Ovarian-Adnexal Reporting Lexicon for MRI: A White Paper of the ACR Ovarian-Adnexal Reporting and Data Systems MRI Committee

ESR Essentials: characterisation and staging of adnexal masses with MRI and CT-practice recommendations by ESUR

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery. This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities. KEY POINTS: MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians. CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery. Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.

ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass, No Acute Symptoms: 2023 Update

Asymptomatic adnexal masses are commonly encountered in daily radiology practice. Although the vast majority of these masses are benign, a small subset have a risk of malignancy, which require gynecologic oncology referral for best treatment outcomes. Ultrasound, using a combination of both transabdominal, transvaginal, and duplex Doppler technique can accurately characterize the majority of these lesions. MRI with and without contrast is a useful complementary modality that can help characterize indeterminate lesions and assess the risk of malignancy is those that are suspicious. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Application of convolutional neural network for differentiating ovarian thecoma-fibroma and solid ovarian cancer based on MRI

BACKGROUND

Ovarian thecoma-fibroma and solid ovarian cancer have similar clinical and imaging features, and it is difficult for radiologists to differentiate them. Since the treatment and prognosis of them are different, accurate characterization is crucial.

PURPOSE

To non-invasively differentiate ovarian thecoma-fibroma and solid ovarian cancer by convolutional neural network based on magnetic resonance imaging (MRI), and to provide the interpretability of the model.

MATERIAL AND METHODS

A total of 156 tumors, including 86 ovarian thecoma-fibroma and 70 solid ovarian cancer, were split into the training set, the validation set, and the test set according to the ratio of 8:1:1 by stratified random sampling. In this study, we used four different networks, two different weight modes, two different optimizers, and four different sizes of regions of interest (ROI) to test the model performance. This process was repeated 10 times to calculate the average performance of the test set. The gradient weighted class activation mapping (Grad-CAM) was used to explain how the model makes classification decisions by visual location map.

RESULTS

ResNet18, which had pre-trained weight, using Adam and one multiple ROI circumscribed rectangle, achieved best performance. The average accuracy, precision, recall, and AUC were 0.852, 0.828, 0.848, and 0.919 (P < 0.01), respectively. Grad-CAM showed areas associated with classification appeared on the edge or interior of ovarian thecoma-fibroma and the interior of solid ovarian cancer.

CONCLUSION

This study shows that convolution neural network based on MRI can be helpful for radiologists in differentiating ovarian thecoma-fibroma and solid ovarian cancer.

O-RADS MRI scoring system: key points for correct application in inexperienced hands

OBJECTIVES

To evaluate the efficacy of the O-RADS MRI criteria in the stratification of risk of malignancy of solid or sonographically indeterminate ovarian masses and assess the interobserver agreement of this classification between experienced and inexperienced radiologists.

METHODS

This single-centre retrospective study included patients from 2019 to 2022 with sonographically indeterminate or solid ovarian masses who underwent MRI with a specific protocol for characterisation according to O-RADS MRI specifications. Each study was evaluated using O-RADS lexicon by two radiologists, one with 17 years of experience in gynaecological radiology and another with 4 years of experience in general radiology. Findings were classified as benign, borderline, or malignant according to histology or stability over time. Diagnostic performance and interobserver agreement were assessed.

RESULTS

A total of 183 patients with US indeterminate or solid adnexal masses were included. Fifty-seven (31%) did not have ovarian masses, classified as O-RADS 1. The diagnostic performance for scores 2-5 was excellent with a sensitivity, specificity, PPV, and NPV of 97.4%, 100%, 96.2%, and 100%, respectively by the experienced radiologist and 96.1%, 92.0%, 93.9%, and 94.8% by the inexperienced radiologist. Interobserver concordance was very high (Kappa index 0.92). Almost all the misclassified cases were due to misinterpretation of the classification similar to reports in the literature.

CONCLUSION

The diagnostic performance of O-RADS MRI determined by either experienced or inexperienced radiologists is excellent, facilitating decision-making with high diagnostic accuracy and high reproducibility. Knowledge of this classification and use of assessment tools could avoid frequent errors due to misinterpretation.

CRITICAL RELEVANCE STATEMENT

Up to 31% of ovarian masses are considered indeterminate by transvaginal US and 32% of solid lesions considered malignant by transvaginal US are benign. The O-RADs MRI accurately classifies these masses, even when used by inexperienced radiologists, thereby avoiding incorrect surgical approaches.

KEY POINTS

• O-RADS MRI accurately classifies indeterminate and solid ovarian masses by ultrasound. • There is excellent interobserver agreement between experienced and non-experienced radiologists. • O-RADS MRI is a helpful tool to assess clinical decision-making in ovarian tumours.

Magnetic resonance imaging-based radiomics analysis of the differential diagnosis of ovarian clear cell carcinoma and endometrioid carcinoma: a retrospective study

PURPOSE

To retrospectively evaluate the diagnostic potential of magnetic resonance imaging (MRI)-based features and radiomics analysis (RA)-based features for discriminating ovarian clear cell carcinoma (CCC) from endometrioid carcinoma (EC).

MATERIALS AND METHODS

Thirty-five patients with 40 ECs and 42 patients with 43 CCCs who underwent pretherapeutic MRI examinations between 2011 and 2022 were enrolled. MRI-based features of the two groups were compared. RA-based features were extracted from the whole tumor volume on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (cT1WI), and apparent diffusion coefficient (ADC) maps. The least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation method was performed to select features. Logistic regression analysis was conducted to construct the discriminating models. Receiver operating characteristic curve (ROC) analyses were performed to predict CCC.

RESULTS

Four features with the highest absolute value of the LASSO algorithm were selected for the MRI-based, RA-based, and combined models: the ADC value, absence of thickening of the uterine endometrium, absence of peritoneal dissemination, and growth pattern of the solid component for the MRI-based model; Gray-Level Run Length Matrix (GLRLM) Long Run Low Gray-Level Emphasis (LRLGLE) on T2WI, spherical disproportion and Gray-Level Size Zone Matrix (GLSZM), Large Zone High Gray-Level Emphasis (LZHGE) on cT1WI, and GLSZM Normalized Gray-Level Nonuniformity (NGLN) on ADC map for the RA-based model; and the ADC value, spherical disproportion and GLSZM_LZHGE on cT1WI, and GLSZM_NGLN on ADC map for the combined model. Area under the ROC curves of those models were 0.895, 0.910, and 0.956. The diagnostic performance of the combined model was significantly superior (p = 0.02) to that of the MRI-based model. No significant differences were observed between the combined and RA-based models.

CONCLUSION

Conventional MRI-based analysis can effectively distinguish CCC from EC. The combination of RA-based features with MRI-based features may assist in differentiating between the two diseases.

O-RADS MRI SCORE: An Essential First-Step Tool for the Characterization of Adnexal Masses

The ovarian-adnexal reporting and data system on magnetic resonance imaging (O-RADS MRI) score is now a well-established tool to characterize pelvic gynecological masses based on their likelihood of malignancy. The main added value of O-RADS MRI over O-RADS US is to correctly reclassify lesions that were considered suspicious on US as benign on MRI. The crucial issue when characterizing an adnexal mass is to determine the presence/absence of solid tissue and thus need to perform gadolinium injection. O-RADS MR score was built on a multivariate analysis and must be applied as a step-by-step analysis: 1) Is the mass an adnexal mass? 2) Is there an associated peritoneal carcinomatosis? 3) Is there any significant amount of fatty content? 4) Is there any wall enhancement? 5) Is there any internal enhancement? 6) When an internal enhancement is detected, does the internal enhancement correspond to solid tissue or not? 7) Is the solid tissue malignant? With its high value to distinguish benign from malignant adnexal masses and its high reproducibility, the O-RADS MRI score could be a valuable tool for timely referral of a patient to an expert center for the treatment of ovarian cancers. Finally, to make a precise diagnosis allowing optimal personalized treatment, the radiologist in gynecological imaging will combine the O-RADS MRI score with many other clinical, biological, and other MR criteria to suggest a pathological hypothesis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

O-RADS MRI risk stratification system: pearls and pitfalls

In 2021, the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee developed a risk stratification system and lexicon for assessing adnexal lesions using MRI. Like the BI-RADS classification, O-RADS MRI provides a standardized language for communication between radiologists and clinicians. It is essential for radiologists to be familiar with the O-RADS algorithmic approach to avoid misclassifications. Training, like that offered by International Ovarian Tumor Analysis (IOTA), is essential to ensure accurate and consistent application of the O-RADS MRI system. Tools such as the O-RADS MRI calculator aim to ensure an algorithmic approach. This review highlights the key teaching points, pearls, and pitfalls when using the O-RADS MRI risk stratification system.Critical relevance statement This article highlights the pearls and pitfalls of using the O-RADS MRI scoring system in clinical practice.Key points• Solid tissue is described as displaying post- contrast enhancement.• Endosalpingeal folds, fimbriated end of the tube, smooth wall, or septa are not solid tissue.• Low-risk TIC has no shoulder or plateau. An intermediate-risk TIC has a shoulder and plateau, though the shoulder is less steep compared to outer myometrium.

The role of gadolinium-based contrast agents in magnetic resonance imaging structured reporting and data systems (RADS)

Among the 28 reporting and data systems (RADS) available in the literature, we identified 15 RADS that can be used in Magnetic Resonance Imaging (MRI). Performing examinations without using gadolinium-based contrast agents (GBCA) has benefits, but GBCA administration is often required to achieve an early and accurate diagnosis. The aim of the present review is to summarize the current role of GBCA in MRI RADS. This overview suggests that GBCA are today required in most of the current RADS and are expected to be used in most MRIs performed in patients with cancer. Dynamic contrast enhancement is required for correct scores calculation in PI-RADS and VI-RADS, although scientific evidence may lead in the future to avoid the GBCA administration in these two RADS. In Bone-RADS, contrast enhancement can be required to classify an aggressive lesion. In RADS scoring on whole body-MRI datasets (MET-RADS-P, MY-RADS and ONCO-RADS), in NS-RADS and in Node-RADS, GBCA administration is optional thanks to the intrinsic high contrast resolution of MRI. Future studies are needed to evaluate the impact of the high T1 relaxivity GBCA on the assignment of RADS scores.

O-RADS MRI to classify adnexal tumors: from clinical problem to daily use

Eighteen to 35% of adnexal masses remain non-classified following ultrasonography, leading to unnecessary surgeries and inappropriate management. This finding led to the conclusion that ultrasonography was insufficient to accurately assess adnexal masses and that a standardized MRI criteria could improve these patients' management. The aim of this work is to present the different steps from the identification of the clinical issue to the daily use of a score and its inclusion in the latest international guidelines. The different steps were the following: (1) preliminary work to formalize the issue, (2) physiopathological analysis and finding dynamic parameters relevant to increase MRI performances, (3) construction and internal validation of a score to predict the nature of the lesion, (4) external multicentric validation (the EURAD study) of the score named O-RADS MRI, and (5) communication and education work to spread its use and inclusion in guidelines. Future steps will include studies at patients' levels and a cost-efficiency analysis. Critical relevance statement We present translating radiological research into a clinical application based on a step-by-step structured and systematic approach methodology to validate MR imaging for the characterization of adnexal mass with the ultimate step of incorporation in the latest worldwide guidelines of the O-RADS MRI reporting system that allows to distinguish benign from malignant ovarian masses with a sensitivity and specificity higher than 90%. Key points • The initial diagnostic test accuracy studies show the limitation of a preoperative assessment of adnexal masses using solely ultrasonography.• The technical developments (DCE/DWI) were investigated with the value of dynamic MRI to accurately predict the nature of benign or malignant lesions to improve management.• The first developing score named ADNEX MR Score was constructed using multiple easily assessed criteria on MRI to classify indeterminate adnexal lesions following ultrasonography.• The multicentric adnexal study externally validated the score creating the O-RADS MR score and leading to its inclusion for daily use in international guidelines.

Distribution of prostate specific membrane antigen (PSMA) on PET-MRI in patients with and without ovarian cancer

OBJECTIVES

Ovarian cancer is the most lethal cancer and future research needs to focus on the early detection and exploration of new therapeutic agents. The objectives of this proof-of-concept study are to assess the feasibility of PSMA 18F-DCFPyl PET/MR imaging for detecting ovarian cancer and to evaluate the PSMA distribution in patients with and without ovarian cancer.

METHODS

This prospective pilot proof-of-concept study in patients with and without ovarian cancers occurred between October 2017 and January 2020. Patients were recruited from gynecologic oncology or hereditary ovarian cancer clinics, and underwent surgical removal of the uterus and ovaries for gynecologic indications. PSMA 18F-DCFPyl PET/MRI was obtained prior to standard of care surgery.

RESULTS

Fourteen patients were scanned: four patients with normal ovaries, six patients with benign ovarian lesions, and four patients with malignant ovarian lesions. Tracer uptake in normal ovaries (SUVmax = 2.8 ± 0.4) was greater than blood pool (SUVmax = 1.8 ± 0.5, p < 0.0001). Tracer uptake in benign ovarian lesions (2.2 ± 1.0) did not differ significantly from blood pool (p = 0.331). Tracer uptake in ovarian cancer (SUVmax = 7.8 ± 3.8) was greater than blood pool (p < 0.0001), normal ovaries (p = 0.0014), and benign ovarian lesions (p = 0.005).

CONCLUSION

PET/MR imaging detected PSMA uptake in ovarian cancer, with little to no uptake in benign ovarian findings. These results are encouraging and further studies in a larger patient cohort would be useful to help determine the extent and heterogeneity of PSMA uptake in ovarian cancer patients.

Improving risk stratification of indeterminate adnexal masses on MRI: What imaging features help predict malignancy in O-RADS MRI 4 lesions?

PURPOSE

Ovarian-Adnexal Reporting and Data System (O-RADS) MRI uses a 5-point scale to establish malignancy risk in sonographically-indeterminate adnexal masses. The management of O-RADS MRI score 4 lesions is challenging, as the prevalence of malignancy is widely variable (5-90%). We assessed imaging features that may sub-stratify O-RADS MRI 4 lesions into malignant and benign subgroups.

METHOD

Retrospective single-institution study of women with O-RADS MRI score of 4 adnexal masses between April 2021-August 2022. Imaging findings were assessed independently by 2 radiologists according to the O-RADS lexicon white paper. MRI and clinical findingswere compared between malignant and benign adnexal masses, and inter-reader agreement was calculated.

RESULTS

Seventy-four women (median age 52 years, IQR 36-61) were included. On pathology, 41 (55.4%) adnexal masses were malignant. Patients with malignant masses were younger (p = 0.02) with higher CA-125 levels (p = 0.03). Size of solid tissue was greater in malignant masses (p = 0.01-0.04). Papillary projections and larger solid portion were more common in malignant lesions; irregular septations and predominantly solid composition were more frequent in benign lesions (p < 0.01). Solid tissue of malignant lesions was more often hyperintense on T2-weighted and diffusion-weighted imaging (p ≤ 0.03). Other imaging findings were not significantly different (p = 0.09-0.77). Inter-reader agreement was excellent-good for most features (ICC = 0. 662-0.950; k = 0. 650-0.860).

CONCLUSION

Various MRI and clinical features differed between malignant and benign O-RADS MRI score 4 adnexal masses. O-RADS MRI 4 lesions may be sub-stratified (high vs low risk) based on solid tissue characteristics and CA-125 levels.

Gynecologic oncology tumor board: the central role of the radiologist

This manuscript is a collaborative, multi-institutional effort by members of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease Focus Panel and the European Society of Urogenital Radiology Women Pelvic Imaging working group. The manuscript reviews the key role radiologists play at tumor board and highlights key imaging findings that guide management decisions in patients with the most common gynecologic malignancies including ovarian cancer, cervical cancer, and endometrial cancer.

A preoperative nomogram incorporating CT to predict the probability of ovarian clear cell carcinoma

OBJECTIVES

To evaluate clinical, laboratory, and radiological variables from preoperative contrast-enhanced computed tomography (CECT) for their ability to distinguish ovarian clear cell carcinoma (OCCC) from non-OCCC and to develop a nomogram to preoperatively predict the probability of OCCC.

METHODS

This IRB-approved, retrospective study included consecutive patients who underwent surgery for an ovarian tumor from 1/1/2000 to 12/31/2016 and CECT of the abdomen and pelvis ≤90 days before primary debulking surgery. Using a standardized form, two experienced oncologic radiologists independently analyzed imaging features and provided a subjective 5-point impression of the probability of the histological diagnosis. Nomogram models incorporating clinical, laboratory, and radiological features were created to predict histological diagnosis of OCCC over non-OCCC.

RESULTS

The final analysis included 533 patients with surgically confirmed OCCC (n = 61) and non-OCCC (n = 472); history of endometriosis was more often found in patients with OCCC (20% versus 3.6%; p < 0.001), while CA-125 was significantly higher in patients with non-OCCC (351 ng/mL versus 70 ng/mL; p < 0.001). A nomogram model incorporating clinical (age, history of endometriosis and adenomyosis), laboratory (CA-125) and imaging findings (peritoneal implant distribution, morphology, laterality, and diameter of ovarian lesion and of the largest solid component) had an AUC of 0.9 (95% CI: 0.847, 0.949), which was comparable to the AUCs of the experienced radiologists' subjective impressions [0.8 (95% CI: 0.822, 0.891) and 0.9 (95% CI: 0.865, 0.936)].

CONCLUSIONS

A presurgical nomogram model incorporating readily accessible clinical, laboratory, and CECT variables was a powerful predictor of OCCC, a subtype often requiring a distinctive treatment approach.

Adnexal Mass Imaging: Contemporary Guidelines for Clinical Practice

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

Practical Tips for Reporting Adnexal Lesions Using O-RADS MRI

The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI risk stratification system provides a standardized lexicon and evidence-based risk score for evaluation of adnexal lesions. The goals of the lexicon and risk score are to improve report quality and communication between radiologists and clinicians, reduce variability in the reporting language, and optimize management of adnexal lesions. The O-RADS MRI risk score is based on the presence or absence of specific imaging features, including the lipid content, enhancing solid tissue, number of loculi, and fluid type. The probability of malignancy ranges from less than 0.5% when there are benign features to approximately 90% when there is solid tissue with a high-risk time-intensity curve. This information can aid in optimizing management of patients with adnexal lesions. The authors present an algorithmic approach to the O-RADS MRI risk stratification system and highlight key teaching points and common pitfalls. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.

MR Imaging of Gynecologic Tumors: Pearls, Pitfalls, and Tumor Mimics

MR imaging is the modality of choice for the pre-treatment evaluation of patients with gynecologic malignancies, given its excellent soft tissue contrast and multi-planar capability. However, it is not without pitfalls. Challenges can be encountered in the assessment of the infiltration of myometrium, vagina, cervical stroma, and parametria, which are crucial prognostic factors for endometrial and cervical cancers. Other challenges can be encountered in the distinction between solid and non-solid tissue and in the identification of peritoneal carcinomatosis for the sonographically indeterminate adnexal mass.

Adnexal Lesion Imaging: Past, Present, and Future

Currently, imaging is part of the standard of care for patients with adnexal lesions prior to definitive management. Imaging can identify a physiologic finding or classic benign lesion that can be followed up conservatively. When one of these entities is not present, imaging is used to determine the probability of ovarian cancer prior to surgical consultation. Since the inclusion of imaging in the evaluation of adnexal lesions in the 1970s, the rate of surgery for benign lesions has decreased. More recently, data-driven Ovarian-Adnexal Reporting and Data System (O-RADS) scoring systems for US and MRI with standardized lexicons have been developed to allow for assignment of a cancer risk score, with the goal of further decreasing unnecessary interventions while expediting the care of patients with ovarian cancer. US is used as the initial modality for the assessment of adnexal lesions, while MRI is used when there is a clinical need for increased specificity and positive predictive value for the diagnosis of cancer. This article will review how the treatment of adnexal lesions has changed due to imaging over the decades; the current data supporting the use of US, CT, and MRI to determine the likelihood of cancer; and future directions of adnexal imaging for the early detection of ovarian cancer.

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.

Impact of DWI and ADC values in Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score

PURPOSE

Introduce DWI and quantitative ADC evaluation in O-RADS MRI system and observe how diagnostic performance changes. Assess its validity and reproducibility between readers with different experience in female pelvic imaging. Finally, evaluate any correlation between ADC value and histotype in malignant lesions.

MATERIALS AND METHODS

In total, 173 patients with 213 indeterminate adnexal masses (AMs) on ultrasound were subjected to MRI examination, from which 140 patients with 172 AMs were included in the final analysis. Standardised MRI sequences were used, including DWI and DCE sequences. Two readers, blinded to histopathological data, retrospectively classified AMs according to the O-RADS MRI scoring system. A quantitative analysis method was applied by placing a ROI on the ADC maps obtained from single-exponential DWI sequences. AMs considered benign (O-RADS MRI score 2) were excluded from the ADC analysis.

RESULTS

Excellent inter-reader agreement was found in the classification of lesions according to the O-RADS MRI score (K = 0.936; 95% CI). Two ROC curves were created to determine the optimal cut-off value for the ADC variable between O-RADS MRI categories 3-4 and 4-5, respectively, 1.411 × 10^-3 mm²/sec and 0.849 × 10^-3 mm²/sec. Based on these ADC values, 3/45 and 22/62 AMs were upgraded, respectively, to score 4 and 5, while 4/62 AMs were downgraded to score 3. ADC values correlated significantly with the ovarian carcinoma histotype (p value < 0.001).

CONCLUSION

Our study demonstrates the prognostic potential of DWI and ADC values in the O-RADS MRI classification for better radiological standardisation and characterisation of AMs.

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

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

Impact of Adding Mean Apparent Diffusion Coefficient (ADCmean) Measurements to O-RADS MRI Scoring For Adnexal Lesions Characterization: A Combined O-RADS MRI/ADCmean Approach

RATIONALE AND OBJECTIVES

Evaluate the impact of adding mean apparent diffusion coefficient (ADCmean) measurements to the Ovarian-Adnexal Imaging Reporting and Data System MRI (O-RADS MRI) scoring for adnexal lesion characterization using a combined O-RADS MRI/ADCmean reading approach.

MATERIALS AND METHODS

This prospective study included 90 women who underwent pelvic MRI for adnexal lesions diagnosis and characterization. Two readers scored the adnexal lesions using the O-RADS MRI scoring independently and in consensus. A third reader calculated ADCmean measurements. The final diagnoses were determined by histo-pathology (n = 77) or follow-up imaging (n = 13). Areas under the curves (AUCs) and diagnostic performance metrics were calculated for the O-RADS MRI scoring, ADCmean, and combined O-RADS MRI/ADCmean thresholds. P-value <0.05 was significant.

RESULTS

116 adnexal lesions (71 benign, 45 malignant) were analyzed. The optimal thresholds to predict malignant adnexal lesions were O-RADS MRI score >3 and ADCmean value ≤1.08 × 10^-3 mm²/s (AUC 0.926 and 0.823; sensitivity 97.7% and 95.5%; specificity 87.3% and 68%; positive predictive value (PPV) 83% and 66.2%; positive likelihood ratio (PLR) 7.7 and 3.08, respectively). Compared to the O-RADS MRI scoring, a combined threshold of O-RADS MRI >3/ADCmean ≤1.08 × 10^-3 mm²/s, yielded a reduction of false positives, a significant increase in the specificity (97.1%, p = 0.005), PPV (95.4%, p = 0.002), and PLR (33.1, p <0.0001), and non-significant change in the AUC (0.953, p = 0.252), and sensitivity (93.3%, p = 0.467).

CONCLUSION

The diagnostic performance of O-RADS MRI scoring to characterize adnexal lesions could be improved by adding the ADCmean values through reducing false positives, increasing specificity, and maintaining good sensitivity.

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

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

Fat-containing adnexal masses on MRI: solid tissue volume and fat distribution as a guide for O-RADS Score assignment

PURPOSE

To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy.

METHODS

This retrospective, single-center study included patients with fat-containing adnexal masses on MRI during 2008-2021. Two radiologists independently reviewed overall size (Sizeoverall), size of any solid tissue (Sizeanysolid), size of solid tissue that was not Rokitansky nodule (Sizenon-Rokitansky), and fat distribution. Wilcoxon test, Fisher-exact test, and ROC curve analysis were performed. Reference standard was pathology or follow-up > 24 months.

RESULTS

188 women (median age 35 years) with 163 benign and 25 malignant lesions were included. Sizeoverall (R1, 9.9 cm vs 5.9 cm; R2, 12.4 cm vs 6.0 cm), Sizeanysolid (R1, 5.1 cm vs 1.2 cm; R2, 3.2 cm vs 0.0 cm), Sizenon-Rokitansky (R1, 5.1 cm vs 0.0 cm; R2, 3.1 cm vs 0.0 cm), and fat distribution differed significantly between malignant and benign lesions (p < 0.01). Area under ROC curve was greatest using Sizenon-Rokitansky (R1, 0.83; R2, 0.86) vs Sizeoverall (R1, 0.78; R2, 0.81) or Sizeanysolid (R1, 0.79; R2, 0.81), though differences were non-significant (p = 0.48-0.93). Cutoffs for Sizenon-Rokitansky (R1, ≥ 1.2 cm; R2, ≥ 1.0 cm) yielded sensitivity and specificity of 0.72 and 0.93 (R1) and 0.76 and 0.95 (R2). Among immature teratomas, 85.7% displayed scattered fat.

CONCLUSION

Overall size, size of (any or non-Rokitansky-nodule) solid tissue, and fat distribution differed between benign and malignant fat-containing adnexal masses. Incorporating these would constitute simple and practical approaches to refining O-RADS MRI scoring.

O-RADS MRI: A Systematic Review and Meta-Analysis of Diagnostic Performance and Category-wise Malignancy Rates

Background US-indeterminate adnexal lesions remain an important indication for gynecologic surgery. MRI can serve as a problem-solving tool through the use of the Ovarian-Adnexal Imaging Reporting and Data System (O-RADS) MRI lexicon, which is based on the ADNEX MR scoring system. Purpose To perform a systematic review and meta-analysis of the diagnostic performance of pelvic MRI interpreted using the ADNEX or O-RADS MRI stratification systems to characterize US-indeterminate adnexal lesions and of the category-wise malignancy rates. Materials and Methods A systematic literature search from May 2013 (publication of the ADNEX MR score) to September 2022 was performed. Studies reporting the use of pelvic MRI interpreted with the ADNEX or O-RADS MRI systems to characterize US-indeterminate adnexal lesions, with pathologic examination and/or follow-up as the reference standard, were included. Summary estimates of diagnostic performance were obtained with the bivariate random-effects model, while category-wise summary malignancy rates of O-RADS MRI 2, 3, 4, and 5 lesions were obtained with a random-effects model. Effects of covariates on heterogeneity and diagnostic performance were investigated through meta-regression. Results Thirteen study parts from 12 studies (3731 women, 4520 adnexal lesions) met the inclusion criteria. Diagnostic performance meta-analysis for 4012 lesions found a 92% summary sensitivity (95% CI: 88, 95) and a 91% summary specificity (95% CI: 89, 93). The meta-analysis of malignancy rates for 3641 lesions showed summary malignancy rates of 0.1% (95% CI: 0, 1) among O-RADS MRI 2 lesions, 6% (95% CI: 3, 9) among O-RADS MRI 3 lesions, 60% (95% CI: 52, 67) among O-RADS MRI 4 lesions, and 96% (95% CI: 92, 99) among O-RADS MRI 5 lesions. Conclusion Pelvic MRI interpreted with the Ovarian-Adnexal Reporting and Data System (O-RADS) MRI lexicon had high diagnostic performance for the characterization of US-indeterminate adnexal lesions. Summary estimates of malignancy rates in the O-RADS MRI 4 and O-RADS MRI 5 categories were higher than predicted ones. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Lee and Kang in this issue.

MRI of Borderline Epithelial Ovarian Tumors: Pathologic Correlation and Diagnostic Challenges

Borderline epithelial ovarian tumors are a distinct pathologic entity characterized by increased epithelial proliferation and nuclear atypia, but without frank stromal invasion. Borderline tumor (BT) is now considered to represent an intermediate phase in the stepwise progression from benign to malignant ovarian epithelial tumor. Since BTs commonly manifest at early stages in women of reproductive age and are associated with a good prognosis, making the correct diagnosis is important in determining whether a patient is a candidate for fertility-sparing surgery. There are six histologic BT subtypes (serous, mucinous, seromucinous, endometrioid, clear cell, and Brenner), and each has different MRI features, reflecting their unique histologic architectures. Radiologists should be aware of the MRI features that can suggest BTs. These features include a hyperintense papillary architecture with hypointense internal branching, which can be observed with serous and seromucinous BTs on T2-weighted images; aggregates of microcysts that have hypointensity on T2-weighted images and reticular enhancement on contrast-enhanced T2-weighted images, which can be seen with mucinous BTs; and moderately high signal intensity on diffusion-weighted images along with relatively high apparent diffusion coefficient values, which can be observed regardless of the histologic subtype. Nevertheless, because the imaging features of BTs overlap with those of many benign lesions (eg, cystadenoma and cystadenofibroma, decidualized endometriosis, and polypoid endometriosis) and malignant tumors (ovarian cancers and metastases), histologic confirmation is required for the final diagnosis. Special emphasis is placed on the MRI features of BTs, pathologic correlation, and the challenges related to diagnosis. ^©RSNA, 2022.

Imaging characteristics of ovarian sclerosing stromal tumor

Objectives

This study was designed to evaluate the specific imaging features of ovarian sclerosing stromal tumor (SST), improve its accuracy as well as the specificity of imaging diagnosing, and prevent overestimation of malignancy to reduce unnecessary surgical procedures.

Methods

Eight patients with magnetic resonance imaging (MRI) and six with computed tomography (CT) images were analyzed in this retrospective observational study. All the cases were confirmed by postoperative pathological examination as those of ovarian SST. Imaging and pathological features were also evaluated.

Results

All the 14 masses displayed cystic and solid components with outer surface of tumors contained a capsular and complete smooth rim. Eight tumors of MRI exhibited “lake-island” sign on T2 weighted imaging (T2WI). Two of the 6 CT cases displayed a flaky calcification. One case showed as a multiloculated cystic mass with irregularly thickened septae and the tumor wall. The solid components in other 13 masses were comb- or wheel-like enhanced. After injection of contrast agent, the solid components in 8 cases (57.1%) appeared as early enhancement, whereas the other 6 cases (42.9%) appeared as progressive enhanced, and the cystic components of all the cases had no enhancement in the whole course. Vascular flow signals or/and marked enhancement of the blood vessels were found in 12 lesions (85.7%). Pathological examination demonstrated pseudolobule patterns, round to spindle shaped cells, collagenous areas, edematous hypocellular areas and prominent vasculatures.

Conclusions

The results demonstrated that MRI with “lake-island” signs on T2WI and MRI/CT dynamic enhancement could potentially play a critical role in facilitating appropriate diagnosis preoperatively.

Discriminating Between Benign and Malignant Solid Ovarian Tumors Based on Clinical and Radiomic Features of MRI

RATIONALE AND OBJECTIVES

To develop and validate a combined model integrating clinical and radiomic features to non-invasive discriminate between the benign and malignant solid ovarian tumors.

MATERIALS AND METHODS

A total of 148 patients with 156 solid ovarian tumors (86 benign and 70 malignant tumors) were included in this study. The dataset was split into the training and the test set with a ratio of 8:2 using stratified random sampling. 12 clinical features and 1612 radiomic features were extracted from each tumor. These features were selected by least absolute shrinkage and selection operator (Lasso). Three classification models were built using extreme gradient boosting (XGB) algorithm: clinical model, radiomic model, combined model. The area under the receiver operating characteristic curve (AUC), accuracy, precision and sensitivity were analyzed to evaluate the performance of these models.

RESULTS

All of the three models obtained good performances in differentiating benign with malignant solid ovarian tumors in both training and test sets. The AUC, accuracy, precision, sensitivity of clinical model and radiomic model in test set were 0.847 (95% confidence interval (CI), 0.707-0.986, p <0.01), 0.774, 0.769, 0.714, and 0.807 (95%CI, 0.652-0.961, p <0.05), 0.677, 0.643, 0.643, respectively. Combined model had the best prediction results, the AUC, accuracy, precision and sensitivity were 0.954 (95%CI, 0.862-1.0, p <0.01), 0.839, 0.909 and 0.714 in test set.

CONCLUSION

Radiomics based on machine learning can be helpful for radiologists in differentiating the benign and malignant solid ovarian tumors.

T2-weighted imaging hypointensity in an ovarian lesion: is it a benign finding?

Objective

To evaluate whether the presence of a hypointense signal at T2-weighted imaging in a solid ovarian lesion on magnetic resonance imaging is a predictor of stability and benignity.

Methods

This is a single center study, prospectively read with retrospective acquired data. The database was searched for patients who underwent magnetic resonance imaging between January 2008 and October 2019 and whose reports mentioned solid ovarian lesions with low signal on T2-weighted imaging. A total of 47 nodules were included. A radiologist who was blinded to the clinical indication for magnetic resonance imaging and original reports evaluated the cases. Objective and subjective criteria of ovarian lesions in magnetic resonance imaging were evaluated.

Results

Thirty-five nodules were considered benign/stable and 12 were considered non-stable. The analysis showed that the non-stable lesions showed statistically more hyperintensity at T1-weighted imaging compared to the stable lesions.

Conclusion

T2-weighted imaging hypointensity can be considered a predictor of stability in solid ovarian lesions when associated with iso/hypointensity in T1-weighted imaging.

Benign-appearing Incidental Adnexal Cysts at US, CT, and MRI: Putting the ACR, O-RADS, and SRU Guidelines All Together

Adnexal cysts are a common incidental finding at US, CT, and MRI but have historically caused a diagnostic dilemma for determining when to follow up and how to manage them. Characteristic imaging features of simple adnexal cysts include a simple fluid collection with smooth walls and no solid or vascular components. Day-to-day practice guidelines were recently updated to reflect the overwhelming evidence that incidental cystic adnexal masses are almost always benign. Three major consensus articles on adnexal cystic masses were published between 2019 and 2020: the Society of Radiologists in Ultrasound (SRU) consensus update on adnexal cysts, the Ovarian-Adnexal Reporting and Data System (O-RADS) US consensus guideline, and the American College of Radiology (ACR) white paper on the management for incidental adnexal findings at CT and MRI. All three standardize reporting terminology, are based on evidence-based data and institutional practice patterns, and apply to nonpregnant women of average risk for ovarian cancer. While there are small differences in follow-up recommendations based on size thresholds, the goal of each is the same-to limit unnecessary imaging follow-up and, by doing so, save the patient time, money, and anxiety. For the diagnostic radiologist to use these guidelines, it is essential that the entire mass is visualized well. Without adequate visualization, further characterization of the mass may be necessary. To put it all together, the SRU consensus guideline and ACR white paper are easily applied in day-to-day practice for masses that are O-RADS 2 and below. An invited commentary by Patel is available online. The online slide presentation from the RSNA Annual Meeting is available for this article. ^©RSNA, 2022.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

O-RADS MRI Risk Stratification System: Guide for Assessing Adnexal Lesions from the ACR O-RADS Committee

MRI plays an important role as a secondary test or problem-solving modality in the evaluation of adnexal lesions depicted at US. MRI has increased specificity compared with US, decreasing the number of false-positive diagnoses for malignancy and thereby avoiding unnecessary or over-extensive surgery in patients with benign lesions or borderline tumors, while women with possible malignancies can be expeditiously referred for oncologic surgical evaluation. The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee is an international collaborative effort formed under the direction of the American College of Radiology and includes a diverse group of experts on adnexal imaging and management who developed the O-RADS MRI risk stratification system. This scoring system assigns a probability of malignancy based on the MRI features of an adnexal lesion and provides information to facilitate optimal patient management. The widespread implementation of a codified reporting system will lead to improved interpretation agreement and standardized communication between radiologists and referring physicians. In addition, it will allow for high-quality multi-institutional collaborations-an important unmet need that has hampered the performance of high-quality research in this area in the past. This article provides guidelines on using the O-RADS MRI risk stratification system in clinical practice, as well as in the educational and research settings.

Predictors of malignancy in incidental adnexal lesions identified on CT in patients with prior non-ovarian cancer

PURPOSE

To identify imaging features in incidental adnexal lesions which are associated with malignancy on portal venous phase contrast-enhanced CT in patients with known non-ovarian cancer.

MATERIALS AND METHODS

This IRB-approved, HIPAA-compliant retrospective study was performed at a tertiary cancer center. Portal venous phase contrast-enhanced CT from January 2010 to December 2015 was reviewed to identify women with non-ovarian malignancy and incidental adnexal lesion, with mean 18 months (range 1-80 months) to definitive diagnosis or last imaging follow-up. Imaging features of adnexal lesions were recorded (size, laterality, shape, attenuation, and composition) and correlated with outcome (benign or malignant) using univariate and multivariate logistic regression analysis. A point-based system was used to predict likelihood of malignancy.

RESULTS

Of 276 women (mean age 45 years), 216 (78.3%) had benign lesions, 58 (21.0%) ovarian metastasis, and 2 (0.7%) had primary ovarian malignancy. On logistic regression model, lesion size > 5 cm (p-value, OR, 95% CI 0.01, 9.11, 1.70-48.87), bilaterality (< 0.0001, 28.34, 7.46-107.67), irregular shape (0.01, 12.31, 1.61-94.05), higher-than-simple-fluid attenuation (< 0.0001, 28.27, 5.65-141.59), and heterogeneous composition (0.0017, 10.75, 2.45-47.23) were associated with malignant outcome (AUC 0.97). A point-based system incorporating these five features (possible 0-5 points) had AUC of 0.97. Rate of malignancy was 0% (0/147) if none of the features of malignancy were present, 12.7% (8/63) if one feature was present, 51.7% (15/29) if two features were present, and 100% (37/37) if three or more features present.

CONCLUSION

Risk of malignancy of incidental adnexal lesions in women with prior non-ovarian cancer can be estimated based on lesion features seen on portal venous phase contrast-enhanced CT.

Accuracy of Magnetic Resonance Imaging for Identifying Ovarian Cancer in a Community-Based Setting

Introduction: Many ovarian or adnexal masses have an indeterminate appearance on ultrasound that can raise concerns about cancer. Although magnetic resonance imaging (MRI) has been reported to reliably distinguish between benign and malignant masses, studies evaluating the accuracy of MRI in community-based practice settings are lacking.

Methods: Women who underwent MRI to further evaluate an ultrasound-detected adnexal mass in 2016–2017 within a large community-based health system were identified. MRI reports were classified as favoring malignancy, benign disease, or indeterminate, blinded to pathological outcome. With a minimum of 2 years of follow-up, all ovarian cancers and borderline tumors were identified, and the accuracy of MRI assessment was determined.

Results: Among 338 women who had MRI to evaluate an adnexal mass, 144 (42.6%) subsequently underwent surgery. MRI favored malignancy in 7 (4.9%) cases, benign disease in 89 (62.2%) cases, and was indeterminate in 48 (33.6%) cases. Of the seven cases in which MRI favored malignancy, two cancers and five benign tumors were found. An additional 10 cases of cancer or borderline tumor were found among women who had MRI reports that were read as indeterminate (n = 6) or that favored benign disease (n = 4). The sensitivity, specificity, positive predictive value, and negative predictive value of an MRI favoring malignancy were 16.7%, 96.2%, 28.5%, and 92.7%, respectively.

Discussion: In a large community-based setting, an MRI favoring malignancy was more likely to be associated with benign disease than cancer and identified only 16.7% of true malignant cases. The findings suggest that the ability of MRI to differentiate between benign and malignant adnexal masses in community-based practice settings is currently limited.

Diagnostic accuracy and validity of the O-RADS MRI score based on a simplified MRI protocol: a single tertiary center retrospective study

BACKGROUND

Adnexal masses (AM) are a common gynecological problem. It is important to use a reliable imaging method in the differentiation of benign and malignant AMs.

PURPOSE

To assess the accuracy and validity of the O-RADS magnetic resonance imaging (MRI) score for characterizing AM using a simplified MRI protocol.

MATERIAL AND METHODS

The study population comprised 332 women who underwent MRI due to the detection of indeterminate AM on ultrasonography between January 2018 and June 2020. An experienced radiologist calculated the O-RADS MRI score into five categories, using an MRI protocol with a simplified dynamic study. Sensitivity, specificity, positive and negative predictive values, and area under the curve (AUC) were calculated (cutoff for malignancy, score ≥ 4). The reference standard was histopathologic diagnosis or imaging findings during >24 months of follow-up.

RESULTS

Of 237 AMs, 28 (11.9%) were malignant. The malignancy rates of AMs with scores of 1, 2, 3, 4, and 5 were 0% (0/12), 0% (0/111), 1.2% (1/77), 50% (10/20), and 100% (17/17), respectively. The O-RADS MRI score showed 96.3% sensitivity, 95.2% specificity, and 95.3% accuracy in malignancy prediction. The AUC for the differentiation of benign and malignant masses were 0.983. False positivity rate was high in cases with an O-RADS MRI score of 4 (50%).

CONCLUSION

The O-RADS MRI score, based on a simplified MRI protocol, has high accuracy and validity in distinguishing benign from malignant sonographically indeterminate AMs. Its use in clinical practice can classify the malignancy risks of masses and prevent unnecessary surgery in benign lesions.

Magnetic Resonance Spectroscopy for Risk Stratification of Sonographically Indeterminate Ovarian Neoplasms: Preliminary Study

We aim to assess the additional value of diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) for the risk stratification of sonographically indeterminate ovarian neoplasms. A total of 21 patients with diagnosed adnexal masses between 2014 and 2017 were divided into malignant (four serous cystadenocarcinomas, four endometrioid carcinomas, three clear cell carcinomas, and one carcinosarcoma) and benign (four cystadenomas, two teratomas, one fibroma, one endometrioma, and one corpus luteal cyst) groups. An apparent diffusion coefficient (ADC) value of 1.27 × 10^-3 mm²/s was considered as the optimal threshold in distinguishing malignant from benign ovarian tumors (sensitivity and specificity: 100% and 77.8%, respectively). Choline peaks were detected in six of seven O-RADS (Ovarian-Adnexal Imaging-Reporting Data System) 4 lesions and corrected all of the DWI false-negative clear cell carcinoma. Based on the presence of the choline peaks, the diagnostic performance of MRS showed a sensitivity of 77.8%, a specificity of 100%, and an accuracy of 85.7%, respectively. In conclusion, MRS could potentially play a complementary role for DWI in tumor characterization, particularly for O-RADS 4 tumors or clear cell carcinomas.

O-RADS MRI score: analysis of misclassified cases in a prospective multicentric European cohort

OBJECTIVE

To retrospectively review the causes of categorization errors using O-RADS-MRI score and to determine the presumptive causes of these misclassifications.

METHODS

EURAD database was retrospectively queried to identify misclassified lesions. In this cohort, 1194 evaluable patients with 1502 pelvic masses (277 malignant / 1225 benign lesions) underwent standardized MRI to characterize adnexal masses with histology or 2 years' follow-up as a reference standard. An expert radiologist reviewed cases with two junior radiologists and lesions termed misclassified if malignant lesion was scored ≤ 3, a benign lesion was scored ≥ 4, the site of origin was incorrect, or a non-adnexal mass was incorrectly categorized as benign or malignant.

RESULTS

There were 139 / 1502 (9.2%) misclassified masses in 116 women including 109 adnexal and 30 non-adnexal masses. False-negative cases corresponded to 16 borderline or invasive malignant adnexal masses rated score ≤ 3 (16 / 139, 11.5%). False-positive cases corresponded to 88 benign masses were rated score 4 (67 / 139, 48.2%) or 5 (18 / 139,12.9%) or considered suspicious non-adnexal lesions (3 / 139, 2.2%). Misclassifications were only due to origin error in 12 adnexal masses (8 benign, 4 malignant) (8.6%, 12 / 139) and 23 non-adnexal masses (18 benign, 5 malignant,16.5%, 23 / 139) perceived respectively as non-adnexal and adnexal masses. Interpretive error (n = 104), failure to recognize technical insufficient exams (n = 9), and perceptual errors (n = 4) were found. Most interpretive was due to misinterpretation of solid tissue or incorrect assignment of mass origin. Eighty-four out of 139 cases were correctly reclassified by the readers with strict adherence to the score rules.

CONCLUSION

Most errors were due to misinterpretation of solid tissue or incorrect assignment of mass origin.

KEY POINTS

• Prospective assignment of O-RADS-MRI score resulted in misclassification of 9.25% of sonographically indeterminate pelvic masses. • Most errors were interpretive (74.8%) due to misinterpretation of solid tissue as defined by the lexicon or incorrect assignment of mass origin. • Pelvic inflammatory disease is a common source of misclassification (8.9%) (12 / 139).

Contemporary Guidelines for Adnexal Mass Imaging: A 2020 Update

Incidental adnexal masses are commonly encountered at ultrasound, computed tomography, and magnetic resonance imaging. Since many of these lesions are surgically resected and ultimately found to be benign, patients may be exposed to personal and economic costs related to unnecessary oophorectomy. Thus, accurate non-invasive risk stratification of adnexal masses is essential for optimal management and outcomes. Multiple consensus guidelines in radiology have been published to assist in characterization of these masses as benign, indeterminate, or likely malignant. In the last two years, several new and updated stratification systems for assessment of incidental adnexal masses have been published. The purpose of this article is to offer a concise review of four recent publications: ACR 2020 update on the management of incidental adnexal findings on CT and MRI, SRU 2019 consensus update on simple adnexal cysts, O-RADS ultrasound risk stratification system (2020), and O-RADS MRI risk stratification system (2020).