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A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response
Authors:Xia Li  Benoit M Dawant  E Brian Welch  A Bapsi Chakravarthy  Darla Freehardt  Ingrid Mayer  Mark Kelley  Ingrid Meszoely  John C Gore  Thomas E Yankeelov  
Institution:1. Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2310, USA;2. Department of Radiology, Vanderbilt University, Nashville, TN 37232-2310, USA;3. Department Radiological Sciences, Vanderbilt University, Nashville, TN 37232-2310, USA;4. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232-2310, USA;5. MR Clinical Science, Philips Healthcare, Cleveland, OH 44143, USA;6. Department of Radiation Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA;g Department of Medical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA;h Department of Surgical Oncology, Vanderbilt University, Nashville, TN 37232-2310, USA;i Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232-2310, USA;j Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232-2310, USA;k Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232-2310, USA;l Department of Cancer Biology, Vanderbilt University, Nashville, TN 37232-2310, USA
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
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