E4 - Imaging in Ovarian Cancer

E4   |  14 min   |   Latest   |  Publication Link

• Podcast based on: D’Amario, A.; Ambrosini, R.; Gullino, A.; Grazioli, L. Role of Imaging Techniques in Ovarian Cancer Diagnosis: Current Approaches and Future Directions. Cancers 2026, 18, 173. https://doi.org/10.3390/cancers18010173
  Type: Review  |  Publication date: 04 January 2026
  
  
• Summary: Ovarian cancer is a leading cause of death among gynecological malignancies. Standard ultrasound scans may not be conclusive, especially when ovarian masses are difficult to classify. This review highlights recent advances aimed at reducing diagnostic uncertainty. Contrast-enhanced MRI has demonstrated high accuracy in differentiating benign from malignant lesions, and the O-RADS MRI scoring system provides structured risk assessment with strong sensitivity and specificity. New classification methods are also being developed to further support clinical decision-making. In addition, artificial intelligence (AI) approaches, including machine learning and deep learning, are being tested to improve diagnostic precision by analyzing complex imaging data. Overall, the integration of advanced imaging with AI has the potential to substantially improve the evaluation and management of women with suspected ovarian cancer.
  
  
• Keywords: ovarian cancer; Ultrasound (US); Computed Tomography (CT); Magnetic Resonance Imaging (MRI); O-RADS MRI Score; Artificial Intelligence (AI); radiomics

 

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