Researchers at the University of Cambridge in England have developed a new computing technique using routine imaging scans that could allow physicians to take fewer, more accurate tumor biopsies. This is an important step toward precision tissue sampling for cancer patients to help select the best treatment, the researchers say. In the future, the technique could even replace clinical biopsies with “virtual biopsies,” sparing patients invasive procedures.

The research, published in European Radiology, shows that combining CT scans with ultrasound images creates a visual guide for physicians to ensure they sample the full complexity of a tumor with fewer targeted biopsies. Capturing the patchwork of different types of cancer cell within a tumor—known as tumor 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 tumor, 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 tumors tend to have a high level of tumor heterogeneity and patients with more genetically different patches of cancer cells tend to have a poorer response to treatment.

Evis Sala, MD, PhD, FRCR, from the University of Cambridge 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 tumor heterogeneity from standard medical images.

This new study, led by Sala, involved a small group of patients with advanced ovarian cancer who were due to have ultrasound-guided biopsies prior to starting chemotherapy. For the study, the patients first had a standard-of-care CT scan.

The researchers then used a process called radiomics—using high-powered computing methods to analyze and extract additional information from the data-rich images created by the CT scanner—to identify and map distinct areas and features of the tumor. The tumor map was then superimposed on the ultrasound image of the tumor and the combined image used to guide the biopsy procedure. By taking targeted biopsies using this method, the research team reported that the diversity of cancer cells within the tumor was successfully captured.

Co-first author Lucian Beer, from the University of Cambridge Department of Radiology and CRUK Cambridge Centre Ovarian Cancer Programme, says of the results: “Our study is a step forward to noninvasively unravel tumor heterogeneity by using standard-of-care CT-based radiomic tumor habitats for ultrasound-guided targeted biopsies.”

Sala adds: “This study provides an important milestone toward precision tissue sampling. We are truly pushing the boundaries in translating cutting edge research to routine clinical care.”