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

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.

Application of Ultrasound Scores (Subjective Assessment, Simple Rules Risk Assessment, ADNEX Model, O-RADS) to Adnexal Masses of Difficult Classification

BACKGROUND

Ultrasound features help to differentiate benign from malignant masses, and some of them are included in the ultrasound (US) scores. The main aim of this work is to describe the ultrasound features of certain adnexal masses of difficult classification and to analyse them according to the most frequently used US scores.

METHODS

Retrospective studies of adnexal lesions are difficult to classify by US scores in women undergoing surgery. Ultrasound characteristics were analysed, and masses were classified according to the Subjective Assessment of the ultrasonographer (SA) and other US scores (IOTA Simple Rules Risk Assessment-SRRA, ADNEX model with and without CA125 and O-RADS).

RESULTS

A total of 133 adnexal masses were studied (benign: 66.2%, n:88; malignant: 33.8%, n:45) in a sample of women with mean age 56.5 ± 7.8 years. Malignant lesions were identified by SA in all cases. Borderline ovarian tumors (n:13) were not always detected by some US scores (SRRA: 76.9%, ADNEX model without and with CA125: 76.9% and 84.6%) nor were serous carcinoma (n:19) (SRRA: 89.5%), clear cell carcinoma (n:9) (SRRA: 66.7%) or endometrioid carcinoma (n:4) (ADNEX model without CA125: 75.0%). While most teratomas and serous cystadenomas have been correctly differentiated, other benign lesions were misclassified because of the presence of solid areas or papillae. Fibromas (n:13) were better identified by SA (23.1% malignancy), but worse with the other US scores (SRRA: 69.2%, ADNEX model without and with CA125: 84.6% and 69.2%, O-RADS: 53.8%). Cystoadenofibromas (n:10) were difficult to distinguish from malignant masses via all scores except SRRA (SA: 70.0%, SRRA: 20.0%, ADNEX model without and with CA125: 60.0% and 50.0%, O-RADS: 90.0%). Mucinous cystadenomas (n:12) were misdiagnosed as malignant in more than 15% of the cases in all US scores (SA: 33.3%, SRRA: 16.7%, ADNEX model without and with CA125: 16.7% and 16.7%, O-RADS:41.7%). Brenner tumors are also difficult to classify using all scores.

CONCLUSION

Some malignant masses (borderline ovarian tumors, serous carcinoma, clear cell carcinoma, endometrioid carcinomas) are not always detected by US scores. Fibromas, cystoadenofibromas, some mucinous cystadenomas and Brenner tumors may present solid components/papillae that may induce confusion with malignant lesions. Most teratomas and serous cystadenomas are usually correctly classified.

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.

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.

Gynecologic Imaging and Reporting Data System for classifying adnexal masses

INTRODUCTION

To perform a systematic review and meta-analysis of the diagnostic performance of the so-called Gynecologic Imaging and Report Data System (GI-RADS) for classifying adnexal masses.

EVIDENCE ACQUISITION

A search for studies reporting about the use of GI-RADS system for classifying adnexal masses from January 2009 to December 2021 was performed in Medline (Pubmed), Google Scholar, Scopus, Cochrane, and Web of Science databases. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odd ratio (DOR) were calculated. Studies' quality was evaluated using QUADAS-2.

EVIDENCE SYNTHESIS

We identified 510 citations. Ultimately, 26 studies comprising 7350 masses were included. Mean prevalence of ovarian malignancy was 26%. The risk of bias was high in eight studies for domain "patient selection" and low for "index test," "reference test" domains for all studies. Overall, pooled estimated sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and DOR of GI-RADS system for classifying adnexal masses were 94% (95% confidence interval [CI]=91-96%), 90% (95% CI=87-92%), 9.1 (95% CI=7.0-11.9), and 0.07 (95% CI=0.05-0.11), and 132 (95% CI=78-221), respectively. Heterogeneity was high for both sensitivity and specificity. Meta-regression showed that multiple observers and study's design explained this heterogeneity among studies.

CONCLUSIONS

GI-RADS system has a good diagnostic performance for classifying adnexal masses.

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

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

Improving diagnostic strategies for ovarian cancer in Filipino women using ultrasound imaging and a multivariate index assay

OBJECTIVE

To evaluate the clinical performance and overall utility of imaging and biomarker assays in discriminating between benign and malignant ovarian masses in a Filipino population.

METHODS

This is a prospective cohort study among Filipino women undergoing assessment for an ovarian mass in a tertiary center. All included patients underwent a physical examination before level III specialist ultrasonographic and Doppler evaluation, multivariate index assay (MIA2G), and surgery for an adnexal mass. Ovarian tumors were classified as high-risk for malignancy based on the International Ovarian Tumour Analysis (IOTA) - Logistic Regression 2 (LR2) score. The ovarian imaging and biomarker results were correlated with the reference standard: histological findings.

RESULTS

Among the 379 women with adnexal masses enrolled in this study, 291 were evaluable with ultrasound imaging, biomarker assays, and histopathological results. The risk of malignancy was higher for women classified as high-risk based on IOTA-LR2 (≥10%). The sensitivity, specificity, and diagnostic accuracy for the prediction of malignancy were 81.2%, 81%, and 0.81 (95% CI: 0.77-0.86) for IOTA-LR2; 77.5%, 66.7%, and 0.72 (95% CI: 0.67-0.77) for CA-125; and 91.3%, 41.2%, and 0.66 (95% CI: 0.62-0.71) for MIA2G. A combination of IOTA-LR2 and MIA2G significantly influenced the diagnostic performance and the result. When MIA2G was combined with IOTA-LR2 in parallel, the sensitivity (94.2%) and NPV (87.7%) increased, but the specificity (37.3%) decreased. When combined with IOTA-LR2 in series, there were fewer false positives, which resulted in improved specificity (85%).

CONCLUSION

This study determined the utility of ovarian imaging and a second-generation multivariate index assay in predicting the risk of ovarian malignancy. IOTA-LR2 and MIA2G were useful in classifying patients with a high risk for ovarian malignancy.