Academic Radiology
Volume 15, Issue 11 , Pages 1425-1436, November 2008

Creating Individual-specific Biomechanical Models of the Breast for Medical Image Analysis1

  • Vijay Rajagopal, BE (Hons), PhD

      Affiliations

    • Auckland Bioengineering Institute, University of Auckland. Level 6, 70 Symonds Street, Auckland City, Auckland, New Zealand
    • Corresponding Author InformationAddress correspondence to: V.R.
  • ,
  • Angela Lee, BE (Hons)

      Affiliations

    • Auckland Bioengineering Institute, University of Auckland. Level 6, 70 Symonds Street, Auckland City, Auckland, New Zealand
  • ,
  • Jae-Hoon Chung, BE (Hons), PhD

      Affiliations

    • Auckland Bioengineering Institute, University of Auckland. Level 6, 70 Symonds Street, Auckland City, Auckland, New Zealand
  • ,
  • Ruth Warren, MD

      Affiliations

    • Addenbrooke's Hospital, Cambridge, UK
  • ,
  • Ralph P. Highnam, BE (Hons), PhD

      Affiliations

    • Highnam Associates Ltd, NZ
  • ,
  • Martyn P. Nash, BE (Hons), PhD

      Affiliations

    • Auckland Bioengineering Institute, University of Auckland. Level 6, 70 Symonds Street, Auckland City, Auckland, New Zealand
    • Department of Engineering Science, Faculty of Engineering, University of Auckland, Auckland, New Zealand
  • ,
  • Poul M.F. Nielsen, BSc, BE (Hons), PhD

      Affiliations

    • Auckland Bioengineering Institute, University of Auckland. Level 6, 70 Symonds Street, Auckland City, Auckland, New Zealand
    • Department of Engineering Science, Faculty of Engineering, University of Auckland, Auckland, New Zealand

Received 15 March 2008; accepted 18 July 2008.

Rationale and Objectives

Anatomically realistic biomechanical models of the breast potentially provide a reliable way of mapping tissue locations across medical images, such as mammograms, magnetic resonance imaging (MRI), and ultrasound. This work presents a new modeling framework that enables us to create biomechanical models of the breast that are customized to the individual. We demonstrate the framework's capabilities by creating models of the left breasts of two volunteers and tracking their deformations across MRIs.

Materials and Methods

We generate customized finite element models by automatically fitting geometrical models to segmented data from breast MRIs, and characterizing the in vivo mechanical properties (assuming homogeneity) of the breast tissues. For each volunteer, we identified the unloaded configuration by acquiring MRIs of the breast under neutral buoyancy (immersed in water). Such imaging is clearly not practical in the clinical setting; however, these previously unavailable data provide us with important data with which to validate models of breast biomechanics. Internal tissue features were identified in the neutral buoyancy images and tracked to the prone gravity-loaded state using the modeling framework.

Results

The models predicted deformations with root-mean-square errors of 4.2 and 3.6 mm in predicting the skin surface of the gravity-loaded state for each volunteer. Internal tissue features were tracked with a mean error of 3.7 and 4.7 mm for each volunteer.

Conclusions

The models capture breast shape and internal deformations across the images with clinically acceptable accuracy. Further refinement of the framework and incorporation of more anatomic detail will make these models useful for breast cancer diagnosis.

Key Words: Breast biomechanics, finite element modeling, image registration, breast cancer, medical image analysis, soft-tissue mechanics

To access this article, please choose from the options below

Login to an existing account or Register a new account.

  • Purchase this article for 31.50 USD (You must login/register to purchase this article)

    Online access for 24 hours. The PDF version can be downloaded as your permanent record.

  • Subscribe to this title

    Get unlimited online access to this article and all other articles in this title 24/7 for one year.

  • Claim access now

    For current subscribers with Society Membership or Account Number.

  • Visit SciVerse ScienceDirect to see if you have access via your institution.
 

1 Supported by the Foundation for Research Science and Technology (FRST, contract UOAX0707).

PII: S1076-6332(08)00422-4

doi:10.1016/j.acra.2008.07.017

Academic Radiology
Volume 15, Issue 11 , Pages 1425-1436, November 2008