Biomechanical breast models have been employed for applications in image registration and 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 movements. Reported stiffness values for adipose, glandular, and cancerous tissue types vary greatly. Variations in reported stiffness properties are mainly due to differences in testing methodologies and assumptions, measurement errors, and natural inter patient differences in tissue elasticity. Therefore, patient specific, in vivo determination of breast tissue properties is ideal for these procedural applications. Many in vivo elastography methods are not quantitative and/or do not measure material properties under deformation conditions that are representative of the procedure being simulated in the model. In this study, we developed an elasticity estimation method that is performed using deformations representative of supine therapeutic procedures. Reconstruction of material properties was performed by iteratively fitting two anatomical images before and after tissue stimulation. The method proposed is work flow friendly, quantitative, and uses a non-contact, gravity-induced deformation source. We tested this material property optimization procedure in a healthy volunteer and in simulation. In simulation, we show that the algorithm can reconstruct properties with errors below 1% for adipose and 5.6% for glandular tissue regardless of the starting stiffness values used as initial guesses. In clinical data, reconstruction errors are higher (3.6% and 24.2%) due to increased noise in the system. In a clinical context, the elastography method was shown to be promising for use in biomechanical model assisted supine procedures.
Rebekah H. Griesenauer, Jared A. Weis, Lori R. Arlinghaus, Ingrid M. Meszoely, and Michael I. Miga, "Towards quantitative quasi-static elastography with a gravity-induced deformation source," Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 1013502 (Presented at SPIE Medical Imaging: February 14, 2017; Published: 3 March 2017); https://doi.org/10.1117/12.2255738.
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