Bridging Communication Gaps Between Radiologists, Referring Physicians, and Patients Through Standardized Structured Cancer Imaging Reporting: The Experience with Female Pelvic MRI Assessment Using O-RADS and a Simulated Cohort Patient Group.

RATIONALE AND OBJECTIVES: This study aimed to evaluate whether implementing structured reporting based on Ovarian-Adnexal Reporting and Data System (O-RADS) magnetic resonance imaging (MRI) in women with sonographically indeterminate adnexal masses improves communication between radiologists, referrers, and patients/caregivers and enhances diagnostic performance for determining adnexal malignancy. MATERIALS AND METHODS: We retrospectively analyzed prospectively issued MRI reports in 2019-2022 performed for characterizing adnexal masses before and after implementing O-RADS MRI; 56 patients/caregivers and nine gynecologic oncologists ("referrers") were surveyed about report interpretability/clarity/satisfaction; responses for pre- and post-implementation reports were compared using Fisher's exact and Chi-squared tests. Diagnostic performance was assessed using receiver operating characteristic curves. RESULTS: A total of 123 reports from before and 119 reports from after O-RADS MRI implementation were included. Survey response rates were 35.7% (20/56) for patients/caregivers and 66.7% (6/9) for referrers. For patients/caregivers, O-RADS MRI reports were clearer (p < 0.001) and more satisfactory (p < 0.001) than unstructured reports, but interpretability did not differ significantly (p = 0.14), as 28.0% (28/100) of postimplementation and 38.0% (38/100) of preimplementation reports were considered difficult to interpret. For referrers, O-RADS MRI reports were clearer, more satisfactory, and easier to interpret (p < 0.001); only 1.3% (1/77) were considered difficult to interpret. For differentiating benign from malignant adnexal lesions, O-RADS MRI showed area under the curve of 0.92 (95% confidence interval [CI], 0.85-0.99), sensitivity of 0.81 (95% CI, 0.58-0.95), and specificity of 0.91 (95% CI, 0.83-0.96). Diagnostic performance of reports before implementation could not be calculated due to many different phrases used to describe the likelihood of malignancy. CONCLUSION: Implementing standardized structured reporting using O-RADS MRI for characterizing adnexal masses improved clarity and satisfaction for patients/caregivers and referrers. Interpretability improved for referrers but remained limited for patients/caregivers.

Characterization of adnexal lesions using photoacoustic imaging to improve sonographic O-RADS risk assessment.

OBJECTIVE: To assess the impact of photoacoustic imaging (PAI) on the assessment of ovarian/adnexal lesion(s) of different risk categories using the sonographic ovarian-adnexal imaging-reporting-data system (O-RADS) in women undergoing planned oophorectomy. METHOD: This prospective study enrolled women with ovarian/adnexal lesion(s) suggestive of malignancy referred for oophorectomy. Participants underwent clinical ultrasound (US) examination followed by coregistered US and PAI prior to oophorectomy. Each ovarian/adnexal lesion was graded by two radiologists using the US O-RADS scale. PAI was used to compute relative total hemoglobin concentration (rHbT) and blood oxygenation saturation (%sO2 ) colormaps in the region of interest. Lesions were categorized by histopathology into malignant ovarian/adnexal lesion, malignant Fallopian tube only and several benign categories, in order to assess the impact of incorporating PAI in the assessment of risk of malignancy with O-RADS. Malignant and benign histologic groups were compared with respect to rHbT and %sO2 and logistic regression models were developed based on tumor marker CA125 alone, US-based O-RADS alone, PAI-based rHbT with %sO2 , and the combination of CA125, O-RADS, rHbT and %sO2. Areas under the receiver-operating-characteristics curve (AUC) were used to compare the diagnostic performance of the models. RESULTS: There were 93 lesions identified on imaging among 68 women (mean age, 52 (range, 21-79) years). Surgical pathology revealed 14 patients with malignant ovarian/adnexal lesion, two with malignant Fallopian tube only and 52 with benign findings. rHbT was significantly higher in malignant compared with benign lesions. %sO2 was lower in malignant lesions, but the difference was not statistically significant for all benign categories. Feature analysis revealed that rHbT, CA125, O-RADS and %sO2 were the most important predictors of malignancy. Logistic regression models revealed an AUC of 0.789 (95% CI, 0.626-0.953) for CA125 alone, AUC of 0.857 (95% CI, 0.733-0.981) for O-RADS only, AUC of 0.883 (95% CI, 0.760-1) for CA125 and O-RADS and an AUC of 0.900 (95% CI, 0.815-0.985) for rHbT and %sO2 in the prediction of malignancy. A model utilizing all four predictors (CA125, O-RADS, rHbT and %sO2 ) achieved superior performance, with an AUC of 0.970 (95% CI, 0.932-1), sensitivity of 100% and specificity of 82%. CONCLUSIONS: Incorporating the additional information provided by PAI-derived rHbT and %sO2 improves significantly the performance of US-based O-RADS in the diagnosis of adnexal lesions. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

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

OBJECTIVE: To evaluate the performance of subjective assessment and the Assessment of Different NEoplasias in the adneXa (ADNEX) model in discriminating between benign and malignant adnexal tumors and between metastatic and primary adnexal tumors in patients with a personal history of breast cancer. METHODS: This was a retrospective single-center study including patients with a history of breast cancer who underwent surgery for an adnexal mass between 2013 and 2020. All patients had been examined with transvaginal or transrectal ultrasound using a standardized examination technique and all ultrasound reports had been stored and were retrieved for the purposes of this study. The specific diagnosis suggested by the original ultrasound examiner in the retrieved report was analyzed. For each mass, the ADNEX model risks were calculated prospectively and the highest relative risk was used to categorize each into one of five categories (benign, borderline, primary Stage I, primary Stages II-IV or metastatic ovarian cancer) for analysis of the ADNEX model in predicting the specific tumor type. The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal tumors and between primary and metastatic adnexal tumors was evaluated, using final histology as the reference standard. RESULTS: Included in the study were 202 women with a history of breast cancer who underwent surgery for an adnexal mass. At histology, 93/202 (46.0%) masses were benign, 76/202 (37.6%) were primary malignancies (four borderline and 72 invasive tumors) and 33/202 (16.3%) were metastases. The original ultrasound examiner classified correctly 79/93 (84.9%) benign adnexal masses, 72/76 (94.7%) primary adnexal malignancies and 30/33 (90.9%) metastatic tumors. Subjective ultrasound evaluation had a sensitivity of 93.6%, specificity of 84.9% and accuracy of 89.6%, while the ADNEX model had higher sensitivity (98.2%) but lower specificity (78.5%), with similar accuracy (89.1%), in discriminating between benign and malignant ovarian masses. Subjective evaluation had a sensitivity of 51.5%, specificity of 88.8% and accuracy of 82.7% in distinguishing metastatic and primary tumors (including benign, borderline and invasive tumors), and the ADNEX model had a sensitivity of 63.6%, specificity of 84.6% and similar accuracy (81.2%). CONCLUSIONS: The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal masses in this series of patients with history of breast cancer was relatively similar. Both subjective assessment and the ADNEX model demonstrated good accuracy and specificity in discriminating between metastatic and primary tumors, but the sensitivity was low. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of performance between O-RADS, IOTA simple rules risk assessment and ADNEX model in the discrimination of ovarian Brenner tumors.

PURPOSE: To describe the clinical and sonographic features of ovarian benign Brenner tumor (BBT) and malignant Brenner tumor (MBT), and to compare performance of four diagnostic models in differentiating them. METHODS: Fifteen patients with BBTs and nine patients with MBTs were retrospectively identified in our institution from January 2003 and December 2021. One ultrasound examiner categorized each mass according to ovarian-adnexal reporting and data system (O-RADS), international ovarian tumor analysis (IOTA) Simple Rules Risk (SR-Risk) assessment and assessment of different neoplasias in the adnexa (ADNEX) models with/without CA125. Receiver operating characteristic curves were generated to compare diagnostic performance. RESULTS: Patients with MBT had higher CA125 serum level (62.5% vs. 6.7%, P = 0.009) and larger maximum diameter of lesion (89 mm vs. 43 mm, P = 0.009) than did those with BBT. BBT tended to have higher prevalence of calcifications (100% vs. 55.6%, P = 0.012) and acoustic shadowing (93.3% vs. 33.3%, P = 0.004), and lower color scores manifesting none or minimal flow (100.0% vs. 22.2%, P < 0.001). Areas under curves of O-RADS, IOTA SR-Risk and ADNEX models with/without CA125 were 0.896, 0.913, 0.892 and 0.896, respectively. There were no significant differences between them. CONCLUSION: BBTs are often small solid tumors with sparse color Doppler signals, which contain calcifications with posterior acoustic shadowing. The most common pattern of MBT is a large multilocular-solid or solid mass with irregular tumor borders, and most were moderately or richly vascularized at color Doppler. These four models have excellent performance in distinguishing them.

Systematic Review and Meta-Analysis of O-RADS Ultrasound and O-RADS MRI for Risk Assessment of Ovarian and Adnexal Lesions.

BACKGROUND. O-RADS ultrasound (US) and O-RADS MRI have been developed to standardize risk stratification of ovarian and adnexal lesions. OBJECTIVE. The purpose of this study was to perform a meta-analysis evaluating the diagnostic performance of O-RADS US and O-RADS MRI for risk stratification of ovarian and adnexal lesions. EVIDENCE ACQUISITION. We searched the Web of Science, PubMed, Cochrane Library, Embase, and Google Scholar databases from January 1, 2020, until October 31, 2022, for studies reporting on the performance of O-RADS US or O-RADS MRI in the diagnosis of malignancy of ovarian or adnexal lesions. Study quality was assessed with QUADAS-2. A hierarchic summary ROC model was used to estimate pooled sensitivity and specificity. Heterogeneity was assessed with the Q statistic. Metaregression analysis was performed to explore potential sources of heterogeneity. O-RADS US was compared with the International Ovarian Tumor Analysis (IOTA) simple rules and Assessment of Different Neoplasias in the Adnexa (ADNEX) model in studies providing head-to-head comparisons. EVIDENCE SYNTHESIS. Twenty-six studies comprising 9520 patients were included. O-RADS US was evaluated in 15 and O-RADS MRI in 12 studies; both systems were evaluated in one of the studies. Quality assessment revealed that risk of bias or concern about applicability most commonly related to patient selection. Pooled sensitivity and specificity of O-RADS US were 95% (95% CI, 91-97%) and 82% (95% CI, 76-87%) and of O-RADS MRI were 95% (95% CI, 92-97%) and 90% (95% CI, 84-94%). Analysis with the Q statistic revealed significant heterogeneity among studies of O-RADS US in both sensitivity and specificity (both p < .001) and among studies of O-RADS MRI in specificity (p < .001) but not sensitivity (p = .07). In metaregression, no factor was significantly associated with sensitivity or specificity of either system (all p > .05). O-RADS US showed no significant difference in sensitivity or specificity versus IOTA simple rules in four studies (sensitivity, 96% vs 93%; specificity, 76% vs 82%) or versus the ADNEX model in three studies (sensitivity, 96% vs 96%; specificity, 79% vs 78%). CONCLUSION. O-RADS US and O-RADS MRI both have high sensitivity for ovarian or adnexal malignancy. O-RADS MRI, but not O-RADS US, also has high specificity. CLINICAL IMPACT. Awareness of the diagnostic performance results regarding O-RADS US and O-RADS MRI will be helpful as these systems are increasingly implemented into clinical practice.

A reflex testing protocol using two multivariate index assays improves the risk assessment for ovarian cancer in patients with an adnexal mass.

OBJECTIVES: Patients with adnexal masses suspicious for malignancy benefit from referral to oncology specialists during presurgical assessment of the mass. OVA1 is a multivariate assay using a five-biomarker panel which offers high overall and early-stage sensitivity. However, OVA1 has a high false-positive rate for benign masses. Overa, a second-generation multivariate index assay was developed to reduce the false-positive rate. The aim of the present study was to use Overa as a reflex for OVA1 and increase specificity. METHODS: OVA1 cut-off scores were established to place patients into three categories: low, intermediate, and high cancer risk. Samples with intermediate-risk OVA1 scores were reflexed to the Overa and defined as high or low risk. This protocol was tested with 1035 prospectively collected serum samples and validated with an independent prospectively collected sample set (N = 207). RESULTS: Thirty-five per cent (359) of samples had intermediate OVA1 scores. Reflexing these to Overa eliminated 58% of the false-positives and improved the overall specificity from 50% to 72%. This finding was confirmed in the independent dataset, in which the specificity increased from 56% to 73%. CONCLUSIONS: Reflexing samples with intermediate OVA1 scores significantly decreases the false-positive rate, thereby reducing unnecessary surgical referrals.

Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital.

OBJECTIVES: The aim of this study was to evaluate the accuracy of IOTA Simple Rules (SR), IOTA ADNEX model, Risk of Malignancy Index (RMI), and subjective assessment (SA) which is used for adnexal mass assessment in our institution. DESIGN: This is a prospective observational study. PARTICIPANTS/MATERIALS, SETTING, METHODS: We included patients with at least one adnexal mass who needed elective surgical evaluation based on clinical and laboratory findings. Patients admitted to Clinic for Gynecology and Obstetrics, University Clinical Center of Serbia, were recruited for the study between January 2019 and June 2021. Level II ultrasonographers performed a gray scale and Doppler exam for each patient. Preoperative classification of adnexal masses (benign or malignant) was performed by SA, the International Ovarian Analysis Group (IOTA) SR, IOTA ADNEX model, and Risk of Malignancy Index (RMI). Postoperatively obtained histological findings were used as a reference. RESULTS: During the study period, we enrolled 179 premenopausal and 217 postmenopausal patients, representing 396 patients in our sample. Prevalence of malignant disease in pre- and postmenopausal groups was 16.2% (29/179) and 41% (89/217), respectively. Malignant disease was diagnosed in 29.8% (118/396) of patients. SA achieved the highest discrimination accuracy between benign and malignant tumors (area under the curve [AUC] of 0.928, 95% CI [0.898-0.952]). For SA, the overall diagnostic accuracy, sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were 91.4%, 88.1%, 92.8%, 12.25, and 0.13. The AUC for Simple Rules with subjective assessment in inconclusive cases (SR + SA) was 0.912 (95% CI [0.880-0.938]). Regarding SR + SA, diagnostic accuracy, sensitivity, specificity, LR+, and LR- were 92.4%, 88.1%, 94.2%, 15.31, and 0.13. The ADNEX model had the AUC of 0.914 (95% CI [0.882-0.940]). Binary classification using the ADNEX model at a cut-off value of 10% for malignancy had the sensitivity, specificity, LR+ and LR- of 92.4%, 73.0%, 3.42, and 0.10. This resulted in the lowest overall accuracy of 78.8%. The AUC for RMI was 0.854 (95% CI [0.815-0.887]), with overall accuracy, sensitivity, specificity, LR+ and LR- of 82.3%, 73.7%, 86.0%, 5.26, and 0.31. There was no difference in the AUCs of the SA and IOTA models for the whole group, premenopausal, and postmenopausal groups. RMI performed worse compared to SA and the IOTA models. The ADNEX model achieved the highest accuracy at the cut-off value of 35%. LIMITATIONS: The data generalizability is limited by a single institution-dependent sampling. CONCLUSIONS: The IOTA SR and ADNEX model were reliable and comparable with the SA and performed better than the RMI. The IOTA SR model offers the potential for immediate and reliable diagnosis, even in the hands of less experienced ultrasonographers. Both IOTA models studied can be a valuable adjunct to a clinician's decision-making process.

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.

O-RADS MRI Classification of Indeterminate Adnexal Lesions: Time-Intensity Curve Analysis Is Better Than Visual Assessment.

Background The MRI Ovarian-Adnexal Reporting and Data System (O-RADS) enables risk stratification of sonographically indeterminate adnexal lesions, partly based on time-intensity curve (TIC) analysis, which may not be universally available. Purpose To compare the diagnostic accuracy of visual assessment with that of TIC assessment of dynamic contrast-enhanced MRI scans to categorize adnexal lesions as benign or malignant and to evaluate the influence on the O-RADS MRI score. Materials and Methods The European Adnex MR Study Group, or EURAD, database, a prospective multicenter study of women undergoing MRI for indeterminate adnexal lesions between March 2013 and March 2018, was queried retrospectively. Women undergoing surgery for an adnexal lesion with solid tissue were included. Solid tissue enhancement relative to outer myometrium was assessed visually and with TIC. Contrast material washout was recorded. Lesions were categorized according to the O-RADS MRI score with visual and TIC assessment. Per-lesion diagnostic accuracy was calculated. Results A total of 320 lesions (207 malignant, 113 benign) in 244 women (mean age, 55.3 years ± 15.8 [standard deviation]) were analyzed. Sensitivity for malignancy was 96% (198 of 207) and 76% (157 of 207) for TIC and visual assessment, respectively. TIC was more accurate than visual assessment (86% [95% CI: 81, 90] vs 78% [95% CI: 73, 82]; P < .001) for benign lesions, predominantly because of higher specificity (95% [95% CI: 92, 98] vs 76% [95% CI: 68, 81]). A total of 21% (38 of 177) of invasive lesions were rated as low risk visually. Contrast material washout and high-risk enhancement (defined as earlier enhancement than in the myometrium) were highly specific for malignancy for both TIC (97% [95% CI: 91, 99] and 94% [95% CI: 90, 97], respectively) and visual assessment (97% [95% CI: 92, 99] and 93% [95% CI: 88, 97], respectively). O-RADS MRI score was more accurate with TIC than with visual assessment (area under the receiver operating characteristic curve, 0.87 [95% CI: 0.83, 0.90] vs 0.73 [95% CI: 0.68, 0.78]; P < .001). Conclusion Time-intensity curve analysis was more accurate than visual assessment for achieving optimal diagnostic accuracy with the Ovarian-Adnexal Reporting and Data System MRI score. Clinical trial registration no. NCT01738789 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Vargas and Woo in this issue. An earlier incorrect version appeared online. This article was corrected on March 7, 2022.

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

OBJECTIVES: To evaluate the performance of a two-step strategy compared with the International Ovarian Tumor Analysis (IOTA) - Assessment of Different NEoplasias in the adneXa (ADNEX) model for preoperative classification of adnexal masses. METHODS: An ambispective diagnostic accuracy study based on ultrasound data collected at one university hospital between 2012 and 2018. Two ultrasonographers classified the adnexal masses using IOTA Simple Rules (first step). Not classifiable masses were evaluated using the IOTA ADNEX model (second step). Also, all masses were classified using the IOTA ADNEX model. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-), and receiver operating characteristic (ROC) curve were estimated. A P value of <.05 was used to determine statistical significance. RESULTS: The study included 548 patients and 606 masses. Patients' median age was 41 years with an interquartile range between 32 and 51 years. In the first step, 89 (14%) masses were not classifiable. In the second step, 55 (61.8%) masses were classified as malignant. Furthermore, for the totality of 606 masses, the IOTA ADNEX model estimated the probability that 126 (20.8%) masses were malignant. The two-step strategy had a sensitivity, specificity, PPV, NPV, LR+, LR-, and ROC curve of 86.8%, 91.01%, 51.9%, 98.4%, 9.7, 0.1, and 0.889, respectively; compared to IOTA ADNEX model that had values of 91.8%, 87.16%, 44.4%, 99%, 7.1, 0.09, and 0.895, respectively. CONCLUSION: The two-step strategy shows a similar diagnostic performance when compared to the IOTA ADNEX model. The IOTA ADNEX model involves only one step and can be more practical, and thus would be recommended to use.

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

OBJECTIVES: To apply the International Ovarian Tumor Analysis (IOTA) Simple Rules (SR), the IOTA Simple Rules risk assessment (SRR), the IOTA Assessment of Different NEoplasias in the adneXa (ADNEX) model and the Ovarian-Adnexal Reporting and Data System (O-RADS) in the same cohort of North American patients and to compare their performance in preoperative discrimination between benign and malignant adnexal lesions. METHODS: This was a single-center diagnostic accuracy study, performed between March 2018 and February 2021, which included 150 women with an adnexal lesion. Using the ADNEX model, lesions were classified prospectively, whereas the SR, SRR assessment and O-RADS were applied retrospectively. Surgery with histological analysis was performed within 6 months of the ultrasound exam. Sensitivity and specificity were determined for each testing modality and the performance of the different modalities was compared. RESULTS: Of the 150 women, 110 (73.3%) had a benign ovarian tumor and 40 (26.7%) had a malignant tumor. The mean risk of malignancy generated by the ADNEX model without CA 125 was significantly higher in malignant vs benign lesions (63.3% vs 11.8%) and the area under the receiver-operating-characteristics curve (AUC) of the ADNEX model for differentiating between benign and malignant adnexal masses at the time of ultrasound examination was 0.937. The mean risk of malignancy generated by SRR assessment was also significantly higher in malignant vs benign lesions (74.1% vs 15.9%) and the AUC was 0.941. To compare the ADNEX model, SRR assessment and O-RADS, the malignancy risk threshold was set at ≥ 10%. This cut-off differentiates O-RADS low-risk categories (Category ≤ 3) from intermediate-to-high-risk categories (Categories 4 and 5). At this cut-off, the sensitivity of the ADNEX model was 97.5% (95% CI, 85.3%-99.9%) and the specificity was 63.6% (95% CI, 53.9%-72.4%), and, for the SRR model, the sensitivity was 100% (95% CI, 89.1%-100%) and the specificity was 51.8% (95% CI, 42.1%-61.4%). In the 113 cases to which the SR could be applied, the sensitivity was 100% (95% CI, 81.5%-100%) and the specificity was 95.6% (95% CI, 88.5%-98.6%). If the remaining 37 cases, which were inconclusive under SR, were designated 'malignant', the sensitivity remained at 100% but the specificity was reduced to 79.1% (95% CI, 70.1%-86.0%). The 150 cases fell into the following O-RADS categories: 17 (11.3%) lesions in Category 2, 34 (22.7%) in Category 3, 66 (44.0%) in Category 4 and 33 (22.0%) in Category 5. There were no histologically proven malignant lesions in Category 2 or 3. There were 14 malignant lesions in Category 4 and 26 in Category 5. The sensitivity of O-RADS using a malignancy risk threshold of ≥ 10% was 100% (95% CI, 89.1%-100.0%) and the specificity was 46.4% (95% CI, 36.9%-56.1%). CONCLUSIONS: When IOTA terms and techniques are used, the performance of IOTA models in a North American patient population is in line with published IOTA results in other populations. The IOTA SR, SRR assessment and ADNEX model and O-RADS have similar sensitivity in the preoperative discrimination of malignant from benign pelvic tumors; however, the IOTA models have higher specificity and the algorithm does not require the use of magnetic resonance imaging. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

External Validation of the Assessment of Different NEoplasias in the adneXa Model Performance in Evaluating the Risk of Ovarian Carcinoma Before Surgery in China: A Tertiary Center Study.

OBJECTIVES: The Assessment of Different NEoplasias in the adneXa (ADNEX) model was developed by the International Ovarian Tumor Analysis group to assess the risk of an ovarian mass being malignant. This study aimed to externally validate the ADNEX model performance in a tertiary center in China. METHODS: This retrospective, single-center university hospital study assessed the model diagnostic accuracy. All patients were examined by transvaginal ultrasonography, and serum CA125 levels were measured. Moreover, clinicopathological information was collected. The diagnostic performance of the ADNEX model was calculated with and without CA125 as a predictor. RESULTS: We retrieved data of 335 patients, of which 53 were excluded based on the exclusion criteria. Of the included 282 patients, 178 (63.1%) had benign tumors, and 104 (36.9%) had malignant tumors. When CA125 was factored in, the area under the receiver operating characteristic curve (AUC) for the distinction between benign and malignant tumors was 0.93 (95% confidence interval [CI], 0.90-0.96), whereas it was 0.91 (95% CI, 0.88-0.95) without CA125. The concordance between the predicted risk of malignancy and the proportion of observed malignancies was well demonstrated by the calibration plots. CONCLUSIONS: The proper performance of the ADNEX model was verified externally in a tertiary center in China, showing a good distinction between tumour subtypes. Our findings suggest the ADNEX model is a valuable tool in clinical practice and may help in managing patients with adnexal masses.

Ultrasound Assessment of Adnexal Pathology: Standardized Methods and Different Levels of Experience.

Background and objectives: An expert's subjective assessment is still the most reliable evaluation of adnexal pathology, thus raising the need for methods less dependent on the examiner's experience. The aim of this study was to evaluate the performance of standardized methods when applied by examiners with different levels of experience and to suggest the most suitable method for less-experienced gynecologists. Materials and methods: This single-center retrospective study included 50 cases of histologically proven first-time benign or malignant adnexal pathology. Three examiners evaluated the same transvaginal ultrasound images: an expert (level III), a 4th year resident in gynecology (level I), and a final year medical student after basic training (labeled as level 0). The assessment methods included subjective evaluation, Simple Rules (SR) with and without algorithm, ADNEX and Gynecologic Imaging Reporting and Data System (GI-RADS) models. Sensitivity, specificity, accuracy, positive and negative predictive values with 95% confidence interval were calculated. Results: Out of 50 cases, 33 (66%) were benign and 17 (34%) were malignant adnexal masses. Using only SR, level III could classify 48 (96%), level I-41 (82%) and level 0-40 (80%) adnexal lesions. Using SR and algorithm, the performance improved the most for all levels and yielded sensitivity and specificity of 100% for level III, 100% and 97% for level I, 94.4% and 100% for level 0, respectively. Compared to subjective assessment, ADNEX lowered the accuracy of level III evaluation from 97.9% to 88% and GI-RADS had no impact. ADNEX and GI-RADS improved the sensitivity up to 100% for the less experienced; however, the specificity and accuracy were notably decreased. Conclusions: SR and SR+ algorithm have the most potential to improve not only sensitivity, but also specificity and accuracy, irrespective of the experience level. ADNEX and GI-RADS can yield sensitivity of 100%; however, the accuracy is decreased.

Magnetic resonance scoring system for assessment of adnexal masses: added value of diffusion-weighted imaging including apparent diffusion coefficient map.

OBJECTIVES: To validate prospectively the ADNEX magnetic resonance (MR) scoring system to assess adnexal masses and to evaluate a new, modified ADNEX MR scoring system that incorporates diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping. METHODS: Between January 2015 and September 2018, 323 consecutive women with adnexal masses diagnosed on transvaginal ultrasound (TVS) underwent standardized MR imaging (MRI) including diffusion and dynamic contrast-enhanced sequences. Of these, 131 underwent subsequent surgery. For interpretation of the MRI examinations, we applied the five-category ADNEX MR scoring system, along with a modified scoring system including DWI with ADC mapping. For both scoring systems, a score was given for all adnexal masses. Histological diagnosis was considered as the gold standard and lesions were classified as benign or malignant. The difference between the predictive values for diagnosing malignancy of the classical and modified scoring systems was assessed on the basis of the areas under the receiver-operating-characteristics (AUC) curves. The sensitivity and specificity for diagnosing malignancy of each score were also calculated. RESULTS: Among the 131 women with adnexal mass(es) diagnosed on TVS who underwent MRI and subsequent surgery, the surgery revealed 161 adnexal masses in 126 women; five women had no mass. Histological examination confirmed 161 adnexal masses, of which all had been detected on MRI: 32 malignant tumors, 15 borderline tumors, which were classified as part of the malignant group (n = 47), and 114 benign lesions. The AUC for prediction of a malignant lesion was 0.938 (95% CI, 0.902-0.975) using the classical ADNEX MR scoring system and 0.974 (95% CI, 0.953-0.996) using the modified scoring system. Pairwise comparison of these AUCs revealed a significant difference (P = 0.0032). The sensitivity and specificity for diagnosing malignancy with an ADNEX MR score of 4 or more were 95.5% and 86.6%, respectively, using the classic scoring system, and 95.7% and 93.3%, respectively, using the modified scoring system. CONCLUSION: DWI with ADC mapping could be integrated into the ADNEX MR scoring system to improve specificity, thereby potentially optimizing clinical management by avoiding unnecessary surgery. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Preoperative CT image-based assessment for estimating risk of ovarian torsion in women with ovarian lesions and pelvic pain.

PURPOSE: To define and weight the preoperative CT findings for ovarian torsion and to develop an integrated nomogram for estimating the probability of ovarian torsion in women with ovarian lesion and pelvic pain. METHODS: This retrospective study included 218 women with surgically resected ovarian lesions who underwent preoperative contrast-enhanced CT for pelvic pain from January 2014 to February 2019. Significant imaging findings for torsion were extracted using regression analyses and a regression coefficient-based nomogram was constructed. The diagnostic performance with sensitivity, specificity, and accuracy of the significant imaging findings and the nomogram were assessed. RESULTS: A total of 255 ovarian lesions (123 lesions with torsion and 132 lesions without torsion) were evaluated. Multivariable regression analysis showed that whirl sign (odds ratio [OR] 11.000; p < 0.001), tubal thickening (OR 4.621; p = 0.001), unusual location of ovarian lesion (OR 2.712; p = 0.020), and hemorrhagic component within adnexal lesion (OR 2.537; p = 0.028) were independent significant parameters predicting ovarian torsion. Tubal thickening showed the highest sensitivity (91.1%) and whirl sign showed the highest specificity (94.7%). When probabilities of ovarian torsion of 0.5 or more in the nomogram were diagnosed as ovarian torsion, sensitivity, specificity, and accuracy of the nomogram were 78.1%, 91.7%, and 85.1%, respectively. CONCLUSION: The whirl sign, tubal thickening, unusual location of ovarian lesion, and hemorrhagic component within adnexal lesion, and an integrated nomogram derived from these significant findings can be useful for predicting ovarian torsion.

Diagnostic Performance of a Sonographic Volume and Solid Vascular Tissue Score (VSVTS) for Preoperative Risk Assessment of Pediatric and Adolescent Adnexal Masses.

STUDY OBJECTIVE: To evaluate the diagnostic performance of a Volume and Solid Vascular Tissue Score (VSVTS) for preoperative risk assessment of pediatric and adolescent adnexal masses. DESIGN: A retrospective cohort study comprised of all female individuals who presented with an adnexal mass that was managed surgically between April 2011 and March 2016. SETTING: The Hospital for Sick Children (Toronto, Ontario, Canada). PARTICIPANTS: Female individuals 1-18 years of age who presented to a large tertiary pediatric hospital with an adnexal mass that was managed surgically. MAIN OUTCOME MEASURES: Main outcome measures included diagnostic performance of the VSVTS for malignancy via sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR-), and receiver operating characteristic area-under-the-curve (AUC) analysis. RESULTS: A total of 179 masses in 169 subjects were included. The malignancy rate was 10.6%. The AUC for the VSTVS was 0.919. A VSTVS cut-off value of 4 achieved a sensitivity of 79% (95% CI 0.54-0.93), specificity of 88% (95% CI 0.82-0.93), PPV of 0.44 (95% CI 0.33-0.56), NPV of 0.97 (95% CI 0.94-0.99), LR+ of 6.77 (95% CI 4.18-10.97), and LR- of 0.24 (95% CI 0.10-0.57). CONCLUSIONS: A sonographic scoring system based on the volume and presence of solid vascular tissue improves PPV for preoperative risk stratification of adnexal masses in the pediatric and adolescent population compared to existing ultrasound-only approaches. Further prospective research is needed to determine how best to incorporate components of such scoring systems into clinical management algorithms.

Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: comparison with expert subjective assessment.

OBJECTIVES: To develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between benign and malignant ovarian tumors and to compare its diagnostic accuracy with that of subjective assessment (SA) by an ultrasound expert. METHODS: We included 3077 (grayscale, n = 1927; power Doppler, n = 1150) ultrasound images from 758 women with ovarian tumors, who were classified prospectively by expert ultrasound examiners according to IOTA (International Ovarian Tumor Analysis) terms and definitions. Histological outcome from surgery (n = 634) or long-term (≥ 3 years) follow-up (n = 124) served as the gold standard. The dataset was split into a training set (n = 508; 314 benign and 194 malignant), a validation set (n = 100; 60 benign and 40 malignant) and a test set (n = 150; 75 benign and 75 malignant). We used transfer learning on three pre-trained DNNs: VGG16, ResNet50 and MobileNet. Each model was trained, and the outputs calibrated, using temperature scaling. An ensemble of the three models was then used to estimate the probability of malignancy based on all images from a given case. The DNN ensemble classified the tumors as benign or malignant (Ovry-Dx1 model); or as benign, inconclusive or malignant (Ovry-Dx2 model). The diagnostic performance of the DNN models, in terms of sensitivity and specificity, was compared to that of SA for classifying ovarian tumors in the test set. RESULTS: At a sensitivity of 96.0%, Ovry-Dx1 had a specificity similar to that of SA (86.7% vs 88.0%; P = 1.0). Ovry-Dx2 had a sensitivity of 97.1% and a specificity of 93.7%, when designating 12.7% of the lesions as inconclusive. By complimenting Ovry-Dx2 with SA in inconclusive cases, the overall sensitivity (96.0%) and specificity (89.3%) were not significantly different from using SA in all cases (P = 1.0). CONCLUSION: Ultrasound image analysis using DNNs can predict ovarian malignancy with a diagnostic accuracy comparable to that of human expert examiners, indicating that these models may have a role in the triage of women with an ovarian tumor. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Análisis de imágenes ecográficas utilizando redes neurales profundas para distinguir entre tumores ováricos benignos y malignos: comparación con la evaluación subjetiva de expertos OBJETIVOS: Desarrollar y probar el desempeño del análisis de imágenes ecográficas computarizadas utilizando redes neurales profundas (RNP) para distinguir entre tumores ováricos benignos y malignos y comparar su precisión en el diagnóstico con la de la evaluación subjetiva (ES) por especialistas expertos en ecografía. MÉTODOS: Se incluyeron 3077 (escala de grises, n=1927; power Doppler, n=1150) imágenes de ultrasonido de 758 mujeres con tumores ováricos, que fueron clasificadas prospectivamente por examinadores especialistas en ecografía, de acuerdo con los términos y definiciones de la IOTA (Análisis Internacional de Tumores Ováricos). El resultado histológico de la cirugía (n=634) o el seguimiento a largo plazo (≥3 años) (n=124) sirvieron como el estándar de referencia. El conjunto de datos se dividió en un subconjunto de formación (n=508; 314 benignos y 194 malignos), un subconjunto de validación (n=100; 60 benignos y 40 malignos) y un subconjunto de pruebas (n=150; 75 benignos y 75 malignos). Se utilizó el aprendizaje de transferencia en tres RNP pre-formadas: VGG16, ResNet50 y MobileNet. Cada modelo fue formado primero mediante escalas de temperatura, al igual que los la calibración de los outputs. A continuación, se utilizó una combinación de los tres modelos para estimar la probabilidad de que el tumor fuera maligno con base en la totalidad de las imágenes de un caso determinado. La combinación de RNP permitió clasificar los tumores como benignos o malignos (modelo Ovry-Dx1); o como benignos, no concluyentes o malignos (modelo Ovry-Dx2). Se comparó el desempeño para el diagnóstico de los modelos de RNP, en términos de sensibilidad y de especificidad, con el de la ES para la clasificación de los tumores ováricos en el subconjunto de formación. RESULTADOS: Con una sensibilidad del 96,0%, Ovry-Dx1 tuvo una especificidad similar a la de la ES (86,7% frente a 88,0%; P=1,0). Ovry-Dx2 tuvo una sensibilidad del 97,1% y una especificidad del 93,7%, y designaron un 12,7% de las lesiones como no concluyentes. Cuando se complementó Ovry-Dx2 con ES en los casos no concluyentes, la sensibilidad general (96,0%) y la especificidad (89,3%) no fueron significativamente diferentes de la utilización de ES en todos los casos (P=1,0). CONCLUSIÓN: El análisis de imágenes ecográficas mediante RNP puede predecir el cáncer de ovario con una precisión en el diagnóstico igual a la de los especialistas expertos humanos, lo que indica que estos modelos pueden jugar un papel en el triaje de mujeres con un tumor de ovario. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Logistic models and artificial intelligence in the sonographic assessment of adnexal masses - a systematic review of the literature.

Adnexal masses are common, yet challenging, in gynecological practice. Making the differential diagnosis between their benign and malignant condition is essential for optimal surgical management, but reliable pre-surgical differentiation is sometimes difficult using clinical features, ultrasound examination, or tumor markers alone. A possible way to improve the diagnosis is using artificial intelligence (AI) or logistic models developed based on compiling and processing clinical, ultrasound, and tumor marker data together. Ample research has already been conducted in this regard that medical practitioners could benefit from. In this systematic review, we present logistic models and methods using AI, chosen based on their demonstrated high performance in clinical practice. Although some external validation of these models has been performed, further prospective studies are needed in order to select the best model or to create a new, more efficient, one for the pre-surgical evaluation of ovarian masses.

[Application of a protocol for the management of adnexal masses: savings in clinically unnecessary activity and costs].

BACKGROUND: Evaluate whether the implementation of an adnexal masses protocol, based on the GI-RADS system, allows a correct management of these masses, avoiding unnecessary clinical activity produced by overdiagnosis and overtreatment, as well as cost savings. METHODS: Retrospective cohort study (July 2015 - June 2017) including women treated at the Gynaecology clinic of the Hospital Universitario Rey Juan Carlos (Móstoles, Madrid), with detection of an adnexal mass in high resolution echography. Adnexal masses were classified by the GI-RADS system, and together with the echographic image and menopausal status, surgery or follow-up was decided. RESULTS: A total of 154 women were studied, 24?% with images suggesting malignancy (G4 and G5). Surgery was performed on 33.1?% of adnexal masses; 33.3?% of them were ovarian carcinoma, mainly (88.2?%) in postmenopausal women with echographic images suggesting malignancy. Three point two percent of patients rejected the recommended surgery. During follow-up 21.4?% of the masses disappeared, 61 patients were only monitored due to a stable mass and two (1.3?%) due to surgical risk. Eventually, 96 (62.3?%) surgeries were avoided, achieving a 57,683 Euro saving. CONCLUSIONS: The application of a protocol based on the GI-RADS classification system avoided unnecessary surgeries, as well as the consequences and economical cost produced by them. Thus, this protocol is a useful and practical tool for the monitoring and treatment of adnexal masses.

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

OBJECTIVES: The ADNEX (Assessment of Different NEoplasias in the adneXa) model was developed using parameters collected by experienced (level III) ultrasound examiners. Our primary aim was to externally validate the ADNEX model. Then, the discriminatory performance of ADNEX was compared with the two-step strategy and subjective assessment by an experienced ultrasound operator. METHODS: Between February 2013 and January 2017, all patients who were scheduled for surgery for an adnexal mass at the Sant'Anna Hospital in Turin were enrolled in this study. Preoperative transvaginal sonography was performed, and the two-step strategy was applied for triage of the adnexal mass. Two ultrasound examiners, IOTA certified, applied the ADNEX model to all the collected masses based on the ultrasound reports. Finally, an experienced operator assigned the subjective assessment based on recorded ultrasound images. The discrimination and calibration performance of ADNEX were evaluated. The AUC was calculated for the basic discrimination between benign and malignant tumours. In addition, AUCs were computed for each pair of tumour types using the conditional risk method. RESULTS: A total of 577 patients were included in the analysis: the overall prevalence of malignancy was 25 %. With ADNEX, the AUC to differentiate between benign and malignant masses was 0.9111 (95 % CI 0. 8788-0.9389). At risk cut-offs of 1%, 10 % and 30 %, sensitivities were 100 %, 89.6 % and 79.2 %, respectively, and specificities were 2.8 %, 76.2 % and 89.6 %, respectively. Discrimination between benign and stage II-IV tumours was good (AUC 0.935). The model had the most difficulties discriminating between borderline and stage I tumours (AUC 0.666), and between stages II-IV invasive and secondary metastatic tumours (AUC 0.736). The polytomous discrimination index (PDI) was 0.61 for ADNEX, whereas PDI for random performance would be 0.25. ADNEX proved to be equally or more accurate than the subjective assessment or the two-step strategy in the discrimination between benign and malignant adnexal masses. CONCLUSIONS: the ADNEX model could probably be successfully applied when an expert examiner is not available and, therefore both a subjective assessment and the two-step strategy cannot be performed.