Diagnostic results for breast disease by real-time elasticity imaging system

We have previously reported our real-time elasticity imaging system and preliminary application to the breast tissue diagnosis. In this paper, we propose several post processing algorithms to stabilize the elasticity imaging, and introduce the scoring method for the clinical usefulness, and report the current status of the scoring method on the breast tissue diagnosis. Our newly implemented post processing algorithms are (1) frame-to-frame smoothing, (2) adaptive contrast optimization, (3) noisy-frame rejection, (4) noisy-region reduction. Using these algorithms, more than 20% of intensity fluctuation (S.D.) in strain images can be reduced. Our newly introduced scoring method is based on the imaging pattern of the low-strain region inside the hypoechoic region in the B-mode image. We classify 5 grades of elasticity score ranging from 1 (no strain-zero brightness region; benign) to 5 (broader strain-zero brightness region; malignant). As the result of applying 137 patients with breast diseases, this method provides a sensitivity of 87%, a specificity of 91%, and an accuracy of 89%.