Contrast-enhanced ultrasound and Ovarian-Adnexal Reporting and Data System ultrasound classification for risk assessment of ovarian and adnexal lesions: a systematic review and meta-analysis

Introduction

Among gynecological malignancies, ovarian cancer is the leading cause of death (1). Adnexal imaging can help detect malignant masses, increasing the rate of early detection and thereby improving the survival rate of patients (2). Therefore, the differentiation of benign and malignant lesions in the ovaries and adnexa is crucial for guiding treatment strategies.

Conventional ultrasound examination, as one of the main detection methods for adnexal masses, has the advantages of convenience, noninvasiveness, and lack of radiation (3). The Ovarian-Adnexal Reporting and Data System (O-RADS) Ultrasound Risk Stratification and Management Consensus and the guidelines officially released by the American College of Radiology (ACR) in 2020 have played a positive role in reducing or eliminating ambiguity in ultrasound reporting and in improving the accuracy and uniformity of benign and malignant risk assessment of ovarian and adnexal masses (4). Studies have shown that the International Ovarian Tumor Analysis (IOTA) Simple Rules Risk Assessment (SRRA) classification, Assessment of Different Neoplasias in the Adnexa (ADNEX) model, and O-RADS system can all effectively differentiate between benign and malignant adnexal masses (5,6). Ultrasound features such as irregular contours, vascularized solid areas, and multilocular structures hold significant value in distinguishing benign from malignant lesions, and these characteristics are also present in small-sized masses (7,8). Furthermore, Moro et al. described the characteristic ultrasound manifestations of different subtypes of ovarian tumors, providing a basis for preoperative differential diagnosis (9,10). Li et al. recently provided a detailed characterization of the conventional and contrast-enhanced ultrasound (CEUS) manifestations of ovarian thecomas and fibromas, which has improved the sonographic recognition of these specific tumor types (11). Among these, the accurate preoperative identification of borderline ovarian tumors (BOTs) holds particular clinical importance. Studies indicate that by analyzing key ultrasound features such as intralesional papillary structures and the number of locules, BOT can be effectively identified preoperatively. This provides crucial reference for developing fertility-sparing surgical strategies for young patients with fertility needs (10,12). However, despite the recognized value of the O-RADS system in clinical practice, it still has certain limitations (13).

The early differentiation between benign and malignant ovarian and adnexal masses is crucial. Conventional ultrasound primarily relies on subjective qualitative assessment, with approximately 20% of adnexal masses remaining indeterminate in nature even after color Doppler examination (14,15). CEUS, by revealing tumor microvascular perfusion and morphological characteristics, can significantly improve imaging quality and provide important references for benign-malignant differentiation (16). The study by Fan et al. demonstrated that the quantitative analysis of CEUS parameters has significant clinical value in differentiating benign from malignant pelvic tumors (17). Although CEUS has been widely adopted in clinical practice, the related studies have been limited by the use of limited sample sizes, lack of standardized protocols, and variations in operator experience, which may compromise the reliability of conclusions (18). Therefore, it is necessary to conduct a comprehensive analysis of this literature to generate more robust evidence for the clinical application of CEUS.

According to the ACR O-RADS US guidelines, risk stratification requires comprehensive evaluation of multiple features, as relying on any single characteristic would significantly reduce diagnostic accuracy (4). Therefore, this study focused on the complete scoring system rather than individual ultrasound variables. A comparison of the individual ultrasound variables between CEUS and O-RADS US is also provided in Table S1.

In this study, we aimed to conduct a systematic review and meta-analysis to compare and evaluate the value of CEUS and O-RADS US in the differential diagnosis of benign and malignant ovarian masses. We present this article in accordance with the PRISMA-DTA reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-49/rc).

Methods

Protocol and registration

This meta-analysis was registered under PROSPERO with the registration number CRD42024609526 (19). The inclusion and exclusion criteria for eligible studies, as well as the methods for data extraction and quality assessment, were established before the literature search was initiated.

Data sources and searches

Two of the authors (H.L. and Y.G.) conducted searches in four electronic databases (PubMed, Embase, Web of Science, and the Cochrane Library) to identify potentially eligible articles published up to October 2024. The search terms and medical subject headings included “neoplasm”, “ovarian and adnexal”, “contrast-enhanced ultrasound”, and “O-RADS”. The search was limited to articles published in English.

Study selection

Two authors screened (H.L. and Z.Y.) the identified titles and abstracts to exclude irrelevant literature and duplicate search results. Subsequently, articles requiring full-text review were selected to determine potentially eligible studies. After a review of the articles’ full texts, disagreements were resolved through group discussion. The following inclusion criteria were applied: (I) prospective or retrospective studies that included adult women diagnosed with at least one adnexal mass following ultrasound examination; (II) diagnostic trials on CEUS and O-RADS US for diagnosing adnexal masses; (III) pathology as the gold standard for diagnosis; and (IV) sufficient data to allow for the construction of a 2×2 table to estimate true positives, true negatives, false positives, and false negatives. The exclusion criteria are as follows: articles not reporting original data (such as reviews, abstracts, letters, and conference papers, etc.), a topic irrelevant to the research question, and data insufficient for constructing a 2×2 contingency table. Disputes that arose during the study selection and data extraction process were resolved through discussion between the two authors.

Data collection

Data recorded for each article included clinical characteristics (number of patients, number of lesions, number of malignant tumors, number of benign tumors, patient age, tumor size, and reference standard) and study characteristics (publication year, study design, level of analysis, patient selection period, number of operators, and operator blinding to the reference standard). The number of true positives, true negatives, false positives, and false negatives for the diagnosis of malignant tumors was inferred and recorded.

Risk of bias in individual studies

The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to evaluate the quality of the articles and the potential for bias (20). Patient selection, index test, reference standard and flow, and timing are the four crucial domains of the QUADAS-2 tool. The first three domains were also used to assess the clinical applicability of the included literature. The quality assessment of the studies included was independently conducted by two researchers (H.L. and C.Z.), with disagreements resolved through discussion.

Statistical analysis

Statistical analysis was performed with the bivariate mixed-effects model in STATA 17.0 software (StataCorp., College Station, TX, USA). The sensitivity and specificity for each study were calculated based on the extracted 2×2 table data. Pooled sensitivity and specificity [95% confidence interval (CI)] were used to assess the diagnostic performance of CEUS and O-RADS US for ovarian and adnexal masses. Forest plots and hierarchic summary receiver operating characteristic (HSROC) curves were constructed to graphically represent the results for each system. Diagnostic performance metrics of at least 90% were considered to indicate high performance. Values with P<0.05 were considered statistically significant. A lack of overlap in the 95% CI was also regarded as evidence of a significant difference. We used the I² inconsistency index, Q statistic, and P value to assess heterogeneity. When significant heterogeneity was present (I²>50% or P<0.05), meta-regression analysis was conducted to ascertain the source of heterogeneity. The Deeks funnel plot was used to evaluate the publication bias across all included studies, with P<0.05 indicating the presence of publication bias.

Results

Search results

Through preliminary electronic database searches, a total of 879 articles were identified. After removal of duplicates, 477 articles were retained. Of these, 402 were excluded because they did not match the research topic or the article type was not appropriate. Thus, the full texts of 75 studies were examined for further evaluation, and 54 of these studies were ultimately excluded due to irrelevance, incomplete data, or inability to obtain the full text. Finally, 21 articles were included in the meta-analysis. Figure 1 shows the detailed results for the selection of the included studies. Studies that met the inclusion criteria comprised 5,433 patients, with a total of 5,617 cases of ovarian adnexal masses, and all included studies obtained informed consent from each study participant. Among these 21 studies, 15 evaluated O-RADS US (5,21-34), seven evaluated CEUS (34-40), and one evaluated both O-RADS US and CEUS (34).

Figure 1 Flowchart for literature according to the PRISMA guidelines. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Characteristics of the included studies

The clinical characteristics of the included studies are shown in Table 1, while the study characteristics are summarized in Table 2. For CEUS, three studies were prospective (35-37) and four were retrospective (34,38-40). For O-RADS US, four studies were prospective (23,25,27,32) and 11 were retrospective (5,21,22,24,26,28-31,33,34). The sample size of CEUS studies ranged from 35 to 180 cases, while the sample size of the O-RADS US studies ranged from 73 to 1,014 cases. In the CEUS studies, the average or median age of patients ranged from 38.0 to 57.8 years, while in the O-RADS US studies, it ranged from 35.0 to 54.6 years. The examination was interpreted by a single reader in one study, by two readers in 14 studies, and by at least three readers in three studies; in another four studies, the number of readers was not reported. For studies on CEUS, the reference standard was pathology in all cases. For studies on O-RADS US, the reference standard was pathology in 14 studies, and in one study, the reference standard was either pathology or radiological follow-up (3 months) (27).

Since the original studies universally used either overall CEUS positivity/negativity or O-RADS classification as diagnostic indicators, only 2 of the 21 (9.5%) included studies reported diagnostic performance data for individual variables (35,36). An additional five studies mentioned single variables but neither provided 2×2 contingency tables for individual parameters nor reported specific data on single sonographic features (5,23,25,26,33). Consequently, we were unable to perform analyses on individual ultrasound variables.

Quality assessment

The assessment of bias risk and applicability concerns for the selected studies through use of QUADAS-2 is shown in Figure 2. Four studies (23,34,36,39) were considered to be at high risk in the patient selection domain due to observed inappropriate exclusions (e.g., exclusion of cases with poor image quality), and one study included nonconsecutive cases (5). Regarding the index test domain, only one study did not clarify whether the result interpretation was performed without knowledge of the gold standard (26). For the reference standard domain, all studies were considered low risk because they correctly related to the target condition according to the reference standard, and the interpretation of the gold standard was made without knowledge of other results. Regarding the flow-and-timing domain, two studies had patients who underwent different reference standards (26,27), two studies did not perform data analysis on all patients (25,34), and three studies did not clearly state whether all cases were included in the analysis (28,30,35).

Figure 2 The quality assessment (risk of bias and concerns regarding applicability) for all studies included in the meta-analysis.

Regarding applicability, all studies were considered at low risk in the domains of patient selection, index test, and reference standard.

Publication bias

The publication bias of the included studies in this meta-analysis was examined with the Deeks funnel plot asymmetry test in Figure 3, with a P value of 0.40, indicating no potential publication bias and suggesting that the diagnostic performance was relatively stable.

Figure 3 Deeks funnel plot asymmetry tests for all studies. ESS, effective sample size.

Data synthesis and statistical analysis

A statistical analysis was performed on the diagnostic performance of CEUS and O-RADS in differentiating benign from malignant adnexal masses. Figure 4 displays the forest plots of the two methods. For CEUS, the range of sensitivity in individual studies was 83–99%, with a pooled sensitivity estimate of 93% (95% CI: 87–96%), and the range of specificity in individual studies was 74–97%, with a pooled specificity estimate of 91% (95% CI: 82–95%). The forest plot for CEUS is shown in Figure 4A. The Q test revealed significant heterogeneity among studies in terms of sensitivity and specificity (all P values <0.05). The I² statistic indicated considerable heterogeneity in sensitivity (63.30%) and specificity (83.46%). For O-RADS US, the range of sensitivity in individual studies was 48–100%, with a pooled sensitivity estimate of 94% (95% CI: 87–98%), and the range of specificity in individual studies was 24–94%, with a pooled specificity estimate of 81% (95% CI: 72–88%). The forest plot for O-RADS US is shown in Figure 4B. The Q test revealed significant heterogeneity among studies in terms of sensitivity and specificity (all P values <0.05). The I² statistic indicated considerable heterogeneity in sensitivity (94.76%) and specificity (95.42%).

Figure 4 Coupled forest plots of pooled sensitivity and specificity. Values are pooled estimates with 95% CIs provided in parentheses. Boxes indicate point estimates; horizontal bars, 95% CIs of the individual studies; diamonds, overall effect estimates (top and bottom peaks, overall point estimate; left and right ends, 95% CI); and the dashed line, the line of no effect. (A) Plot showing the results for CEUS. (B) Plot results for O-RADS US. CEUS, contrast-enhanced ultrasound; CI, confidence interval; O-RADS US, Ovarian-Adnexal Reporting and Data System ultrasound classification.

Figure 5 shows the corresponding HSROC curve analysis. The HSROC curve for CEUS (Figure 5A) revealed a considerable visual discrepancy between the 95% confidence region and the 95% prediction region. The HSROC curve for O-RADS (Figure 5B) shows that this discrepancy was more pronounced than that for CEUS.

Figure 5 HSROC plots with summary point and 95% confidence regions. (A) Plot showing the results for CEUS. (B) Plot showing results for O-RADS US. AUC, area under the curve; CEUS, contrast-enhanced ultrasound; CI, confidence interval; HSROC, hierarchic summary receiver operating characteristic; O-RADS US, Ovarian-Adnexal Reporting and Data System ultrasound classification; SENS, sensitivity; SPEC, specificity; SROC, summary receiver operating characteristic.

Meta-regression

As the obtained results [the I² statistic indicated considerable heterogeneity for CEUS and O-RADS in terms of sensitivity (63.30% and 94.76%, respectively) and specificity (83.46% and 95.42%, respectively)] suggested significant heterogeneity, meta-regression analyses were conducted separately for CEUS and O-RADS US, with covariates including the total number of lesions, study design, and reader’s experience to clarify the potential sources of heterogeneity. The results of the meta-analysis are displayed in Table 3 and indicated that for CEUS, reader experience had a significant correlation with its heterogeneity (P<0.05) and could be considered one of the sources of heterogeneity. Other covariates (total number of lesions and study design) were not significantly correlated with the heterogeneity of CEUS. Regarding O-RADS US, compared to prospective studies, retrospective studies had lower sensitivity and higher specificity, but these differences were not statistically significant. Other covariates (total number of lesions and reader’s experience) were not significantly correlated with the heterogeneity of O-RADS US.

Discussion

Summary of evidence

In this systematic review and meta-analysis, we assessed the diagnostic performance of CEUS (seven studies) and O-RADS US (15 studies) for the risk assessment of ovarian and adnexal lesions. This meta-analysis demonstrates that both CEUS and O-RADS US classification exhibit excellent diagnostic performance in differentiating benign from malignant ovarian and adnexal masses. Specifically, both modalities showed high sensitivity (>90%) for detecting malignancy. Notably, CEUS demonstrated significantly higher specificity than did O-RADS US (>90% vs. 81%). Most included studies were retrospective and exhibited substantial heterogeneity, with reader experience being identified as a significant source of heterogeneity for CEUS studies, while the sources of heterogeneity for O-RADS US remained unclear. Through comprehensive literature search, rigorous quality assessment using QUADAS-2 tools, and implementation of appropriate bias control measures, we minimized potential biases in this meta-analysis.

Limitations and strengths

Our study involved several limitations: (I) CEUS and O-RADS US were evaluated in different patient cohorts, and direct comparability was thus lacking. (II) Due to the inherent limitations of meta-analysis, we consider the number of included studies to be small (36), with most being retrospective in design, which may affect the accuracy of the results. (III) The diagnostic performance in multiple studies was determined with a single cutoff risk category, and we did not obtain aggregated results for individual O-RADS US classifications. Therefore, our analytical findings should be interpreted with caution.

Nevertheless, from a clinical perspective, our data remain highly valuable. This study confirms that CEUS holds significant value in the risk assessment of adnexal masses. By using microbubble contrast agents to enhance blood flow imaging quality, CEUS provides more precise hemodynamic evaluation while offering advantages such as absence of radiation and a high safety profile. Additionally, CEUS demonstrates nonlinear effects, is unaffected by respiratory motion, and shows no angular dependence (41). Furthermore, ultrasound contrast agents have minimal side effects, with microbubble diameter being substantially smaller than vascular lumens, exhibiting sufficient stability to remain in circulation for an adequate duration to complete ultrasound imaging (42). Based on our analytical results, CEUS possesses considerable clinical value and should be more widely implemented in the risk assessment of ovarian and adnexal masses, particularly in early-stage tumor screening.

Future research agenda

The limitations to this study also provide directions for future research. First, the number of included studies and their sample sizes were limited, particularly those investigating CEUS. Therefore, large-scale, prospective, multicenter studies are needed to further validate our conclusions and identify the most valuable clinical scenarios for CEUS within the standardized O-RADS framework. Second, due to insufficient primary data, we were unable to conduct an in-depth analysis of the diagnostic performance of both CEUS and O-RADS for BOT—a crucial subgroup that warrants focused investigation in future studies. A promising future direction involves combining the system with artificial intelligence to improve diagnostic accuracy and consistency, as exemplified in the study by Çamur et al. who examined the potential of large language models to master and utilize O-RADS (43). Furthermore, investigating artificial intelligence models that integrate quantitative CEUS parameters with O-RADS morphological features may represent the next-generation solution for achieving more precise and individualized risk assessment.

Conclusions

Both CEUS and O-RADS US have high sensitivity for malignant lesions of the ovary and adnexa. CEUS also has high specificity, while O-RADS US does not. They can serve as effective preoperative diagnostic methods for patients suspected of having ovarian cancer. As O-RADS US and CEUS systems are increasingly being applied in clinical practice, understanding these diagnostic performance results will be helpful. However, due to the aforementioned limitations, large-sample, multicenter studies, and high-quality prospective trials are needed to confirm our analysis and for further investigation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA-DTA reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-49/rc

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-49/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Gray)