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Medical & Biological Engineering & Computing

, Volume 57, Issue 4, pp 913–924 | Cite as

Iterative simulations to estimate the elastic properties from a series of MRI images followed by MRI-US validation

  • Francesco VisentinEmail author
  • Vincent Groenhuis
  • Bogdan Maris
  • Diego Dall’Alba
  • Françoise Siepel
  • Stefano Stramigioli
  • Paolo Fiorini
ORIGINAL ARTICLE
  • 152 Downloads

Abstract

The modeling of breast deformations is of interest in medical applications such as image-guided biopsy, or image registration for diagnostic purposes. In order to have such information, it is needed to extract the mechanical properties of the tissues. In this work, we propose an iterative technique based on finite element analysis that estimates the elastic modulus of realistic breast phantoms, starting from MRI images acquired in different positions (prone and supine), when deformed only by the gravity force. We validated the method using both a single-modality evaluation in which we simulated the effect of the gravity force to generate four different configurations (prone, supine, lateral, and vertical) and a multi-modality evaluation in which we simulated a series of changes in orientation (prone to supine). Validation is performed, respectively, on surface points and lesions using as ground-truth data from MRI images, and on target lesions inside the breast phantom compared with the actual target segmented from the US image. The use of pre-operative images is limited at the moment to diagnostic purposes. By using our method we can compute patient-specific mechanical properties that allow compensating deformations.

Graphical Abstract

Workflow of the proposed method and comparative results of the prone-to-supine simulation (red volumes) validated using MRI data (blue volumes)

Keywords

Magnetic resonance imaging Elastic properties Breast Image alignment Deformable models 

Notes

Funding information

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no.688188 as part of the MURAB project.

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Copyright information

© International Federation for Medical and Biological Engineering 2018

Authors and Affiliations

  1. 1.Istituto Italiano di Tecnologia, Center for Micro-BioRoboticsPontederaItaly
  2. 2.Universitá di VeronaVeronaItaly
  3. 3.University of TwenteEnschedeThe Netherlands

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