Ovarian-adnexal reporting and data system ultrasound evaluation and pathological characteristics of ovarian collision tumor.

BACKGROUND: Collision tumor are neoplasms, including two histologically distinct tumors that coexist in the same mass without histological admixture. The incidence of collision tumor is low and is rare clinically. AIM: To investigate ultrasound images and application of ovarian-adnexal reporting and data system (O-RADS) to evaluate the risk and pathological characteristics of ovarian collision tumor. METHODS: This study retrospectively analyzed 17 cases of ovarian collision tumor diagnosed pathologically from January 2020 to December 2023. All clinical features, ultrasound images and histopathological features were collected and analyzed. The O-RADS score was used for classification. The O-RADS score was determined by two senior doctors in the gynecological ultrasound group. Lesions with O-RADS score of 1-3 were classified as benign tumors, and lesions with O-RADS score of 4 or 5 were classified as malignant tumors. RESULTS: There were 17 collision tumors detected in 16 of 6274 patients who underwent gynecological surgery. The average age of 17 women with ovarian collision tumor was 36.7 years (range 20-68 years), in whom, one occurred bilaterally and the rest occurred unilaterally. The average tumor diameter was 10 cm, of which three were 2-5 cm, 11 were 5-10 cm, and three were > 10 cm. Five (29.4%) tumors with O-RADS score 3 were endometriotic cysts with fibroma/serous cystadenoma, and unilocular or multilocular cysts contained a small number of parenchymal components. Eleven (64.7%) tumors had an O-RADS score of 4, including two in category 4A, six in category 4B, and three in category 4C; all of which were multilocular cystic tumors with solid components or multiple papillary components. One (5.9%) tumor had an O-RADS score of 5. This case was a solid mass, and a small amount of pelvic effusion was detected under ultrasound. The pathology was high-grade serous cystic cancer combined with cystic mature teratoma. There were nine (52.9%) tumors with elevated serum carbohydrate antigen (CA)125 and two (11.8%) with elevated serum CA19-9. Histological and pathological results showed that epithelial-cell-derived tumors combined with other tumors were the most common, which was different from previous results. CONCLUSION: The ultrasound images of ovarian collision tumor have certain specificity, but diagnosis by preoperative ultrasound is difficult. The combination of epithelial and mesenchymal cell tumors is one of the most common types of ovarian collision tumor. The O-RADS score of ovarian collision tumor is mostly ≥ 4, which can sensitively detect malignant tumors.

Diagnostic performance of a modified O-RADS classification system for adnexal lesions incorporating clinical features.

PURPOSE: To compare the diagnostic efficacy of the Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score with that of the modified O-RADS score on the basis of a simplified contrast-enhanced (CE) MRI protocol in characterizing adnexal masses with solid tissue. The added value of clinical features was evaluated to improve the ability of the scoring system to classify adnexal masses. METHODS: A total of 124 patients with 124 adnexal lesions containing solid tissue were included in this two-center retrospective study. Among them, there were 40 benign lesions (40/124, 32.3%) and 84 were malignant lesions (84/124, 67.7%). Three radiologists independently reviewed the images and assigned the O-RADS MRI score and the modified O-RADS score for each adnexal mass. Histopathology was used as the reference standard. The diagnostic efficacy of the two scoring methods was compared. Univariate and multivariate logistic regression were performed to evaluate the value of significant features in the prediction of malignant tumors. RESULTS: The O-RADS MRI score and modified O-RADS score showed sensitivity at 100.0% (95% CI, 95.7-100.0%) and 71.4% (95% CI, 60.5-80.8%), specificity at 12.5% (95% CI, 4.2-26.8%) and 75.0% (95% CI, 58.8-87.3%), respectively. The area under the curve of the modified O-RADS score was higher than the O-RADS score (0.732 [95% CI, 0.645-0.808] vs 0.575 [95% CI, 0.483-0.663]; p < 0.001). Multivariate analysis showed that the modified O-RADS score 4b or 5 combined with patient age > 38.5 years, nullipara, maximum diameter > 40.5 mm and HE4 > 78.9 pmol/L significantly improved the diagnostic efficacy up to 0.954 (95% CI, 0.901-0.984) (p < 0.001). CONCLUSION: A modified O-RADS score combined with certain clinical features can significantly improve the diagnostic efficacy in predicting malignant tumors.

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.

Diagnostic performance of the O-RADS MRI system for magnetic resonance imaging in discriminating benign and malignant adnexal lesions: a systematic review, meta-analysis, and meta-regression.

PURPOSE: After the introduction of the Ovarian-Adnexal Reporting and Data System (O-RADS) for magnetic resonance imaging (MRI), several studies with diverse characteristics have been published to assess its diagnostic performance. This systematic review and meta-analysis aimed to assess the diagnostic performance of O-RADS MRI scoring for adnexal masses, accounting for the risk of selection bias. METHODS: The PubMed, Scopus, Web of Science, and Cochrane databases were searched for eligible studies. Borderline or malignant lesions were considered malignant. All O-RADS MRI scores ≥4 were considered positive. The quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity, specificity, and likelihood ratio (LR) values were calculated, considering the risk of selection bias. RESULTS: Fifteen eligible studies were found, and five of them had a high risk of selection bias. Between-study heterogeneity was low-to-moderate for sensitivity but substantial for specificity (I2 values were 35.5% and 64.7%, respectively). The pooled sensitivity was significantly lower in the studies with a low risk of bias compared with those with a high risk of bias (93.0% and 97.5%, respectively; P = 0.043), whereas the pooled specificity was not different (90.4% for the overall population). The negative and positive LRs were 0.08 [95% confidence interval (CI) 0.05­0.11] and 10.0 (95% CI 7.7­12.9), respectively, for the studies with low risk of bias and 0.03 (95% CI 0.01­0.10) and 10.3 (95% CI 3.8­28.3), respectively, for those with high risk of bias. CONCLUSION: The overall diagnostic performance of the O-RADS system is very high, particularly for ruling out borderline/malignant lesions, but with a moderate ruling-in potential. Studies with a high risk of selection bias lead to an overestimation of sensitivity. CLINICAL SIGNIFICANCE: The O-RADS system demonstrates considerable diagnostic performance, particularly in ruling out borderline or malignant lesions, and should routinely be used in practice. The high between-study heterogeneity observed for specificity suggests the need for improvement in the consistent characterization of the benign lesions to reduce false positive rates.

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.

Evaluation of American College of Radiology Ovarian-Adnexal Reporting and Data System ultrasound to predict malignancy risk in adnexal lesions.

AIMS: To validate the diagnostic performance of Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound for preoperative adnexal lesions in an external center. The secondary aim was to evaluate the performance of a strategy test including O-RADS ultrasound evaluation and subjective assessment of higher malignant risk lesions. METHODS: One hundred thirty patients with 158 ovarian-adnexal lesions were enrolled in the study. Each lesion was assigned an O-RADS score after real-time ultrasound examination by one experienced radiologist. A second subjective assessment by an expert was performed for O-RADS 4 and O-RADS 5 lesions. The histopathological diagnosis was used as the reference standard. RESULTS: A total of 126 benign and 32 malignant adnexal masses were included in the study. The area under the receiver operating characteristic curve of O-RADS ultrasound was 0.950, with a cutoff value > O-RADS 3. The sensitivity, specificity, and negative and positive predictive values were 100% (95% confidence interval [CI], 0.867-1), 83.3% (95% CI, 0.754-0.892), 60.4% (95% CI, 0.460-0.732), and 100% (95% CI, 0.956-1), respectively. For the strategy test, the sensitivity, specificity, negative and positive predictive values were 100% (95% CI, 0.867-1), 92.1% (95% CI, 0.855-0.959), 76.2% (95% CI, 0.602-0.874), and 100% (95% CI, 0.960-1), respectively. In comparison with O-RADS ultrasound, the specificity and negative predictive value of the strategy test were slightly higher (p < 0.05). CONCLUSIONS: Good diagnostic performance of the O-RADS ultrasound in adnexal lesions can be achieved by experienced radiologists in clinical practice. A second subjective assessment of sonographic findings can be applied to O-RADS 4 and 5 lesions.

Comparative study of Ovarian-Adnexal Ultrasound Reporting and Data System and the ADNEX Model in the diagnostic performance of ovarian-adnexal lesions / 中华超声影像学杂志

Objective:To compare and validate the diagnostic performance of the Ovarian-Adnexal Reporting and Data System (O-RADS ) and the ADNEX model in the diagnosis of malignant ovarian-adnexal lesions.Methods:A total of 275 patients who underwent surgery for ovarian-adnexal lesions at Tianjin Medical University Cancer Institute and Hospital from December 2020 to December 2022 were retrospectively collected. The clinical, pathological aud ultrasound dates of the patients were collected.Statistical methods, including chi-square tests and ROC curve analysis, were employed to assess the diagnostic performance of O-RADS and the ADNEX model for ovarian-adnexal lesions.Results:Among the 275 patients included in this study, 127 (46.2%) had benign lesions, and 148 (53.8%) had malignant lesions.Based on the O-RADS classification, 46 cases (16.7%) were O-RADS 2, 50 cases (18.2%) were O-RADS 3, 66 cases (24.0%) were O-RADS 4, and 113 cases (41.1%) were O-RADS 5. The malignancy rates for O-RADS 2, O-RADS 3, O-RADS 4, and O-RADS 5 were 0%, 0.08%, 56.06%, and 94.7%, respectively. ROC curve analysis for malignant ovarian-adnexal lesions yielded an area under ROC curve of 0.93(95% CI=0.90-0.96) for O-RADS and 0.94(95% CI=0.91-0.97) for the ADNEX model. Using O-RADS ≥4 and ADNEX model ≥10% as cutoff values, there was no significant difference in sensitivity between the two methods( P=0.740), but O-RADS exhibited higher specificity compared to the ADNEX model (72.4% vs 56.7%, P=0.044). Conclusions:When O-RADS ≥4 and the ADNEX model ≥10% are used as cutoff values, both methods demonstrate excellent diagnostic performance for malignant ovarian-adnexal lesions, with O-RADS exhibiting higher specificity.

Can the Combination of Magnetic Resonance Imaging, Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio Predict the Mass Origin in Ovarian Masses?

Objective: Evaluate the effectiveness of magnetic resonance imaging (MRI), blood parameters, and tumor markers to determine the role of objective criteria in distinguishing malignant, borderline, and benign masses and to minimize unnecessary surgical interventions by reducing interpretation differences. Methods: The histopathological and clinical-laboratory results of the patients who underwent surgery for the initial diagnosis and whose ovarian masses were confirmed were retrospectively reviewed. Between groups, age, cancer antigen 125, mean platelet volume (MPV), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), the presence of ascites, the ovarian-adnexal reporting and data system MRI scores, mass characteristics, and lymphocyte count were compared. Results: The study comprised a total of 191 patients. These patients were categorized into three groups: Benign (n=113), borderline (n=26), and malignant (n=52). No noteworthy correlation was detected between the unilocular or multilocular nature of solid, cystic, or mixed masses and the rates of NLR, PLR, or MPV. However, a notable correlation was identified between NLR and the presence of acidity (p=0.003). In ovarian cancer patients, there was no significant difference in NLR and MPV between malignant epithelial and malignant sex cord-stromal types (p>0.05), whereas a significant difference emerged in the PLR ratio (p=0.013). Conclusion: In ovarian masses with malignant potential, laboratory parameters such as NLR and PLR can guide the diagnosis process. In the future, various studies such as the development of different tests, markers, and imaging methods, the use of blood tests such as NLR, PLR, and MPV in cancer diagnosis will be possible. The results of these studies may contribute to the development of new methods for the diagnosis of ovarian cancer and the improvement of treatment protocols.

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.

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

OBJECTIVE: The aim of this study was to determine whether incorporating qualitative parameters of contrast-enhanced ultrasound (CEUS) can increase the accuracy of adnexal lesion assessments with Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound category 4 or 5. METHODS: Retrospective analysis of patients with adnexal masses who underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations between January and August of 2020. The study investigators reviewed and analyzed the morphological features of each mass before categorizing the US images independently according to the O-RADS system published by the American College of Radiology. In the CEUS analysis, the initial time and intensity of enhancement involving the wall and/or septation of the mass were compared with the uterine myometrium. Internal components of each mass were observed for signs of enhancement. The sensitivity, specificity, and Youden's index were calculated as the contrast variables and O-RADS. RESULTS: Receiver operating characteristic curve analysis revealed that the best cutoff value was higher than O-RADS 4. When information on the extent of enhancement was applied to selectively upgrade O-RADS category 4 and selectively downgrade O-RADS category 5, the overall sensitivity increased to 90.2%, while the level of specificity (91.3%) remained the same. CONCLUSION: Incorporating additional information from CEUS with respect to the extent of enhancement helped to improve the sensitivity of O-RADS category 4 and 5 masses without loss of specificity.

Value of MRI Ovarian-Adnexal Reporting and Data System in Differentiating Benign and Malignant Ovarian-Adnexal Lesions / 中山大学学报(医学科学版)

ObjectiveTo explore the value of MRI ovarian-adnexal reporting and data system （O-RADS MRI） in differentiating benign and malignant ovarian-adnexal masses.MethodsTotally 146 patients （202 masses） with ovarian-adnexal lesions who underwent pelvic examination at 3.0 T MRI according to standardized scan protocol of O-RADS MRI and were pathologically confirmed in The First Affiliated Hospital of Sun Yat-sen University between January 2020 and February 2022 were retrospectively analyzed. Two radiologists classified the ovarian-adnexal masses as risk levels 1~5 according to O-RADS MRI and evaluated their consistency by Cohen’s kappa. Using pathological findings as the gold standard， the detection yield of malignant lesions with O-RADS MRI classification was analyzed. Sensitivity， specificity， accuracy， and the area under the receiver operating characteristic curve were calculated （cutoff for malignancy， score ≥ 4）.ResultsOf 202 masses， 62 （30.7%） were malignant， 140 （69.3%） were benign. The two radiologists presented good agreement in O-RADS MRI classification of ovarian adnexal masses （Kappa=0.932）. The malignancy rates of masses with scores of 1， 2， 3， 4 and 5 were 0%， 0%， 7.7%， 95%， 97.6%， respectively. Sensitivity， specificity， accuracy， and the area under the receiver operating characteristic curve were 96.8% （60/62）， 98.6% （138/140）， 98.0% （198/202）， 0.977.ConclusionsO-RADS MRI yields high diagnostic efficiency for benign and malignant ovarian adnexal masses and its widespread implementation will improve communication between radiologists and clinicians， and facilitate optimal patient management. Therefore， O-RADS MRI warrants widespread use in clinical setting.

Ovarian-Adnexal Reporting and Data System for Magnetic Resonance Imaging (O-RADS MRI): Genesis and Future Directions.

Imaging plays an important role in characterizing and risk-stratifying commonly encountered adnexal lesions. Recently, the American College of Radiology (ACR) released the Ovarian-Adnexal Reporting and Data System (O-RADS) for ultrasound and subsequently for magnetic resonance imaging (MRI). The goal of the recently developed ACR O-RADS MRI risk stratification system is to improve the quality of imaging reports as well as the reproducibility of evaluating adnexal lesions on MRI. This review focuses on exploring this new system and its future refinements.

Accuracy and reproducibility of the O-RADS MRI risk stratification system based on enhanced non-DCE MRI in the assessment of adnexal masses.

OBJECTIVE: Evaluation of the diagnostic performance and reproducibility of the Ovarian-Adnexal Reporting and Data System (O-RADS) Magnetic Resonance Imaging (MRI) risk stratification system based on enhanced non-dynamic contrast-enhanced (non-DCE) MRI in the diagnosis of adnexal masses. METHODS: Patients who underwent conventional pelvic enhanced non-DCE MRI examination within one month prior to surgery formed the study population. Two experienced radiologists independently evaluated the images and assigned a score according to the O-RADS MRI risk stratification system. One of the radiologists reviewed the images and reassigned the scores after three months. Intra- and inter-observer agreement was evaluated with the k coefficient value. The adnexal masses that attained scores between 1 and 3 were considered benign, while those with scores of 4 or 5 were considered malignant. Analyses were conducted to determine the sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic (ROC) curve, which were then used for evaluating the diagnostic efficacy of the developed system based on enhanced non-DCE MRI scan. The reference standard was histology. RESULTS: A total of 308 patients (mean age: 42.09 ± 12.42 years, age range: 20-84 years) were enrolled in the study. Among the 362 adnexal masses from the included patients, there were 320 benign masses and 42 malignant masses. In the case of three readers, there were no malignant tumors scored 1-2. The O-RADS MRI score ≥ 4 was associated with malignancy resulted in a good diagnostic efficacy with the areas under the curve (AUC) values of 0.918 (95 % CI, 0.864-0.972), 0.905 (95 % CI, 0.842-0.968), and 0.882 (95 % CI, 0.815-0.950), the sensitivity values of 90.5 % (95 % CI, 87.5-93.5 %), 85.7 % (95 % CI, 82.1-89.3 %), and 83.3 % (95 % CI, 79.5-87.2 %), and the specificity values of 93.1 % (95 % CI, 90.5-95.7 %), 95.3 % (95 % CI, 93.1-97.5 %), and 93.1 % (95 % CI, 90.5-95.7 %) obtained for the three readers, respectively. Excellent intra-observer agreement and inter-observer agreement were observed with the k values of 0.883 (95 % CI, 0.814-0.952) and 0.848 (95 % CI, 0.770-0.926), respectively. CONCLUSIONS: The O-RADS MRI risk stratification system based on enhanced non-DCE MRI scans exhibited high accuracy and reproducibility in the prediction of adnexal masses malignancy. Enhanced non-DCE MRI scan may offer an alternative diagnostic tool when DCE is not possible.

The consistency and application value of MRI-based ovarian-adnexal reporting and data system in the diagnosis of ovarian adnexal masses / 中华放射学杂志

Objective:To explore the consistency of MRI-based ovarian-adnexal report and data system (O-RADS) score and its diagnostic value for ovarian adnexal masses.Methods:The MRI data of 309 patients with ovarian adnexal masses confirmed by pathology were retrospectively collected from January 2017 to August 2021 in the Second Affiliated Hospital of Soochow University, including 327 lesions consisted of 250 benign lesions, 21 borderline lesions, and 56 malignant lesions confirmed by pathology. Borderline and malignant lesions were classified into the malignant group ( n=77) and benign lesions were classified as benign group ( n=250). Two radiologists scored all lesions according to the MRI-based O-RADS, and scored again after 6 months. The proportion of borderline/malignant lesions in each MRI-based O-RADS score was calculated. The weighted Kappa test was used to assess the intra-reader and inter-reader consistency of the image interpretation results. The receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic efficacy of MRI-based O-RADS classification for distinguishing benign and malignant ovarian adnexal masses. Results:The weighted Kappa value of the MRI-based O-RADS score between the two radiologists was 0.810 (95%CI 0.764-0.855), and the weighted Kappa values of the two radiologists′ scores at different times were 0.848 (95%CI 0.806-0.889) and 0.875 (95%CI 0.835-0.914), respectively. The borderline/malignant lesions accounted for 0/16, 0.8% (1/127), 10.1% (10/99), 76.0% (57/75), 9/10 and 0/17, 0 (0/122), 8.0% (8/100), 76.2% (48/63), and 84.0% (21/25) of the lesions in the two radiologists based on the MRI O-RADS score of 1, 2, 3, 4, and 5, respectively. When adopting O-RADS score>3 as a cut-off value, the area under the ROC curve of the two radiologists for distinguishing benign and malignant ovarian adnexal masses was 0.928 (95%CI 0.895-0.954) and 0.942 (95%CI 0.911-0.965), respectively. The sensitivity was 0.857 and 0.896, the specificity was 0.924 and 0.924, and the accuracy was 0.908 and 0.917 respectively.Conclusion:The MRI-based O-RADS yields high diagnostic efficiency in the evaluation of benign and malignant ovarian adnexal masses, and the intra-reader and inter-reader consistency of the image interpretation is strong.

Reliability of ultrasound ovarian-adnexal reporting and data system amongst less experienced readers before and after training.

BACKGROUND: The 2018 ovarian-adnexal reporting and data system (O-RADS) guidelines are aimed at providing a system for consistent reports and risk stratification for ovarian lesions found on ultrasound. It provides key characteristics and findings for lesions, a lexicon of descriptors to communicate findings, and risk characterization and associated follow-up recommendation guidelines. However, the O-RADS guidelines have not been validated in North American institutions or amongst less experienced readers. AIM: To evaluate the diagnostic accuracy and inter-reader reliability of ultrasound O-RADS risk stratification amongst less experienced readers in a North American institution with and without pre-test training. METHODS: A single-center retrospective study was performed using 100 ovarian/adnexal lesions of varying O-RADS scores. Of these cases, 50 were allotted to a training cohort and 50 to a testing cohort via a non-randomized group selection process in order to approximately equal distribution of O-RADS categories both within and between groups. Reference standard O-RADS scores were established through consensus of three fellowship-trained body imaging radiologists. Three PGY-4 residents were independently evaluated for diagnostic accuracy and inter-reader reliability with and without pre-test O-RADS training. Sensitivity, specificity, positive predictive value, negative predictive value (NPV), and area under the curve (AUC) were used to measure accuracy. Fleiss kappa and weighted quadratic (pairwise) kappa values were used to measure inter-reader reliability. Statistical significance was P < 0.05. RESULTS: Mean patient age was 40 ± 16 years with lesions ranging from 1.2 to 22.5 cm. Readers demonstrated excellent specificities (85%-100% pre-training and 91%-100% post-training) and NPVs (89%-100% pre-training and 91-100% post-training) across the O-RADS categories. Sensitivities were variable (55%-100% pre-training and 64%-100% post-training) with malignant O-RADS 4 and 5 Lesions pre-training and post-training AUC values of 0.87-0.95 and 0.94-098, respectively (P < 0.001). Nineteen of 22 (86%) misclassified cases in pre-training were related to mischaracterization of dermoid features or wall/septation morphology. Fifteen of 17 (88%) of post-training misclassified cases were related to one of these two errors. Fleiss kappa inter-reader reliability was 'good' and pairwise inter-reader reliability was 'very good' with pre-training and post-training assessment (k = 0.76 and 0.77; and k = 0.77-0.87 and 0.85-0.89, respectively). CONCLUSION: Less experienced readers in North America achieved excellent specificities and AUC values with very good pairwise inter-reader reliability. They may be subject to misclassification of potentially malignant lesions, and specific training around dermoid features and smooth vs irregular inner wall/septation morphology may improve sensitivity.

Contrast-enhanced ultrasound combined with Ovarian-Adnexal Reporting and Data System US risk stratification and management system for diagnosis of adnexal masses / 中华超声影像学杂志

Objective:To explore the value of contrast-enhanced ultrasound (CEUS) combined with Ovarian-Adnexal Reporting and Data System (O-RADS US) risk stratification and management system in differential diagnosis of ovarian-adnexal mass.Methods:Fifty-six patients with ovarian-adnexal mass who received transabdominal transvaginal ultrasound and CEUS in the Third People′s Hospital of Longgang District from September 2018 to January 2021 were enrolled. The images were classified by O-RADS US and diagnosed by CEUS by experienced and senior radiologist. On the basis of O-RADS US classification, the enhancement time, enhancement level and enhancement mode of CEUS were combined to upgrade or degrade the classification results of O-RADS US. The diagnostic accuracy was assessed using ROC curve analysis, the area under the ROC curve (AUC) was calculated. The reproducibility of O-RADS US was assessed by another senior radiologist.Results:The AUC of O-RADS US for diagnosing benign and malignant ovarian-adnexal masses was 0.844(0.722, 0.927), the AUC of CEUS was 0.833(0.710, 0.920), the AUC of O-RADS US combined with CEUS was 0.940(0.842, 0.986) (compared with O-RADS US, P=0.020; compared with CEUS, P=0.031). The intra-class correlation coefficient (ICC) was 0.897(0.824, 0.940) for O-RADS US. Conclusions:CEUS combined with O-RADS US classification can effectively improve the diagnostic efficiency for benign and malignant ovarian-adnexal masses.

Reproducibility study of Ovarian-Adnexal Reporting and Data System in describing adnexal masses / 中华超声影像学杂志

Objective:To investigate the intra- and inter-observer agreements of different experiencers using the Ovaria-adnexal Reporting and Data System (O-RADS) in the evaluation of adnexal masses.Methods:Totally 48 patients with adnexal masses (48 masses, mean size 9.5±4.7 cm, range 2.3-18.6 cm) found by ultrasound examination in the Third Affiliated Hospital of Sun Yat-sen University, from May 2019 to March 2020 were retrospectively analyzed. All the masses were confirmed by pathology or surgery. Four observers were divided into 2 senior doctors (Doctor 1 and Doctor 2) and 2 junior doctors (Doctor 3 and Doctor 4). Each observer independently evaluated adnexal masses twice using ultrasound O-RADS before and after systematic training, with an interval of 60 days. The intra-observer and inter-observer agreements were analyzed before and after training.Results:The inter-observer agreement between senior doctors were both excellent before and after systematic training (weight Kappa: 0.833 vs 0.802, percentage of agreement: 83.3% vs 81.3%). Whereas there was difference in the inter-observer agreement between non-experienced observers before and after training (weight Kappa: 0.399 vs 0.824, percentage of agreement: 50.0% vs 77.1%). After training, inter-observer agreement between junior doctors was significantly improved and comparable to senior (weight Kappa: 0.824 vs 0.802, percentage of agreement: 77.1% vs 81.3%). Before and after systematic training, the intra-observer agreements of the same doctor, the senior physicians were better than the junior (weight Kappa: 0.882 and 0.843 vs 0.440 and 0.605; percentage of agreement: 87.5% and 83.3% vs 58.3% and 54.2%).Conclusions:O-RADS risk classification system is a highly reproducible method in the subjective assessment of an adnexal mass among observers with varying levels of expertise. However, systematic training before clinical application is necessary and effective for non-experienced observers.

Imaging and diagnostic approach of the adnexal mass: what the oncologist should know.

Early detection and characterization of ovarian lesions is of utmost importance for adequate management. Ovarian cancer accounts for 3.3% of all cancers in women worldwide but has only a 5% of female cancer deaths because of low survival rates. The majority of ovarian lesions are benign and have spontaneous resolution. The adequate discrimination between benign and malignant lesions is the most important starting point for a correct and optimal management. Ultrasound is the method of choice up until now for adequate assessment of adnexal abnormalities, no other method has proven superior. Along time, there has been many classification systems that aim standardization of adnexal masses The Gynecology Imaging Reporting and Data System (GI-RADS), published in 2019. The International Ovarian Tumor Analysis (IOTA) group standardized in 2013 the approach of adnexal pathology descriptions by ultrasound with the limitation of needing pathologic reports for complete assessment. The Ovarian Adnexal Reporting and Data System (O-RADS) is a lexicon designed in 2018 to standardize definitions of characteristics by ultrasound. This system offers an interpretation method to decrease ambiguity and recommends management guides according to its classification.