ARFI, VisR and DDAI Ultrasound for Improving Discrimination of Malignant and Unresponsive Breast Cancer
NCT ID: NCT03785782
Last Updated: 2025-02-20
Study Results
Outcome measurements, participant flow, baseline characteristics, and adverse events have been published for this study.
View full resultsBasic Information
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COMPLETED
45 participants
OBSERVATIONAL
2018-05-10
2021-07-15
Brief Summary
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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.
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Women scheduled for biopsy
40 participants with diagnosed BIRADS-4a, 4b, 4c, or -5 masses will be recruited. The investigators aim to have approximately 10 in each of the BIRADS categories (4a, 4b, 4c, 5), resulting in 40 total subjects for Aim #1.
Ultrasound
Breast ultrasound
Women scheduled for neoadjuvant chemo
40 participants with malignant masses undergoing neoadjuvant chemotherapy (NAC) will be recruited.
Ultrasound
Breast ultrasound
Interventions
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Ultrasound
Breast ultrasound
Eligibility Criteria
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Inclusion Criteria
Aim 1:
* 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:
* 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
* 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
30 Years
90 Years
FEMALE
No
Sponsors
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UNC Lineberger Comprehensive Cancer Center
OTHER
Responsible Party
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Principal Investigators
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Caterina Gallippi, PhD
Role: PRINCIPAL_INVESTIGATOR
University of North Carolina
Locations
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University of North Carolina
Chapel Hill, North Carolina, United States
Countries
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Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Document Type: Informed Consent Form: Arm 1
Document Type: Informed Consent Form: Arm 2
Other Identifiers
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LCCC1745
Identifier Type: -
Identifier Source: org_study_id
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