A comparison of the diagnostic performance of the O-RADS, RMI4, IOTA LR2, and IOTA SR systems by senior and junior doctors

Clinical value of ACR O-RADS combined with CA125 in the risk stratification of adnexal masses

Purpose

To develop a combined diagnostic model integrating the subclassification of the 2022 version of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) with carbohydrate antigen 125 (CA125) and to validate whether the combined model can offer superior diagnostic efficacy than O-RADS alone in assessing adnexal malignancy risk.

Methods

A retrospective analysis was performed on 593 patients with adnexal masses (AMs), and the pathological and clinical data were included. According to the large differences in malignancy risk indices for different image features in O-RADS category 4, the lesions were categorized into groups A and B. A new diagnostic criterion was developed. Lesions identified as category 1, 2, 3, or 4A with a CA125 level below 35 U/ml were classified as benign. Lesions identified as category 4A with a CA125 level more than or equal to 35 U/ml and lesions with a category of 4B and 5 were classified as malignant. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) of O-RADS (v2022), CA125, and the combined model in the diagnosis of AMs were calculated and compared.

Results

The sensitivity, specificity, PPV, NPV, accuracy, and AUCs of the combined model were 92.4%, 96.5%, 80.2%, 98.8%, 94.1%, and 0.945, respectively. The specificity, PPV, accuracy, and AUC of the combined model were significantly higher than those of O-RADS alone (all P < 0.01). In addition, both models had acceptable sensitivity and NPV, but there were no significant differences among them (P > 0.05).

Conclusion

The combined model integrating O-RADS subclassification with CA125 could improve the specificity and PPV in diagnosing malignant AMs. It could be a valuable tool in the clinical application of risk stratification of AMs.

The Roles of Ovarian-Adnexal Reporting and Data System US and Ovarian-Adnexal Reporting and Data System MRI in the Evaluation of Adnexal Lesions

The Ovarian-Adnexal Reporting and Data System (O-RADS) is an evidence-based clinical support system for ovarian and adnexal lesion assessment in women of average risk. The system has both US and MRI components with separate but complementary lexicons and assessment categories to assign the risk of malignancy. US is an appropriate initial imaging modality, and O-RADS US can accurately help to characterize most adnexal lesions. MRI is a valuable adjunct imaging tool to US, and O-RADS MRI can help to both confirm a benign diagnosis and accurately stratify lesions that are at risk for malignancy. This article will review the O-RADS US and MRI systems, highlight their similarities and differences, and provide an overview of the interplay between the systems. When used together, the O-RADS US and MRI systems can help to accurately diagnose benign lesions, assess the risk of malignancy in lesions suspicious for malignancy, and triage patients for optimal management.

Ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features for automatic classification of ovarian masses according to O-RADS

Background

Accurate and rapid discrimination between benign and malignant ovarian masses is crucial for optimal patient management. This study aimed to establish an ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features to automatically classify the ovarian masses into low risk and intermediate-high risk of malignancy lesions according to the Ovarian- Adnexal Reporting and Data System (O-RADS).

Methods

The ultrasound images of 1,080 patients with 1,080 ovarian masses were included. The training cohort consisting of 683 patients was collected at the South China Hospital of Shenzhen University, and the test cohort consisting of 397 patients was collected at the Shenzhen University General Hospital. The workflow included image segmentation, feature extraction, feature selection, and model construction.

Results

The pre-trained Resnet-101 model achieved the best performance. Among the different mono-modal features and fusion feature models, nomogram achieved the highest level of diagnostic performance (AUC: 0.930, accuracy: 84.9%, sensitivity: 93.5%, specificity: 81.7%, PPV: 65.4%, NPV: 97.1%, precision: 65.4%). The diagnostic indices of the nomogram were higher than those of junior radiologists, and the diagnostic indices of junior radiologists significantly improved with the assistance of the model. The calibration curves showed good agreement between the prediction of nomogram and actual classification of ovarian masses. The decision curve analysis showed that the nomogram was clinically useful.

Conclusion

This model exhibited a satisfactory diagnostic performance compared to junior radiologists. It has the potential to improve the level of expertise of junior radiologists and provide a fast and effective method for ovarian cancer screening.

Comparison of O-RADS with the ADNEX model and IOTA SR for risk stratification of adnexal lesions: a systematic review and meta-analysis

Purpose

This study aims to systematically compare the diagnostic performance of the Ovarian-Adnexal Reporting and Data System with the International Ovarian Tumor Analysis Simple Rules and the Assessment of Different NEoplasias in the adneXa model for risk stratification of ovarian cancer and adnexal masses.

Methods

A literature search of online databases for relevant studies up to July 2023 was conducted by two independent reviewers. The summary estimates were pooled with the hierarchical summary receiver-operating characteristic model. The quality of the included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 and the Quality Assessment of Diagnostic Accuracy Studies-Comparative Tool. Metaregression and subgroup analyses were performed to explore the impact of varying clinical settings.

Results

A total of 13 studies met the inclusion criteria. The pooled sensitivity and specificity for eight head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model were 0.96 (95% CI 0.92-0.98) and 0.82 (95% CI 0.71-0.90) vs. 0.94 (95% CI 0.91-0.95) and 0.83 (95% CI 0.77-0.88), respectively, and for seven head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the International Ovarian Tumor Analysis Simple Rules, the pooled sensitivity and specificity were 0.95 (95% CI 0.93-0.97) and 0.75 (95% CI 0.62-0.85) vs. 0.91 (95% CI 0.82-0.96) and 0.86 (95% CI 0.76-0.93), respectively. No significant differences were found between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model as well as the International Ovarian Tumor Analysis Simple Rules in terms of sensitivity (P = 0.57 and P = 0.21) and specificity (P = 0.87 and P = 0.12). Substantial heterogeneity was observed among the studies for all three guidelines.

Conclusion

All three guidelines demonstrated high diagnostic performance, and no significant differences in terms of sensitivity or specificity were observed between the three guidelines.

Comparison of Simple Ultrasound Rules by International Ovarian Tumor Analysis (IOTA) with RMI-1 and RMI-4 (Risk of Malignancy Index) in Preoperative Differentiation of Benign and Malignant Adnexal Masses

Background

IOTA proposed Simple Ultrasound Rules in 2009 for preoperative diagnosis of ovarian masses based on ultrasound only. It is an accurate, simple and inexpensive method. RMI, however, requires CA125 level. While RMI-4 is the latest, RMI-1 is still the most widely used method. The present study was done to compare IOTA Rules with RMI-1 and RMI-4.

Purpose

To differentiate benign and malignant adnexal masses preoperatively using IOTA simple rules and compare its accuracy with RMI-1 and RMI-4.

Methods

A prospective observational study was performed from 1st November 2019 to 31st March 2021 in the Department of Obstetrics and Gynaecology, ABVIMS and Dr. RML Hospital, New Delhi. This study was conducted on 70 patients with adnexal masses who underwent pre-operative evaluation using IOTA Simple Rules, RMI-1 and RMI-4. Histopathology was used to compare the results.

Results

Out of 70 patients, 59 (84.3%) cases were benign and 11 (15.7%) were malignant. The IOTA Rules were applicable to 60 cases (85.7%), and the results were inconclusive in 10 cases (14.3%). Where applicable, the sensitivity and specificity of the IOTA Rules (88.9% and 94.1%, respectively) were significantly higher than RMI-1 (45.5% and 93.2%, respectively) and RMI-4 (45.5% and 89.8%, respectively). When inconclusive results were included as malignant, the sensitivity of the IOTA Rules increased (88.9% vs 90.9%); however, the specificity decreased (94.1% vs 81.4%).

Conclusion

IOTA Simple Rules were more accurate at diagnosing benign from malignant adnexal masses than RMI-1 and RMI-4. However, the rules were not applicable to 14% of the cases.

Application of O-RADS US combined with MV-Flow to diagnose ovarian-adnexal tumors

PURPOSE

This study aimed to explore the application of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) combined with MV-Flow (Samsung Medison Co., Ltd.) to diagnose ovarian-adnexal masses.

METHODS

A total of 112 ovarian-adnexal masses (81 benign and 31 malignant) from 105 consecutive patients were analyzed. The O-RADS US and vascular index from MV-Flow (VIMV) were measured and compared with the reference standard. O-RADS US and MV-Flow were tested for consistency.

RESULTS

Receiver operating characteristic curves were drawn for O-RADS US, MV-Flow, and their combination. The combined methods had the largest area under the curve (0.955), followed by O-RADS US (0.929) and MV-Flow (0.923). A mass was considered malignant when the O-RADS US classification was 5 and VIMV was ≥7.15. With this definition, MV-Flow had the highest sensitivity (87.10%), with consistent findings for the combined diagnostic methods and O-RADS US (83.87%). The specificity of the combined diagnostic methods (93.83%) was higher than that of MV-Flow (91.36%). O-RADS US had the lowest specificity (90.12%). The combined diagnostic methods had the highest coincidence rate (91.07%), and MV-Flow (90.18%) had a significantly higher coincidence rate than O-RADS US (88.39%). Both O-RADS US and MV-Flow showed good consistency among different physicians (former kappa, 0.974; latter intraclass correlation coefficient [ICC], 0.986). MV-Flow had a high consistency for the same physician (ICC, 1).

CONCLUSION

O-RADS US and MV-Flow exhibited good diagnostic efficacy, and their combined diagnostic efficacy was higher than that of each individually. O-RADS US and MV-Flow can improve the diagnosis of benign and malignant ovarian-adnexal masses.

Comparison of the diagnostic efficiency between the O-RADS US risk stratification system and doctors' subjective judgment

BACKGROUND

This study aimed to compare the diagnostic efficiency of Ovarian-Adnexal Reporting and Data System (O-RADS) and doctors' subjective judgment in diagnosing the malignancy risk of adnexal masses.

METHODS

This was an analysis of 616 adnexal masses between 2017 and 2020. The clinical findings, preoperative ultrasound images, and pathological diagnosis were recorded. Each adnexal mass was evaluated by doctors' subjective judgment and O-RADS by two senior doctors and two junior doctors. A mass with an O-RADS grade of 1 to 3 was a benign tumor, and a mass with an O-RADS grade of 4-5 was a malignant tumor. All outcomes were compared with the pathological diagnosis.

RESULTS

Of the 616 adnexal masses, 469 (76.1%) were benign, and 147 (23.9%) were malignant. There was no difference between the area under the curve of O-RADS and the subjective judgment for junior doctors (0.83 (95% CI: 0.79-0.87) vs. 0.79 (95% CI: 0.76-0.83), p = 0.0888). The areas under the curve of O-RADS and subjective judgment were equal for senior doctors (0.86 (95% CI: 0.83-0.89) vs. 0.86 (95% CI: 0.83-0.90), p = 0.8904). O-RADS had much higher sensitivity than the subjective judgment in detecting malignant tumors for junior doctors (84.4% vs. 70.1%) and senior doctors (91.2% vs. 81.0%). In the subgroup analysis for detecting the main benign lesions of the mature cystic teratoma and ovarian endometriosic cyst, the junior doctors' diagnostic accuracy was obviously worse than the senior doctors' on using O-RADS.

CONCLUSIONS

O-RADS had excellent performance in predicting malignant adnexal masses. It could compensate for the lack of experience of junior doctors to a certain extent. Better performance in discriminating various benign lesions should be expected with some complement.

Comparative diagnostic accuracy of the IOTA SRR and LR2 scoring systems for discriminating between malignant and Benign Adnexal masses by junior physicians in Chinese patients: a retrospective observational study

BACKGROUND

The accuracy of ultrasound in distinguishing benign from malignant adnexal masses is highly correlated with the experience of ultrasound physicians. In China, most of ultrasound differentiation is done by junior physicians.

PURPOSE

To compare the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) Simple Rules Risk (SRR) and IOTA Logistic Regression Model 2 (LR2) scoring systems in Chinese patients with adnexal masses.

METHODS

Retrospective analysis of ovarian cancer tumor patients who underwent surgery at a hospital in China from January 2016 to December 2021. Screening patients with at least one adnexal mass on inclusion and exclusion criteria. Two trained junior physicians evaluated each mass using the two scoring systems. A receiver operating characteristic curve was used to test the diagnostic performance of each system.

RESULTS

A total of 144 adnexal masses were retrospectively collected. Forty masses were histologically diagnosed as malignant. Compared with premenopausal women, postmenopausal women had a much higher rate of malignant masses. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of the SRR was 97.5% (95% CI: 86.8 -99.9%), 82.7% (95% CI: 74.0 -89.4%), 68.4% (95% CI: 58.7 -76.8%) and 98.9% (95% CI: 92.5 -99.8%). The sensitivity, specificity, PPV, NPV of the LR2 were 90.0% (95% CI: 76.5 -97.2%), 89.4% (95% CI: 81.9 -94.6%), 76.6% (95% CI: 65.0 -85.2%), and 95.9% (95% CI: 90.2 -98.3%). There was good agreement between two scoring systems, with 84.03% total agreement and a kappa value of 0.783 (95% CI: 0.70-0.864). The areas under the curve for predicting malignant tumours using SRR and LR2 were similar for all patients (P > 0.05 ).

CONCLUSION

The two scoring systems can effectively distinguish benign from malignant adnexal masses. Both scoring systems have high diagnostic efficacy, and diagnostic efficacy is stable, which can provide an important reference for clinical decision making.

Effect of differences in O-RADS lexicon interpretation between senior and junior sonologists on O-RADS classification and diagnostic performance

PURPOSE

To assess the consistency of Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon interpretation between senior and junior sonologists and to investigate its impact on O-RADS classification and diagnostic performance.

METHODS

We prospectively studied 620 patients with adnexal lesions, all of whom underwent transvaginal or transrectal ultrasound performed by a senior sonologist (R1) who selected the O-RADS lexicon description and O-RADS category for the lesion after the examination. Meanwhile, the junior sonologist (R2) analyzed the images retained by R1 and divided the lesion in the same way. Pathological findings were used as a reference standard. kappa (к) statistics were used to assess the interobserver agreement.

RESULTS

Of the 620 adnexal lesions, 532 were benign and 88 were malignant. When using the O-RADS lexicon, R1 and R2 had almost perfect agreement regarding lesion category, external contour of solid lesions, presence of papillary inside cystic lesions, and fluid echogenicity (к: 0.81-1.00). Substantial agreement in solid components, acoustic shadow, vascularity and O-RADS categories (к: 0.61-0.80). Consistency in classifying classic benign lesions in the O-RADS category was only moderate (к = 0.535). No significant difference in diagnostic performance between them using O-RADS (P = 0.1211).

CONCLUSION

There was good agreement between senior and junior sonologists in the interpretation of the O-RADS lexicon and in the classification of O-RADS, except for a moderate agreement in the interpretation and classification of classic benign lesions. Differences in O-RADS category delineation between sonologists had no significant effect on the diagnostic performance of O-RADS.

O-RADS US v2022: An Update from the American College of Radiology's Ovarian-Adnexal Reporting and Data System US Committee

First published in 2019, the Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, enables stratification of these lesions with use of a numeric score based on morphologic features to indicate the risk of malignancy, and offers management guidance. This risk stratification system has subsequently been validated in retrospective studies and has yielded good interreader concordance, even with users of different levels of expertise. As use of the system increased, it was recognized that an update was needed to address certain clinical challenges, clarify recommendations, and incorporate emerging data from validation studies. Additional morphologic features that favor benignity, such as the bilocular feature for cysts without solid components and shadowing for solid lesions with smooth contours, were added to O-RADS US for optimal risk-appropriate scoring. As O-RADS US 4 has been shown to be an appropriate cutoff for malignancy, it is now recommended that lower-risk O-RADS US 3 lesions be followed with US if not excised. For solid lesions and cystic lesions with solid components, further characterization with MRI is now emphasized as a supplemental evaluation method, as MRI may provide higher specificity. This statement summarizes the updates to the governing concepts, lexicon terminology and assessment categories, and management recommendations found in the 2022 version of O-RADS US.

O-RADS combined with contrast-enhanced ultrasound in risk stratification of adnexal masses

BACKGROUND

Ovarian-Adnexal Reporting and Data System (O-RADS) for ultrasound is a lexicon and risk stratification system that includes all risk categories and relevant management recommendation. It has high sensitivity in diagnosing malignant adnexal tumors, but the specificity is lower.

OBJECTIVE

To explore the value of O-RADS combined with contrast-enhanced ultrasound (CEUS) in risk stratification of adnexal masses.

METHODS

A retrospective study was performed on 85 patients with 100 adnexal masses that preoperatively underwent conventional ultrasound as well as CEUS examination and obtained the postoperative pathological results. The masses were classified into O-RADS2, 3, 4, and 5 by conventional ultrasound. After contrast enhancement, the classification of O-RADS was adjusted according to CEUS imaging features. The O-RADS 2 and 3 lesions with suspected malignant features like irregular blood vessels or internal inhomogeneous hyperenhancement were upgraded to O-RADS 4, and the O-RADS 4 lesions with the above features were upgraded to O-RADS 5. The O-RADS 4 lesions with suspicious benign angiographic features like a regular vessel, interior hypoenhancement or non-enhancement were downgraded to O-RADS 3; the O-RADS 5 lesions with rim ring-enhancement and interior non-enhancement were downgraded to O-RADS 3. The sensitivity, specificity, accuracy, PPV, NPV, and AUC of the two methods were compared, taking pathological results as the gold standard.

RESULTS

The sensitivity, specificity, accuracy, PPV, NPV, and AUC of O-RADS and O-RADS combined with CEUS in the diagnosis of malignant adnexal tumors were 96.6%, 66.2%, 75.0%, 53.8%, 97.9%, 0.910 and 96.6%, 91.5%, 93.0%, 82.4%, 98.5%, 0.962, respectively. The specificity, accuracy, PPV, and AUC of O-RADS combined with CEUS were considerably higher than those of O-RADS (P < 0.01). Furthermore, both methods had excellent sensitivity and NPV but there were no significant differences between them(P > 0.05).

CONCLUSION

Combination of O-RADS and CEUS can significantly improve the specificity and PPV in diagnosing malignant adnexal tumors. It seems promising in the clinical application of risk stratification of adnexal masses.

O-RADS US: A Systematic Review and Meta-Analysis of Category-specific Malignancy Rates

Background Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized method with which to stratify lesions into risk of malignancy categories, which is crucial for proper management. Purpose To perform a systematic review and meta-analysis to estimate malignancy rates for each O-RADS US score and evaluate the diagnostic performance of combined O-RADS US scores 4 and 5 in the diagnosis of malignancy. Materials and Methods A systematic literature search from the inception of the MEDLINE, EMBASE, and Web of Science databases through January 27, 2023, was performed for articles that reported using the O-RADS US stratification system and included malignancy rates per each O-RADS score. Bivariate random-effects models were used to determine the pooled malignancy rates for each O-RADS US score and to obtain summary estimates of the diagnostic performance of combined O-RADS US scores 4 and 5 in the diagnosis of malignant lesions. Results The final analysis included 18 studies consisting of 11 605 patients and 11 818 ovarian-adnexal lesions, with 2996 malignant (25.4%) and 8822 benign (74.6%) lesions. No malignant lesions were reported in O-RADS 1 category. The pooled percentages of malignancy were 0.6% (95% CI: 0.3, 1.0) for O-RADS 2, 3.9% (95% CI: 2.5, 5.4) for O-RADS 3, 43.5% (95% CI: 33.8, 53.2) for O-RADS 4, and 87.3% (95% CI: 83.0, 91.7) for O-RADS 5. The pooled sensitivity and specificity of combined O-RADS scores 4 and 5 in the diagnosis of malignant lesions were 95.6% (95% CI: 94.0, 97.2) and 76.6% (95% CI: 70.4, 82.7), respectively. Conclusion Each O-RADS US score provided the intended probability of malignant lesions as outlined by the O-RADS risk stratification system. When O-RADS US scores 4 and 5 were combined as a predictor for malignancy, O-RADS US showed a high sensitivity and moderate specificity. Clinical trial registration no. CRD42022352166 © RSNA, 2023 Supplemental material is available for this article.

Predictive accuracy and reproducibility of the O-RADS US scoring system among sonologists with different training levels

PURPOSE

To investigate the predictive performance and reproducibility of Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) system in evaluating adnexal masses between sonologists with varying levels of expertise.

METHODS

This was a single-center retrospective study conducted between May 2019 and May 2020, which included 147 adnexal mases with pathological results. Four sonologists with varying experiences independently assigned an O-RADS US category to each adnexal mass twice. The intra- and inter-observer agreement was assessed using weighted kappa values. The area under the curve (AUC), sensitivity, specificity, positive and negative predictive value (PPV and NPV) were assessed for each sonologist.

RESULTS

Of the 147 adnexal mases, 115 (78.2%) lesions were benign and 32 (21.8%) lesions were malignant. Considering O-RADS > 3 as a predictor for adnexal malignancy, the predictive accuracies of the four sonologists were excellent, with AUCs ranging from 0.831 to 0.926. The predictive accuracies of O-RADS US by experienced sonologists were significantly higher compared to inexperienced sonologists (all P values < 0.005). The O-RADS US presented high sensitivity and NPV value for each sonologist. With regard to the reproducibility of O-RADS, the intra- and inter-observer agreement among experienced sonologists performed better than inexperienced sonologists.

CONCLUSION

O-RADS showed difference in the predictive accuracy and reproducibility in the evaluation of adnexal masses among sonologists with different levels of expertise. Training is required for inexperienced sonologists before the generalization of O-RADS classification system in clinical practice.

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.

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.

Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology

OBJECTIVE

The accurate preoperative differentiation of benign and malignant adnexal masses, especially those with complex ultrasound morphology, remains a great challenge for junior sonographers. The purpose of this study was to develop and validate a nomogram based on the Ovarian-Adnexal Reporting and Data System (O-RADS) for predicting the malignancy risk of adnexal masses with complex ultrasound morphology.

METHODS

A total of 243 patients with data on adnexal masses with complex ultrasound morphology from January 2019 to December 2020 were selected to establish the training cohort, while 106 patients with data from January 2021 to December 2021 served as the validation cohort. Univariate and multivariate analyses were used to determine independent risk factors for malignant tumors in the training cohort. Subsequently, a predictive nomogram model was developed and validated in the validation cohort. The calibration, discrimination, and clinical net benefit of the nomogram model were assessed separately by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Finally, we compared this model to the O-RADS.

RESULTS

The O-RADS category, an elevated CA125 level, acoustic shadowing and a papillary projection with color Doppler flow were the independent predictors and were incorporated into the nomogram model. The area under the ROC curve (AUC) of the nomogram model was 0.958 (95% CI, 0.932-0.984) in the training cohort. The specificity and sensitivity were 0.939 and 0.893, respectively. This nomogram also showed good discrimination in the validation cohort (AUC = 0.940, 95% CI, 0.899-0.981), with a sensitivity of 0.915 and specificity of 0.797. In addition, the nomogram model showed good calibration efficiency in both the training and validation cohorts. DCA indicated that the nomogram was clinically useful. Furthermore, the nomogram model had higher AUC and net benefit than the O-RADS.

CONCLUSION

The nomogram based on the O-RADS showed a good predictive ability for the malignancy risk of adnexal masses with complex ultrasound morphology and could provide help for junior sonographers.

External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups

Importance

Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy.

Objective

To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy.

Design, Setting, and Participants

Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022.

Exposures

Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy.

Main Outcomes and Measures

Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information.

Results

Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%).

Conclusions and Relevance

The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.

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.

Comparison of diagnostic efficiency between IOTA LR2 model and doctors experiences

OBJECTIVES

International Ovarian Tumor Analysis (IOTA) working group proposed a logistic regression (IOTA LR2) model. It is served as a risk prediction model for benign and malignant adnexal tumors. This study aims to compare the diagnostic efficiency between the IOTA LR2 model and doctors' subjective assessment on diagnosing benign and malignant adnexal mass.

METHODS

The ultrasonographic images of 616 adnexal masses were retrospectively analyzed by the senior doctors' group and the junior doctors' group using the IOTA LR2 model and subjective assessment. The postoperative pathological diagnosis was used as the gold standard to compare the diagnostic efficiency of the 2 methods.

RESULTS

The area under the curves of subjective assessment and IOTA LR2 model for diagnosing malignant adnexal masses were 0.86 and 0.90 for the senior doctors' group and 0.79 and 0.88 for the junior doctors' group, respectively. The sensitivity and specificity of subjective assessment for diagnosing the malignant adnexal masses were 81.0% and 91.3% for the senior doctors' group and 70.1% and 88.7% for the junior doctors' group, respectively. The sensitivity and specificity of the IOTA LR2 model for diagnosing the malignant adnexal masses were 79.6% and 88.1% for the senior doctors' group, and 79.6% and 81.7% for the junior doctors' group, respectively.There were no significant difference in the sensitivities between the senior doctors' group and junior doctors' group using the IOTA LR2 model and the senior doctors' group using subjective assessment (both P>0.05).

CONCLUSIONS

The diagnostic efficiency of the IOTA LR2 model is equal to the senior doctors' experiences. This model can help junior doctors to reduce the missed diagnosis of malignant adnexal masses.

Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis

Simple Summary

We performed a systematic review and meta-analysis aiming to assess the diagnostic performance of the Ovarian Adnexal Report Data System (O-RADS) using transvaginal ultrasound for classifying adnexal masses. Data from 11 studies comprising 4634 masses showed that the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%–98%), 77% (95% CI = 68%–84%), 4.2 (95% CI= 2.9–6.0), 0.04 (95% CI = 0.03–0.07), and 96 (95% CI = 50–185), respectively. We concluded that the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses.

Abstract

In this systematic review and meta-analysis, we aimed to assess the pooled diagnostic performance of the so-called Ovarian Adnexal Report Data System (O-RADS) for classifying adnexal masses using transvaginal ultrasound, a classification system that was introduced in 2020. We performed a search for studies reporting the use of the O-RADS system for classifying adnexal masses from January 2020 to April 2022 in several databases (Medline (PubMed), Google Scholar, Scopus, Cochrane, and Web of Science). We selected prospective and retrospective cohort studies using the O-RADS system for classifying adnexal masses with histologic diagnosis or conservative management demonstrating spontaneous resolution or persistence in cases of benign appearing masses after follow-up scan as the reference standard. We excluded studies not related to the topic under review, studies not addressing O-RADS classification, studies addressing MRI O-RADS classification, letters to the editor, commentaries, narrative reviews, consensus documents, and studies where data were not available for constructing a 2 × 2 table. The pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated. The quality of the studies was evaluated using QUADAS-2. A total of 502 citations were identified. Ultimately, 11 studies comprising 4634 masses were included. The mean prevalence of ovarian malignancy was 32%. The risk of bias was high in eight studies for the “patient selection” domain. The risk of bias was low for the “index test” and “reference test” domains for all studies. Overall, the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and DOR of the O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%–98%), 77% (95% CI = 68%–84%), 4.2 (95% CI = 2.9–6.0), 0.04 (95% CI = 0.03–0.07), and 96 (95% CI = 50–185), respectively. Heterogeneity was moderate for sensitivity and high for specificity. In conclusion, the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses.

New Analytical Approach for the Alignment of Different HE4 Automated Immunometric Systems: An Italian Multicentric Study

Human epididymal secretory protein 4 (HE4) elevation has been studied as a crucial biomarker for malignant gynecological cancer, such us ovarian cancer (OC). However, there are conflicting reports regarding the optimal HE4 cut-off. Thus, the goal of this study was to develop an analytical approach to harmonize HE4 values obtained with different laboratory resources. To this regard, six highly qualified Italian laboratories, using different analytical platforms (Abbott Alinity I, Fujirebio Lumipulse G1200 and G600, Roche Cobas 601 and Abbott Architett), have joined this project. In the first step of our study, a common reference calibration curve (designed through progressive HE4 dilutions) was tested by all members attending the workshop. This first evaluation underlined the presence of analytical bias in different devices. Next, following bias correction, we started to analyze biomarkers values collected in a common database (1509 patients). A two-sided p-value < 0.05 was considered statistically significant. In post-menopausal women stratified between those with malignant gynecological diseases vs. non-malignant gynecological diseases and healthy women, dichotomous HE4 showed a significantly better accuracy than dichotomous Ca125 (AUC 0.81 vs. 0.74, p = 0.001 for age ≤ 60; AUC 0.78 vs. 0.72, p = 0.024 for age > 60). Still, in post-menopausal status, similar results were confirmed in patients with malignant gynecological diseases vs. patients with benign gynecological diseases, both under and over 60 years (AUC 0.79 vs. 0.73, p = 0.006; AUC 0.76 vs. 0.71, p = 0.036, respectively). Interestingly, in pre-menopausal status women over 40 years, HE4 showed a higher accuracy than Ca125 (AUC 0.73 vs. 0.66, p = 0.027), thus opening new perspective for the clinical management of fertile patients with malignant neoplasms, such as ovarian cancer. In summary, this model hinted at a new approach for identifying the optimal cut-off to align data detected with different HE4 diagnostic tools.