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A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions
Published on: March 3, 2023
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Imaging-Based Pre-Operative Differentiation of Ovarian Tumours-A Retrospective Cross-Sectional Study.
Assel Kabibulatova1, Mehzabin Kazi2, Peter Berglund2
1Scientific Research Institute of Radiology Named After ZH.H. Khamzabayev, Astana Medical University, Astana 010000, Kazakhstan.
Diagnostics (Basel, Switzerland)
|October 29, 2025
Summary
Radiological stage (rFIGO) and MRI-based O-RADS-MRI scores effectively predict ovarian malignancy. However, these imaging biomarkers do not improve the prediction of adverse features in borderline ovarian tumours.
Area of Science:
- Radiology
- Oncology
- Gynaecology
Background:
- Accurate prediction of ovarian tumour malignancy is crucial for patient management.
- Imaging biomarkers play a role in differentiating benign, borderline, and malignant ovarian lesions.
Purpose of the Study:
- To evaluate the diagnostic performance of imaging biomarkers from CT and MRI for predicting malignant and borderline ovarian tumours.
- To compare the efficacy of radiological stage (rFIGO), Ovarian-Adnexal Reporting and Data System MRI score (O-RADS-MRI), and apparent diffusion coefficient (ADCmean) in malignancy prediction.
Main Methods:
- Retrospective analysis of 195 patients with suspected epithelial ovarian cancer from the PRODIGYN study.
- Assessment of rFIGO stage, O-RADS-MRI score, and ADCmean for predicting ovarian malignancy against histopathology.
- Application of these biomarkers to a borderline tumour cohort (n=33) to identify adverse features.
Main Results:
- rFIGO stage showed high accuracy for ovarian malignancy (AUC=0.98).
- O-RADS-MRI score demonstrated high sensitivity (1) and specificity (0.82) for malignancy prediction.
- ADCmean had moderate performance (AUC=0.78) for malignancy prediction.
- No improvement in discriminating adverse features in borderline tumours was observed.
Conclusions:
- rFIGO and O-RADS-MRI are excellent predictive tools for ovarian malignancy, outperforming ADCmean.
- These imaging biomarkers are not effective in predicting adverse features within borderline ovarian tumours.
