| 摘要 |
A novel method for soft tissue characterization includes obtaining a sequence of surface stress patterns as a function of an increasing compression force when a probe is pressed against the tissue over the location of the lesion of interest. A number of elasticity features are then calculated to characterize the tissue and the lesion located therein including strain hardening, loading curve average slope, lesion peak signal under a predetermined load, tissue heterogeneity, lesion shape and lesion mobility. At least three elasticity features are provided as an input to a statistical Bayesian classifier trained on a clinical database to calculate the probability of the lesion being benign or malignant. Additional patient-related parameters may be further provided as inputs to the classifier to increase the accuracy of differentiation between benign and malignant lesions. These parameters include a family history of cancer disease, a patient-inherited genetic factor, a history of said tissue related diseases, patient's age, patient's weight, and patient's lifestyle and dietary factors. The method of the invention along with other non-invasive examinations of lesions may help in reducing the rate of biopsies, specifically breast tissue biopsies. |
