The University of Texas at El Paso (UTEP) is developing a technology to detect and predict if and when breast cancer occurs. A study on the technology was published in the Computerized Medical Imaging and Graphics journal and researchers expect this approach might save some women from unnecessary annual mammograms.
“We’re creating a breast cancer risk analysis system. It will be able to inform doctors about the patient’s risk of developing cancer within a few years,” explained Wei Qian, electrical engineer, responsible for the UTEP’s Medical Imaging Informatics Lab.
This computer-aided detection system is not yet complete but it has already proved efficient in previous studies. The system has shown a 70 percent accuracy rate in predicting which women would develop breast cancer and which would not by the time of their next mammogram.
Wenqing Sun, a UTEP electrical engineering doctoral student, stated: “For low risk populations, it would be better to increase the interval between their screenings. Mammograms frequently generate false positives and can be an unnecessary mental burden.”
The ideal scenario would be each woman receiving a normal mammogram to be assessed for her risks for cancer. The resulting X-ray images would run through the system in order to have multiple features analyzed such as texture and breast density, crucial parameters for predicting breast cancer risk. Previous studies have revealed that women with extremely dense breasts are 5 times more likely to develop breast cancer in comparison to those with low breast densities.
This technology would highlight suspicious areas and alert the doctor about any differences between the breasts. “Breasts are naturally symmetrical. But if there’s a loss of balance between the two, that could signify a high possibility that a change is occurring,” Qian explained. The computer would be able to suggest more screening for women with high risk levels and would allow women with lower risks to be screened 2 or 3 years later.
The UTEP engineers strongly believe that breast cancer screenings would be more efficient, less worrisome, cost-effective and could save more lives if patients were stratified in low and high risk groups.