ARFI, VisR and DDAI Ultrasound for Improving Discrimination of Malignant and Unresponsive Breast Cancer
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About
Purpose: The purpose of this study is to evaluate in vivo the diagnostic relevance of ultrasound-derived metrics for stiffness, elasticity, viscosity, and anisotropy.
Participants: Forty women with breast lesions that have a BIRADS-4 or BIRADS-5 rating and forty women undergoing neoadjuvant chemotherapy (NAC) for malignant breast lesions will be recruited. Subjects will be recruited from the Breast Imaging Division of UNC Hospitals.
Procedures (methods): In this exploratory clinical study, the investigators will attempt to demonstrate that ARFI, VisR, and DDAI ultrasound reliably detect malignant breast masses (Aim #1) and distinguish masses that respond to chemotherapy from those that do not (Aim #2). The ARFI, VisR, and DDAI imaging location will be on the surface of the breast, above the suspicious or malignant mass. This unblinded, open-label, exploratory study will be conducted in 40 women with diagnosed BIRADS-4 or -5 masses in Aim #1 and in 40 women with malignant masses undergoing neoadjuvant chemotherapy (NAC) in Aim #2.
Full description
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 increase3. 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 diagnostic relevance 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.
A.1.2.State the research question(s) (i.e., specific study aims and/or hypotheses).
The investigators hypothesize that ultrasound-derived stiffness, elasticity, viscosity, and anisotropy will correlate with lesion malignancy and response to treatment. To test this hypothesis, they will pursue the following specific aims:
Aim #1: Quantify the ability of ultrasound-derived stiffness, elasticity, viscosity, and anisotropy to detect malignancy. ARFI, VisR, and DDAI imaging will be performed on suspicious breast lesions in 40 women with BIRADS-4a, 4b, 4c, or -5 ratings. The diagnostic accuracy of imaging metrics will analyzed, with malignancy confirmed by histology as the outcome.
Aim #2: Quantify the ability of ultrasound-derived stiffness, elasticity, viscosity, and anisotropy to predict a positive response to treatment. ARFI, VisR, and DDAI imaging will be performed serially - once every four weeks over the course of neoadjuvant chemotherapy (NAC) - on malignant breast lesions in 40 women. Changes in outcome metrics over time will be correlated to overall reduction in tumor size (diameter and area). The ability of ultrasound metrics to predict a positive response to treatment will be examined. A positive response to treatment will be determined according to the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines.
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Inclusion and exclusion criteria
Inclusion Criteria:
Aim 1:
Inclusion Criteria:
- Patients are 30-90 years of age
- Patients have breast masses with BIRADS 4a, 4b, 4c, or 5 rating
- Lesion is sonographically visible with B-Mode ultrasound on diagnostic workup
- Informed consent obtained and signed
Aim 2:
Inclusion Criteria:
- Patients are 30-90 years
- Patients who are or will be undergoing neoadjuvant chemotherapy (NAC) for stage 2 or 3 malignant breast lesions
- Lesion is sonographically visible with B-Mode ultrasound on diagnostic workup
- Informed consent is obtained and signed
Exclusion Criteria: Subjects who meet any of the exclusion criteria will be excluded from study participation for both Aim 1 and Aim 2.
- Inability to provide informed consent
- Inability to communicate in English
- Inability to remain motionless for 15 minutes
- Suspicious or malignant breast mass deeper than 3 cm from skin surface
- Previous biopsy or surgery to the site of the suspicious or malignant mass
- Patients who are pregnant
- Patients who are lactating
- Patients with a history of masectomy
- Patients with breast implants
Trial design
45 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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