A Proof of Concept of a Non-Invasive Image-Based Material Characterization Method for Enhanced Patient-Specific Computational Modeling

Cardiovasc Eng Technol. 2020 Oct;11(5):532-543. doi: 10.1007/s13239-020-00479-7. Epub 2020 Aug 3.

Abstract

Purpose: Computational models of cardiovascular structures rely on their accurate mechanical characterization. A validated method able to infer the material properties of patient-specific large vessels is currently lacking. The aim of the present study is to present a technique starting from the flow-area (QA) method to retrieve basic material properties from magnetic resonance (MR) imaging.

Methods: The proposed method was developed and tested, first, in silico and then in vitro. In silico, fluid-structure interaction (FSI) simulations of flow within a deformable pipe were run with varying elastic modules (E) between 0.5 and 32 MPa. The proposed QA-based formulation was assessed and modified based on the FSI results to retrieve E values. In vitro, a compliant phantom connected to a mock circulatory system was tested within MR scanning. Images of the phantom were acquired and post-processed according to the modified formulation to infer E of the phantom. Results of in vitro imaging assessment were verified against standard tensile test.

Results: In silico results from FSI simulations were used to derive the correction factor to the original formulation based on the geometrical and material characteristics. In vitro, the modified QA-based equation estimated an average E = 0.51 MPa, 2% different from the E derived from tensile tests (i.e. E = 0.50 MPa).

Conclusion: This study presented promising results of an indirect and non-invasive method to establish elastic properties from solely MR images data, suggesting a potential image-based mechanical characterization of large blood vessels.

Keywords: 3D printing; FSI; Material properties assessment; Mock circulation loop; PC MRI; QA method.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Blood Vessels / diagnostic imaging*
  • Elastic Modulus
  • Humans
  • Image Interpretation, Computer-Assisted*
  • Magnetic Resonance Imaging* / instrumentation
  • Models, Cardiovascular*
  • Patient-Specific Modeling*
  • Phantoms, Imaging
  • Predictive Value of Tests
  • Printing, Three-Dimensional
  • Proof of Concept Study
  • Reproducibility of Results
  • Tensile Strength