Three-dimensional ultrasound and three-dimensional power Doppler in the assessment of ovarian tumors

Is three-dimensional ultrasonography a valuable diagnostic tool for patients with ovarian cancer? Systematic review and meta-analysis

Introduction

This paper was to assess the diagnostic performance and clinical value of three-dimensional ultrasonography (3DUS), three-dimensional ultrasonography power Doppler (3DPD), and 3DUS combined with 3DPD in ovarian cancer (OC).

Methods

The study was registered with PROSPERO (CRD 42023405765). PubMed and Web of Science were searched from inception to 25 January 2022, and reference lists of potentially eligible studies were also manually searched. Patient and study characteristics were extracted by two independent reviewers. Any discrepancies were addressed through discussion. The sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR, respectively), and the area under the receiver operating characteristic curve (AUC) were pooled separately.

Results

We retrieved 2,566 studies, of which 18 were finally enrolled, with 2,548 cases. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS were 0.89 (95% CI: 0.85-0.93), 0.93 (95% CI: 0.88-0.96), 13.1 (95% CI: 7.3-23.4), 0.11 (95% CI: 0.08-0.16), and 0.90 (95% CI: 0.87-0.93), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DPD were 0.90 (95% CI: 0.80-0.95), 0.85 (95% CI: 0.71-0.92), 5.8 (95% CI: 3.0-11.2), 0.12 (95% CI: 0.06-0.24), and 0.94 (95% CI: 0.91-0.96), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS combined with 3DPD were 0.99 (95% CI: 0.73-1.00), 0.95 (95% CI: 0.85-0.99), 21.9 (95% CI: 6.1-78.9), 0.01 (95% CI: 0.00-0.37), and 0.99 (95% CI: 0.98-1.00), respectively.

Conclusions

3DUS, 3DPD, and 3DUS combined with 3DPD are promising diagnostic tools for OC, alongside elevated sensitivity and specificity. However, the combination of 3DUS and 3DPD techniques has higher diagnostic efficiency.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023405765.

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.

Clinical management of incidental findings on pelvic adnexal masses

Due to widespread use of pelvic and transvaginal ultrasound in routine gynecological evaluation, the incidental finding of adnexal masses has led to discussions about management in asymptomatic patients regarding the risk of ovarian cancer. Transvaginal ultrasonography remains the modality of choice in the evaluation of suspicious characteristics. The combined analysis of ultrasound morphological parameters with Doppler study, serum carcinoma antigen 125 and investigation of a symptom index may improve diagnosis. Surgical approach should be considered whenever there are suspicious images, rapid growth of cysts, changes in the appearance compared to the initial evaluation or when the patient has symptoms. Future studies on genetic and molecular mechanisms may help explain the pathophysiology of ovarian cancer, improving early diagnosis and treatment.

GyneScan: an improved online paradigm for screening of ovarian cancer via tissue characterization

Ovarian cancer is the fifth highest cause of cancer in women and the leading cause of death from gynecological cancers. Accurate diagnosis of ovarian cancer from acquired images is dependent on the expertise and experience of ultrasonographers or physicians, and is therefore, associated with inter observer variabilities. Computer Aided Diagnostic (CAD) techniques use a number of different data mining techniques to automatically predict the presence or absence of cancer, and therefore, are more reliable and accurate. A review of published literature in the field of CAD based ovarian cancer detection indicates that many studies use ultrasound images as the base for analysis. The key objective of this work is to propose an effective adjunct CAD technique called GyneScan for ovarian tumor detection in ultrasound images. In our proposed data mining framework, we extract several texture features based on first order statistics, Gray Level Co-occurrence Matrix and run length matrix. The significant features selected using t-test are then used to train and test several supervised learning based classifiers such as Probabilistic Neural Networks (PNN), Support Vector Machine (SVM), Decision Tree (DT), k-Nearest Neighbor (KNN), and Naive Bayes (NB). We evaluated the developed framework using 1300 benign and 1300 malignant images. Using 11 significant features in KNN/PNN classifiers, we were able to achieve 100% classification accuracy, sensitivity, specificity, and positive predictive value in detecting ovarian tumor. Even though more validation using larger databases would better establish the robustness of our technique, the preliminary results are promising. This technique could be used as a reliable adjunct method to existing imaging modalities to provide a more confident second opinion on the presence/absence of ovarian tumor.

Role of Three-Dimensional Ultrasound in Gynecology

Three-dimensional ultrasound (3D USG) is a fast-evolving imaging technique that holds a great potential for use in gynecology. Its sensitivity and specificity is reported to be close to 100 % for diagnosing congenital uterine anomalies, comparable with those of magnetic resonance imaging (MRI) and laparoscopy. With 3D USG, a coronal view of the uterus can be obtained, clearly outlining the external contour of the uterus and providing accurate information about the shape of the cavity. Although 3D USG may not perform well in thin endometria, combining it with saline infusion sonography (SIS) overcomes this problem. Research shows that 3D USG is more sensitive and specific than two-dimensional ultrasound (2D USG) in defining and mapping uterine lesions, such as fibroids, adenomyosis, and intrauterine synechia. In cases of suspected malignancy, 3D USG is mainly used in the initial evaluation of patients. Measuring various indices and mapping vascular architecture with 3D power Doppler have been proposed for evaluating adnexal masses. Although some studies raised hope, no consensus is reached about its use, success, and limitations. In urogynecology, translabial 3D USG is proved to be a valuable tool, as it provides instant access to the axial plane, which clearly depicts the relationship of the vagina, urethra, rectum, and the muscular pelvic floor. Studies report no significant differences between translabial 3D USG and MRI measurements for evaluation of the pelvic floor. In conclusion, adding 3D USG to routine gynecological workup can be beneficial for clinicians, as it provides fast and accurate results in a relatively cost-effective setting.

Ovarian tumor characterization and classification using ultrasound-a new online paradigm

Among gynecological malignancies, ovarian cancer is the most frequent cause of death. Image mining algorithms have been predominantly used to give the physicians a more objective, fast, and accurate second opinion on the initial diagnosis made from medical images. The objective of this work is to develop an adjunct computer-aided diagnostic technique that uses 3D ultrasound images of the ovary to accurately characterize and classify benign and malignant ovarian tumors. In this algorithm, we first extract features based on the textural changes and higher-order spectra information. The significant features are then selected and used to train and evaluate the decision tree (DT) classifier. The proposed technique was validated using 1,000 benign and 1,000 malignant images, obtained from ten patients with benign and ten with malignant disease, respectively. On evaluating the classifier with tenfold stratified cross validation, the DT classifier presented a high accuracy of 97 %, sensitivity of 94.3 %, and specificity of 99.7 %. This high accuracy was achieved because of the use of the novel combination of the four features which adequately quantify the subtle changes and the nonlinearities in the pixel intensity variations. The rules output by the DT classifier are comprehensible to the end-user and, hence, allow the physicians to more confidently accept the results. The preliminary results show that the features are discriminative enough to yield good accuracy. Moreover, the proposed technique is completely automated, accurate, and can be easily written as a software application for use in any computer.

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.

Ovarian tumor characterization and classification: a class of GyneScan™ systems

In this work, we have developed an adjunct Computer Aided Diagnostic (CAD) technique that uses 3D acquired ultrasound images of the ovary and data mining algorithms to accurately characterize and classify benign and malignant ovarian tumors. In this technique, we extracted image-texture based and Higher Order Spectra (HOS) based features from the images. The significant features were then selected and used to train and test the Decision Tree (DT) classifier. The proposed technique was validated using 1000 benign and 1000 malignant images, obtained from 10 patients with benign and 10 with malignant disease, respectively. On evaluating the classifier with 10-fold stratified cross validation, we observed that the DT classifier presented a high accuracy of 95.1%, sensitivity of 92.5% and specificity of 97.7%. Thus, the four significant features could adequately quantify the subtle changes and nonlinearities in the pixel intensities. The preliminary results presented in this paper indicate that the proposed technique can be reliably used as an adjunct tool for ovarian tumor classification since the system is accurate, completely automated, cost-effective, and can be easily written as a software application for use in any computer.

Doppler imaging in the diagnosis of ovarian disease

INTRODUCTION

Pelvic ultrasonography remains the non-invasive imaging modality of choice for detecting and characterising adnexal masses. The use of Doppler ultrasound has improved the differential diagnosis of ovarian disease and helped to widen the understanding of the aetiology and possible pathophysiology of the various underlying conditions with an aim of improved diagnosis and management.

AREAS COVERED

This review describes the basis of different Doppler techniques and their application in ovarian disease. The present evidence is critically analysed in an attempt to define the current role of Doppler ultrasound of the ovaries. The technique holds promise in certain ovarian diseases but remains controversial in others.

EXPERT OPINION

Doppler ultrasound has a role in both the clinical and research settings. Clinically, it can be used to differentiate benign and malignant disease and help confirm diagnoses suggested on grey-scale imaging giving the user more confidence. Its use here, however, is generally restricted to a subjective impression of colour flow rather than a quantitative analysis of vascularity or blood flow velocity. These measures are more relevant in the research setting where quantitative Doppler is being used to clarify the possible underlying aetiology of various ovarian diseases such as polycystic ovarian syndrome and benign cysts. Doppler ultrasound has also been used in various models to evaluate the response to ovarian stimulation and the effect of surgery on the ovary.

Preoperative diagnosis of ovarian malignancy: preliminary results of the use of 3-dimensional vascular ultrasound

OBJECTIVE

To estimate the accuracy of 3-dimensional (3D) vascular ultrasound in the preoperative assessment of pelvic masses for malignancy.

METHODS

We performed a chart review of 66 patients who underwent 3D ultrasound for pelvic masses. Each mass was preoperatively judged to be benign or malignant based upon a study of vascularity within an ovarian mass using 3D ultrasound. Masses with orderly vascular architecture were categorized as probably benign, and masses with chaotic vascular patterns were categorized as malignant. The predictive value of 3D vascular ultrasound was compared with that of 2-dimensional ultrasound and cancer antigen 125 as a predictor of malignancy.

RESULTS

Among the 66 patients examined, 34 underwent a documented surgical intervention. Of those 34 patients, 10 had primary malignant neoplasms including 2 with low-malignant potential tumors. Suspicious 3D vascular ultrasound findings predicted malignant neoplasm in 10 patients. Two patients had recurrent cancer; however, only 1 had a suspicious ultrasound finding. There was 1 case of a low-malignant potential tumor without a suspicious ultrasound finding. Excluding the recurrent cancers and the observed patients, the positive predictive value (PPV) and the negative predictive value (NPV) of 3D vascular ultrasound were 100% and 95%, respectively. The PPV and the NPV of 2-dimensional ultrasound in predicting malignancy were 37% and 100%, respectively. An abnormal level of cancer antigen 125 had a PPV and an NPV of 73% and 83%, respectively, in this patient population.

CONCLUSIONS

In this preliminary and observational study, 3D ultrasound examination of vascular architecture was discriminatory in distinguishing benign ovarian masses from malignancy. Chaotic vascular architecture correlated with malignancy in this group of high-risk patients.