8 February 2018 Toward quantitative quasistatic elastography with a gravity-induced deformation source for image-guided breast surgery
Author Affiliations +
Abstract
Biomechanical breast models have been employed for applications in image registration and diagnostic analysis, breast augmentation simulation, and for surgical and biopsy guidance. Accurate applications of stress–strain relationships of tissue within the breast can improve the accuracy of biomechanical models that attempt to simulate breast deformations. Reported stiffness values for adipose, glandular, and cancerous tissue types vary greatly. Variations in reported stiffness properties have been attributed to differences in testing methodologies and assumptions, measurement errors, and natural interpatient differences in tissue elasticity. Therefore, the ability to determine patient-specific in vivo breast tissue properties would be advantageous for these procedural applications. While some in vivo elastography methods are not quantitative and others do not measure material properties under deformation conditions that are appropriate to the application of concern, in this study, we developed an elasticity estimation method that is performed using deformations representative of supine therapeutic procedures. More specifically, reconstruction of mechanical properties appropriate for the standard-of-care supine lumpectomy was performed by iteratively fitting two anatomical images before and after deformations taking place in the supine breast configuration. The method proposed is workflow-friendly, quantitative, and uses a noncontact, gravity-induced deformation source.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Rebekah H. Griesenauer, Rebekah H. Griesenauer, Jared A. Weis, Jared A. Weis, Lori R. Arlinghaus, Lori R. Arlinghaus, Ingrid M. Meszoely, Ingrid M. Meszoely, Michael I. Miga, Michael I. Miga, } "Toward quantitative quasistatic elastography with a gravity-induced deformation source for image-guided breast surgery," Journal of Medical Imaging 5(1), 015003 (8 February 2018). https://doi.org/10.1117/1.JMI.5.1.015003 . Submission: Received: 27 October 2017; Accepted: 15 January 2018
Received: 27 October 2017; Accepted: 15 January 2018; Published: 8 February 2018
JOURNAL ARTICLE
11 PAGES


SHARE
Back to Top