Automated analysis of breast cancer patients' routine scans can predict which women have a greater than one in four risk of going on to develop cardiovascular disease, according to research presented at the 12th European Breast Cancer Conference.
Women who have been treated for breast cancer may have a higher risk of developing cardiovascular disease and in some groups the risk of dying from cardiovascular disease is higher than the risk of dying from breast cancer.
The new study shows that it is possible to spot those at the greatest risk using computer analysis of the CT scans that are taken for planning cancer treatments. Researchers say that identifying patients most at risk of cardiovascular disease could allow steps to be taken to lower the risk.
Numed, a well established company in business since 1975 provides a wide range of service options including time & material service, PM only contracts, full service contracts, labor only contracts & system relocation. Call 800 96 Numed for more info.
The research was presented by Professor Helena Verkooijen, from the Division of Imaging and Oncology at the University Medical Center Utrecht in The Netherlands. She said: "We've seen great improvement in breast cancer survival, thanks in part to better treatment. However, treatments have side effects and some treatments - such as radiotherapy and certain types of cancer drug - can increase the risk of cardiovascular disease. In my opinion, treating breast cancer means finding the right balance between maximising chances of tackling the tumour, while minimising the risks of side effects, including the risk of cardiovascular disease."
The study included around 14,000 breast cancer patient who were treated with radiotherapy in three large hospitals in The Netherlands between 2005 and 2016.
Professor Verkooijen and her colleagues used a measure called coronary artery calcium (CAC) score. This is a calculation of the amount of calcium in the walls of the heart's arteries and it is known to be strong risk factor in cardiovascular disease because calcifications can lead to narrowing or blocking of the blood vessels.
The researchers developed a deep learning algorithm that could gauge the presence and extent of coronary artery calcifications from the CT scans that were already being carried out to help plan each woman's radiotherapy treatment. This allowed them to automate the measurement of CAC for all the women with only minimal extra workload.
Researchers followed the women for an average of 52 months to see whether any of them developed cardiovascular disease. In women with no calcifications (a score of zero), 5% went on to be hospitalised or to die from cardiovascular disease. In women with a score of between one and ten, 8.9% were hospitalised with or died from cardiovascular disease. In women with a score of 11-100, the figure was 13.5%, in women with a score of 101-400 it was 17.5% and in women with a score above 400, it was 28.3%.