Quantitative diagnosis of breast tumors by characterization of viscoelastic behavior of healthy breast tissue

The main objective of the present study is to propose a model for characterizing the viscoelastic behavior of the healthy breast tissue. The study population consisted of 60 healthy regions of the breast tissue belonged to 9 female cases. To accomplish this, the attending cases were examined by a robot-assisted device and the mechanical stress resulted from an applied compressive strain was measured. Correlation between the experimental stress and the strain data identifies the breast tissue mechanical behavior. The tissue behavior was modeled by a five-element Maxwell-Wiechert model called model E. The model was personalized for every attending case via its coefficients based on a personalized diagnosis idea. The model performance was assessed by measuring the Mean Squared Error (MSE) and the match percentage of the model to the experimental data. Moreover, the model performance was compared with three common spring-dashpot models included the Maxwell model, the Burgers model and Standard Linear Solid model. Results affirmed that model E had the best data match in the whole mechanical loading and the MSE was considerably reduced. Subsequently model E was implemented for the tumor-included regions among the population study. Results showed that with a high match percentage, coefficients had significant deviations from the corresponding healthy regions’ values for every individual. Consequently, personalized model E can be used for the healthy tissue characterization and tumor detection. [Display omitted] •Healthy breast tissue was characterized with the aim to diagnose breast tumors.•Stress-strain data from experimental examinations were used for characterization.•Special spring-dashpot model was used to represent viscoelastic behavior of tissue.•The model was personalized for each case via coefficients of its transfer function.•Deviation from the healthy tissue behavior was indicative of tumor existence.