Hyperelastic Elastography for Breast Cancer Assessment

By Ryan Armstrong

Under Guidance of Hosein Amooshahi

In Dr. Samani’s Lab

OutlineBreast Cancer

OverviewBreast AnatomyCurrent Diagnostic Techniques

ElastographyConcept of ElastographyLinear ElastographyNon-Linear (Hyperelastic) ElastographyBiological Stress-Strain CurveElastography as Inverse Problem

Current Lab WorkNumerical PhantomNumerical Phantom AlgorithmTissue Mimicking Phantom

Summary

Breast Cancer Overview

Second most prevalent cancer worldwide 3

Fifth most common cause of cancer related death 4

Early diagnosis is a huge factor in survival

Anatomy of Breast

Figure 1: Taken from Mehrabian, 2008. 1

Current Diagnostic Techniques

Self Examination (Manual Palpation)

Mammography

Magnetic Resonance Imaging

Ultrasound

Biopsy

Elastography Overview Images taken pre and post-compression

Stress-strain relationships in tissues are analyzed

Reconstruction technique used to determine elastic parameters of tissues

Tumours in breast tend to be abnormally stiff compared to surrounding tissue

Linear Elastography For each tissue type, only a single elastic

parameter

Young’s Modulus: E = σ/ε

Only valid for low strains

Significant errors associated with technique

Hyperelastic Elastography

Generally more than one hyperelastic parameter per tissue

Defined by strain energy functions

Valid for large strain values

Calculations more complicated

Biological Stress-Strain Curve

Figure 2: Taken from http://www.smpp.northwestern.edu/. . . 2

Elastography as Inverse Problem

Reconstructing hyperelastic parameters from data is an inverse problem

Involves initial estimates and numerous iterations

Numerical Phantom Computerized proof of concept

Boundary conditions and geometry defined consistent with real breast anatomy

Finite Element calculations performed in ABAQUS to generate displacement data

Iterative inversion algorithm runs to convergence leading to hyperelastic parameter reconstruction

Numerical Phantom (3D)

Before deformation After deformation

Hyperelastic Parameters Reconstruction Algorithm

Calculate displacement field using OF

Calculate Deformation Gradient

Calculate Stress tensor using ABAQUS

Averaging & updating HE parameters (1 to 3)

Converge EndYes

No

Main pre-

image

Main post-image

Initial HEPs

Latest artificial deformed image

Updated HEPs

Figure 3: Taken from Amooshahi 5

Tissue Mimicking Phantom Construction of phantom with PVA,

Biocide, and heat-cool cycles

Unaxial test for parameter measurement

Pre and Post Compression US images are taken

Hyperelastic parameters reconstructed

Summary Breast cancer has high prevalence and

mortality rate

Early detection is vital for treatment and ultimately survival

Elastography shows great potential as a diagnostic tool with high specificity

Hyperelastic models allow us to reconstruct parameters for high strain

References1. H Mehrabian. Soft Tissue Hyperelastic Parameter Reconstruction. Masters thesis submitted to the

University of Western Ontario. Supervisor: Abbas Samani. (2008)2. Mechanical Properties of Soft Tissue. In Sitting Biomechanics Laboratory. Retrieved May 30th, 2010

from:http://www.smpp.northwestern.edu/Makhsous/Mechanical%20Properties%20of%20Soft%2 0Tissue.shtml

3. World Health Organization International Agency for Research on Cancer (2008). "World Cancer Report". Retrieved on May 30th, 2010.4. World Health Organization (February 2006). "Fact sheet No. 297: Cancer". Retrieved on May 30th, 2010.5. M Amooshahi. (Nov. 17, 2009) Classification of Breast Tumours Using Hyperelastic Elastography

PowerPoint presentation presented at the University of Western Ontario.

Questions?