Bhavika K Patel1, Kay Pepin2, Kathy R Brandt2, Gina L Mazza3, Barbara A Pockaj4, Jun Chen2, Yuxiang Zhou5, Donald W Northfelt6, Karen Anderson6, Juliana M Kling7, Celine M Vachon8, Kristin R Swanson9, Mehdi Nikkhah10,11, Richard Ehman2. 1. Diagnostic Radiology, Mayo Clinic, 5777 E. Mayo Blvd., Phoenix, AZ, 85054, USA. patel.bhavika@mayo.edu. 2. Diagnostic Radiology, Mayo Clinic, Rochester, MN, USA. 3. Department of Biostatistics, Mayo Clinic, Phoenix, AZ, USA. 4. Department of Surgery, Mayo Clinic, Phoenix, AZ, USA. 5. Diagnostic Radiology, Mayo Clinic, 5777 E. Mayo Blvd., Phoenix, AZ, 85054, USA. 6. Department of Oncology, Mayo Clinic, Phoenix, AZ, USA. 7. Department of Internal Medicine, Mayo Clinic, Phoenix, AZ, USA. 8. Department of Epidemiology, Mayo Clinic, Rochester, MN, USA. 9. Department of Neurosurgery, Mayo Clinic, Phoenix, AZ, USA. 10. School of Biological and Health Systems Engineering, Arizona State University, Phoenix, AZ, USA. 11. Biodesign Virginia G. Piper Center for Personalized Diagnostics, Arizona State University, Tempe, AZ, USA.
Abstract
PURPOSE: Quantify in vivo biomechanical tissue properties in various breast densities and in average risk and high-risk women using Magnetic Resonance Imaging (MRI)/MRE and examine the association between breast biomechanical properties and cancer risk based on patient demographics and clinical data. METHODS: Patients with average risk or high-risk of breast cancer underwent 3.0 T breast MR imaging and elastography. Breast parenchymal enhancement (BPE), density (from most recent mammogram), stiffness, elasticity, and viscosity were recorded. Within each breast density group (non-dense versus dense), stiffness, elasticity, and viscosity were compared across risk groups (average versus high). Separately for stiffness, elasticity, and viscosity, a multivariable logistic regression model was used to evaluate whether the MRE parameter predicted risk status after controlling for clinical factors. RESULTS: 50 average risk and 86 high-risk patients were included. Risk groups were similar in age, density, and menopausal status. Among patients with dense breasts, mean stiffness, elasticity, and viscosity were significantly higher in high-risk patients (N = 55) compared to average risk patients (N = 34; all p < 0.001). Stiffness remained a significant predictor of risk status (OR = 4.26, 95% CI [1.96, 9.25]) even after controlling for breast density, BPE, age, and menopausal status. Similar results were seen for elasticity and viscosity. CONCLUSION: A structurally based, quantitative biomarker of tissue stiffness obtained from MRE is associated with differences in breast cancer risk in dense breasts. Tissue stiffness could provide a novel prognostic marker to help identify high-risk women with dense breasts who would benefit from increased surveillance and/or risk reduction measures.
PURPOSE: Quantify in vivo biomechanical tissue properties in various breast densities and in average risk and high-risk women using Magnetic Resonance Imaging (MRI)/MRE and examine the association between breast biomechanical properties and cancer risk based on patient demographics and clinical data. METHODS: Patients with average risk or high-risk of breast cancer underwent 3.0 T breast MR imaging and elastography. Breast parenchymal enhancement (BPE), density (from most recent mammogram), stiffness, elasticity, and viscosity were recorded. Within each breast density group (non-dense versus dense), stiffness, elasticity, and viscosity were compared across risk groups (average versus high). Separately for stiffness, elasticity, and viscosity, a multivariable logistic regression model was used to evaluate whether the MRE parameter predicted risk status after controlling for clinical factors. RESULTS: 50 average risk and 86 high-risk patients were included. Risk groups were similar in age, density, and menopausal status. Among patients with dense breasts, mean stiffness, elasticity, and viscosity were significantly higher in high-risk patients (N = 55) compared to average risk patients (N = 34; all p < 0.001). Stiffness remained a significant predictor of risk status (OR = 4.26, 95% CI [1.96, 9.25]) even after controlling for breast density, BPE, age, and menopausal status. Similar results were seen for elasticity and viscosity. CONCLUSION: A structurally based, quantitative biomarker of tissue stiffness obtained from MRE is associated with differences in breast cancer risk in dense breasts. Tissue stiffness could provide a novel prognostic marker to help identify high-risk women with dense breasts who would benefit from increased surveillance and/or risk reduction measures.
Authors: Charlotte C Gard; Erin J Aiello Bowles; Diana L Miglioretti; Stephen H Taplin; Carolyn M Rutter Journal: Breast J Date: 2015-07-01 Impact factor: 2.431