Magnetic Resonance Imaging
Volume 27, Issue 9 , Pages 1258-1270, November 2009

A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response

  • Xia Li

      Affiliations

    • Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Radiology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department Radiological Sciences, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Benoit M. Dawant

      Affiliations

    • Department of Radiology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department Radiological Sciences, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • E. Brian Welch

      Affiliations

    • Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2310, USA
    • MR Clinical Science, Philips Healthcare, Cleveland, OH 44143, USA
  • ,
  • A. Bapsi Chakravarthy

      Affiliations

    • Department of Radiation Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Darla Freehardt

      Affiliations

    • Department of Radiation Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Ingrid Mayer

      Affiliations

    • Department of Medical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Mark Kelley

      Affiliations

    • Department of Surgical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Ingrid Meszoely

      Affiliations

    • Department of Surgical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • John C. Gore

      Affiliations

    • Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Radiology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department Radiological Sciences, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Surgical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232-2310, USA
  • ,
  • Thomas E. Yankeelov

      Affiliations

    • Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Radiology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department Radiological Sciences, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Department of Cancer Biology, Vanderbilt University, Nashville, TN 37232-2310, USA
    • Corresponding Author InformationCorresponding author. Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232-2310, USA.

Received 21 October 2008; received in revised form 27 January 2009; accepted 6 May 2009. published online 15 June 2009.

Abstract 

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can estimate parameters relating to blood flow and tissue volume fractions and therefore may be used to characterize the response of breast tumors to treatment. To assess treatment response, values of these DCE-MRI parameters are observed at different time points during the course of treatment. We propose a method whereby DCE-MRI data sets obtained in separate imaging sessions can be co-registered to a common image space, thereby retaining spatial information so that serial DCE-MRI parameter maps can be compared on a voxel-by-voxel basis. In performing inter-session breast registration, one must account for patient repositioning and breast deformation, as well as changes in tumor shape and volume relative to other imaging sessions. One challenge is to optimally register the normal tissues while simultaneously preventing tumor distortion. We accomplish this by extending the adaptive bases algorithm through adding a tumor-volume preserving constraint in the cost function. We also propose a novel method to generate the simulated breast magnetic resonance (MR) images, which can be used to evaluate the proposed registration algorithm quantitatively. The proposed nonrigid registration algorithm is applied to both simulated and real longitudinal 3D high resolution MR images and the obtained transformations are then applied to lower resolution physiological parameter maps obtained via DCE-MRI. The registration results demonstrate the proposed algorithm can successfully register breast MR images acquired at different time points and allow for analysis of the registered parameter maps.

Keywords: Breast Cancer, Image registration, DCE-MRI, Neoadjuvant chemotherapy, Treatment monitoring

To access this article, please choose from the options below

Login to an existing account or Register a new account.

 

PII: S0730-725X(09)00086-1

doi:10.1016/j.mri.2009.05.007

Magnetic Resonance Imaging
Volume 27, Issue 9 , Pages 1258-1270, November 2009