Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation. (18th May 2017)

• Record Type: Journal Article
• Authors: Griesenauer, Rebekah H; Weis, Jared A; Arlinghaus, Lori R; Meszoely, Ingrid M; Miga, Michael I
• Is Part Of: Physics in medicine & biology. Volume 62:Number 12(2017:Jun.)
• Page Start: 4756
• Page End: 4776
• Publication Date: 2017-05-18
• Subjects: mechanical properties -- breast cancer -- lumpectomy -- elastography -- biomechanical model -- magnetic resonance imaging -- registration; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aa700a
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test–retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91–0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows.