Triage for surgical management of ovarian tumors in asymptomatic women: assessment of an ultrasound-based scoring system

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment

Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed with multimodal US. Purpose To develop DL algorithms for the automated classification of benign versus malignant ovarian tumors assessed with US and to compare algorithm performance to Ovarian-Adnexal Reporting and Data System (O-RADS) and subjective expert assessment for malignancy. Materials and Methods This retrospective study included consecutive women with ovarian tumors undergoing gray scale and color Doppler US from January 2019 to November 2019. Histopathologic analysis was the reference standard. The data set was divided into training (70%), validation (10%), and test (20%) sets. Algorithms modified from residual network (ResNet) with two fusion strategies (feature fusion [hereafter, DL_feature] or decision fusion [hereafter, DL_decision]) were developed. DL prediction of malignancy was compared with O-RADS risk categorization and expert assessment by area under the receiver operating characteristic curve (AUC) analysis in the test set. Results A total of 422 women (mean age, 46.4 years ± 14.8 [SD]) with 304 benign and 118 malignant tumors were included; there were 337 women in the training and validation data set and 85 women in the test data set. DL_feature had an AUC of 0.93 (95% CI: 0.85, 0.97) for classifying malignant from benign ovarian tumors, comparable with O-RADS (AUC, 0.92; 95% CI: 0.85, 0.97; P = .88) and expert assessment (AUC, 0.97; 95% CI: 0.91, 0.99; P = .07), and similar to DL_decision (AUC, 0.90; 95% CI: 0.82, 0.96; P = .29). DL_decision, DL_feature, O-RADS, and expert assessment achieved sensitivities of 92%, 92%, 92%, and 96%, respectively, and specificities of 80%, 85%, 89%, and 87%, respectively, for malignancy. Conclusion Deep learning algorithms developed by using multimodal US images may distinguish malignant from benign ovarian tumors with diagnostic performance comparable to expert subjective and Ovarian-Adnexal Reporting and Data System assessment. © RSNA, 2022 Online supplemental material is available for this article.

Ultrasonographic evaluation of ovarian mass for predicting malignancy in pregnant women

OBJECTIVE

The purpose of this study is to compare ultrasonographic ovarian mass scoring systems in pregnant women.

STUDY DESIGN

This multicenter study included women with an ovarian mass during pregnancy who were evaluated using ultrasound and underwent surgery in 11 referral hospitals. The ovarian mass was evaluated and scored using three different scoring systems(International Ovarian Tumor Analysis Assessment of Different NEoplasias in the adnexa[IOTA ADNEX], Sassone, and Lerner). The final diagnosis was made histopathologically. Receiver operating characteristic(ROC) curves were generated for each scoring system.

RESULTS

During the study period, 236 pregnant women underwent surgery for an ovarian mass, including 223 women(94.5%) with a benign ovarian mass and 13 women(5.5%) with a malignant ovarian mass. Among 10 ultrasound image findings, six findings were different between benign and ovarian masses(maximal diameter of mass, maximal diameter of solid mass, wall thickness of mass, inner wall structure, thickness of septations, and papillarity). In all three scoring systems, the ovarian mass scores were significantly higher in malignant masses than in benign masses, with the highest area under the ROC curve(AUROC) in the Sassone scoring system(AUROC: 0.831 for Sassone, 0.710 for Lerner vs 0.709 for IOTA ADNEX; p < 0.05, between the Sassone and Lerner/ IOTA ADNEX). A combined model was developed with the six different ultrasound findings, and the AUROC of the combined model was 0.883(p = not significant between the combined model and Sassone).

CONCLUSION

In pregnant women, malignant ovarian tumors can be predicted with high accuracy using either the Sassone scoring system or the combined model.

External Validation of the IOTA Classification in Women with Ovarian Masses Suspected to Be Endometrioma

The study aimed to perform external validation of the International Ovarian Tumor Analysis (IOTA) classification of adnexal masses as benign or malignant in women with suspected endometrioma. A retrospective study including women referred to an endometriosis tertiary referral center for dedicated transvaginal ultrasound (TVUS). Adnexal masses were evaluated using the IOTA classification simple descriptors, simple rules and expert opinion. The reference standard was definitive histology after mass removal at laparoscopy. In total, 621 women were evaluated and divided into four groups: endometrioma on TVUS and confirmed on surgery (Group 1 = 181), endometrioma on TVUS but other benign cysts on surgery (Group 2 = 9), other cysts on TVUS but endometrioma on surgery (Group 3 = 2), masses classified as other findings or suspicious for malignancy on TVUS and confirmed on surgery (Group 4 = 5 potentially malignant, 11 benign). This gave a sensitivity 98.9%, specificity 64%, positive 95.3% and negative 88.9% predictive values, positive 2.74 and negative 0.02 likelihood ratios and 94.7% overall accuracy. The surgical diagnosis for the five masses suspected to be malignant was: borderline serous tumor (2), borderline mucinous tumor (2), and endometrioid lesion with complex hyperplasia without atypia (1). The conclusions were that the IOTA classification simple descriptors, simple rules and expert opinion performs well for classifying adnexal masses suspected to be endometrioma. The most common potentially malignant masses in these women were borderline ovarian tumors.

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and their extraction methods. Several texture features have been recently applied in discriminating malignant and benign ovarian masses by analysing B-mode images from ultrasound scan of the ovary with different levels of performance. However, comparative performance evaluation of these reported features using common sets of clinically approved images is lacking. This paper presents an empirical evaluation of seven commonly used texture features (histograms, moments of histogram, local binary patterns [256-bin and 59-bin], histograms of oriented gradients, fractal dimensions, and Gabor filter), using a collection of 242 ultrasound scan images of ovarian masses of various pathological characteristics. The evaluation examines not only the effectiveness of classification schemes based on the individual texture features but also the effectiveness of various combinations of these schemes using the simple majority-rule decision level fusion. Trained support vector machine classifiers on the individual texture features without any specific pre-processing, achieve levels of accuracy between 75% and 85% where the seven moments and the 256-bin LBP are at the lower end while the Gabor filter is at the upper end. Combining the classification results of the top k (k = 3, 5, 7) best performing features further improve the overall accuracy to a level between 86% and 90%. These evaluation results demonstrate that each of the investigated image-based texture features provides informative support in distinguishing benign or malignant ovarian masses.

Appropriate surgical management of ovarian endometrioma: excision or drainage?

Endometriosis negatively impacts the lives of countless women around the world. When medical management fails to improve quality of life often women are left making a decision whether or not to proceed with surgery. With endometriomas, patient's surgical options include complete surgical removal or drainage via laparoscopy. Here, we review the literature to discuss both techniques, excision and drainage of endometriomas, and what the research supports for endometrioma management.

The diagnostic efficacy of Gynecology Imaging Reporting and Data System (GI-RADS): single-center prospective cross-sectional study

Background

To assess the validity and accuracy of GI-RADS classification in the prediction of malignancy and in triaging the management protocol in ovarian lesions.

Results

One hundred fifty-six ovarian lesions were detected in the examined 116 women. The prevalence of malignant tumors was 44%. Overall GI-RADS classification rates were as follows: 41 cases (26.3%) were classified as GI-RADS 1, 26 cases (16 .7%) as GI-RADS 2, 34 cases (21.8%) as GI-RADS 3, 14 cases (8.9%) as GI-RADS 4, and 41 cases (26.3%) as GI-RADS 5. No follow-up was done in GI-RADS 1 patients. A final diagnosis of all GI-RADS 2 ovarian masses such as functional cyst (n = 10), hemorrhagic cysts (n = 8), corpus luteal cysts (n = 6), and some GI-RADS 3 as simple cysts (n = 10) was made by spontaneous resolution of these masses at follow-up after 6 weeks. Fifteen cases of GI-RADS 3 as mature teratoma, serous and mucinous cystadenoma, endometrioma, and ovarian torsion and all GI-RADS 4 and 5 underwent laparoscopic or surgical removal of the ovarian mass with histopathological examination. The diagnostic performance of the GI-RADS in predicting the risk of malignancy in ovarian masses was as follows: 98.11% sensitivity, 95.15% specificity, 91.2% positive predictive value (PPV), 99.2% negative predictive value (NPV), and 20.2 positive likelihood ratio, and the overall accuracy was 96.2% (area under receiver operating curve (AUC) = 0.96, P < 0.001).

Conclusion

GI-RADS classification performs well as a reporting system of the ovarian masses with high diagnostic performance in the prediction of malignancy, and it seems to be a helpful tool in triaging management in patients with ovarian masses.

Trial registration

The trial was registered in the US National Library of Medicine, under clinical trial number NCT03175991. Also, the ethical committee approval number of the Faculty of Medicine, Assiut University, was 17100016 on February 28, 2017.

Assessment of the diagnostic value of using serum CA125 and GI-RADS system in the evaluation of adnexal masses

Cancer antigen 125 (CA125) is a valuable tumor marker for ovarian cancer. Gynecology Imaging Reporting and Data System (GI-RADS) is proved to be effective at identifying the adnexal masses. We investigated whether the combination of these two methods can improve the diagnostic accuracy of ovarian cancer.We retrospectively analyzed preoperative data of 325 patients diagnosed with suspected adnexal mass, 196 patients with benign ovarian masses and 129 with malignant ovarian cancer (stage I: 34, II: 16, III: 61, IV: 18). CA125 was analyzed using the ARCHITECT system, GI-RADS was evaluated according to the International Ovarian Tumor Analysis consensus nomenclature and definitions. Sensitivities and specificities were also calculated for GI-RADS, CA125 and the combinations.The sensitivity, specificity and accuracy of CA125, GI-RADS were 75.97%, 79.59%, 78.15%, and 90.70%, 90.82%,90.77%, the combination data were 94.79%, 96.00%,95.53%. The AUC of combined diagnostic methods was the largest and significantly better compared with each method alone, P < .001). For stage I-II malignancy, GI-RADS as a single method was superior to CA125.Combined use of serum CA 125 and GI-RADS system improved the identification of adnexal masses at high risk of malignancy and could be used for clinical decision-making.

A Decision support system (DSS) for municipal nurses encountering health deterioration among older people

Background

This study is part of a larger project called ViSam and includes testing of a decision support system developed and adapted for older people on the basis of M (R) ETTS (Rapid Emergency Triage and Treatment System). The system is designed to allow municipal nurses to determine the optimal level of care for older people whose health has deteriorated. This new system will allow more structured assessment, the patient should receive optimal care and improved data transmission to the next caregiver.

Methods

This study has an explanatory approach, commencing with quantitative data collection phase followed by qualitative data arising from focus group discussions over the RNs professional experience using the Decision Support system. Focus group discussions were performed to complement the quantitative data to get a more holistic view of the decision support system.

Results

Using elements of the decision support system (vital parameters for saturation, pain and affected general health) together with the nurses' decision showed that 94 % of the older persons referred to hospital were ultimately hospitalized. Nurses felt that they worked more systematically, communicated more effectively with others and felt more professional when using the decision support system.

Conclusions

The results of this study showed that, with the help of a decision support system, the correct patients are sent to the Emergency Department from municipal home care. Unnecessary referrals of older patients that might lead to poorer health, decreased well-being and confusion can thus be avoided. Using the decision support system means that healthcare co-workers (nurses, ambulance/emergency department/district doctor/SOS alarm) begin to communicate more optimally. There is increased understanding leading to the risk of misinterpretation being reduced and the relationship between healthcare co-workers is improved. However, the decision support system requires more extensive testing in order to enhance the evidence base relating to the vital parameters among older people and the use of the decision support system.

Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach

The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses based on a neural networks approach was tested. The proposed method first calculates seven different types of characteristics (local binary pattern, fractal dimension, entropy, invariant moments, gray level co-occurrence matrix, law texture energy and Gabor wavelet) from ultrasound images of the ovary, from which several features are extracted and collected together with the clinical patient age. The proposed technique was validated using 106 benign and 39 malignant images obtained from 145 patients, corresponding to its probability of appearance in general population. On evaluation of the classifier, an accuracy of 98.78%, sensitivity of 98.50%, specificity of 98.90% and area under the curve of 0.997 were calculated.

Laparoscopy as the most effective tool for management of postmenopausal complex adnexal masses when expectancy is not advisable

Postmenopausal women with adnexal masses suspicious for malignancy must undergo surgery for histopathologic confirmation. The low positive predictive value for malignancy of the currently available preoperative examinations results in 5 to 220 surgeries performed for each case of pelvic malignancy detected, depending on the evaluation method and patient selection. Although extensively reviewed as an effective tool for the investigation and treatment of adnexal masses, laparoscopy is still underused for this purpose in postmenopausal women. Some reasons are uncertainty about the incidental diagnosis of a malignant lesion during laparoscopy, concern about the effect of laparoscopy over the course of a pelvic malignant lesion, and inadequate referral of patients at high risk to specialized centers with oncologic gynecologists. Identification of patients at low risk might also be inadequate, causing them to undergo unnecessary laparotomy. Herein we demonstrate through a comprehensive literature review that laparoscopy is a highly effective tool for investigation and treatment of suspected adnexal masses in postmenopausal women, both in general medical settings without oncologic backup and in specialized centers. The indications for laparoscopy in this context can be further expanded without oncologic harm if patients at low and high risk are appropriately selected for surgery at general and specialized settings, respectively.

Pediatric risk of malignancy index for preoperative evaluation of childhood ovarian tumors

PURPOSE

This study aimed to develop and provisionally validate a novel scoring index for preoperative cancer-risk prediction in childhood ovarian tumors.

METHODS

Fifty-five girls aged 18 and below underwent surgery for ovarian masses between 2004 and 2009. Benign or non-benign histological diagnoses (the latter including all malignant and borderline tumors and tumors containing immature components) were correlated with clinical and biochemical parameters, and blinded scores of ultrasound and computed-tomography using multivariate logistic regression. Regression coefficients were used as weighting factors to create an additive index. This index was validated prospectively against 23 consecutive adnexal masses operated in 2010.

RESULTS

In total, 67 tumors were benign and 11 non-benign. Non-benign diagnosis was independently associated with the maximum diameter of the largest solid component (score = value in cm), the presence of sex hormone-related symptoms (score = +6), and enhancement or flow in a septum or solid papillary projection (score = +4). The novel scoring index was calculated as the total score of these three parameters. A cutoff score of 7 gave a specificity of 97.9% and sensitivity of 87.5% for the training data set, and specificity and sensitivity of 100% for the pilot testing set.

CONCLUSION

The novel pediatric risk-of-malignancy index is able to accurately discriminate between benign and non-benign ovarian tumors in children and adolescents. Its preoperative application may guide surgical management decisions before the availability of histological confirmation.

GI-RADS reporting system for ultrasound evaluation of adnexal masses in clinical practice: a prospective multicenter study

OBJECTIVE

To assess the clinical usefulness of a structured reporting system based on ultrasound findings for management of adnexal masses.

METHODS

This was a prospective multicenter study comprising 432 adnexal masses in 372 women (mean age, 44.0 (range, 13-78) years) over a 36-month period. Ninety-three (25%) women were postmenopausal and 279 (75%) women were premenopausal. Patients were evaluated with transvaginal ultrasound by one of three examiners expert in gynecological ultrasound. Reporting was provided to referring clinicians according to the Gynecologic Imaging Report and Data System (GI-RADS) classification. A predetermined management protocol was offered to referral clinicians. It was suggested that patients classified as GI-RADS 2 be managed with follow-up scan, patients classified as GI-RADS 3 undergo laparoscopic surgery and patients classified as GI-RADS 4 or 5 be referred to a gynecologic oncologist. Definitive histologic diagnosis was available in 370 cases and 62 additional cases were considered as benign because of spontaneous resolution during follow-up. These outcomes were used as the gold standard for calculating the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) of GI-RADS classification for identifying adnexal masses at high risk of malignancy, considering GI-RADS 4 and 5 as being malignant.

RESULTS

Of the 432 tumors, 112 were malignant and 320 benign. The GI-RADS classification rate was as follows: GI-RADS 2, 92 (21%) cases; GI-RADS 3, 184 (43%) cases; GI-RADS 4, 40 (9%) cases; GI-RADS 5, (27%) 116 cases. Sensitivity for this system was 99.1% (95% CI, 95.1-99.8%), specificity was 85.9% (95% CI, 81.7-89.3%), LR+ was 7.05 (95% CI, 5.37-9.45) and LR- was 0.01 (95% CI, 0.001-0.07). PPV and NPV were 71.1% and 99.6%, respectively.

CONCLUSIONS

The GI-RADS reporting system performed well in identifying adnexal masses at high risk of malignancy and seems to be useful for clinical decision-making.

Emergency department triage scales and their components: a systematic review of the scientific evidence

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED?2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥ 15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted.We found ED triage scales to be supported, at best, by limited and often insufficient evidence.The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity).

Contribution of power Doppler blood flow mapping to gray-scale ultrasound for predicting malignancy of adnexal masses in symptomatic and asymptomatic women

OBJECTIVE

To determine the contribution of power Doppler blood flow mapping to gray-scale ultrasound for predicting malignancy of adnexal masses in symptomatic and asymptomatic women.

STUDY DESIGN

One thousand and ninety-four women with adnexal mass were included. Patients were divided into three groups according to clinical complaints: asymptomatic (group A), patients with symptoms non-suspicious of ovarian cancer (group B) and patients with symptoms suspicious of ovarian cancer (group C). All patients underwent transvaginal power Doppler ultrasound prior to surgery. Any mass in which the echo architecture at B-mode ultrasound was not highly suggestive of benign histology was categorized as questionable. In these cases power Doppler was performed as the second step. Definitive histological diagnosis was used as the standard reference. Sensitivity, specificity, positive likelihood ratio (+LR) and negative likelihood ratio (-LR) were calculated for B-mode diagnosis and B-mode plus Doppler in each group.

RESULTS

In group A, B-mode was significantly more sensitive (98.1%) than Doppler ultrasound (91.3%) (p<0.01). In group B Doppler ultrasound (97.0%) was more specific than B-mode ultrasound (92.2%) (p<0.001). In group C Doppler ultrasound (84.0%) was more specific than B-mode ultrasound (68.0%) (p<0.001). Positive LR was significantly higher after Doppler evaluation in all groups (30.5 vs 12.8 in group A, 33.2 vs 12.8 in group B and 6.0 vs 3.1 in group C).

CONCLUSIONS

The diagnostic performance of B-mode and power Doppler ultrasound is different depending on patients' complaints.

Does sphere volume affect the performance of three-dimensional power Doppler virtual vascular sampling for predicting malignancy in vascularized solid or cystic-solid adnexal masses?

OBJECTIVE

To assess whether, when using spherical sampling with Virtual Organ Computer-Aided Analysis (VOCAL) for calculating three-dimensional (3D) power Doppler angiography (PDA) indices, the sphere volume affects performance in the prediction of malignancy in vascularized cystic-solid or solid adnexal masses.

METHODS

One hundred and thirty-eight women (mean +/- SD age, 51.8 +/- 14.1 years) diagnosed as having vascularized cystic-solid or solid adnexal masses on B-mode and two-dimensional (2D) power Doppler ultrasound were evaluated by 3D-PDA prior to surgery. Five women had bilateral masses, giving a total number of 143 masses analyzed. Vascularization was assessed using VOCAL software. 3D-PDA vascular indices (vascularization index (VI), flow index (FI) and vascularization flow index (VFI)) from the most vascularized area within papillary projections and solid areas were calculated automatically using spherical sampling. Five different volumes of sphere were used (1 cm(3), 2 cm(3), 3 cm(3), 4 cm(3) and 5 cm(3)) in each case. A definitive histological diagnosis was obtained in each case after surgical tumor removal.

RESULTS

One hundred and seventeen (82%) masses were malignant and 26 (18%) were benign. Morphological evaluation revealed 34 (24%) unilocular solid masses, 49 (34%) multilocular solid masses and 60 (42%) mostly solid masses. The 1-cm(3) sphere could be used in 100% of the cases, the 2-cm(3) sphere could be used in 98.2% of the cases and the 3-5-cm(3) spheres could be used in 97.2% of the cases. The median VI, FI and VFI for all sphere volumes were significantly higher in malignant compared with non-malignant tumors. Receiver-operating characteristics curve analysis showed that VI and VFI, independently of sphere volume, were better predictors of malignancy than was FI. The best cut-off values for the 3D-PDA indices differed depending on sphere volume. VI was significantly more specific than were VFI and FI.

CONCLUSIONS

Sphere volume does not affect the performance of 3D-PDA. We recommend the use of different cut-off values for 3D-PDA indices for discriminating between benign and malignant adnexal masses, depending on the sphere volume used. Use of VI is preferable due to its higher specificity.

Gynecologic imaging reporting and data system: a new proposal for classifying adnexal masses on the basis of sonographic findings

OBJECTIVE

The purpose of this study was to describe a new reporting system called the Gynecologic Imaging Reporting and Data System (GI-RADS) for reporting findings in adnexal masses based on transvaginal sonography.

METHODS

A total of 171 women (mean age, 39 years; range, 16-77 years) suspected of having an adnexal mass were evaluated by transvaginal sonography before treatment. Pattern recognition analysis and color Doppler blood flow location were used for determining the presumptive diagnosis. Then the GI-RADS was used, with the following classifications: GI-RADS 1, definitively benign; GI-RADS 2, very probably benign; GI-RADS 3, probably benign; GI-RADS 4, probably malignant; and GI-RADS 5, very probably malignant. Patients with GI-RADS 1 and 2 tumors were treated expectantly. All GI-RADS 3, 4, and 5 tumors were removed surgically, and a definitive histologic diagnosis was obtained. The GI-RADS classification was compared with final histologic diagnosis.

RESULTS

A total of 187 masses were evaluated. The prevalence rate for malignant tumors was 13.4%. Overall GI-RADS classification rates were as follows: GI-RADS 1, 4 cases (2.1%); GI-RADS 2, 52 cases (27.8%); GI-RADS 3, 90 cases (48.1%); GI-RADS 4, 13 cases (7%); and GI-RADS 5, 28 cases (15%). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 92%, 97%, 85%, 99%, and 96%, respectively.

CONCLUSIONS

Our proposed reporting system showed good diagnostic performance. It is simple and could facilitate communication between sonographers/sonologists and clinicians.

Three-dimensional power Doppler vascular sonographic sampling for predicting ovarian cancer in cystic-solid and solid vascularized masses

OBJECTIVE

The purpose of this study was to explore the role of 3-dimensional (3D) power Doppler (PD) sonography to discriminate between benign and malignant cystic-solid and solid vascularized adnexal masses and to define cutoff values for 3D PD indices to be used in a clinical setting.

METHODS

A total of 143 consecutive women (mean age, 50.4 years; range, 17-82 years) with diagnoses of cystic-solid or solid vascularized adnexal masses on B-mode and 2-dimensional PD sonography were evaluated by 3D PD sonography before surgery. Three-dimensional PD sonography was used to assess vascularization within papillary projections and solid areas with a virtual organ computer-aided analysis program. Three-dimensional PD vascular indices (vascularization index [VI], flow index [FI], and vascularization-flow index [VFI]) were automatically calculated. A definitive histologic diagnosis was obtained in each case.

RESULTS

A total of 113 masses (74%) were malignant, and 39 (26%) were benign. Morphologic evaluation revealed 30 unilocular solid masses (19.7%), 43 multilocular solid masses (28.3%), and 79 mostly solid masses (52%). The mean VI (9.365% versus 3.3%; P< .001), FI (34.318 versus 28.794; P< .001), and VFI (3.233 versus 1.15; P<0.01) were significantly higher in malignant tumors. No differences were found in the resistive index, pulsatility index, and peak systolic velocity. Receiver operating characteristic analysis revealed an area under the curve of 0.77 (95% confidence interval, 0.69-0.85), 0.71 (0.60-0.81), and 0.75 (0.66-0.83) for the VI, FI and VFI, respectively. For reducing the false-positive rate by almost one-third, sensitivity values for the VI (cutoff, 1.556%), FI (25.212), and VFI (0.323) were 92%, 95%, and 93%, respectively.

CONCLUSIONS

Three-dimensional PD vascular indices could be helpful for reducing the false-positive rate in cystic-solid and solid vascularized adnexal masses.