 benign lesions and 131 malignant lesions. There were 361 premenopausal and 82 postmenopausal patients. The inter-reviewer agreement for the two radiologists was very good (weighted κ: 0.833). Combing O-RADS US and CA-125 significantly increased diagnostic accuracy for classifying malignant from benign adnexal masses, compared with O-RADS US alone (AUC: 0.97 vs 0.95, P < .001 for premenopausal population and AUC: 0.93 vs 0.85, P < .001 for postmenopausal population). The AUCs of O-RADS with and without CA-125 ranged from 0.50 to 0.99 for different adnexal pathology subtypes (ie, benign, borderline, Stage I-IV, and metastatic tumors).

CONCLUSION

The addition of CA-125 helps improve discrimination of O-RADS US between benign and malignant adnexal masses, especially in postmenopausal women.

Management of Borderline ovarian tumors (BOT): results of a retrospective, single center study in Switzerland

BACKGROUND

Borderline tumors are malignant epithelial ovarian tumors with a very low incidence. Thus experience in diagnostics and treatment is still rare. The aim of this study was to present and analyze data of women with borderline ovarian tumor (BOT) regarding clinical features, histological characteristics, diagnostics and treatment management.

METHODS

In this single center retrospective study women with BOT treated at the Departement of Gynecology and Obstetrics at the Kantonsspital Luzern between 2011 and 2018 were analyzed according to their clinical and histological reports.

RESULTS

A total of 42 women were enrolled. The median age was 58.5 with a range from 26 to 85, of which 31 (73.8%) were postmenopausal. Regarding the histological subtypes, 23 women (54.8%) had serous and 15 (35.7%) had mucinous BOT. Seromucinous histology was found in 3 patients (7.1%) and endometrioid in 1 woman (2.4%), respectively. All women underwent surgery. In a total of 39 women (92.9%) a complete surgical staging for BOT was performed. In 29 women (69.0%) staging was performed by laparoscopy, 13 (31.0%) underwent laparotomy. The mean follow up was 52 months (range = 16.3-101.4 months). During this period two patients, initially diagnosed in FIGO stage 1, recurred after 21.7 and 44 months, respectively, the second woman died after 53 months because of the BOT.

CONCLUSION

In the present study women were treated according to the international therapy recommendations and the rate of recurrence was very low. The most common risk factors for relapse are known to be FIGO stage, incomplete staging and peritoneal implants but were not present in our group. Thus further studies are necessary to investigate additional recurrence risks.

Comparison of ultrasound-based ADNEX model with magnetic resonance imaging for discriminating adnexal masses: a multi-center study

Objectives

The ADNEX model offered a good diagnostic performance for discriminating adnexal tumors, but research comparing the abilities of the ADNEX model and MRI for characterizing adnexal tumors has not been reported to our knowledge. The aim of this study was to evaluate the diagnostic accuracy of the ultrasound-based ADNEX (Assessment of Different NEoplasias in the adneXa) model in comparison with that of magnetic resonance imaging (MRI) for differentiating benign, borderline and malignant adnexal masses.

Methods

This prospective study included 529 women with adnexal masses who underwent assessment via the ADNEX model and subjective MRI analysis before surgical treatment between October 2019 and April 2022 at two hospitals. Postoperative histological diagnosis was considered the gold standard.

Results

Among the 529 women, 92 (17.4%) masses were diagnosed histologically as malignant tumors, 67 (12.7%) as borderline tumors, and 370 (69.9%) as benign tumors. For the diagnosis of malignancy, including borderline tumors, overall agreement between the ADNEX model and MRI pre-operation was 84.9%. The sensitivity of the ADNEX model of 0.91 (95% confidence interval [CI]: 0.85-0.95) was similar to that of MRI (0.89, 95% CI: 0.84-0.94; P=0.717). However, the ADNEX model had a higher specificity (0.90, 95% CI: 0.87-0.93) than MRI (0.81, 95% CI: 0.77-0.85; P=0.001). The greatest sensitivity (0.96, 95% CI: 0.92-0.99) and specificity (0.94, 95% CI: 0.91-0.96) were achieved by combining the ADNEX model and subjective MRI assessment. While the total diagnostic accuracy did not differ significantly between the two methods (P=0.059), the ADNEX model showed greater diagnostic accuracy for borderline tumors (P<0.001).

Conclusion

The ultrasound-based ADNEX model demonstrated excellent diagnostic performance for adnexal tumors, especially borderline tumors, compared with MRI. Accordingly, we recommend that the ADNEX model, alone or with subjective MRI assessment, should be used for pre-operative assessment of adnexal masses.

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.

Evaluation of IOTA-ADNEX Model and Simple Rules for Identifying Adnexal Masses by Operators with Varying Levels of Expertise: A Single-Center Diagnostic Accuracy Study

Objectives The discrimination of ovarian lesions presents a significant problem in everyday clinical practice with ultrasonography appearing to be the most effective diagnostic technique. The aim of our study was to externally evaluate the performance of different diagnostic models when applied by examiners with various levels of experience. Methods This was a diagnostic accuracy study including women who were admitted for adnexal masses, between July 2018 and April 2021, to a Greek tertiary oncology center. Preoperatively sonographic data were evaluated by an expert gynecologist, a 6 th and a 1 st year gynecology resident, who applied the International Ovarian Tumor Analysis (IOTA) Simple Rules (SR) and Assessment of Different NEoplasias in the adneXa (ADNEX) model to discriminate between benign and malignant ovarian tumors. The explant pathology report was used as the reference diagnosis. Kappa statistics were used for the investigation of the level of agreement between the examined systems and the raters. Results We included 66 women, 39 with benign and 27 with malignant ovarian tumors. ADNEX (with and without "CA-125") had high sensitivity (96-100%) when applied by all raters but a rather low specificity (36%) when applied by the 1st year resident. SR could not be applied in 6% to 17% of the cases. It had slightly lower sensitivity, higher specificity, and higher overall accuracy, especially when applied by the 1st year resident (61% vs. 92%), compared to ADNEX. Conclusion Both ADNEX and SR can be utilized for screening in non-oncology centers since they offer high sensitivity even when used by less experienced examiners. In the hands of inexperienced examiners, SR appears to be the best model for assessing ovarian lesions.

Laparoscopic Surgery for Ovarian Neoplasms - What is Possible, What is Useful?

The use of minimally invasive surgical techniques is becoming increasingly important in gynecologic oncology due to technical advances and the increasing level of surgical expertise. In addition to laparoscopic approaches for the treatment of benign neoplasms, minimally invasive surgical methods have also become established in some areas for treating gynecologic malignancies. For tumor entities such as endometrial and cervical carcinoma, there are conclusive studies emphasizing the role of laparoscopy in surgical therapy. By contrast, due to a lack of prospective data with survival analyses, no clear conclusions can be drawn on the significance of laparoscopy in the surgical treatment of ovarian carcinoma. However, some smaller, mostly retrospective case-control studies and cohort studies open the way for a discussion, positing the possibility that laparoscopic surgical procedures, particularly for early ovarian carcinoma, are technically feasible and of a quality equivalent to that of conventional longitudinal laparotomy, and may also be associated with lower perioperative morbidity. In this article we discuss the most important aspects of using minimally invasive surgical techniques for ovarian carcinoma based on the current literature. In particular we look at the relevance of laparoscopy as a primary approach for surgical staging of early ovarian carcinoma, and we evaluate the role of diagnostic laparoscopy in assessing the operability of advanced ovarian carcinoma.

Evaluation of Adnexal Masses: The IOTA Concept

Ovarian lesions have a wide range of sonomorphological features with numerous different underlying benign and malignant histologies. Based on the studies conducted by the International Ovarian Tumor Analysis (IOTA) group, ovarian masses can currently be reliably characterized by ultrasound. In the following article, we explain how to use the IOTA terms and definitions and we provide insight into how to safely triage patients with an ovarian mass.

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.

Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer

Objective

This work was designed to investigate the performance of the International Ovarian Tumor Analysis (IOTA) ADNEX (Assessment of Different NEoplasias in the adneXa) model combined with human epithelial protein 4 (HE4) for early ovarian cancer (OC) detection.

Methods

A total of 376 women who were hospitalized and operated on in Women and Children’s Hospital of Chongqing Medical University were selected. Ultrasonographic images, cancer antigen-125 (CA 125) levels, and HE4 levels were obtained. All cases were analyzed and the histopathological diagnosis serves as the reference standard. Based on the IOTA ADNEX model post-processing software, the risk prediction value was calculated. We analyzed receiver operating characteristic curves to determine whether the IOTA ADNEX model alone or combined with HE4 provided better diagnostic accuracy.

Results

The area under the curve (AUC) of the ADNEX model alone or combined with HE4 in predicting benign and malignant ovarian tumors was 0.914 (95% CI, 0.881–0.941) and 0.916 (95% CI, 0.883–0.942), respectively. With the cutoff risk of 10%, the ADNEX model had a sensitivity of 0.93 (95% CI, 0.87–0.97) and a specificity of 0.73 (95% CI, 0.67–0.78), while combined with HE4, it had a sensitivity of 0.90 (95% CI, 0.84–0.95) and a specificity of 0.81 (95% CI, 0.76–0.86). The IOTA ADNEX model combined with HE4 was better at improving the accuracy of the differential diagnosis between different OCs than the IOTA ADNEX model alone. A significant difference was found in separating borderline masses from Stage II–IV OC (p = 0.0257).

Conclusions

A combination of the IOTA ADNEX model and HE4 can improve the specificity of diagnosis of ovarian benign and malignant tumors and increase the sensitivity and effectiveness of the differential diagnosis of Stage II–IV OC and borderline tumors.

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.

Performance of IOTA Simple Rules, Simple Rules risk assessment, ADNEX model and O-RADS in differentiating between benign and malignant adnexal lesions in North American women

OBJECTIVES

To apply the International Ovarian Tumor Analysis (IOTA) Simple Rules (SR), the IOTA Simple Rules risk assessment (SRR), the IOTA Assessment of Different NEoplasias in the adneXa (ADNEX) model and the Ovarian-Adnexal Reporting and Data System (O-RADS) in the same cohort of North American patients and to compare their performance in preoperative discrimination between benign and malignant adnexal lesions.

METHODS

This was a single-center diagnostic accuracy study, performed between March 2018 and February 2021, which included 150 women with an adnexal lesion. Using the ADNEX model, lesions were classified prospectively, whereas the SR, SRR assessment and O-RADS were applied retrospectively. Surgery with histological analysis was performed within 6 months of the ultrasound exam. Sensitivity and specificity were determined for each testing modality and the performance of the different modalities was compared.

RESULTS

Of the 150 women, 110 (73.3%) had a benign ovarian tumor and 40 (26.7%) had a malignant tumor. The mean risk of malignancy generated by the ADNEX model without CA 125 was significantly higher in malignant vs benign lesions (63.3% vs 11.8%) and the area under the receiver-operating-characteristics curve (AUC) of the ADNEX model for differentiating between benign and malignant adnexal masses at the time of ultrasound examination was 0.937. The mean risk of malignancy generated by SRR assessment was also significantly higher in malignant vs benign lesions (74.1% vs 15.9%) and the AUC was 0.941. To compare the ADNEX model, SRR assessment and O-RADS, the malignancy risk threshold was set at ≥ 10%. This cut-off differentiates O-RADS low-risk categories (Category ≤ 3) from intermediate-to-high-risk categories (Categories 4 and 5). At this cut-off, the sensitivity of the ADNEX model was 97.5% (95% CI, 85.3%-99.9%) and the specificity was 63.6% (95% CI, 53.9%-72.4%), and, for the SRR model, the sensitivity was 100% (95% CI, 89.1%-100%) and the specificity was 51.8% (95% CI, 42.1%-61.4%). In the 113 cases to which the SR could be applied, the sensitivity was 100% (95% CI, 81.5%-100%) and the specificity was 95.6% (95% CI, 88.5%-98.6%). If the remaining 37 cases, which were inconclusive under SR, were designated 'malignant', the sensitivity remained at 100% but the specificity was reduced to 79.1% (95% CI, 70.1%-86.0%). The 150 cases fell into the following O-RADS categories: 17 (11.3%) lesions in Category 2, 34 (22.7%) in Category 3, 66 (44.0%) in Category 4 and 33 (22.0%) in Category 5. There were no histologically proven malignant lesions in Category 2 or 3. There were 14 malignant lesions in Category 4 and 26 in Category 5. The sensitivity of O-RADS using a malignancy risk threshold of ≥ 10% was 100% (95% CI, 89.1%-100.0%) and the specificity was 46.4% (95% CI, 36.9%-56.1%).

CONCLUSIONS

When IOTA terms and techniques are used, the performance of IOTA models in a North American patient population is in line with published IOTA results in other populations. The IOTA SR, SRR assessment and ADNEX model and O-RADS have similar sensitivity in the preoperative discrimination of malignant from benign pelvic tumors; however, the IOTA models have higher specificity and the algorithm does not require the use of magnetic resonance imaging. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Two-Step Strategy for Optimizing the Preoperative Classification of Adnexal Masses in a University Hospital, Using International Ovarian Tumor Analysis Models: Simple Rules and Assessment of Different NEoplasias in the adneXa Model

OBJECTIVES

To evaluate the performance of a two-step strategy compared with the International Ovarian Tumor Analysis (IOTA) - Assessment of Different NEoplasias in the adneXa (ADNEX) model for preoperative classification of adnexal masses.

METHODS

An ambispective diagnostic accuracy study based on ultrasound data collected at one university hospital between 2012 and 2018. Two ultrasonographers classified the adnexal masses using IOTA Simple Rules (first step). Not classifiable masses were evaluated using the IOTA ADNEX model (second step). Also, all masses were classified using the IOTA ADNEX model. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-), and receiver operating characteristic (ROC) curve were estimated. A P value of <.05 was used to determine statistical significance.

RESULTS

The study included 548 patients and 606 masses. Patients' median age was 41 years with an interquartile range between 32 and 51 years. In the first step, 89 (14%) masses were not classifiable. In the second step, 55 (61.8%) masses were classified as malignant. Furthermore, for the totality of 606 masses, the IOTA ADNEX model estimated the probability that 126 (20.8%) masses were malignant. The two-step strategy had a sensitivity, specificity, PPV, NPV, LR+, LR-, and ROC curve of 86.8%, 91.01%, 51.9%, 98.4%, 9.7, 0.1, and 0.889, respectively; compared to IOTA ADNEX model that had values of 91.8%, 87.16%, 44.4%, 99%, 7.1, 0.09, and 0.895, respectively.

CONCLUSION

The two-step strategy shows a similar diagnostic performance when compared to the IOTA ADNEX model. The IOTA ADNEX model involves only one step and can be more practical, and thus would be recommended to use.

Ultrasonographic ovarian mass scoring system for predicting malignancy in pregnant women with ovarian mass

During routine antenatal ultrasound examinations, an ovarian mass can be found incidentally. In clinical practice, the differential diagnosis between benign and malignant ovarian masses is essential for planning further management. Ultrasound imaging has become the most popular diagnostic tool during pregnancy, with the recent development of ultrasonography. In non-pregnant women, several methods have been used to predict malignant ovarian masses before surgery. The International Ovarian Tumor Analysis (IOTA) group reported several scoring systems, such as the IOTA simple rules, IOTA logistic regression models, and IOTA assessment of different NEoplasias in the adneXa. Other researchers have also evaluated the malignancy of ovarian masses before surgery using scoring systems such as the Sassone score, pelvic mass score, DePriest score, Lerner score, and Ovarian-Adnexal Reporting and Data System. These researchers suggested specific features of ovarian masses that can be used for differential diagnosis, including size, proportion of solid tissue, papillary projections, inner wall structure, locules, wall thickness, septa, echogenicity, acoustic shadows, and presence of ascites. Although these factors can also be measured in pregnant women using ultrasound, only a few studies have applied ovarian scoring systems in pregnant women. In this article, we reviewed various scoring systems for predicting malignant tumors of the ovary and determined whether they can be applied to pregnant women.

Estimating the risk of malignancy of adnexal masses: validation of the ADNEX model in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China

Background

This study aims to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) the Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China.

Methods

This was a single oncology centre, retrospective diagnostic accuracy study of 620 patients. All patients underwent surgery, and the histopathological diagnosis was used as a reference standard. The masses were divided into five types according to the ADNEX model: benign ovarian tumours, borderline ovarian tumours (BOTs), stage I ovarian cancer (OC), stage II-IV OC and ovarian metastasis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the ADNEX model to classify tumours into different histological types with and without cancer antigen 125 (CA 125) results.

Results

Of the 620 women, 402 (64.8%) had a benign ovarian tumour and 218 (35.2%) had a malignant ovarian tumour, including 86 (13.9%) with BOT, 75 (12.1%) with stage I OC, 53 (8.5%) with stage II-IV OC and 4 (0.6%) with ovarian metastasis. The AUC of the model to differentiate benign and malignant adnexal masses was 0.97 (95% CI, 0.96–0.98). Performance was excellent for the discrimination between benign and stage II-IV OC and between benign and ovarian metastasis, with AUCs of 0.99 (95% CI, 0.99–1.00) and 0.99 (95% CI, 0.98–1.00), respectively. The model was less effective at distinguishing between BOT and stage I OC and between BOT and ovarian metastasis, with AUCs of 0.54 (95% CI, 0.45–0.64) and 0.66 (95% CI, 0.56–0.77), respectively. When including CA125 in the model, the performance in discriminating between stage II–IV OC and stage I OC and between stage II–IV OC ovarian metastasis was improved (AUC increased from 0.88 to 0.94, P = 0.01, and from 0.86 to 0.97, p = 0.01).

Conclusions

The IOTA ADNEX model has excellent performance in differentiating benign and malignant adnexal masses in the hands of nonexpert ultrasonographers with limited experience in China. In classifying different subtypes of ovarian cancers, the model has difficulty differentiating BOTs from stage I OC and BOTs from ovarian metastases.

Evaluation of the Diagnostic Value of the Ultrasound ADNEX Model for Benign and Malignant Ovarian Tumors

Objective

To investigate the diagnostic performance of the ADNEX model in the International Ovarian Tumor Analysis diagnostic models for ovarian tumors and further explore its application value in the staging of ovarian tumors.

Methods

A total of 224 patients who underwent ultrasound for evaluation of adnexal masses and were treated surgically owing to adnexal masses from January 2018 to June 2020 in our hospital were selected for research on the diagnostic accuracy of the ADNEX model. The clinical information and ultrasonographic findings of the patients were collected, and the pathological diagnosis was taken as the gold standard. According to the ADNEX model, the ovarian tumors were divided into five subtypes: benign and borderline, stage I, stage II–IV, and metastatic cancer. The sensitivity, specificity, positive predictive value, negative predictive value, diagnostic odds ratio, and area under the receiver operating characteristics curve (AUC) of the ADNEX model were calculated.

Results

Of the 224 patients, 119 (53.1%) developed benign tumors and 105 (46.9%) had malignant tumors. When the cut-off value for malignancy risk was 10%, the ADNEX model including CA 125 achieved a sensitivity of 94.3% (95% CI: 88.0–97.9%), specificity of 74.0% (95% CI: 65.1–81.6%), positive predictive value of 76.2% (95% CI: 70.2–81.3%), negative predictive value of 93.6% (95% CI: 87.0–97.0%), diagnostic odds ratio of 45.25, and an AUC of 0.94 (95% CI: 0.90–0.97) for differentiating between benign and malignant ovarian tumors. The AUC in the model excluding CA 125 was 0.93 (95% CI: 0.89–0.96), but the difference was not statistically significant (P=0.20). The accuracy of the ADNEX model for the diagnosis of ovarian tumors of all subtypes exceeds 80% when CA 125 measurements were included in the application, but the sensitivity for diagnosing borderline, stage I, and metastatic ovarian tumors was only 60.0% (95% CI:36.1–80.9%), 28.6% (95% CI:8.4–58.1%) and 45.5% (95% CI:16.7–76.6%).

Conclusion

The ADNEX model shows good diagnostic performance in differentiating between benign and malignant ovarian tumors. The model has a certain clinical value in the diagnosis of all subtypes of ovarian tumors, but the sensitivity is unsatisfactory for the diagnosis of borderline, stage I, and metastatic ovarian tumors and needs to be verified.

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.

Comparison of the Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients With Adnexal Masses

AIM

This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass.

METHODS

This single-centre diagnostic accuracy study involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios.

RESULTS

To discriminate benign and malignant tumors, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92-0.96) with CA125 and 0.94 (95% CI: 0.91-0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83-0.90), 0.83 (95% CI: 0.80-0.86), and 0.82 (95% CI: 0.78-0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87-0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86-0.97) and a specificity of 0.86 (95% CI: 0.82-0.89) when inconclusive diagnoses (11.7%) were classified as malignant.

CONCLUSION

ADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients.

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.

Preoperative Evaluation of the ADNEX Model for the Prediction of the Ovarian Cancer Risk of Adnexal Masses at Siriraj Hospital

INTRODUCTION

Distinguishing benign adnexal masses from malignant tumors plays an important role in preoperative planning and improving patients' survival rates. The International Ovarian Tumor Analysis (IOTA) group developed a model termed the Assessment of Different NEoplasias in the adneXa (ADNEX).

OBJECTIVE

Our objective was to evaluate the performance of the ADNEX model in distinguishing between benign and malignant tumors at a cutoff value of 10%.

METHODS

This was a prospective diagnostic study. 357 patients with an adnexal mass who were scheduled for surgery at Siriraj Hospital were included from May 1, 2018, to May 30, 2019. All patients were undergoing ultrasonography, and serum CA125 was measured. Data were calculated by the ADNEX model via an IOTA ADNEX calculator.

RESULTS

Of the 357 patients, 296 had benign tumors and 61 had malignant tumors. The area under the receiver operating characteristic curve for using the ADNEX model was 0.975 (95% confidence interval, 0.953-0.988). At a 10% cutoff, the sensitivity was 98.4% and specificity was 87.2%. The best cutoff value was at 16.6% in our population.

CONCLUSIONS

The performance of the ADNEX model in differentiating benign and malignant tumors was excellent.

Assessment of different NEoplasias in the adneXa model for differentiation of benign and malignant adnexal masses in Korean women

OBJECTIVE

Ultrasonographic differential diagnosis of ovarian tumors is important for appropriate management. We conducted study to compare the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with a subjective assessment (SA) in differentiating between benign and malignant adnexal masses in Korean women.

METHODS

A total of 353 patients who underwent adnexal surgery with abnormal pelvic ultrasonographic findings from August 2016 to August 2017 were included in study. The presumptive diagnosis of adnexal malignancy was determined by both SA and the ADNEX model to be >10% calculated risk of malignancy. The area under the curve (AUC) comparison between the SA and ADNEX models was performed using DeLong's method.

RESULTS

340 patients with benign tumors and 13 with malignant adnexal tumors among 292 (82.72%) premenopausal and 61 (17.28%) postmenopausal women were included. The AUCs of SA and the ADNEX model for discrimination between benign and malignant tumors were 0.79 and 0.92, respectively (P=0.10). The sensitivity and specificity of SA and the ADNEX model were 83.5% and 97.0%, and 90.0% and 82.0%, respectively. Comparison of the ADNEX model regarding menopausal status revealed that the predictability was not different. The AUCs of SA and the ADNEX model in premenopausal women were 0.74 and 0.89, respectively (P=0.12). The AUCs of SA and the ADNEX model in postmenopausal women were 0.86 and 0.94, respectively (P=0.60).

CONCLUSION

The ADNEX model offers excellent discrimination between benign and malignant ovarian tumors with similar sensitivity and specificity to SA in both premenopausal and postmenopausal Korean women.

Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study

OBJECTIVE

To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively.

DESIGN

Multicentre cohort study.

SETTING

36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre.

PARTICIPANTS

Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up.

MAIN OUTCOME MEASURES

Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain.

RESULTS

The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125.

CONCLUSIONS

Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01698632.

Validation of IOTA-ADNEX Model in Discriminating Characteristics of Adnexal Masses: A Comparison with Subjective Assessment

(1) Background: The aim of this study is to compare the IOTA-ADNEX (international ovarian tumor analysis–assessment of different neoplasias in the adnexa) model with gynecologic experts in differentiating ovarian diseases. (2) Methods: All participants in this prospective study underwent ultrasonography (US) equipped with the IOTA-ADNEX^TM model and subjective assessment by a sonographic expert. Receiver operating characteristic (ROC) curves were also generated to compare overall accuracies. The optimal cut-off value of the ADNEX model for excluding benign diseases was calculated. (3) Results: Fifty-nine participants were eligible: 54 and 5 underwent surgery and follow-up computed tomography (CT), respectively. Benign and malignant diseases were confirmed in 49 (83.1%) and 10 (16.9%) participants, respectively. The specificity of the ADNEX model was 0.816 (95% confidence interval (CI): 0.680–0.912) in all participants and 0.795 (95% CI, 0.647–0.902) in the surgical group. The area under the ROC curve of the ADNEX model (0.924) was not significantly different from that of subjective assessment (0.953 in all participants, 0.951 in the surgical group; p = 0.391 in all participants, p = 0.407 in the surgical group). The optimal cut-off point using the ADNEX model was 47.3%, with a specificity of 0.977 (95% CI: 0.880–0.999). (4) Conclusions: The IOTA-ADNEX model is equal to gynecologic US experts in excluding benign ovarian tumors. Subsequently, being familiar with this US software may help gynecologic beginners to reduce unnecessary surgery.

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

OBJECTIVES

The ADNEX (Assessment of Different NEoplasias in the adneXa) model was developed using parameters collected by experienced (level III) ultrasound examiners. Our primary aim was to externally validate the ADNEX model. Then, the discriminatory performance of ADNEX was compared with the two-step strategy and subjective assessment by an experienced ultrasound operator.

METHODS

Between February 2013 and January 2017, all patients who were scheduled for surgery for an adnexal mass at the Sant'Anna Hospital in Turin were enrolled in this study. Preoperative transvaginal sonography was performed, and the two-step strategy was applied for triage of the adnexal mass. Two ultrasound examiners, IOTA certified, applied the ADNEX model to all the collected masses based on the ultrasound reports. Finally, an experienced operator assigned the subjective assessment based on recorded ultrasound images. The discrimination and calibration performance of ADNEX were evaluated. The AUC was calculated for the basic discrimination between benign and malignant tumours. In addition, AUCs were computed for each pair of tumour types using the conditional risk method.

RESULTS

A total of 577 patients were included in the analysis: the overall prevalence of malignancy was 25 %. With ADNEX, the AUC to differentiate between benign and malignant masses was 0.9111 (95 % CI 0. 8788-0.9389). At risk cut-offs of 1%, 10 % and 30 %, sensitivities were 100 %, 89.6 % and 79.2 %, respectively, and specificities were 2.8 %, 76.2 % and 89.6 %, respectively. Discrimination between benign and stage II-IV tumours was good (AUC 0.935). The model had the most difficulties discriminating between borderline and stage I tumours (AUC 0.666), and between stages II-IV invasive and secondary metastatic tumours (AUC 0.736). The polytomous discrimination index (PDI) was 0.61 for ADNEX, whereas PDI for random performance would be 0.25. ADNEX proved to be equally or more accurate than the subjective assessment or the two-step strategy in the discrimination between benign and malignant adnexal masses.

CONCLUSIONS

the ADNEX model could probably be successfully applied when an expert examiner is not available and, therefore both a subjective assessment and the two-step strategy cannot be performed.

Performance of IOTA ADNEX model in evaluating adnexal masses in a gynecological oncology center in China

OBJECTIVE

To evaluate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses using data from a gynecological oncology center in China.

METHODS

This was a single-center, retrospective diagnostic accuracy study based on ultrasound data collected prospectively, between May and December 2017, from 278 patients with at least one adnexal (ovarian, paraovarian or tubal) mass. Clinical and pathologic information, serum CA 125 level and ultrasonographic findings were collected. All patients underwent surgery and the histopathological diagnosis was used as reference standard. The final diagnosis was classified into five tumor types according to the ADNEX model: benign ovarian tumor, borderline ovarian tumor (BOT), Stage-I ovarian cancer (OC), Stages-II-IV OC and ovarian metastasis. Receiver-operating characteristics (ROC) curve analysis was used to evaluate the diagnostic accuracy of the ADNEX model, with and without inclusion of CA 125 level in the model.

RESULTS

Of the 278 women included, 203 (73.0%) had a benign ovarian tumor and 75 (27.0%) had a malignant ovarian tumor, including 18 (6.5%) with BOT, 17 (6.1%) with Stage-I OC, 32 (11.5%) with Stages-II-IV OC and eight (2.9%) with ovarian metastasis. The performance of the IOTA ADNEX model was good for discriminating between benign and malignant tumors, with an area under the ROC curve (AUC) of 0.94 (95% CI, 0.91-0.97) when CA 125 was included in the model and AUC of 0.93 (95% CI, 0.90-0.96) without CA 125. The AUC values of the model including CA 125 ranged between 0.61 and 0.99 for distinguishing between the different types of tumor, and it showed excellent performance in discriminating between a benign ovarian tumor and Stages-II-IV OC, with an AUC of 0.99 (95% CI, 0.97-1.00). The performance of the model was less effective at distinguishing between BOT and Stage-I OC and between Stages-II-IV OC and ovarian metastasis, with AUC values of 0.61 (95% CI, 0.43-0.77) and 0.78 (95% CI, 0.62-0.90), respectively. Although inclusion of CA 125 did not alter the performance of the ADNEX model in discriminating between benign and malignant lesions (AUC of 0.94 and 0.93 with and without CA 125 level, respectively; P = 0.54), the inclusion of CA 125 in the model improved its performance in discriminating between Stage-I OC and Stages-II-IV OC (AUC increased from 0.81 to 0.92; P = 0.04) and between Stages-II-IV OC and metastatic cancer (AUC increased from 0.58 to 0.78; P = 0.01).

CONCLUSIONS

The IOTA ADNEX model showed good to excellent performance in distinguishing between benign and malignant adnexal masses and between the different types of ovarian tumor in a Chinese setting. Based on our findings, the ADNEX model has high value in clinical practice and can aid in the preoperative diagnosis of patients with an adnexal mass. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Methods of Assessing Ovarian Masses: International Ovarian Tumor Analysis Approach

There are many diagnostic methods to assist clinicians in assessing adnexal masses on ultrasound. After suggesting a standardized terminology and measurement technique to evaluate adnexal masses, the International Ovarian Tumor Analysis (IOTA) group has developed different strategies such as the Simple Rules and Assessment of Different Neoplasias in the adneXa (ADNEX) model, which have been shown to outperform other available methods. Besides differentiating between benign neoplasms and malignancies, the ADNEX model can also give the predicted risk for different subtypes of malignant adnexal masses, which is clinically very relevant for guiding patient management.

Imaging and Differential Diagnosis of Ovarian Cancer

Ovarian cancer is the seventh most common cancer affecting women. Despite advances in cancer control and healthcare in general, mortality from ovarian cancer remains unacceptably high due to diagnosis at an advanced stage of the disease. The 5-year survival rate is 47.4% because a majority of ovarian cancers are diagnosed when advanced. Only 14.9% of ovarian cancers are diagnosed when localized where the survival rate is 92.3%. Mortality rate reduction by screening has not been proven in women at an average risk for ovarian cancer. Ultrasound remains the primary modality for assessment of ovarian tumors. The need for standardizing terminology is critical for optimal assessment of the risk of malignancy in an ovarian tumor. The international ovarian tumor analysis group and more recently the American College of Radiology Ovarian - Adnexal Reporting and Data System Committee have published standardized lexicon for ovarian lesions and encourage ultrasound imagers to adopt this standardized terminology. The aim is to apply the lexicon for risk stratification to allow for consistent follow-up and management. Various methodologies have been tested for characterization of adnexal tumors and to assess risk of malignancy preoperatively. Risk assessment models have been studied against the gold standard of a pattern recognition approach and subjective assessment by an experienced imager. The morphologic patterns of ovarian tumors are detailed and features that are more discriminatory than others in suggesting an ovarian malignancy are described. The imaging pathologic correlation for different tumor types is presented. A brief summary of the ovarian cancer pathologic types and staging of cancer is presented. Finally, the current role of transvaginal sonography as a screening modality for ovarian cancer is discussed. Recently published data show encouraging results, that a multimodal approach of screening for ovarian cancer using transvaginal sonography in women with an elevated CA-125 may prove beneficial and cost effective.

Imaging in the pre-operative staging of ovarian cancer

The main prognostic factor in ovarian cancer is the stage of disease at diagnosis. The staging system in use (FIGO classification, updated in 2014) is based on the surgical-pathological findings. Although surgical staging is the gold standard in ovarian cancer, the initial patient management depends on the imaging-based pre-surgical staging assessment, in order to identify unresectable or difficult to resect disease. Radiologists need to be aware of the strengths of the available imaging modalities, as well as the imaging pitfalls. Clear understanding of pattern of disease spread and review areas are critical for accurate staging and treatment planning. The current standard of care for pre-surgical staging is CT of the thorax, abdomen, and pelvis. This allows a rapid evaluation of disease extent and is fairly accurate in identifying bulky disease but has definite limitations in assessing the extent of small volume disease and in the confirmation of certain sites of disease beyond the abdomen. Functional MRI has been reported to be superior in detecting small peritoneal deposits. PET/CT may be used as a problem-solving tool in some patients where determination remains unclear, particularly in confirmation of advanced stage beyond the abdomen.

Diagnostic value of the gynecology imaging reporting and data system (GI-RADS) with the ovarian malignancy marker CA-125 in preoperative adnexal tumor assessment

Objectives

The purpose of this study is to assess the preoperative evaluation of an adnexal mass using the GI-RADS classification and to verify whether CA-125 measurement can offer any additional benefits to the GI-RADS-based prediction of ovarian tumor malignancy.

Material and methods

In this study, we assessed a total of 215 women with an adnexal tumor using the GI-RADS classification combined with CA-125 measurement. All adnexal masses underwent histological verification.

Results

Of a total of 215 lesions, we classified 2 lesions as GI-RADS 2 (0.9%), 118 lesions as GI-RADS 3 (54.9%), 86 lesions as GI-RADS 4 (40.0%) and 9 lesions as GI-RADS 5 (4.2%). For GI-RADS 4–5 lesions, the sensitivity, specificity, PPV, NPV, ACC and OR were as follows: 94.3, 72.2, 52.6, 97.5, 77.7%, and 43.3 (CI 12.0–146), respectively. The corresponding parameters resulting from combining the GI-RADS classification with the CA-125 marker were as follows: 66.0, 93.8, 77.8, 89.4, 87.0%, and 29.6 (CI 12.6–69.6), respectively, with p < 0.001. For Ca-125 > 30 IU/mL alone, the results were as follows: 70.0, 80.3, 53.8, 89.1, 77.7%, and 9.5 (4.6–19.6), respectively, with p < 0.0001.

Additionally, 47.8% of the patients had no symptoms, 36.5% had back pain, 5.2% had an increased abdominal size, 4.3% had menstrual irregularities and 2.6% had constipation. There were 152 benign and 18 malignant cases in the low risk group (GIRADS 1–3 and GIRADS 4 + CA-125 < 30 IU/mL) and 10 benign and 35 malignant tumors in the high-risk group (GIRADS 4 + CA125 > 30 IU/mL and GIRADS 5).

Conclusions

GI-RADS classification had good performance in discriminating ovarian tumors. The additional measurement of CA-125 improves the system specificity, PPV and ACC for preoperative adnexal tumor assessment.

Ovarian mass-differentiating benign from malignant: the value of the International Ovarian Tumor Analysis ultrasound rules

Ovarian cancer, the fifth most common cause of cancer death among women, has the highest mortality rate of all gynecologic cancers. General survival rate is <50% but can reach 90% if disease is detected early. Ultrasound is presently the best modality to differentiate between benign and malignant status. The patient with a malignant mass should be referred to an oncology surgeon since results have been shown to be superior to treatment by a specialist. Several ultrasound-based scoring systems exist for assessing the risk of an ovarian tumor to be malignant. The International Ovarian Tumor Analysis group published 2 such systems: the ultrasound Simple Rules and the Assessment of Different NEoplasias in the adneXa model. The Simple Rules classifies a tumor as benign, malignant, or indeterminate and the Assessment of Different NEoplasias in the adneXa model determines the risk for a tumor to be benign or malignant and, if malignant, the risk of various stages. Sensitivity of the Simple Rules and Assessment of Different NEoplasias in the adneXa model (using a cut-off of 10% to predict malignancy) are 92% and 96.5%, respectively, and specificities are 96% and 71.3%, respectively. These models are the best predictive tests for the preoperative classification of adnexal tumors. Their intent is to help the specialist make management decisions when faced with a patient with a persistent ovarian mass. The models are simple, are easy to use, and have been validated in multiple reports but not in the United States. We suggest they should be validated and widely introduced into medical practice in the United States.

Validation of the Performance of International Ovarian Tumor Analysis (IOTA) Methods in the Diagnosis of Early Stage Ovarian Cancer in a Non-Screening Population

Background: The aim of this study was to assess and compare the performance of different ultrasound-based International Ovarian Tumor Analysis (IOTA) strategies and subjective assessment for the diagnosis of early stage ovarian malignancy. Methods: This is a secondary analysis of a prospective multicenter cross-sectional diagnostic accuracy study that included 1653 patients recruited at 18 centers from 2009 to 2012. All patients underwent standardized transvaginal ultrasonography by experienced ultrasound investigators. We assessed test performance of the IOTA Simple Rules (SRs), Simple Rules Risk (SRR), the Assessment of Different NEoplasias in the adneXa (ADNEX) model and subjective assessment to discriminate between stage I-II ovarian cancer and benign disease. Reference standard was histology after surgery. Results: 230 (13.9%) patients proved to have stage I–II primary invasive ovarian malignancy, and 1423 (86.1%) had benign disease. Sensitivity and specificity with respect to malignancy (95% confidence intervals) of the original SRs (classifying all inconclusive cases as malignant) were 94.3% (90.6% to 96.7%) and 73.4% (71.0% to 75.6%). Subjective assessment had a sensitivity and specificity of 90.0% (85.4% to 93.2%) and 86.7% (84.9% to 88.4%), respectively. The areas under the receiver operator characteristic curves of SRR and ADNEX were 0.917 (0.902 to 0.933) and 0.905 (0.920 to 0.934), respectively. At a 1% risk cut-off, sensitivity and specificity for SRR were 100% (98.4% to 100%) and 38.0% (35.5% to 40.6%), and for ADNEX were 100% (98.4% to 100%) and 19.4% (17.4% to 21.5%). At a 30% risk cut-off, sensitivity and specificity for SRR were 88.3% (83.5% to 91.8%) and 81.1% (79% to 83%), and for ADNEX were 84.5% (80.5% to 89.6%) and 84.5% (82.6% to 86.3%). Conclusion: This study shows that all three IOTA strategies have good ability to discriminate between stage I-II ovarian malignancy and benign disease.

Clinical Utility of Risk Models to Refer Patients with Adnexal Masses to Specialized Oncology Care: Multicenter External Validation Using Decision Curve Analysis

Purpose: To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)].Experimental Design: A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2,763 patients (2,403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals.Results: The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar.Conclusions: All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care. Clin Cancer Res; 23(17); 5082-90. ©2017 AACR.

Role of Imaging Tools for the Diagnosis of Borderline Ovarian Tumors: A Systematic Review and Meta-Analysis

Borderline ovarian tumors (BOTs) have a low malignant potential and occur most often in young women. Its preoperative diagnosis can improve surgical strategy and reproductive approach. This study systematically reviews the literature for the accuracy of transvaginal ultrasound (TVUS), magnetic resonance (MRI), and computed tomography (CT) in the diagnostic of BOTs. We conducted a search in PubMed/Medline of articles in English from the last 5 years and included 14 studies for systematic review, 9 of them in the meta-analysis. The pooled sensibility and specificity was respectively 77.0% and 83.0% for TVUS (5 studies) and 85% and 74% for MRI (4 studies) in differentiating benign from malignant BOTs. CT and positron emission tomography (PET)-CT techniques were heterogeneous between studies, so a meta-analysis was not performed for the 4 studies on CT and PET-CT. However, these 4 studies have also shown a high accuracy in differentiating BOTs from malignant ovarian cancers.