Image analysis software firm Diagnosoft, in partnership with Johns Hopkins University, was awarded a $1 million phase I and II Fast-Track Small Business Innovation Research (SBIR) grant from the National Institutes of Health (NIH) to develop a novel breast tissue stiffness quantification method utilizing MRI.
The stiffness quantification method is based on strain encoding (SENC) and was co-developed by Diagnosoft and Johns Hopkins University.
SENC technology is used in cardiac MRI to measure subtle changes in heart muscle performance, Diagnosoft said. Measuring the stiffness of breast tissue could provide tissue characteristic data and enhance the specificity of MRI breast imaging.
The new method, combined with the high sensitivity of MRI, could permit more accurate diagnoses and earlier detection of breast cancer, according to the vendor. The system is also intended to reduce costs through the early detection and identification of noncancerous lesions.
