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VisR for Noninvasively Interrogating Stromal Collagen Organization as a Breast Cancer Biomarker: Evaluation of Compression in Control Subjects

UNC Lineberger Comprehensive Cancer Center logo

UNC Lineberger Comprehensive Cancer Center

Status

Completed

Conditions

Breast Cancer

Treatments

Device: Ultrasound

Study type

Observational

Funder types

Other
NIH

Identifiers

NCT06547034
5R01CA281150-02 (U.S. NIH Grant/Contract)
LCCC2411

Details and patient eligibility

About

Purpose: The purpose of this study is to evaluate in vivo the diagnostic relevance of ultrasound-derived metrics for elasticity, viscosity, and anisotropy. To this end, we will investigate the effect of applied compression during imaging on elasticity, viscosity, and anisotropy measurements.

Participants: Twenty women with negative mammograms and no history of breast disease will be recruited. The subjects will be split into two cohorts of ten each, the first cohort aged 30-45 and the second cohort aged 46-90. 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 measurements of elasticity, viscosity, and anisotropy in healthy breast tissue vary based on applied pre-compression. This unblinded, open-label study will be conducted in 20 women with negative mammogram results and no history of breast disease.

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 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).

Enrollment

20 patients

Sex

Female

Ages

30 to 90 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Patients are 30-90 years of age
  • Patients have received a negative result from mammogram screening in past year
  • Patients have no history of breast disease
  • Informed consent obtained and signed

Exclusion criteria

  • Inability to provide informed consent
  • Inability to communicate in English
  • Inability to remain motionless for 15 minutes
  • Any pathologies of the breast or history of breast disease
  • Patients who are pregnant
  • Patients who are lactating
  • Patients with breast implants
  • Patients with implanted cardioverters or pacemakers

Trial design

20 participants in 2 patient groups

Ages 30-45
Description:
Women ages 30-45 who have received a mammogram in the past year with negative results and have no history of breast disease.
Treatment:
Device: Ultrasound
Ages 46-90
Description:
Women ages 46-90 who have received a mammogram in the past year with negative results and have no history of breast disease.
Treatment:
Device: Ultrasound

Trial contacts and locations

1

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Central trial contact

Desma Jones; Caterina Gallippi, PhD

Data sourced from clinicaltrials.gov

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