Chicago, Illinois: A novel technique involving the combination of quantitative three-compartment breast image analysis of breast masses and mammography radiomics, may help in the reduction of unnecessary breast biopsies for breast cancer detection, according to a new study.
The new study uses mammography to determine the biological tissue composition of a tumor during breast cancer screening, report authors in the journal Radiology.
Karen Drukker, research associate professor from the Department of Radiology at the University of Chicago in Chicago, and colleagues conducted the study to investigate the combination of mammography radiomics and quantitative three-compartment breast (3CB) image analysis of dual-energy mammography to limit unnecessary benign breast biopsies.
Mammography reduces deaths from breast cancer by detecting cancer in its treatable stages. However, many women are called back for additional diagnostic imaging and, in many cases, biopsies, for abnormal findings that are ultimately proven benign.
“The callback rate with mammography is much higher than ideal,” said Dr. Drukker. “There are costs and anxiety associated with recalls, and our goal is to reduce these costs but not miss anything that should be biopsied.”
The authors studied a new technique called three-compartment breast (3CB) imaging. By measuring the water, lipid and protein tissue composition throughout the breast, 3CB might provide a biological signature for a tumor. For instance, more water in the tumor tissue might indicate angiogenesis, or the production of new blood vessels, an early sign of cancer development.
For the study, the researchers acquired dual-energy mammograms from 109 women with breast masses that were suspicious or highly suggestive of a malignancy–the types of lesions that typically would be biopsied–immediately prior to biopsy, and the ensuing biopsies showed 35 masses to be invasive cancers, while the remaining 74 were benign.
3CB images were derived from the dual-energy mammograms and analyzed along with mammography radiomics, a method that uses artificial intelligence algorithms to analyze features and patterns in images–some of which are difficult for human perception–developed by Maryellen L. Giger, Ph.D., and her team at the University of Chicago for use in computer-aided diagnosis on breast images.
- The combination of 3CB image analysis and radiomics improved the positive predictive value, or the ability to predict cancer, in breast masses deemed suspicious by the breast radiologist.
- The combined method improved positive predictive value from 32 percent for visual interpretation alone to almost 50 percent, with an almost 36 percent reduction in biopsies.
- The 3CB-radiomics method missed one of the 35 cancers, for a 97 percent sensitivity rate.
“These results are very promising,” Dr. Drukker said. “Combining 3CB image analysis with mammography radiomics, the reduction in recalls was substantial.”
Dr. Drukker said the combined 3CB-radiomics approach has the potential to play an increasingly prominent role in breast cancer diagnosis and perhaps also screening. She noted that 3CB can easily be added to mammography without requiring extensive modifications of existing equipment.
“The patient is already getting the mammography, plus we get all this extra information with only a 10 percent additional dose of radiation,” she said.
This approach is still experimental at this stage, and further work is needed to make it available to patients. The researchers plan to study how the combined approach will help radiologists make their final determinations. They also want to study the approach using digital breast tomosynthesis, sometimes called “3D” mammography, which reduces the problem of overlapping breast tissue inherent to regular mammography. A tumor’s unique water-lipid-protein signature might be even clearer with tomosynthesis, Dr. Drukker said.
For further reference follow the link: https://pubs.rsna.org/doi/10.1148/radiol.2018180608