The primary objective of breast cancer screening is to identify early stage cancer, or
precancerous lesions, at a time before symptoms emerge and when treatment is likely to
result in a cure. Screening is beneficial when it averts progression of disease to
metastasis and/or death, but adverse effects to patients (and unnecessary medical
expense) may result downstream from false positives and indiscrimination of masses that
will not respond to treatment. The sensitivity of digital mammography, the current
screening standard in the US, has been reported in the range of 0.40 to 0.85, with a
positive predictive value of 0.31. Sensitivity is increased by augmenting mammography
with MRI and B-Mode ultrasound, but false positive rates may also increase. There exists
a vital need for a screening technology that exhibits high sensitivity and specificity
for cancer detection with early identification of unresponsive masses.
This urgent need could be met by exploiting new imaging biomarkers. Specifically, the
mechanical properties of breast tissue have been used for cancer detection, with both
elasticity and viscosity demonstrated for discriminating malignant from benign lesions.
Further, tissue anisotropy has been shown to correlate with core biopsy result and tumor
grade, with large cancers significantly more anisotropic than small cancers. Importantly,
while both MRI and ultrasound can be used to measure these biomarkers, ultrasound's cost
effectiveness and ease of implementation render it an efficient platform to pursue.
The long-term goal of this research program is to develop a new ultrasound-based
breast-screening tool to augment mammography. As a critical first step toward achieving
this goal, the primary objective of the proposed research is to evaluate in vivo the
replicability of ultrasound-derived metrics for stiffness, elasticity, viscosity, and
anisotropy. These biomarkers will be measured using novel, noninvasive ultrasound
technologies under development in Dr. Gallippi's laboratory: 1) Acoustic Radiation Force
Impulse (ARFI) ultrasound for interrogating tissue stiffness, 2) Viscoelastic Response
(VisR) ultrasound for assessing tissue elasticity and viscosity, and 3) Dynamic
Displacement Anisotropy Imaging (DDAI) for measuring tissue anisotropy. These
technologies have been demonstrated previously for delineating atherosclerosis, muscular
dystrophy, and renal dysfunction.
The investigators hypothesize that ultrasound-derived stiffness, elasticity, viscosity,
and anisotropy measurements will vary based on applied compression from the sonographer.
This is because applying compression to tissue alters its organization, typically
reflected by increased stiffness and viscosity and changes in mechanical anisotropy. To
test this hypothesis, they will pursue the following specific aim:
Aim #1: Quantify the change in ultrasound-derived stiffness, elasticity, viscosity, and
anisotropy measurements from applied pre-compression. ARFI, VisR, and DDAI imaging will
be performed on breast stromal tissue in 20 women with negative mammograms and no history
of breast disease. Changes in the ultrasound-derived metrics will be evaluated between no
applied compression, 10% applied strain, and 25% applied strain. Additionally, magnitude
of change in these metrics with applied strain will be compared between two age cohorts
(aged 30-45 vs 46-90) and between breast density levels (as rated on BIRADS scale).
