State of the art imaging in ovarian carcinomatosis: how the radiologist can help plan management.
Authors
Affiliations (3)
Affiliations (3)
- Department of Radiology, Imperial College Healthcare NHS Trust, London, UK. Electronic address: [email protected].
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK.
- Department of Radiology, Imperial College Healthcare NHS Trust, London, UK; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK.
Abstract
Ovarian cancer (OC) is the leading cause of gynaecological cancer mortality and is most often diagnosed at an advanced stage due to its subtle early clinical presentation and characteristic peritoneal dissemination. High-grade serous carcinoma represents the predominant epithelial subtype and frequently presents with extensive peritoneal disease, making accurate preoperative evaluation essential. Management of advanced OC (AOC) hinges on the selection of patients for primary cytoreductive surgery vs neoadjuvant chemotherapy followed by interval cytoreduction, with complete cytoreduction remaining the strongest prognostic factor. Radiologists therefore play a critical role in assessing disease distribution, identifying features suggestive of unresectability, and guiding multidisciplinary decision-making. Contrast-enhanced computed tomography (CT) is the first-line modality for staging AOC, providing comprehensive assessment of peritoneal, nodal, and extra-abdominal disease. Despite its established utility, CT has reduced sensitivity for small-volume implants and involvement in surgically complex regions. Magnetic resonance imaging (MRI) offers superior soft tissue characterisation and improves detection of peritoneal disease along the bowel serosa, mesentery, and subdiaphragmatic spaces, particularly through diffusion-weighted and contrast-enhanced techniques. Positron emission tomography (PET)/CT provides complementary metabolic information that can enhance detection of nodal and extraperitoneal metastases in selected cases. Emerging quantitative techniques, including radiomics and machine learning-based analysis, have the potential to extract biologically relevant imaging biomarkers, refine predictions of resectability, and stratify recurrence risk. Integrating these tools with conventional imaging may further support personalised treatment pathways. This review summarises current evidence regarding CT, MRI, and PET in the evaluation of peritoneal disease in AOC and highlights how imaging advances and radiologist expertise can optimise surgical planning and guide management strategies.