The research published in European Radiology shows that combining computed tomography (CT) scans with ultrasound images creates a visual guide for doctors to ensure they sample the full complexity of a tumour with fewer targeted biopsies.
Capturing the patchwork of different types of cancer cell within a tumour – known as tumour heterogeneity – is critical for selecting the best treatment because genetically-different cells may respond differently to treatment.
Most cancer patients undergo one or several biopsies to confirm diagnosis and plan their treatment. But because this is an invasive clinical procedure, there is an urgent need to reduce the number of biopsies taken and to make sure biopsies accurately sample the genetically-different cells in the tumour, particularly for ovarian cancer patients.
High grade serous ovarian (HGSO) cancer, the most common type of ovarian cancer, is referred to as a ‘silent killer’ because early symptoms can be difficult to pick up. By the time the cancer is diagnosed, it is often at an advanced stage, and survival rates have not changed much over the last 20 years.
But late diagnosis isn’t the only problem. HGSO tumours tend to have a high level of tumour heterogeneity and patients with more genetically-different patches of cancer cells tend to have a poorer response to treatment.
Professor Evis Sala from the Department of Radiology, co-lead CRUK Cambridge Centre Advanced Cancer Imaging Programme, leads a multi-disciplinary team of radiologists, physicists, oncologists and computational scientists using innovative computing techniques to reveal tumour heterogeneity from standard medical images. This new study, led by Professor Sala, involved a small group of patients with advanced ovarian cancer who were due to have ultrasound-guided biopsies prior to starting chemotherapy.
Image :shows individual and combined scans
Credit: Evis Sala
Reproduced courtesy of the University of Cambridge