Cancer patients may one day be able to forgo invasive tissue sampling thanks to ‘virtual biopsies’ that combine CT and ultrasound scans, a study has reported.
Cambridge experts showed that the routine medical scans can be used to create a visual guide of tumours to help doctors pick the best site for targeted biopsies.
This could allow fewer biopsies whilst still allowing comprehensive sampling of a tumour — and may one day even be able to render physical biopsies redundant.
Cancer patients may one day be able to forgo invasive tissue sampling thanks to ‘virtual biopsies’ that combine CT and ultrasound scans, a study has reported. Pictured, scans of a patient with a pelvic tumour, showing on the left an ultrasound image with the tumour outline as derived from CT scans and, on the right, the same with the tumour map overlain
‘Our study is a step forward to non-invasively unravel tumour heterogeneity by using standard-of-care CT-based radiomic tumour habitats for ultrasound-guided targeted biopsies,’ said radiologist Lucian Beer of the University of Cambridge.
Tumour heterogeneity is the term doctors give to the extent to which a given lump of cancerous tissues is made up of different types of cell.
Understanding the makeup of a given tumour is key to picking the best treatment for the patient — as genetically-different cells can vary in their responses to treatments.
Cancer patients thus typically undergo a number of biopsies in order to confirm their diagnose and help guide their treatment plan — with doctors balancing the need to take comprehensive samples against the invasive nature of the procedure.
Accurate biopsies are particularly important, the researchers explained, in the case of ovarian cancer. The most common type — ‘high grade serous ovarian cancer’ — tends to come with high levels of tumour heterogeneity.
Those patients with higher levels of variation among their tumour cell types tend, unfortunately, to have poorer responses to treatment regimes.
In their study, Dr Beer and colleagues recruited six patients with advanced ovarian cancer who were scheduled to have ultrasound-guided biopsies prior to starting their chemotherapy regimen.
The team used standard CT scans to create a three-dimensional image of the patients tumours, built up ‘slice-by-slice’ by a series of X-ray images.
The researchers then used high-powered computing techniques to map out the extent and internal features of the tumour — which was finally overlain onto the ultrasound scan in order to guide each patient’s biopsies.
According to the team, the approach was successful in capturing the diversity of cancer cells within each patient’s tumour.
Understanding the makeup of a given tumour is key to picking the best treatment for the patient — as genetically-different cells can vary in their responses to treatments. Cancer patients thus typically undergo a number of biopsies in order to confirm their diagnose and help guide their treatment plan — with doctors balancing the need to take comprehensive samples against the invasive nature of the procedure. Pictured, an excision biopsy
‘When you are first undergoing the diagnosis of cancer, you feel as if you are on a conveyor belt, every part of the journey being extremely stressful,’ commented Fiona Barve, a science teacher from Cambridge who is an ovarian cancer survivor.
‘This new enhanced technique will reduce the need for several procedures and allow patients more time to adjust to their circumstances.’
‘It will enable more accurate diagnosis with less invasion of the body and mind. This can only be seen as positive progress,’ she concluded.
‘This study provides an important milestone towards precision tissue sampling,’ said research leader and Cancer Research UK radiologist Evis Sala.
‘We are truly pushing the boundaries in translating cutting edge research to routine clinical care.’
With their initial research complete, the team are now looking to apply their new imaging technique within a larger clinical study.
The full findings of the study were published in the journal European Radiology.