Intra- and interobserver variability of 2D and 3D transvaginal sonography in the diagnosis of benign versus malignant adnexal masses

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.

Ultrasound-based radiomics score: a potential biomarker for the prediction of progression-free survival in ovarian epithelial cancer

PURPOSE

More than 80% of patients with ovarian epithelial cancer (OEC) show complete remission after initial treatment but eventually experience recurrence of the disease. This study aimed to develop a radiomics signature to identify a new prognostic indicator based on preoperative ultrasound imaging.

METHODS

A total of 111 patients with OEC who underwent transvaginal ultrasound before surgery were included. Of these, 76 were divided into the training cohort and 35 into the test cohort. We defined the region of interest (ROI) of the tumor by manually drawing the tumor contour on the ultrasound image of the lesion. The radiomics features were extracted from ultrasound images. The radiomics score (Rad-Score) was constructed using the least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Combined with the ultrasound radiomics features, significant clinical variables were also used to establish predictive models for 5-year progression-free survival (PFS) prediction. The efficiency of the model was evaluated using the area under the curve (AUC). Kaplan-Meier analysis was used to evaluate the association between the Rad-Score and PFS.

RESULTS

The combined model was superior to the clinical and Rad-Score models in estimating 5-year PFS and achieved an AUC of 0.868 (95%CI 0.766-0.971) in the training cohort. The Rad-Score was negatively correlated with prognosis in the training and test cohorts.

CONCLUSIONS

The combined model that incorporated both clinical parameters and ultrasound radiomics features achieved a good prognosis in patients with OEC, which might aid clinical decision-making.

Noninvasive prediction of lymph node status for patients with early-stage cervical cancer based on radiomics features from ultrasound images

OBJECTIVE

To investigate the feasibility of a noninvasive detection of lymph node metastasis (LNM) for early-stage cervical cancer (ECC) patients with radiomics methods based on the textural features from ultrasound images.

METHODS

One hundred seventy-two ECC patients between January 2014 and September 2018 with pathologically confirmed lymph node status (LNS) and preoperative ultrasound images were retrospectively reviewed. Regions of interest (ROIs) were delineated by a senior radiologist in the ultrasound images. LIFEx was applied to extract textural features for radiomics study. Least absolute shrinkage and selection operator (LASSO) regression was applied for dimension reduction and for selection of key features. A multivariable logistic regression analysis was adopted to build the radiomics signature. The Mann-Whitney U test was applied to investigate the correlation between radiomics and LNS for both training and validation cohorts. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the radiomics prediction models.

RESULTS

A total of 152 radiomics features were extracted from ultrasound images, in which 6 features were significantly associated with LNS (p < 0.05). The radiomics signatures demonstrated a good discrimination between patients with LNM and non-LNM groups. The best radiomics performance model achieved an area under the curve (AUC) of 0.79 (95% confidence interval (CI), 0.71-0.88) in the training cohort and 0.77 (95% CI, 0.65-0.88) in the validation cohort.

CONCLUSIONS

The feasibility of radiomics features from ultrasound images for the prediction of LNM in ECC was investigated. This noninvasive prediction method may be used to facilitate preoperative identification of LNS in patients with ECC.

KEY POINTS

• Few studied had investigated the feasibility of radiomics based on ultrasound images for cervical cancer, even though it is the most common practice for gynecological cancer diagnosis and treatment. • The radiomics signatures based on ultrasound images demonstrated a good discrimination between patients with and without lymph node metastasis with an area under the curve (AUC) of 0.79 and 0.77 in the training and validation cohorts, respectively. • The radiomics model based on preoperative ultrasound images has the potential ability to predict lymph node status noninvasively in patients with early-state cervical cancer, so as to reduce the impact of invasive examination and to optimize the treatment choices.

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.

Characterization of Ovarian Tumors and Staging Ovarian Cancer With 3-Dimensional Power Doppler Angiography: Correlation With Pathologic Findings

Objective

The aims of this study were to evaluate ovarian tumors with 3-dimensional power Doppler angiography (3-DPDA), to determine its correlation with histology findings, and to explore its role in staging patients with ovarian cancer.

Methods

Three hundred eighteen women with an unknown unilateral pelvic mass were referred for preoperative evaluation by 3-DPDA angiography. Patients’ ages ranged from 18 to 72 years (47.4 ± 13.8 years). Sonographic criteria used for the characterization of ovarian tumors were based on a system that included morphological characteristics, histological evaluation, and Power Doppler imaging.

Results

Two hundred twenty-five tumors were histopathologically diagnosed as benign and 93 as malignant. Sensitivity and specificity of the 3-DPDA of ovarian masses reached 93.5% and 92.9%, respectively, whereas positive predictive value was 84.5% and negative predictive value was 97.2%.

Conclusions

Three-dimensional power Doppler sonography is an effective imaging technique for discriminating ovarian neoplasms and classifying them according to histopathology.

Current Role of 3D/4D Sonography in Obstetrics and Gynecology

Modern 3D/4D sonography provides a routine method not only for storing single image planes as in 2D ultrasound but also for storing complete sets of volume data in the computer memory. Once acquisition is completed, all volumes can be accessed from the memory and normal and abnormal findings in both obstetrics and gynecology can be demonstrated in different display modes. Furthermore digital storage of volumes permits virtual examinations by reloading of volumes and navigating through them in the absence of the patient.

This review article would like to give an illustration of the latest technologies in 3D/4D ultrasound in obstetrics and gynecology.

How to cite this article

Merz E, Pashaj S. Current Role of 3D/ 4D Sonography in Obstetrics and Gynecology. Donald School J Ultrasound Obstet Gynecol 2013;7(4):400-408.

Detection of intracavitary uterine pathology using offline analysis of three-dimensional ultrasound volumes: interobserver agreement and diagnostic accuracy

OBJECTIVE

To estimate the diagnostic accuracy and interobserver agreement in predicting intracavitary uterine pathology at offline analysis of three-dimensional (3D) ultrasound volumes of the uterus.

METHODS

3D volumes (unenhanced ultrasound and gel infusion sonography with and without power Doppler, i.e. four volumes per patient) of 75 women presenting with abnormal uterine bleeding at a 'bleeding clinic' were assessed offline by six examiners. The sonologists were asked to provide a tentative diagnosis. A histological diagnosis was obtained by hysteroscopy with biopsy or operative hysteroscopy. Proliferative, secretory or atrophic endometrium was classified as 'normal' histology; endometrial polyps, intracavitary myomas, endometrial hyperplasia and endometrial cancer were classified as 'abnormal' histology. The diagnostic accuracy of the six sonologists with regard to normal/abnormal histology and interobserver agreement were estimated.

RESULTS

Intracavitary pathology was diagnosed at histology in 39% of patients. Agreement between the ultrasound diagnosis and the histological diagnosis (normal vs abnormal) ranged from 67 to 83% for the six sonologists. In 45% of cases all six examiners agreed with regard to the presence/absence of intracavitary pathology. The percentage agreement between any two examiners ranged from 65 to 91% (Cohen's κ, 0.31-0.81). The Schouten κ for all six examiners was 0.51 (95% CI, 0.40-0.62), while the highest Schouten κ for any three examiners was 0.69.

CONCLUSION

When analyzing stored 3D ultrasound volumes, agreement between sonologists with regard to classifying the endometrium/uterine cavity as normal or abnormal as well as the diagnostic accuracy varied substantially. Possible actions to improve interobserver agreement and diagnostic accuracy include optimization of image quality and the use of a consistent technique for analyzing the 3D volumes.