External Validation of O-RADS US Risk Stratification and Management System

Ovarian-Adnexal Reporting and Data System Ultrasound v2022: From Origin to Everyday Use

This review of the American College of Radiology Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) v2022 will familiarize the reader with the updated O-RADS US system, highlight new updates, and outline key technical and reporting components. Additionally, this review will outline how to approach and incorporate the system into clinical practice, with reporting and real-world examples. Future directions will focus on addressing knowledge gaps and expanding on research opportunities.

Ultrasound-based ADNEX model for differentiating between benign, borderline, and malignant epithelial ovarian tumours

BACKGROUND

The purpose of this study was to evaluate the ability of the International Ovarian Tumor Analysis-Assessment of Different NEoplasias in the adneXa (IOTA-ADNEX) model to distinguish among benign, borderline, and malignant epithelial ovarian tumours (BeEOTs, BEOTs, and MEOTs, respectively).

METHODS

The study included 813 patients with BeEOTs, BEOTs, and MEOTs who underwent ultrasound examinations and pelvic operations. Comparisons were made between the clinical information and ultrasonographic features of the three patient groups, and the histopathological diagnosis was the gold standard. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of the ADNEX model were calculated.

RESULTS

This was a single-centre retrospective study. Of the 813 patients, 257 (31.6%) had BeEOTs, 114 (14.0%) had BEOTs, and 442 (54.4%) had MEOTs. For a cut-off value of 10% to identify the overall risk for ovarian cancer (OC), the sensitivity and specificity were 99.1% and 73.2%, respectively. According to the receiver operating characteristicscurves, the AUC was 0.987 (95% CI: 0.981-0.993) for BeEOTs compared with MEOTs, 0.820 (95% CI: 0.768-0.872) for BeEOTs compared with BEOTs, 0.912 (95% CI: 0.876-0.948) for BeEOTs compared with stage I OC, and 0.995 (95% CI: 0.992-0.998) for BeEOTs compared with stages II-IV OC. The AUC was 0.614 (95% CI: 0.519-0.709) for BEOTs compared with stage I OC, 0.903 (95% CI: 0.869-0.937) for BEOTs compared with stages II-IV OC, and 0.851 (95% CI: 0.800-0.902) for stage I OC compared with stages II-IV OC.

CONCLUSIONS

The IOTA-ADNEX model demonstrated good diagnostic performance for the three categories of EOTs and may have the potential to be popularised in assisting radiologists in the assessment of adnexal masses in the future.

Ovarian-Adnexal Imaging-Reporting and Data System (O-RADS) ultrasound version 2019: a prospective validation and comparison to updated version (v2022) in pathologically confirmed adnexal masses

OBJECTIVE

To evaluate the diagnostic accuracy and reliability of the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound v2019 in classifying adnexal masses (AMs) and compare the old and updated systems (v2022).

PATIENTS AND METHODS

This prospective study enrolled 977 consecutive women with suspected AMs from three institutions between January 2022 and December 2023. Ultrasound examinations were performed by three experienced radiologists who categorized AMs according to O-RADS ultrasound v2019. The same radiologists retrospectively reviewed the stored ultrasound images and provided the O-RADS ultrasound v2022 classification. Histopathology was used as the reference standard to calculate the diagnostic accuracy of the O-RADS versions in predicting malignant AMs. Inter-observer agreement (IOA) of the O-RADS scoring results was evaluated using the Fleiss kappa (κ) test.

RESULTS

The final analysis included 803 women with 855 AMs (219 (25.6%) malignant and 636 (74.4%) benign). Both O-RADS versions demonstrated good diagnostic accuracy, with area under the curve (AUC) values ranging from 0.906 to 0.923 (v2019) and 0.919 to 0.936 (v2022). The updated v2022 showed a slightly higher accuracy (82.5-86.7% vs. 80.7-85.3%), sensitivity (93.6-95.0% vs. 92.2-94.1%), and specificity (78.1-84.1% vs. 76.1-82.9%) compared to v2019. The IOA for the overall O-RADS classification was perfect for both versions (κ = 0.96-0.97).

CONCLUSIONS

The O-RADS ultrasound classification system demonstrated good diagnostic accuracy and reliability in predicting malignant AMs, with the updated v2022 showing modest improvements.

KEY POINTS

Question Accurate classification of adnexal masses is essential for management. Can updated O-RADS ultrasound v2022 improve diagnostic accuracy and reliability compared to v2019 in predicting malignancies? Findings O-RADS ultrasound v2022 demonstrated slightly higher diagnostic accuracy for identifying malignant adnexal masses compared to v2019, reflecting modest improvements in risk stratification and clinical decision-making. Clinical relevance The updated O-RADS ultrasound v2022 provides improved risk stratification for adnexal masses, enhancing diagnostic confidence, supporting more precise clinical decision-making, and improving patient outcomes through timely intervention or tailored management strategies in ovarian cancer care.

The predictive value of nomogram for adnexal cystic-solid masses based on O-RADS US, clinical and laboratory indicators

BACKGROUND

Ovarian cancer remains a leading cause of death among women, largely due to its asymptomatic early stages and high mortality when diagnosed late. Early detection significantly improves survival rates, and the Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) is currently the most commonly used method, but has limitations in specificity and accuracy. While O-RADS US has standardized reporting, its sensitivity can lead to the misdiagnosis of benign masses as malignant, resulting in overtreatment. This study aimed to construct a nomogram model based on the O-RADS US and clinical and laboratory indicators to predict the malignancy risk of adnexal cystic-solid masses.

METHODS

This retrospective study collected data from patients with adnexal cystic-solid masses who underwent ultrasonography and were pathologically confirmed between January 2021 and December 2023 at the First Affiliated Hospital of Shenzhen University. They were categorized into benign and malignant groups according to pathological findings. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select the most relevant predictors of ovarian cancer. A nomogram model was constructed, and its diagnostic performance was calculated. We bootstrapped the data 500 times to perform internal verification, drew a calibration curve to verify the prediction ability, and performed a decision curve analysis to assess clinical usefulness.

RESULTS

A total of 399 patients with adnexal cystic-solid masses were included in this study: 327 in the benign group and 72 in the malignant group. Five predictors associated with the risk of malignancy of adnexal cystic-solid masses were selected using LASSO regression: O-RADS, acoustic shadowing, postmenopausal status, CA125, and HE4. The area under the curve, sensitivity, specificity, accuracy, positive and negative predictive values of the nomogram were 0.909, 83.3%, 82.9%, 83.0%, 51.7%, and 95.8%, respectively. The calibration curve of the nomogram showed good consistency between the predicted and actual probabilities, and the decision curve showed good clinical usefulness.

CONCLUSION

The nomogram model based on O-RADS US and clinical and laboratory indicators can be used to predict the risk of malignancy in adnexal cystic-solid masses, with high predictive performance, good calibration, and clinical usefulness.

Accuracy of O-RADS System in Differentiating Between Benign and Malignant Adnexal Masses Assessed via External Validation by Inexperienced Gynecologists

Objective: To evaluate the accuracy of the O-RADS system in differentiating between benign and malignant adnexal masses, as assessed by inexperienced gynecologists. Methods: Ten gynecologic residents attended a 20 h training course on the O-RADS system conducted by experienced examiners. Following the training, the residents performed ultrasound examinations on patients admitted with adnexal masses under supervision, recording the data in a database that included videos and still images. The senior author later accessed this ultrasound database and presented the cases offline to ten residents for O-RADS rating, with the raters being blinded to the final diagnosis. The efficacy of the O-RADS system by the residents and inter-observer variability were assessed. Results: A total of 201 adnexal masses meeting the inclusion criteria were evaluated, consisting of 136 (67.7%) benign masses and 65 (32.3%) malignant masses. The diagnostic performance of the O-RADS system showed a sensitivity of 90.8% (95% CI: 82.2-96.2%) and a specificity of 86.8% (95% CI: 80.4-91.8%). Inter-observer variability in scoring was analyzed using multi-rater Fleiss Kappa analysis, yielding Kappa indices of 0.642 (95% CI: 0.641-0.643). The false positive rate was primarily due to the misclassification of solid components in classic benign masses as O-RADS-4 or O-RADS-5. Conclusions: The O-RADS system demonstrates high diagnostic performance in distinguishing benign from malignant adnexal masses, even when used by inexperienced examiners. However, the false positive rate remains relatively high, mainly due to the over-interpretation of solid-appearing components in classic benign lesions. Despite this, inter-observer variability among non-expert raters was substantial. Incorporating O-RADS system training into residency programs is beneficial for inexperienced practitioners. This study could be an educational model for gynecologic residency training for other systems of sonographic features.

Diagnostic accuracy of ultrasound classifications - O-RADS US v2022, O-RADS US v2020, and IOTA SR - in distinguishing benign and malignant adnexal masses: Enhanced by combining O-RADS US v2022 with tumor marker HE4

PURPOSE

To assess the diagnostic accuracy of O-RADS Ultrasound (O-RADS US) v2022, O-RADS US v2020, and IOTA SR, and to evaluate whether combining imaging findings with tumor markers enhances the diagnosis of adnexal masses.

METHODS

This retrospective study, conducted between January 2018 and December 2023, included consecutive women with adnexal masses scheduled for surgery. Histopathologic results served as the reference standard. Risk factors for malignancy were identified using univariate and multivariate logistic regression analyses. ROC analysis was employed to assess diagnostic test performances, while Kappa statistics evaluated inter-reviewer agreement.

RESULTS

A total of 613 women (mean age, 49.39 ± 12.81 years; range, 16-87 years) with pelvic masses were included. O-RADS US v2022 exhibited comparable performance to O-RADS US v2020, with areas under the curve (AUC) values of 0.940 and 0.937, respectively (p = 0.02, exceeding the adjusted significance level of 0.0167). Both O-RADS models outperformed the IOTA SR, which had an AUC of 0.862 (p < 0.0001 for both comparisons). Multivariate analysis revealed that O-RADS US v2022 [OR 9.148, 95 %CI (4.912-17.039), p < 0.001] and HE4 [OR 1.023, 95 %CI (1.010-1.036), p = 0.001] were significant factors associated with malignant lesions. Furthermore, the combination of O-RADS US v2022 and HE4 demonstrated an AUC of 0.98, significantly outperforming either O-RADS US v2022 alone (AUC = 0.94) or HE4 alone (AUC = 0.92). The Kappa values for O-RADS US v2022, O-RADS US v2020 and IOTA SR were 0.933, 0.891 and 0.923, respectively, indicating substantial inter-reader agreement.

CONCLUSIONS

The O-RADS US v2022 demonstrates comparable performance in predicting ovarian malignant lesions when compared to O-RADS US v2020, while surpassing the performance of IOTA SR. Additionally, the combination of O-RADS US v2022 and HE4 provides improved diagnostic effectiveness over using either O-RADS US v2022 or HE4 alone.

GI-RADS versus O-RADS in the differential diagnosis of adnexal masses: a systematic review and head-to-head meta-analysis

PURPOSE

The aim of this study was to compare the diagnostic performance of the Gynecology Imaging Reporting and Data System (GI-RADS) and Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) classification systems and assess their capacity to stratify the risk of malignancy in adnexal masses (AMs).

METHODS

A comprehensive search of MEDLINE (PubMed), Scopus, Web of Science, and Google Scholar was conducted to identify articles published between January 2020 and August 2023. The quality of the studies, the risk of bias, and concerns regarding applicability were assessed using QUADAS-2.

RESULTS

The search yielded 132 citations. Five articles, which included a total of 2,448 AMs, were ultimately selected for inclusion. The risk of bias was high in all articles regarding patient selection, low in four studies for the index test, and unclear in three papers for the reference test. For GI-RADS, the pooled sensitivity and specificity were 90.8% (95% confidence interval [CI], 86.0% to 94.0%) and 91.5% (95% CI, 89.0% to 93.0%), respectively. For O-RADS, the pooled sensitivity and specificity were 95.1% (95% CI, 93.0% to 97.0%) and 88.8% (95% CI, 85.0% to 92.0%), respectively. O-RADS demonstrated greater sensitivity for malignancy than GI-RADS (P<0.05). Heterogeneity was moderate for both sensitivity and specificity with respect to GIRADS; for O-RADS, heterogeneity was moderate for sensitivity and high for specificity.

CONCLUSION

Both GI-RADS and O-RADS US demonstrate good diagnostic performance in the preoperative assessment of AMs. However, the O-RADS classification provides superior sensitivity.

Canadian radiology: 2024 update

Radiology in Canada is advancing through innovations in clinical practices and research methodologies. Recent developments focus on refining evidence-based practice guidelines, exploring innovative imaging techniques and enhancing diagnostic processes through artificial intelligence. Within the global radiology community, Canadian institutions play an important role by engaging in international collaborations, such as with the American College of Radiology to refine implementation of the Ovarian-Adnexal Reporting and Data System for ultrasound and magnetic resonance imaging. Additionally, researchers have participated in multidisciplinary collaborations to evaluate the performance of artificial intelligence-driven diagnostic tools for chronic liver disease and pediatric brain tumors. Beyond clinical radiology, efforts extend to addressing gender disparities in the field, improving educational practices, and enhancing the environmental sustainability of radiology departments. These advancements highlight Canada's role in the global radiology community, showcasing a commitment to improving patient outcomes and advancing the field through research and innovation. This update underscores the importance of continued collaboration and innovation to address emerging challenges and further enhance the quality and efficacy of radiology practices worldwide.

The Ovarian-Adnexal Reporting and Data System (O-RADS) US Score Effect on Surgical Resection Rate

Background The Ovarian-Adnexal Imaging Reporting and Data System (O-RADS) US risk score can be used to accurately stratify ovarian lesions based on morphologic characteristics. However, there are no large multicenter studies assessing the potential impact of using O-RADS US version 2022 risk score in patients referred for surgery for an ovarian or adnexal lesion. Purpose To retrospectively determine the proportion of patients with ovarian or adnexal lesions without acute symptoms who may have been managed conservatively by using the O-RADS US version 2022 risk score. Materials and Methods This multicenter retrospective study included patients with ovarian cystic lesions and nonacute symptoms who underwent surgical resection after US before the introduction of O-RADS US between January 2011 and December 2014. Investigators blinded to the final diagnoses recorded lesion imaging features and O-RADS US risk scores. The frequency of malignancy and the diagnostic performance of the risk score were calculated. The Mann-Whitney test and Fisher exact test were performed, with P < .05 indicating a statistically significant difference. Results A total of 377 patients with surgically resected lesions were included. Among the resected lesions, 42% (157 of 377) were assigned an O-RADS US risk score of 2. Of the O-RADS US 2 lesions, 54% (86 of 157) were nonneoplastic, 45% (70 of 157) were dermoids or other benign tumors, and less than 1% (one of 157) were malignant. Using O-RADS US 4 as the optimal threshold for malignancy prediction yielded a 94% (68 of 72) sensitivity, 64% (195 of 305) specificity, 38% (68 of 178) positive predictive value, and 98% (195 of 199) negative predictive value. Conclusion In patients without acute symptoms who underwent surgery for ovarian and adnexal lesions before the O-RADS US risk score was published, nearly half (42%) of surgically resected lesions retrospectively met the O-RADS US 2 version 2022 criteria. In these patients, imaging follow-up or conservative management could have been offered. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Fournier in this issue.

Diagnostic performance of ultrasound reporting systems in evaluation of adnexal masses: A prospective observational study

OBJECTIVE(S)

To evaluate and compare diagnostic performance of ultrasound-based reporting systems IOTA SR, ADNEX, GIRADS, ORADS for discrimination between benign and malignant adnexal masses.

STUDY DESIGN

A prospective observational study in a tertiary care hospital's Obstetrics and Gynaecology department evaluated pre-operative ultrasound imaging for adnexal masses in 80 cases, comparing various reporting systems' sensitivity and specificity against histopathology as gold standard using STATA version 17.0 for data analysis.

RESULTS

Among the 80 masses, 55 % (44/80) were confirmed as benign on histopathology, while 45 % were identified as malignant. The sensitivity and specificity of SR was 100 % (95 %CI: 90.0-100) and 97.1 % (95 %CI: 84.7-99.9) respectively. Eleven masses (13.8 %) were inconclusive, reducing specificity to 75 % (95 %CI:59.7-86.8).In ADNEX optimal cut-off for risk of malignancy was 34.1 % with sensitivity of 86.1 % (95 % CI: 70.5-95.3) and specificity of 90.9 % (95 % CI: 78.3-97.5). Considering GIRADS 4-5 and risk threshold of ≥10 % (ORADS 4-5) as predictors of malignancy sensitivity was 100 % (95 %CI: 90.3-100) and specificity was 70.5 % (95 %CI: 54.8-83.2) for GIRADS and ORADS. All reporting systems were comparable (p = 0.7). ADNEX identified 72.7 % (8/11) of inconclusive cases, outperforming GIRADS/ORADS which correctly classified 27.2 % (3/11) cases. When applied to misclassified GIRADS/ORADS 4-5 category, ADNEX demonstrated superior performance by correctly classifying 76.9 % (10/13) masses, while SR achieved correct classification in only 38.5 % (5/13) masses.

CONCLUSION(S)

All classification systems showed comparable accuracy in malignancy risk identification on imaging. GIRADS/ORADS tended to overestimate malignancy risk. The present study recommends a two-step strategy, leveraging higher specificity of ADNEX model for improved stratification of adnexal masses.

Diagnostic performances of the Ovarian Adnexal Reporting and Data System, the Risk of Ovarian Malignancy Algorithm, and the Copenhagen Index in the preoperative prediction of ovarian cancer: a prospective cohort study

OBJECTIVE

This study aimed to assess the diagnostic performance of the Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH-I), and Ovarian Adnexal Reporting and Data System (O-RADS) for the preoperative prediction of ovarian cancer (OC).

METHODS

A prospective cohort study was conducted on 462 patients diagnosed with ovarian tumors admitted to the Departments of Obstetrics and Gynecology, Hue University of Medicine and Pharmacy Hospital, and Hue Central Hospital from May 2020 to December 2022. ROMA and CPH-I were calculated using cancer antigen 125 (CA125), human epididymal protein 4 (HE4) levels, and patient characteristics (age and menopausal status). O-RADS criteria were applied to describe ovarian tumor characteristics from ultrasound findings. Compared with histopathological results, the predictive values of ROMA, CPH-I, and O-RADS alone or in combination with CA125/HE4 for OC were calculated.

RESULTS

Among 462 patients, 381 had benign tumors, 11 had borderline tumors, and 50 had OC. At optimal cut-off points, ROMA's and CPH-I's areas under the curves (AUCs) were 0.880 (95% confidence interval [CI]=0.846-0.909) and 0.890 (95% CI=0.857-0.918), respectively, and ROMA and CPH-I sensitivities/specificities (Se/Sp) were 68.85%/95.01% and 77.05%/91.08%, respectively. O-RADS ≥3 yielded an AUCs of 0.949 (95% CI=0.924-0.968), with Se/Sp of 88.52%/88.98% (p<0.001). Combining O-RADS with CA125 demonstrated the highest predictive value, with AUCs of 0.969 (95% CI=0.949-0.983) and Se/Sp of 98.36%/86.09% (p<0.001).

CONCLUSION

The ROMA, CPH-I, O-RADS, O-RADS + CA125, and O-RADS + HE4 models demonstrated good predictive values for OC; the combination of O-RADS and CA125 yielded the highest values.

Differentiating Benign From Malignant Ovarian Masses With Solid Components: Diagnostic Performance of CEUS Combined With IOTA Simple Rules and O-RADS

OBJECTIVE

This study aimed to apply the International Ovarian Tumor Analysis (IOTA) Simple Rules (SR), the Ovarian-Adnexal Reporting and Data System (O-RADS) and contrast-enhanced ultrasound (CEUS) in an identical cohort of Chinese patients and to analyze their performance in discrimination of ovarian masses with solid components.

METHODS

This was a two-center retrospective study that included a total of 94 ovarian lesions in 86 women enrolled from January 2018 to February 2023. The lesions were classified by using the IOTA terminology and CEUS was performed for the lesions exhibiting solid components on ultrasonography, IOTA SR and O-RADS were applied, and CEUS images were analyzed retrospectively. We assessed the time to wash-in, time to peak intensity (PI), PI compared to myometrium, and time to wash-out, and observed statistically significant differences between benign and malignant lesions in the first three parameters. CEUS characteristics were employed to determine CEUS scores for benign (score 0) and malignant (score 3) lesions. Subsequently, the lesions were reassessed based on the IOTA SR and O-RADS classifications and CEUS scores. The sensitivity, specificity, and area under the receiver-operating-characteristics curve (AUC) of the different models were also determined.

RESULTS

Among the 94 ovarian lesions, 46 (48.9%) were benign and 48 (51.1%) were malignant. It was found that in the 60 lesions to which the SR could be applied, the sensitivity, specificity, and AUC was 0.900, 0.667, and 0.783, respectively. The sensitivity, specificity, and AUC of O-RADS was observed to be 1.000, 0.283 and 0.641, respectively. When SR and O-RADS were combined with CEUS, their sensitivity, specificity, and AUC values were increased to 0.917, 0.891, 0.904, and 0.958, 0.783, 0.871, respectively.

CONCLUSION

IOTA SR and O-RADS exhibited relatively low specificity in differentiating malignant from benign ovarian lesions with the solid components, and their diagnostic performance can be significantly improved when combined with CEUS.

A modified CEUS risk stratification model for adnexal masses with solid components: prospective multicenter study and risk adjustment

OBJECTIVES

To evaluate the additional advantages of integrating contrast-enhanced ultrasound (CEUS) into the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) for the characterization of adnexal lesions with solid components.

MATERIALS AND METHODS

This prospective multicenter study recruited women suspected of having adnexal lesions with solid components between September 2021 and December 2022. All patients scheduled for surgery underwent preoperative CEUS and US examinations. The lesions were categorized according to the O-RADS US system, and quantitative CEUS indexes were recorded. Pathological results served as the reference standard. Univariable and multivariable analyses were performed to identify risk factors for malignancy in adnexal lesions with solid components. Receiver operating characteristic (ROC) curve analysis was employed to assess diagnostic performance.

RESULTS

A total of 180 lesions in 175 women were included in the study. Among these masses, 80 were malignant and 100 were benign. Multivariable analysis revealed that serum CA-125, the presence of acoustic shadowing, and peak intensity (PI) ratio (PImass/PIuterus) of solid components on CEUS were independently associated with adnexal malignancy. The modified CEUS risk stratification model demonstrated superior diagnostic value in assessing adnexal lesions with solid components compared to O-RADS US (AUC: 0.91 vs 0.78, p < 0.001) and exhibited comparable performance to the Assessment of Different NEoplasias in the adnexa (ADNEX) model (AUC 0.91 vs 0.86, p = 0.07).

CONCLUSION

Our findings underscore the potential value of CEUS as an adjunctive tool for enhancing the precision of diagnostic evaluations of O-RADS US.

CLINICAL RELEVANCE STATEMENT

The promising performance of the modified CEUS risk stratification model suggests its potential to mitigate unnecessary surgeries in the characterization of adnexal lesions with solid components.

KEY POINTS

• The additional value of CEUS to O-RADS US in distinguishing between benign and malignant adnexal lesions with solid components requires further evaluation. • The modified CEUS risk stratification model displayed superior diagnostic value and specificity in characterizing adnexal lesions with solid components when compared to O-RADS US. • The inclusion of CEUS demonstrated potential in reducing the need for unnecessary surgeries in the characterization of adnexal lesions with solid components.

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.

Developing a deep learning model for predicting ovarian cancer in Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) Category 4 lesions: A multicenter study

PURPOSE

To develop a deep learning (DL) model for differentiating between benign and malignant ovarian tumors of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) Category 4 lesions, and validate its diagnostic performance.

METHODS

A retrospective analysis of 1619 US images obtained from three centers from December 2014 to March 2023. DeepLabV3 and YOLOv8 were jointly used to segment, classify, and detect ovarian tumors. Precision and recall and area under the receiver operating characteristic curve (AUC) were employed to assess the model performance.

RESULTS

A total of 519 patients (including 269 benign and 250 malignant masses) were enrolled in the study. The number of women included in the training, validation, and test cohorts was 426, 46, and 47, respectively. The detection models exhibited an average precision of 98.68% (95% CI: 0.95-0.99) for benign masses and 96.23% (95% CI: 0.92-0.98) for malignant masses. Moreover, in the training set, the AUC was 0.96 (95% CI: 0.94-0.97), whereas in the validation set, the AUC was 0.93(95% CI: 0.89-0.94) and 0.95 (95% CI: 0.91-0.96) in the test set. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive values for the training set were 0.943,0.957,0.951,0.966, and 0.936, respectively, whereas those for the validation set were 0.905,0.935, 0.935,0.919, and 0.931, respectively. In addition, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the test set were 0.925, 0.955, 0.941, 0.956, and 0.927, respectively.

CONCLUSION

The constructed DL model exhibited high diagnostic performance in distinguishing benign and malignant ovarian tumors in O-RADS US category 4 lesions.

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.

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.

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.

O-RADS scoring system for adnexal lesions: Diagnostic performance on TVUS performed by an expert sonographer and MRI

RATIONALE AND OBJECTIVE

To determine the diagnostic performance of transvaginal ultrasound (TVUS) performed by an US specialist and MRI based on the O-RADS scoring system.

MATERIALS AND METHODS

Between March 5th 2013 and December 31st 2021, 227 patients, referred to our center, underwent TVUS and pelvic MRI for characterization of an adnexal lesion proven by surgery or two years of negative follow-up. All lesions were classified according to O-RADS US and O-RADS MRI risk scoring systems. Imaging data were then correlated with histopathological diagnosis or negative follow-up for 2 years.

RESULTS

The prevalence of malignancy was 11.1%. Sensitivity of O-RADS US / O-RADS MRI were respectively of 83.3%/83.3% and specificity was 73.2%/92.9% (p < 0.001). O-RADS MRI was more accurate than O-RADS US even when performed by an US specialist (p < 0.001). When MRI was used after US, 51 lesions were reclassified correctly by MRI and only 4 lesions incorrectly reclassified. Most of the lesions (49/51) rated O-RADS US 4 or 5 and reclassified correctly by MRI were benign, mainly including cystadenomas or cystadenofibromas. Only 4 lesions were misclassified by MRI but correctly classified by ultrasound.

CONCLUSION

Our study suggests that MR imaging has equally high sensitivity but higher specificity than TVUS for the characterization of adnexal lesions based on O-RADS scoring system. MRI should be the recommended second-line technique when a mass is discovered during TVUS and is rated O-RADS 4 and 5 over than TVUS by an US specialist.

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.

Contrast-enhanced US to Improve Diagnostic Performance of O-RADS US Risk Stratification System for Malignancy

Background The Ovarian-Adnexal Reporting and Data System (O-RADS) has limited specificity for malignancy. Contrast-enhanced US can help distinguish malignant from benign lesions, but its added value to O-RADS has not yet been assessed. Purpose To establish a diagnostic model combining O-RADS and contrast-enhanced US and to validate whether O-RADS plus contrast-enhanced US has a better diagnostic performance than O-RADS alone. Materials and Methods This prospective study included participants from May 2018 to March 2021 who underwent contrast-enhanced US before surgery and had lesions categorized as O-RADS 3, 4, or 5 by US, with a histopathologic reference standard. From April 2021 to July 2022, participants with pathologically confirmed ovarian-adnexal lesions were recruited for the validation group. In the pilot group, the initial enhancement time and enhancement intensity in comparison with the uterine myometrium, contrast agent distribution pattern, and dynamic changes in enhancement of lesions were assessed. Contrast-enhanced US features were used to calculate contrast-enhanced US scores for benign (score ≤2) and malignant (score ≥4) lesions. Lesions were then re-rated according to O-RADS category plus contrast-enhanced US scores. Receiver operating characteristic curves were constructed and compared using the DeLong method. The combined system was validated in an independent group. Results The pilot group included 76 women (mean age, 44 years ± 13 [SD]), and the validation group included 46 women (mean age, 42 years ± 14). Differences in initial enhancement time (P < .001), enhancement intensity (P < .001), and dynamic changes in enhancement (P < .001) between benign and malignant lesions were observed in the pilot group. Contrast-enhanced US scores were calculated using these features. The O-RADS risk stratification was upgraded one level for contrast-enhanced US scores of 4 or more and downgraded one level for contrast-enhanced US scores of 2 or less. In the validation group, the diagnostic performance of O-RADS plus contrast-enhanced US score was higher (area under the receiver operating characteristic curve [AUC] = 0.93) than O-RADS (AUC = 0.71, P < .001). Conclusion Contrast-enhanced US improved the diagnostic performance for malignancy of the O-RADS categories 3-5. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grant in this issue.

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.

Adnexal Mass Imaging: Contemporary Guidelines for Clinical Practice

Several recent guidelines have been published to improve accuracy and consistency of adnexal mass imaging interpretation and to guide management. Guidance from the American College of Radiology (ACR) Appropriateness Criteria establishes preferred adnexal imaging modalities and follow-up. Moreover, the ACR Ovarian-Adnexal Reporting Data System establishes a comprehensive, unified set of evidence-based guidelines for classification of adnexal masses by both ultrasound and MR imaging, communicating risk of malignancy to further guide management.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Diagnostic performance of IOTA SR and O-RADS combined with CA125, HE4, and risk of malignancy algorithm to distinguish benign and malignant adnexal masses

PURPOSE

To compare the diagnostic performance of International Ovarian Tumour Analysis Simple Rules (IOTA SR) and Ovarian-Adnexal Reporting and Data System (O-RADS), and to analyse whether combining IOTA SR and O-RADS with the biomarkers cancer antigen 125 (CA125), human epididymis protein 4 (HE4), and risk of malignancy algorithm (ROMA) further improves diagnostic performance in women with different menopause status.

METHODS

This study retrospectively included patients with ovarian adnexal masses confirmed by surgical pathology between September 2021 and February 2022. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the diagnostic efficacy of IOTA SR, O-RADS, and their combination with CA125, HE4, and ROMA.

RESULTS

This study included 1,179 ovarian adnexal masses. In all women, the AUC of IOTA SR was comparable to O-RADS (0.879 vs. 0.889, P = 0.361), and O-RADS had a significantly higher sensitivity than IOTA SR (95.77 % vs. 87.32 %, P < 0.001). In premenopausal women, O-RADS had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 93.33 %, 84.74 %, and 85.59 %, respectively. In postmenopausal women, IOTA SR + ROMA had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 85.37 %, 93.88 %, and 90.00 %, respectively.

CONCLUSIONS

Our study supports the high diagnostic value of IOTA SR or O-RADS alone in all women, and O-RADS was more sensitive than IOTA SR. In premenopausal women, O-RADS had the highest diagnostic value. In postmenopausal women, IOTA SR outperformed O-RADS, and IOTA SR + ROMA had the highest diagnostic value.

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.

The Ovarian/Adnexal Reporting and Data System for Ultrasound: From Standardized Terminology to Optimal Risk Assessment and Management

The American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon and risk assessment tool for ultrasound (US) provides a framework for characterization of ovarian and adnexal pathology with the ultimate goal of harmonizing reporting and patient management strategies. Since the first O-RADS US publication in 2018, multiple validation studies have shown O-RADS US to have excellent diagnostic accuracy, with the majority of these studies using O-RADS 4 as the optimal cut-off for detecting ovarian cancer. Most of the existing validation studies include a dedicated training phase and confirm that ORADS US categories and lexicon descriptors are associated with high level inter-read agreement, regardless of radiologist training level or practice experience. O-RADS US has a similar inter-reader agreement when compared to Gynecologic Imaging Reporting and Data System (GIRADS), Assessment of Different Neoplasias in the adnexa (ADNEX), and International Tumor Analysis Group (IOTA) simple rules. System descriptors have been shown to correlate with expected malignancy rates and the O-RADS US risk stratification system has been shown to perform in the expected range of malignancy risk per category. Further directions will focus on clarifying governing concepts and lexicon terminology as well as further refining risk stratification categories based on data from published validation studies.

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%.

O-RADS MRI After Initial Ultrasound for Adnexal Lesions: AJR Expert Panel Narrative Review

The Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) and MRI risk stratification systems were developed by an international group of experts in adnexal imaging to aid radiologists in assessing adnexal lesions. The goal of imaging is to appropriately triage patients with adnexal lesions. US is the first-line imaging modality for assessment, whereas MRI can be used as a problem-solving tool. Both US and MRI can accurately characterize benign lesions such as simple cysts, endometriomas, hemorrhagic cysts, and dermoid cysts, avoiding unnecessary or inappropriate surgery. In patients with a lesion that does not meet criteria for one of these benign diagnoses, MRI can further characterize the lesion with an improved specificity for cancer and the ability to provide a probable histologic subtype in the presence of certain MRI features. This allows personalized treatment, including avoiding overly extensive surgery or allowing fertility-sparing procedures for suspected benign, borderline, or low-grade tumors. When MRI findings indicate a risk of an invasive cancer, patients can be expeditiously referred to a gynecologic oncologic surgeon. This narrative review provides expert opinion on the utility of multiparametric MRI when using the O-RADS US and MRI management systems.

O-RADS Ultrasound Version 1: A Scenario-Based Review of Implementation Challenges

The Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) risk stratification and management system was first published by the American College of Radiology in 2020. It provides standardized terminology for evaluation of ovarian and adnexal masses, aids risk stratification, and provides management guidelines for different categories of lesions. This system has been validated by subsequent research and found to be a useful diagnostic and management tool. However, as noted in the system's governing concepts, in some clinical scenarios, such as patients with acute symptoms or with a history of ovarian malignancy, O-RADS US does not apply, or the system's standard management may be adjusted. Additional scenarios, such as an adnexal mass in pregnancy, present challenges in the application of O-RADS US to assist diagnosis and management. The purpose of this article is to highlight 10 clinical scenarios in which O-RADS US version 1 may not apply, may be difficult to apply, or may require modified management. Additional scenarios in which O-RADS US can be appropriately applied are also described.

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.