A Non-invasive modality: The US virtual touch tissue quantification (VTTQ) for evaluation of breast cancer

Objective: We evaluated the biologic features of breast tissues using a newly developed noninvasive diagnostic system, named virtual touch tissue quantification. Methods: A total of 180 patients including 115 invasive ductal carcinoma, 30 ductal carcinoma in situ, 4 mucinous carcinoma, 7 invasive lobular carcinoma, 8 fibroadenoma, 12 fibrocystic change and 4 intraductal papilloma were studied at Nahanishi Clinic, Okinawa. We first compared the results of virtual touch tissue quantification according to each histologic subtype and determined the optimal cutoffvalues for virtual touch tissue quantification to distinguish benign from malignant tissues, using the receiver operating characteristic method. In addition, we also examined the correlation between virtual touch tissue quantification velocities and Ki-67, estrogen receptor, progesterone receptor or human epidermal growth factor receptor 2 in cases of invasive ductal carcinoma using linear regression analyses and Student's t-test. Results: Virtual touch tissue quantification velocities were statistically higher in malignant cases than in benign cases (P < 0.05, respectively) and the best cutoffvalue for the virtual touch tissue quantification velocity which could differentiate benign from malignant cases was 2.89 m/s. There were statistically significant correlations between the virtual touch tissue quantification velocity and the Ki-67 labeling index (r = 0.338, r² = 0.114 and P ≤ 0.001) and significant inverse correlations between virtual touch tissue quantification and the estrogen receptor (r = 20.311, r2 = 0.097 and P ≤ 0.001) or progesterone receptor (r = 20.361, r² = 0.131 and P ≤ 0.001) status of invasive ductal carcinoma. There were also significant differences of the average velocities between human epidermal growth factor receptor 2-positive (6.39±1.44 m/s) and -negative (4.43±1.41 m/s) cases (P < 0.001). Conclusion: Virtual touch tissue quantification could be a valuable clinical tool for estimating breast cancer pathology in a non-invasive fashion.