Differentiation of benign and malignant breast lesions by mechanical imaging

Abstract

Mechanical imaging yields tissue elasticity map and provides quantitative characterization of a detected pathology. The changes in the surface stress patterns as a function of applied load provide information about the elastic composition and geometry of the underlying tissue structures. The objective of this study is the clinical evaluation of breast mechanical imager for breast lesion characterization and differentiation between benign and malignant lesions. The breast mechanical imager includes a probe with pressure sensor array, an electronic unit providing data acquisition from the pressure sensors and communication with a touch-screen laptop computer. We have developed an examination procedure and algorithms to provide assessment of breast lesion features such as hardness related parameters, mobility, and shape. A statistical Bayesian classifier was constructed to distinguish between benign and malignant lesions by utilizing all the listed features as the input. Clinical results for 179 cases, collected at four different clinical sites, have demonstrated that the breast mechanical imager provides a reliable image formation of breast tissue abnormalities and calculation of lesion features. Malignant breast lesions (histologically confirmed) demonstrated increased hardness and strain hardening as well as decreased mobility and longer boundary length in comparison with benign lesions. Statistical analysis of differentiation capability for 147 benign and 32 malignant lesions revealed an average sensitivity of 91.4% and specificity of 86.8% with a standard deviation of ±6.1%. The area under the receiver operating characteristic curve characterizing benign and malignant lesion discrimination is 86.1% with the confidence interval ranging from 80.3 to 90.9%, with a significance level of P = 0.0001 (area = 50%). The multisite clinical study demonstrated the capability of mechanical imaging for characterization and differentiation of benign and malignant breast lesions. We hypothesize that the breast mechanical imager has the potential to be used as a cost effective device for cancer diagnostics that could reduce the benign biopsy rate, serve as an adjunct to mammography and to be utilized as a screening device for breast cancer detection.

Diagnostic accuracy of tactile imaging in selecting patients with palpable breast abnormalities: a prospective comparative study

“…It is therefore far more important to ensure that any new technological modality has particularly high sensitivity in detecting those lumps that subsequently prove to be cancers. In this respect, TI performed very well as it confirmed the presence of a lump in all 13 carcinomas that [21,23,24]. Our study, however, is the only study to date that compared the two examination methods in a blinded and unbiased way.…”

“…The changes in the surface stress patterns, as a function of applied load, provide information about the elastic composition and geometry of the underlying tissue structures. As a result, mechanical imaging yields a tissue elasticity map and provides quantitative characterization of a detected pathology [23]. The sensor array measures 40 by 30 mm and comprises 192 capacitive pressure sensors.…”

Development of array piezoelectric fingers towards in vivo breast tumor detection

“…2(c), the bottom surface of the handheld unit was mostly flat to flatten out tissues surrounding the area under testing and make sure that the contact area of each of the four PEF was fully in contact with the tissue. Note that, because the PEFs were in a cantilever geometry, they had only one end fixed to the housing, which is different from sensors in "SureTouch" [38][39][40] that have all edges fixed to the housing of the device. This allowed the probe surface of a PEF at the free end of the cantilever to be free from the pressure exerted on the housing as long as the PEF was "recessed" from the bottom surface of the housing (see Fig.…”

“…[33][34][35][36][37] Increasingly researchers have sought to detect breast tumors by means of tissue stiffness contrast by mechanical 33,34,[38][39][40][41][42][43][44][45][46] or optical 47,48 means. Ultrasound elastography (UE) detects breast tumors by measuring the difference in the distribution of the echo times with and without applying pressure which is further analyzed with inversion simulations.…”

“…[49][50][51][52] Breast mechanical imager (BMI or "SureTouch") detects breast tumors with great promise by measuring the compressive stress distribution with a pressure sensor array followed by the inversion simulation anal- ysis. [38][39][40] In recent years, more studies were also aiming to detect breast tumors using mechanical means. For example, a new study used an indenter to measure the normal and lateral forces which were further analyzed by artificial neural network to differentiate hard inclusions from the surrounding matrix.…”