A comparison of methods for preoperative discrimination between malignant and benign adnexal masses: the development of a new logistic regression model

Artificial Intelligence in Ultrasound Diagnoses of Ovarian Cancer: A Systematic Review and Meta-Analysis

Ovarian cancer is the sixth most common malignancy, with a 35% survival rate across all stages at 10 years. Ultrasound is widely used for ovarian tumour diagnosis, and accurate pre-operative diagnosis is essential for appropriate patient management. Artificial intelligence is an emerging field within gynaecology and has been shown to aid in the ultrasound diagnosis of ovarian cancers. For this study, Embase and MEDLINE databases were searched, and all original clinical studies that used artificial intelligence in ultrasound examinations for the diagnosis of ovarian malignancies were screened. Studies using histopathological findings as the standard were included. The diagnostic performance of each study was analysed, and all the diagnostic performances were pooled and assessed. The initial search identified 3726 papers, of which 63 were suitable for abstract screening. Fourteen studies that used artificial intelligence in ultrasound diagnoses of ovarian malignancies and had histopathological findings as a standard were included in the final analysis, each of which had different sample sizes and used different methods; these studies examined a combined total of 15,358 ultrasound images. The overall sensitivity was 81% (95% CI, 0.80-0.82), and specificity was 92% (95% CI, 0.92-0.93), indicating that artificial intelligence demonstrates good performance in ultrasound diagnoses of ovarian cancer. Further prospective work is required to further validate AI for its use in clinical practice.

Ovarian Masses: The Value of Acoustic Shadowing on Ultrasound Examination

Adnexal lesions are a common finding in women and pose a clinical challenge since ovarian cancer is a highly lethal disease. However, most adnexal masses are benign, benefiting from a more conservative approach. In preoperative assessment, transvaginal ultrasound plays a key role in evaluating morphologic features that correlate with the risk of malignancy. The acoustic shadow is the loss of echo behind sound-absorbing components, such as calcifications or fibrous tissues, which are predominantly found in benign lesions. However, recognizing the acoustic shadow is a difficult skill to master, and its usefulness may be underappreciated.

Comparative assessment of RMI-IV and RMI-V in preoperative prediction of ovarian tumor type in pregnant women

Prediction of ovarian tumor type in pregnant women is of great clinical significance, however, it is vastly difficult. In the last 5–10 years gynecologists were suggested to use RMI (Risk of Malignancy Index) in non-pregnant women, however the value of the test for obstetric practice has yet to be established. The study was aimed to determine RMI-IV and RMI-V during preoperative non-invasive prediction of ovarian tumor type in pregnant women. Retrospective and prospective clinical and laboratory data of 114 pregnant women aged 20–38 were collected. Among them 15 patients had malignant ovarian tumors (MOTs), 28 had borderline ovarian tumors (BOTs), and 71 had benign ovarian tumors. Color Doppler and pulsed wave Doppler ultrasound was performed. The levels of СА-125 were defined by enzyme immunoassay. Models IV, V were used to assess the risk of ovarian cancer. A moderate non-significant increase in blood levels of СА-125 compared to patients with benign ovarian tumors and BOTs was found in pregnant women with MOTs. Patients with BOTs and MOTs showed higher RMI-IV and RMI-V values compared to the group of pregnant women with benign ovarian tumors. Extreme values are required to guarantee the differences in the diagnosis of tumors (RMI-IV > 3500 indicate the presence of MOTs, the values below 100 indicate no malignancy). Similar RMI-V values are 1500 and 60. However, in most cases, availability of RMI-IV and RMI-V is insufficient for decision making, and a comprehensive approach has to be used. Thus, it is difficult to define ovarian mass type in pregnant women using RMI only. Comprehensive clinical assessment with the use of imaging methods is required for preoperative prediction of ovarian mass type in pregnant women, along with the use of prognostic models taking into account the majority of descriptive “morphological” tumor characteristics.

Artificial Intelligence and Machine Learning in Cancer Research: A Systematic and Thematic Analysis of the Top 100 Cited Articles Indexed in Scopus Database

INTRODUCTION

Cancer is a major public health problem and a global leading cause of death where the screening, diagnosis, prediction, survival estimation, and treatment of cancer and control measures are still a major challenge. The rise of Artificial Intelligence (AI) and Machine Learning (ML) techniques and their applications in various fields have brought immense value in providing insights into advancement in support of cancer control.

METHODS

A systematic and thematic analysis was performed on the Scopus database to identify the top 100 cited articles in cancer research. Data were analyzed using RStudio and VOSviewer.Var1.6.6.

RESULTS

The top 100 articles in AI and ML in cancer received a 33 920 citation score with a range of 108 to 5758 times. Doi Kunio from the USA was the most cited author with total number of citations (TNC = 663). Out of 43 contributed countries, 30% of the top 100 cited articles originated from the USA, and 10% originated from China. Among the 57 peer-reviewed journals, the "Expert Systems with Application" published 8% of the total articles. The results were presented in highlight technological advancement through AI and ML via the widespread use of Artificial Neural Network (ANNs), Deep Learning or machine learning techniques, Mammography-based Model, Convolutional Neural Networks (SC-CNN), and text mining techniques in the prediction, diagnosis, and prevention of various types of cancers towards cancer control.

CONCLUSIONS

This bibliometric study provides detailed overview of the most cited empirical evidence in AI and ML adoption in cancer research that could efficiently help in designing future research. The innovations guarantee greater speed by using AI and ML in the detection and control of cancer to improve patient experience.

Magnetic Resonance Imaging Findings in Patients with Benign and Malignant Ovarian Masses Versus Pathologic Outcomes

Background:

The results of the former study confirmed the accuracy of magnetic resonance imaging (MRI) in determining the origin and content of ovarian masses. The present study aimed to evaluate the diagnostic value of MRI in differentiating benign and malignant ovarian masses in women.

Materials and Methods:

This was a cross-sectional study. All candidates for surgery to remove ovarian masses were selected to participate in this study. They underwent MRI with gadolinium before the surgery. MRI images were reviewed by an experienced radiologist who was aware of the ovarian mass found in pelvic ultrasonography (US). A thick-enhancing wall, mural nodules, septations, and internal enhancement within the mass were reviewed by the radiologist. Mass specimens were examined in the laboratory by an experienced pathologist to determine malignancy or benignancy of the masses. Pathological findings were compared with MRI results.

Results:

there was no significant difference between MRI findings and pathology denoted by benign and malignant (P = 0.06), but results showed a significant difference between US and pathology (P = 0.002). In MRI findings related to a thick-enhancing wall (P = 0.18), internal enhancement (P = 0.18), and pelvic fluid (P = 1.00), no significant difference was seen in benign or malignant masses. However, in findings related to septation, all cases had malignant reports (P = 0.006), and in mural nodule, 80% had malignant reports (P = 0.006). CA-125 blood level in patients with benign masses (1.72 ± 0.97) was significantly less than patients with malignant masses (3.20 ± 0.83) (P < 0.001).

Conclusion:

We showed that MRI has better results in diagnosing adnexal masses and their characteristics compared to simple ultrasound imaging based on pathological studies.

Unraveling a difficult diagnosis: the tricks for early recognition of ovarian cancer

Epithelial ovarian cancer (EOC) is the predominant type of ovarian cancer (OC). The 5-year survival of patients has improved over the last three decades, although the overall cure rate of OC if about 30%. Despite high response rates after initial chemotherapy, most patients with advanced ovarian cancer ultimately develop the recurrent disease because of resistance to chemotherapy. A proper early diagnosis and treatment of patients with ovarian cancer are urgently needed. Nowadays the diagnosis is performed by means of clinical symptoms and signs, often indicators of a disease already at an advanced stage, tumor markers (CA125 and HE4), transvaginal ultrasonography and imaging, very useful in distinguishing adnexal masses. Understand the nature of an adnexal mass is the primary point to begin the diagnosis of OC. Validated different model to approach and characterize adnexal pathology preoperatively are described, such as the International Ovarian Tumor Analysis (IOTA) and the Assessment of Different NEoplasias in the AdneXa (ADNEX) model. New tumor markers, such as PRSS8, FOLR1, KLK6/7, GSTT1, and miRNAs, are getting ahead and are worth noting for early detection of ovarian cancer. Despite the development of numerous ultrasound models for the diagnosis of adnexal masses and the analysis of different tumor markers, the early diagnosis of ovarian cancer is still difficult to practice. Moreover, identifying genetic risk alleles, such as germline BRCA1 and BRCA2 mutations, for ovarian cancer has had a significant impact on disease prevention strategies.

Ovarian mass-differentiating benign from malignant: the value of the International Ovarian Tumor Analysis ultrasound rules

Ovarian cancer, the fifth most common cause of cancer death among women, has the highest mortality rate of all gynecologic cancers. General survival rate is <50% but can reach 90% if disease is detected early. Ultrasound is presently the best modality to differentiate between benign and malignant status. The patient with a malignant mass should be referred to an oncology surgeon since results have been shown to be superior to treatment by a specialist. Several ultrasound-based scoring systems exist for assessing the risk of an ovarian tumor to be malignant. The International Ovarian Tumor Analysis group published 2 such systems: the ultrasound Simple Rules and the Assessment of Different NEoplasias in the adneXa model. The Simple Rules classifies a tumor as benign, malignant, or indeterminate and the Assessment of Different NEoplasias in the adneXa model determines the risk for a tumor to be benign or malignant and, if malignant, the risk of various stages. Sensitivity of the Simple Rules and Assessment of Different NEoplasias in the adneXa model (using a cut-off of 10% to predict malignancy) are 92% and 96.5%, respectively, and specificities are 96% and 71.3%, respectively. These models are the best predictive tests for the preoperative classification of adnexal tumors. Their intent is to help the specialist make management decisions when faced with a patient with a persistent ovarian mass. The models are simple, are easy to use, and have been validated in multiple reports but not in the United States. We suggest they should be validated and widely introduced into medical practice in the United States.

Evolving Role of Serum Biomarkers in the Management of Ovarian Cancer

The availability of an ideal serum tumor marker would be of great clinical benefit for both the diagnosis and management of patients with epithelial ovarian cancer. Serum cancer antigen 125 assay significantly increases the diagnostic reliability of ultrasound in discriminating a malignant from a benign ovarian mass, especially in postmenopausal women, and it is the only well validated tumor marker for monitoring disease course. Several other tumor-associated antigens have been assessed, including glycoprotein antigens other than cancer antigen 125, soluble cytokeratin fragments, kallikreins, cytokines and cytokine receptors, vascular endothelial growth factor, D-dimer, and lisophosphatidic acid. This article assesses the potential diagnostic and prognostic role of these novel biomarkers, both alone and in combination with cancer antigen 125. The future for serum tumor marker research is represented by the emerging technology of proteomics, which may allow scientific advances comparable to those achieved with the introduction of monoclonal antibody technology.

Past, present and future ultrasonographic techniques for analyzing ovarian masses

Ultrasonography is today the method of choice for distinguishing between benign and malignant adnexal pathologies. Using pattern recognition several types of tumors can be recognized according to their characteristic appearance on gray-scale imaging. Color Doppler imaging should be used only to perform a semiquantitative color score or evaluate the flow location. International Ovarian Tumor Analysis group had standardized definitions characterizing adnexal masses and suggested the use of 'simple rules' in premenopausal women. Recently, the use of 3D vascular indices has been proposed but its potential use in clinical practice is debated. Also computerized aided diagnosis algorithms showed encouraging results to be confirmed in the future.

Pearls and pitfalls in surgery for endometrioma

Endometrioma surgery should be planned and executed very carefully as it is associated with risks that may hamper future reproductive potential. Symptoms, age, risk of malignancy, bilaterality, ovarian reserve, and desire to have children should all be taken into account prior to surgical intervention. Cyclic and noncyclic severe pain may be an indicator or deep infiltrating diseases. Laparoscopic surgery is the gold standard, however, the issue of resection versus ablation should be further studied.

Simple descriptors and simple rules of the International Ovarian Tumor Analysis (IOTA) Group: a prospective study of combined use for the description of adnexal masses

OBJECTIVE

External validation of the IOTA group's three-step diagnostic model (Strategy 1) and comparison with assessment by an expert sonographer (Strategy 2).

STUDY DESIGN

Prospective study in patients with persistent adnexal masses, in which an inexperienced sonographer performed transvaginal ultrasound applying simple descriptors (SD) and rules (SR) for classifying as benign or malignant. Any non-classifiable mass was then submitted to an expert examiner for subjective assessment (SA).

RESULTS

Eighty-one patients (mean age, 43; 27.2% postmenopausal) were included in this prospective study. Surgery was performed for 30 (8 malignant and 22 benign) masses; 51 masses were considered as benign and managed expectantly (they were assumed to be benign for statistical purposes). Diagnostic performance for Strategy 1 (SD+SR+SA) was sensitivity (SN): 87.5% (7/8, 95% CI, 47.3-99.7%) and specificity (SP): 100% (73/73, 95% CI, 95.1-100%). For Strategy 2 (SA only) it was SN 87.5% (7/8, 95% CI, 47.3-99.7%), SP 98.6% (72/73, 95% CI, 92.6-100%).

CONCLUSIONS

The three-step diagnostic strategy designed by the IOTA group for adnexal masses has a diagnostic performance comparable to that of subjective expert assessment and could be used as a triage method by nonexpert sonographers.

Usefulness of diagnostic indices comprising clinical, sonographic, and biomarker data for discriminating benign from malignant ovarian masses

The objective of this study was to review the accuracy of indices combining several diagnostic variables, in comparison to other models, sonography alone, and biomarker assays, for predicting benign or malignant ovarian lesions. Different single modalities were reviewed. The most useful complex models were International Ovarian Tumor Analysis (IOTA) sonographic logistic regression model 2 (area under the curve, 0.949), risk of malignancy index-cancer antigen 125-human epididymis protein 4 (0.950), risk of malignancy algorithm (0.953), pelvic mass score (0.960), non-IOTA logistic regression model (0.970), and histoscanning score logistic regression model (0.970). None of the indices was superior to an expert subjective sonographic assessment (0.968). For women with adnexal tumors, indices with high accuracy are available that are applicable in clinical practice and comparable to an expert subjective sonographic assessment for discriminating benign from malignant masses.

Interobserver agreement in describing the ultrasound appearance of adnexal masses and in calculating the risk of malignancy using logistic regression models

PURPOSE

To estimate interobserver agreement with regard to describing adnexal masses using the International Ovarian Tumor Analysis (IOTA) terminology and the risk of malignancy calculated using IOTA logistic regression models LR1 and LR2, and to elucidate what explained the largest interobserver differences in calculated risk of malignancy.

EXPERIMENTAL DESIGN

One hundred and seventeen women with adnexal masses were examined with transvaginal gray scale and power Doppler ultrasound by two independent experienced sonologists who described the masses using IOTA terminology. The risk of malignancy was calculated using LR1 and LR2. A predetermined risk of malignancy cutoff of 10% indicated malignancy.

RESULTS

There were 94 benign, four borderline, and 19 invasively malignant tumors. There was substantial variability between the two sonologists in measurement results and some variability in assessment of categorical variables (agreement 40%-98%, Kappa 0.30-0.91). Interobserver agreement when classifying tumors as benign or malignant was 84% (98/117), Kappa 0.68 for LR1, and for LR2 85% (99/117), Kappa 0.68. When using LR1 and LR2, the interobserver difference in calculated risk was ≥ 25 percentage units in 9% (11/117) and 12% (14/117) of tumors, respectively. Differences in assessment of wall irregularity, acoustic shadowing, color score, and color flow in papillary projections explained most of these largest differences.

CONCLUSIONS

Interobserver agreement in classifying tumors as benign or malignant using the risk of malignancy cutoff of 10% for LR1 and LR2 was good. However, because risk estimates may differ substantially between sonologists, one should be cautious with using the risk value for counseling patients about their individual risk.

[Ovarian cysts: sonographic score of malignancy]

Les kystes de l'ovaire constituent l'un des motifs les plus fréquents de consultation en gynécologie. L’étape diagnostique repose principalement sur l’échographie. Nous proposons dans ce travail un score échographique reproductible prédictif de malignité. Nous évaluons la fiabilité de ce score après confrontations des données échographiques et histologiques. Il s'agit d'une étude rétrospective réalisée sur une période de 3 ans. Nous avons élaboré un score basé sur les signes échographiques décrits dans la littérature comme prédictifs de malignité et avons classé les examens échographiques préopératoires selon leurs scores respectifs. Les données échographiques étaient comparées aux résultats histologiques et un seuil prédictif de malignité a été déterminé pour le score adopté. 150 patientes ont été colligées. Les deux signes échographiques les plus prédictifs de malignité étaient: les végétations endo-kystiques, avec une Valeur Prédictive Positive (VPP) à 86,67% et une Valeur Prédictive Négative (VPN) à 100%, et le caractère vascularisé au Doppler couleur avec une VPP à 72,52% et une VPN à 100%. Le seuil retenu pour le score proposé était de 6 avec une spécificité de 100%, une sensibilité de 100%, une VPP de 100% et une VPN de 100%. L’échographie joue un rôle décisif dans la conduite à tenir devant une masse ovarienne. Seul un faisceau d'arguments permet d’évoquer la malignité lors de l'examen échographique. L'utilisation de scores basés sur des signes simples, reproductibles augmente la valeur diagnostique de l’échographie en matière de malignité.

Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research

BACKGROUND

Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models.

OBJECTIVE

The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring.

METHODS

The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM's design is split over a number of modules, to ensure future extendability.

RESULTS

The TDD approach has enabled us to deliver high software quality. CDM's eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase.

CONCLUSIONS

To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries. This integration improves the efficiency of the clinical diagnostic model research workflow. Moreover, by simplifying the generation of learning curves, CDM enables study coordinators to assess more accurately when data collection can be terminated, resulting in better models or lower patient recruitment costs.

Color Doppler score: a new approach for monitoring a large placental chorioangioma

We employed color Doppler score as an innovative approach for the prenatal diagnosis and monitoring of a large placental chorioangioma case diagnosed at 26 weeks and the subjective semiquantitative assessment of the vascularization. The blood flow was assessed by a color Doppler score based on the intensity of the color signal with the following value ranges: (1) no flow, (2) minimal flow, (3) moderate flow, and (4) high vascular flow. Weekly examinations were programmed. Initially, a color Doppler score 3 was assigned, remaining unchanged at the following two exams and decreasing to Score 2 in the following 2 exams and to Score 1 thereafter. The ultrasonographic scan showed an increase of the mass size at the second and third exams and was followed by an arrest of the growth persisting for the rest of the pregnancy. Some hyperechogenic spots inside the mass appeared at the end. Expectant management was opted for, and the delivery was at 39, 2 weeks and maternal and fetal outcomes were favourable. The color Doppler score employed for assessment of vascularization in successive examinations proved to be an important tool for the prediction of the chorioangioma involution, and this new approach of monitoring allowed effective surveillance and successful tailored management.

Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis

BACKGROUND Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. METHODS An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95% confidence intervals or plot summary ROC curves for all models considered. RESULTS Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27%) malignant and 19 239 (73%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-off of 10% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95% CI 0.88-0.95] and 0.83 [95% CI 0.77-0.88] for LR2 and 0.93 [95% CI 0.89-0.95] and 0.81 [95% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-off of 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95% CI 0.75-0.91] and 0.91 [95% CI 0.83-0.96] compared with 0.93 [95% CI 0.84-0.97] and 0.83 [95% CI 0.73-0.90] for SR and 0.44 [95% CI 0.28-0.62] and 0.95 [95% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95% CI 0.89-0.97] and 0.70 [95% CI 0.62-0.77], 0.93 [95% CI 0.88-0.96] and 0.76 [95% CI 0.69-0.82], and 0.79 [95% CI 0.72-0.85] and 0.90 [95% CI 0.84-0.94], respectively. CONCLUSIONS An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age.

Assessing the risk of ovarian malignancy in asymptomatic women with abnormal CA 125 and transvaginal ultrasound scans in the prostate, lung, colorectal, and ovarian screening trial

OBJECTIVE

To estimate the risk of ovarian malignancy among asymptomatic women with abnormal transvaginal ultrasound scans or CA 125 and to provide guidance to physicians managing these women.

METHODS

A cohort of women from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial with abnormal ovarian results at the initial (T0) and subsequent (T1+) screens were analyzed to estimate which findings were associated with high risk of ovarian cancer. Cancer risks more than 10% were designated as high and risks of 3% or less were designated as low.

RESULTS

For the T0 screen, two high-risk categories were identified: CA 125 of 70 or more with negative transvaginal ultrasound scan (positive predictive value [PPV] 15.9%, CI 14.7-17.7%); and positive for both CA 125 and transvaginal ultrasound scan (PPV 25.0%, CI 23.3-27.3%). For T1+ screens, three high-risk categories were identified: negative transvaginal ultrasound scan with change in CA 125 of 45 or more (PPV 29.0%, CI 28.3-30.3%); increase in size of cyst 6 cm or more with negative CA 125 (PPV 13.3%, CI 10.5-18.0%); and positive for both tests (PPV 42.9%, CI 40.0-46.0%). High-risk criteria for T0 provide a sensitivity of 60%, specificity of 96.2%, PPV of 19.7%, and a negative predictive value (NPV) of 99.3%. T1+ criteria yielded a sensitivity of 85.3%, specificity of 95.6%, PPV of 29.6%, and NPV of 99.7%.

CONCLUSIONS

High-risk categories for predicting risk of cancer in women with abnormal CA 125, transvaginal ultrasound scan, or both at initial and subsequent screens have been identified. The large number of women in this study, the 4-year complete follow-up, and small number of invasive cancers in the low-risk categories provide guidance for clinical decisions regarding need for surgery in these women.

LEVEL OF EVIDENCE

II.

Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies

In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two-step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence-based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2 or IOTA simple rules and subjective assessment by an experienced examiner.

Ultrasonographic markers and preoperative CA-125 to distinguish between borderline ovarian tumors and stage I ovarian cancer

OBJECTIVE

Preoperative evaluation of ovarian masses has become increasingly important for optimal planning of treatment. The aim of this study was to assess the role of preoperative serum cancer antigen 125 (CA-125) levels in correlation with ultrasonographic features in order to distinguish between borderline ovarian tumors (BOTs) and stage I epithelial ovarian carcinoma (EOC).

DESIGN

Retrospective study.

SETTING

Tertiary University Hospital.

POPULATION

We reviewed all women with BOTs and stage I EOC from January 2000 to December 2010. Data from 165 women (66 BOTs and 99 stage I EOC) were analyzed.

METHODS

Multivariable logistic regression with stepwise selection of variables was used to determine which clinical variables, ultrasound features and CA-125 level were independently associated with invasiveness.

MAIN OUTCOME MEASURES

Utility of ultrasonographic markers and CA-125 in the preoperative differential diagnosis between BOTs and stage I EOC.

RESULTS

Women with CA-125 > 100 IU mL(-1) had almost three times greater likelihood of belonging in the EOC group [odds ratio (OR) 3.02; confidence interval (CI) 95%: 1.13-8.12]. Furthermore, the presence of large solid component (≥20% of the tumor comprised of solid components) was associated with 4.25 times greater odds of it to representing ovarian cancer rather than a BOT (OR 4.25; 95% CI: 2.05-8.82). In contrast, the presence of papillary projections was associated with a 73% lower likelihood of EOC (OR 0.27; 95% CI: 0.13-0.58).

CONCLUSIONS

Preoperative CA-125 > 100 IU mL(-1) combined with the presence of a large solid component and the absence of papillary projections seems to improve the discriminative ability in favor of stage I EOC.

Clinically oriented three-step strategy for assessment of adnexal pathology

OBJECTIVE

To determine the diagnostic performance of ultrasound-based simple rules, risk of malignancy index (RMI), two logistic regression models (LR1 and LR2) and real-time subjective assessment by experienced ultrasound examiners following the exclusion of masses likely to be judged as easy and 'instant' to diagnose by an ultrasound examiner, and to develop a new strategy for the assessment of adnexal pathology based on this.

METHODS

3511 patients with at least one persistent adnexal mass preoperatively underwent transvaginal ultrasonography to assess tumor morphology and vascularity. They were included in two consecutive prospective studies by the International Ovarian Tumor Analysis (IOTA) group: Phase 1 (1999-2005), development of the simple rules and logistic regression models LR1 and LR2, and Phase 2, a validation study (2005-2007).

RESULTS

Almost half of the cases (43%) were identified as 'instant' to diagnose on the basis of descriptors applied to the database. To assess diagnostic performance in the more difficult 'non-instant' masses, we used only Phase 2 data (n = 1036). The sensitivity of LR2 was 88%, of RMI it was 41% and of subjective assessment it was 87%. The specificity of LR2 was 67%, of RMI it was 90% and of subjective assessment it was 86%. The simple rules yielded a conclusive result in almost 2/3 of the masses, where they resulted in sensitivity and specificity similar to those of real-time subjective assessment by experienced ultrasound examiners: sensitivity 89 vs 89% (P = 0.76), specificity 91 vs 91% (P = 0.65). When a three-step strategy was applied with easy 'instant' diagnoses as Step 1, simple rules where conclusive as Step 2 and subjective assessment by an experienced ultrasound examiner in the remaining masses as Step 3, we obtained a sensitivity of 92% and specificity of 92% compared with sensitivity 90% (P = 0.03) and specificity 93% (P = 0.44) when using real-time subjective assessment by experts in all tumors.

CONCLUSION

A diagnostic strategy using simple descriptors and ultrasound rules when applied to the variables contained in the IOTA database obtains results that are at least as good as those obtained by subjective assessment of a mass by an expert.

Management of a suspicious adnexal mass: a clinical practice guideline

QUESTIONS

What is the optimal strategy for preoperative identification of the adnexal mass suspicious for ovarian cancer? What is the most appropriate surgical procedure for a woman who presents with an adnexal mass suspicious for malignancy?

PERSPECTIVES

In Canada in 2010, 2600 new cases of ovarian cancer were estimated to have been diagnosed, and of those patients, 1750 were estimated to have died, making ovarian cancer the 7th most prevalent form of cancer and the 5th leading cause of cancer death in Canadian women. Women with ovarian cancer typically have subtle, nonspecific symptoms such as abdominal pain, bloating, changes in bowel frequency, and urinary or pelvic symptoms, making early detection difficult. Thus, most ovarian cancer cases are diagnosed at an advanced stage, when the cancer has spread outside the pelvis. Because of late diagnosis, the 5-year relative survival ratio for ovarian cancer in Canada is only 40%. Unfortunately, because of the low positive predictive value of potential screening tests (cancer antigen 125 and ultrasonography), there is currently no screening strategy for ovarian cancer. The purpose of this document is to identify evidence that would inform optimal recommended protocols for the identification and surgical management of adnexal masses suspicious for malignancy.

OUTCOMES

Outcomes of interest for the identification question included sensitivity and specificity. Outcomes of interest for the surgical question included optimal surgery, overall survival, progression-free or disease-free survival, reduction in the number of surgeries, morbidity, adverse events, and quality of life.

METHODOLOGY

After a systematic review, a practice guideline containing clinical recommendations relevant to patients in Ontario was drafted. The practice guideline was reviewed and approved by the Gynecology Disease Site Group and the Report Approval Panel of the Program in Evidence-based Care. External review by Ontario practitioners was obtained through a survey, the results of which were incorporated into the practice guideline.

PRACTICE GUIDELINE

These recommendations apply to adult women presenting with a suspicious adnexal mass, either symptomatic or asymptomatic. IDENTIFICATION OF AN ADNEXAL MASS SUSPICIOUS FOR OVARIAN CANCER: Sonography (particularly 3-dimensional sonography), magnetic resonance imaging (mri), and computed tomography (ct) imaging are each recommended for differentiating malignant from benign ovarian masses. However, the working group offers the following further recommendations, based on their expert consensus opinion and a consideration of availability, access, and harm: Where technically feasible, transvaginal sonography should be the modality of first choice in patients with a suspicious isolated ovarian mass.To help clarify malignant potential in patients in whom ultrasonography may be unreliable, mri is the most appropriate test.In cases in which extra-ovarian disease is suspected or needs to be ruled out, ct is the most useful technique.Evaluation of an adnexal mass by Doppler technology alone is not recommended. Doppler technology should be combined with a morphology assessment.Ultrasonography-based morphology scoring systems can be used to differentiate benign from malignant adnexal masses. These scoring systems are based on specific ultrasound parameters, each with several scores base on determined features. All evaluated scoring systems were found to have an acceptable level of sensitivity and specificity; the choice of scoring system may therefore be made based on clinician preference.As a standalone modality, serum cancer antigen 125 is not recommended for distinguishing between benign and malignant adnexal masses.Frozen sections for the intraoperative diagnosis of a suspicious adnexal mass is recommended in settings in which availability and patient preference allow. SURGICAL PROCEDURES FOR AN ADNEXAL MASS SUSPICIOUS FOR MALIGNANCY: To improve survival, comprehensive surgical staging with lymphadenectomy is recommended for the surgical management of patients with early-stage ovarian cancer. Laparoscopy is a reasonable alternative to laparotomy, provided that appropriate surgery and staging can be done. The choice between laparoscopy and laparotomy should be based on patient and clinician preference. Discussion with a gynecologic oncologist is recommended. Fertility-preserving surgery is an acceptable alternative to more extensive surgery in patients with low-malignant-potential tumours and those with well-differentiated surgical stage i ovarian cancer. Discussion with a gynecologic oncologist is recommended.

The sonographic prediction of invasive carcinoma in unilocular-solid ovarian cysts in premenopausal patients: a pilot study

BACKGROUND

Unilocular-solid ovarian cysts are a rare but challenging pathology in young women, with a desire to spare their fertility. In these cases, the risks of borderline and invasive disease are around 10 and 20%, respectively. No ultrasound rule has yet demonstrated the ability to discriminate with high accuracy, a borderline tumor from a benign tumor or 'invasive tumor'. The aim of this study was to assess the predictive performance of different ultrasound parameters in differentiating benign and borderline tumors versus invasive malignant tumors in premenopausal patients with unilocular-solid ovarian masses.

METHODS

Women aged ≤ 50 years with unilocular-solid adnexal masses with a maximum diameter ≤ 10 cm, undergoing surgery in our department within 3 months from ultrasound examination, were included in this retrospective study. A standardized ultrasound examination technique and predefined definitions of ultrasound characteristics were used. The results of ultrasound examination using gray scale and color Doppler were compared with the histological examination of the respective surgical specimens.

RESULTS

The study included 51 patients. On histological examination, 36 (70%) lesions were classified as benign, 10 (20%) as borderline ovarian tumors and 5 (10%) as invasively malignant tumors. In receiver-operating characteristic curve analysis, the best cut-off for the largest solid component with regard to discriminating non-invasive (benign or borderline) from invasive tumors was 14 mm. A largest solid component >14 mm, the presence of papillation blood flow and the combination of the two parameters provided a sensitivity of 100% and a specificity of 63, 63 and 80%, respectively.

CONCLUSIONS

Transvaginal ultrasound examination seems to be able to discriminate between invasive and non-invasive tumors in the premenopausal patients with unilocular-solid adnexal masses. Because of the retrospective nature of the study, further prospective clinical trials are needed to confirm the accuracy of the selected sonographic parameters in discriminating the invasive and non-invasive adnexal tumors.

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.

Screening for ovarian cancer in the general population

Advances in screening and early detection of ovarian cancer over the past decade have included novel interpretation of serum CA125, discovery of human epididymis protein 4, which has the potential to add to CA125, and the growing understanding of the flaws of previous biomarker studies. No mortality effect was found in the ovarian screening arm of the Prostate Lung Colorectal and Ovarian Cancer Screening Trial.(87) Concerns, however, have been raised about trial design, and the results from the UK Collaborative Trial of Ovarian Cancer Screening in the general population(38) and other ongoing studies in the high-risk population are awaited for a definitive conclusion. Future work needs to take into account the new insights into ovarian cancer subtypes and the growing evidence that a significant proportion of ovarian cancers might originate in premalignant lesions in the distal fallopian tube.

Determination of serum CRP, VEGF, Leptin, CK-MB, CA-15-3 and IL-6 levels for malignancy prediction in adnexal masses

OBJECTIVE

Investigation of serum markers which could be used in the malignancy prediction of adnexal masses.

MATERIAL AND METHODS

Vascular endothelial growth factor (VEGF), interleukin 6 (IL-6), leptin, C-reactive protein (CRP), creatine-kinase-MB (CK-MB) and cancer antigen 15-3 (CA 15-3) levels were determined prospectively in serum samples that were obtained from patients who underwent surgery for an adnexal mass and who were referred to Istanbul University, Faculty of Medicine, Department of Obstetrics and Gynecology, between 2009 and 2011, and then were compared with the serum samples of completely healthy outpatient patients as a control group. Based onto the ovarian cancer status, cases were divided into four groups: 13 patients were included in the early-stage malignant group, 12 patients were included in the advanced-stage malignant group, 25 in the benign group and 19 in the healthy control group. Patients with only epithelial ovarian cancer were included into the cancer group. Ethics Commitee approval was obtained for this study. The budget was supported by the Istanbul University Scientific Research Projects Unit.

RESULTS

RESULTS RELATED WITH SENSITIVITY, SPECIFICITY, POSITIVE PREDICTIVE VALUE (PPV), NEGATIVE PREDICTIVE VALUE (NPV) AND ODDS RATIO (OR), RESPECTIVELY, AND THE FOLLOWING VALUES WERE CALCULATED: 48%, 95%, 92%, 59% and +OR 9.6 -OR 0.5 for CA; 15-3; 52%, 75%, 72%, 55%, +OR 2.08 -OR 0.64 for leptin; 72%, 70%, 75%, 66% 2.4-0.5 for IL-6; 24%, 80%, 60%, 45%, 1.2-0.92 for VEGF; 68%, 30%, 55%, 43%, 0.97-1.06 for CRP; and 8%, 70%, 25%, 38%, 026-1.31 for CK-MB.

CONCLUSION

CA 15-3, IL-6, Leptin, VEGF and CRP were effective in the prediction of benign and malignant masses; however they may be more suitable in selected cases as they have a limited use because of their inadequate potential regarding sensitivity and specificity.

External validation of diagnostic models to estimate the risk of malignancy in adnexal masses

PURPOSE

To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses.

EXPERIMENTAL DESIGN

We externally validated the diagnostic performance of 11 models developed by the International Ovarian Tumor Analysis (IOTA) group and 12 other (non-IOTA) models on 997 prospectively collected patients. The non-IOTA models included the original risk of malignancy index (RMI), three modified versions of the RMI, six logistic regression models, and two artificial neural networks. The ability of the models to discriminate between benign and malignant adnexal masses was expressed as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and likelihood ratios (LR(+), LR(-)).

RESULTS

Seven hundred and forty-two (74%) benign and 255 (26%) malignant masses were included. The IOTA models did better than the non-IOTA models (AUCs between 0.941 and 0.956 vs. 0.839 and 0.928). The difference in AUC between the best IOTA and the best non-IOTA model was 0.028 [95% confidence interval (CI), 0.011-0.044]. The AUC of the RMI was 0.911 (difference with the best IOTA model, 0.044; 95% CI, 0.024-0.064). The superior performance of the IOTA models was most pronounced in premenopausal patients but was also observed in postmenopausal patients. IOTA models were better able to detect stage I ovarian cancer.

CONCLUSION

External validation shows that the IOTA models outperform other models, including the current reference test RMI, for discriminating between benign and malignant adnexal masses.

A nomogram for estimating the probability of ovarian cancer

OBJECTIVE

Accurate preoperative estimates of the probability of malignancy in women with adnexal masses are essential for ensuring optimal care. This study presents a new statistical model for combining predictive information and a graphic decision support tool for calculating risk of malignancy.

METHODS

The study included 153 women treated with definitive surgery for adnexal mass between 2001 and 2007 with preoperative ultrasound testing and a serum CA125. Multivariable logistic regression was used to develop a statistical model for estimating the probability of ovarian cancer as a function of age, ultrasound score, and CA125 value, with adjustments for nonlinear and interactive relationships.

RESULTS

A total of 20 cases of pathologically confirmed cancer (13 invasive malignancies, and 7 tumors of low malignant potential) were identified (20/153=13%). The model obtained excellent discrimination (ROC area=0.87), explained nearly half of the observed variation in the risk of malignancy (R²=0.43), and was well calibrated across the full range of malignancy probabilities. The model equation is represented in the form of a nomogram, which can be used to calculate preoperative probability of malignancy. At a 5% risk of malignancy threshold, the model has a sensitivity of 90% and a specificity of 73%.

CONCLUSIONS

Statistical models for estimating the probability of adnexal mass malignancy are substantially improved by including adjustments for non-linear relationships among key variables. A clinically relevant nomogram provides an objective tool to further aid clinicians in counseling patients and ensuring proper referral to surgical sub-specialists when indicated.

Laparoscopy versus laparotomy for benign ovarian tumour

BACKGROUND

Over the last 10 years laparoscopy and minilaparotomy have become increasingly common approaches for the surgical removal of benign ovarian tumours. However, in the event that a tumour is found to be malignant, laparotomy is the appropriate procedure. Careful preoperative assessment including transvaginal ultrasound with morphological scoring, colour doppler assessment of vascular quality, and serum cancer antigen 125 (CA 125) level is desirable.

OBJECTIVES

To determine the benefits, harms, and cost of laparoscopy or minilaparotomy compared with laparotomy in women with benign ovarian tumours.

SEARCH STRATEGY

We searched electronic databases, trial registers, and reference lists of published trial reports. Reference lists from trials and review articles were searched.

SELECTION CRITERIA

All randomised controlled trials comparing either laparoscopy or minilaparotomy with laparotomy for benign ovarian tumours.

DATA COLLECTION AND ANALYSIS

Eight review authors independently assessed the eligibility and quality of each study and extracted the data.

MAIN RESULTS

The results of nine randomised controlled trials (N = 482 women) showed that laparoscopic surgery was associated with fewer adverse events of surgery (surgical injury or postoperative complications including fever or infection) (OR 0.3, 95% CI 0.2 to 0.5), less postoperative pain (VAS score WMD -2.4, 95% CI -2.7 to -2.0), greater likelihood of being pain free after two days (OR 7.42, 95% CI 4.86 to 11.33), and fewer days in hospital (WMD -2.88, 95% CI -3.1 to -2.7) than with laparotomy.In one study that reported costs, laparoscopy was associated with a significant reduction in costs compared to laparotomy (WMD - USD 1045, 95% CI -1348 to -742) in 1993. Very high levels of heterogeneity made it inappropriate to pool data on duration of surgery.Three RCTs compared laparoscopy versus minilaparotomy and found that laparoscopy was associated with reduced odds of any adverse event (surgical injury or postoperative complications) (OR 0.10, 95% CI 0 to 0.8) and lower VAS scores for pain (WMD -1.0, 95% CI -1.6 to -0.45). Duration of hospital stay ranged between 1 and 2.2 days, with substantial heterogeneity.

AUTHORS' CONCLUSIONS

In women undergoing surgery for benign ovarian tumours, laparoscopy was associated with a reduction in fever, urinary tract infection, postoperative complications, postoperative pain, number of days in hospital, and total cost. These findings should be interpreted with caution since only a small number of studies were identified. These included a total of only 769 women and not all of the important outcomes were reported in each study.

The accuracy of risk scores in predicting ovarian malignancy: a systematic review

OBJECTIVE

To perform a systematic review of the literature on the accuracy of prediction models in the preoperative assessment of adnexal masses.

DATA SOURCES

Studies were identified through the MEDLINE and EMBASE databases from inception to March 2008. The MEDLINE search was performed using the keywords ["ovarian neoplasms"[MeSH] NOT "therapeutics"[MeSH] AND "model"] and ["ovarian neoplasms"[MeSH] NOT "therapeutics"[MeSH] AND "prediction"]. The Embase search was performed using the keywords [ovary tumor AND prediction], [ovary tumor AND Mathematical model], and [ovary tumor AND statistical model].

METHODS OF STUDY SELECTION

The search detected 1,161 publications; from the cross-references, another 116 studies were identified. Language restrictions were not applied. Eligible studies contained data on the accuracy of models predicting the risk of malignancy in ovarian masses. Models were required to combine at least two parameters.

TABULATION, INTEGRATION, AND RESULTS

Two independent reviewers selected studies and extracted study characteristics, study quality, and test accuracy. There were 109 accuracy studies that met the selection criteria. Accuracy data were used to form two-by-two contingency tables of the results of the risk score compared with definitive histology. We used bivariate meta-analysis to estimate pooled sensitivities and specificities and to fit summary receiver operating characteristic curves.Studies included in our analysis reported on 83 different prediction models. The model developed by Sassone was the most evaluated prediction model. All models has acceptable sensitivity and specificity. However, the Risk of Malignancy Index I and the Risk of Malignancy Index II, which use the product of the serum CA 125 level, an ultrasound scan result, and the menopausal state, were the best predictors. When 200 was used as the cutoff level, the pooled estimate for sensitivity was 78% for a specificity of 87%.

CONCLUSION

Based on our review, the Risk of Malignancy Index should be the prediction model of choice in the preoperative assessment of the adnexal mass.

A scoring system to differentiate malignant from benign masses in specific ultrasound-based subgroups of adnexal tumors

OBJECTIVE

To investigate if the prediction of malignant adnexal masses can be improved by considering different ultrasound-based subgroups of tumors and constructing a scoring system for each subgroup instead of using a risk estimation model applicable to all tumors.

METHODS

We used a multicenter database of 1573 patients with at least one persistent adnexal mass. The masses were categorized into four subgroups based on their ultrasound appearance: (1) unilocular cyst; (2) multilocular cyst; (3) presence of a solid component but no papillation; and (4) presence of papillation. For each of the four subgroups a scoring system to predict malignancy was developed in a development set consisting of 754 patients in total (respective numbers of patients: (1) 228; (2) 143; (3) 183; and (4) 200). The subgroup scoring system was then tested in 312 patients and prospectively validated in 507 patients. The sensitivity and specificity, with regard to the prediction of malignancy, of the scoring system were compared with that of the subjective evaluation of ultrasound images by an experienced examiner (pattern recognition) and with that of a published logistic regression (LR) model for the calculation of risk of malignancy in adnexal masses. The gold standard was the pathological classification of the mass as benign or malignant (borderline, primary invasive, or metastatic).

RESULTS

In the prospective validation set, the sensitivity of pattern recognition, the LR model and the subgroup scoring system was 90% (129/143), 95% (136/143) and 88% (126/143), respectively, and the specificity was 93% (338/364), 74% (270/364) and 90% (329/364), respectively.

CONCLUSIONS

In the hands of experienced ultrasound examiners, the subgroup scoring system for diagnosing malignancy has a performance that is similar to that of pattern recognition, the latter method being the best diagnostic method currently available. The scoring system is less sensitive but more specific than the LR model.

Comparison of the risk of malignancy index and self-constructed logistic regression models in preoperative evaluation of adnexal masses

OBJECTIVE

The aim of this study was to evaluate women with adnexal masses in the preoperative period by creating 2 logistic regression models, 1 including sonographic morphologic characteristics and the other including both morphologic and color Doppler characteristics, to compare the diagnostic accuracy of these 2 models with the risk of malignancy index (RMI).

METHODS

This prospective study included 38 malignant, 7 borderline, and 244 benign ovarian masses. The menopausal status, presence of septa, presence of papillary projections, location of the tumor, presence of ascites, presence of metastases, cancer antigen 125 level, tumor volume, septa thickness, and percentage of the solid component were included in the initial analysis. A second regression analysis was performed with the addition of Doppler parameters (location of blood flow and lowest resistive index) in the data set. Diagnostic performance of the 2 regression models and RMI were described and compared by generating receiver operating characteristic curves for each model.

RESULTS

The area under the curve values for the morphologic model (model 1), Doppler model (model 2), and RMI were 0.907, 0.971, and 0.889, respectively. Significance levels of model 1 and the RMI were similar (P = .23), whereas model 2 had a significantly higher area under the curve compared with both model 1 (P = .037) and the RMI (P = .018).

CONCLUSIONS

The addition of Doppler parameters in the regression model significantly increases the predictive performance. Nevertheless, in low-resource settings, the RMI remains the method of choice for distinguishing adnexal masses and referral to gynecologic oncology clinics.

The early detection of ovarian cancer: from traditional methods to proteomics. Can we really do better than serum CA-125?

Ovarian cancer is the leading cause of death from gynecologic malignancy in the United States. More than 80% of patients present with advanced disease, with 5 year survival rates between 15% and 45%. In contrast, the survival rate for stage I disease, with malignancy confined to the ovary, is approximately 95%. Given the discrepancy in survival outcomes between early- and late-stage disease, strategies that would allow for the detection of ovarian cancer in its early stages would hold promise to significantly improve the mortality rate from ovarian cancer. Unfortunately, current screening methods for the detection of early stage ovarian cancer are inadequate. However, several recent proteomics-based biomarker discovery projects show promise for the development of highly sensitive and specific markers for gynecological malignancies, including ovarian cancer. In this review, we hope to provide an overview of the early detection ovarian cancer from traditional methods to recent promises in the proteomics pipeline.

Simple ultrasound-based rules for the diagnosis of ovarian cancer

OBJECTIVE

To derive simple and clinically useful ultrasound-based rules for discriminating between benign and malignant adnexal masses.

METHODS

In a multicenter study involving nine centers consecutive patients with persistent adnexal tumors underwent transvaginal gray-scale and Doppler ultrasound examination using a standardized examination technique and standardized terms and definitions. Information on 42 gray-scale ultrasound variables and six Doppler variables was collected and entered into a research protocol. When developing simple ultrasound-based rules to predict malignancy (M-rules) we chose the ultrasound variable or the combination of ultrasound variables that had the highest positive predictive value (PPV) with regard to malignancy; when developing simple rules to predict a benign tumor (B-rules) we chose the ultrasound variable or the combination of ultrasound variables that had the lowest PPV with regard to malignancy. We selected ten rules that were in agreement with our clinical experience and were applicable to at least 30 tumors and then tested them prospectively on 507 tumors examined in three of the nine centers.

RESULTS

1066 patients with 1233 adnexal tumors were included. There were 903 benign tumors (73%) and 330 malignant tumors (27%). In 167 patients the tumors were bilateral. We selected five simple rules to predict malignancy (M-rules): (1) irregular solid tumor; (2) ascites; (3) at least four papillary structures; (4) irregular multilocular-solid tumor with a largest diameter of at least 100 mm; and (5) very high color content on color Doppler examination. We chose five simple rules to suggest a benign tumor (B-rules): (1) unilocular cyst; (2) presence of solid components where the largest solid component is < 7 mm in largest diameter; (3) acoustic shadows; (4) smooth multilocular tumor less than 100 mm in largest diameter; and (5) no detectable blood flow on Doppler examination. These ten rules were applicable to 76% of all tumors, where they resulted in a sensitivity of 93%, specificity of 90%, positive likelihood ratio (LR+) of 9.45 and negative likelihood ratio (LR-) of 0.08. When prospectively tested the rules were applicable in 76% (386/507) of the tumors, where they had a sensitivity of 95% (106/112), a specificity of 91% (249/274), LR+ of 10.37, and LR- of 0.06.

CONCLUSION

Most adnexal tumors in an ordinary tumor population can be correctly classified as benign or malignant using simple ultrasound-based rules. For tumors that cannot be classified using simple rules, ultrasound examination by an expert examiner might be useful.