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International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2012: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012 pp 1–9Cite as

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Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body

Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body

  • M. Freiman19,
  • S. D. Voss20,
  • R. V. Mulkern20,
  • J. M. Perez-Rossello20,
  • M. J. Callahan20 &
  • …
  • Simon K. Warfield19 
  • Conference paper
  • 5623 Accesses

  • 5 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7510)

Abstract

Diffusion-weighted MRI of the body has the potential to provide important new insights into physiological and microstructural properties. The Intra-Voxel Incoherent Motion (IVIM) model relates the observed DW-MRI signal decay to parameters that reflect perfusivity (D *) and its volume fraction (f), and diffusivity (D). However, the commonly used voxel-wise fitting of the IVIM model leads to parameter estimates with poor precision, which has hampered their practical usage. In this work, we increase the estimates’ precision by introducing a model of spatial homogeneity, through which we obtain estimates of model parameters for all of the voxels at once, instead of solving for each voxel independently. Furthermore, we introduce an efficient iterative solver which utilizes a model-based bootstrap estimate of the distribution of residuals and a binary graph cut to generate optimal model parameter updates. Simulation experiments show that our approach reduces the relative root mean square error of the estimated parameters by 80% for the D * parameter and by 50% for the f and D parameters. We demonstrated the clinical impact of our model in distinguishing between enhancing and nonenhancing ileum segments in 24 Crohn’s disease patients. Our model detected the enhanced segments with 91%/92% sensitivity/specificity which is better than the 81%/85% obtained by the voxel-independent approach.

Keywords

  • Relative Root Mean Square Error
  • Ileal Segment
  • Intravoxel Incoherent Motion
  • IVIM Parameter
  • Relative Root Mean Square

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This investigation was supported in part by NIH grants R01 EB008015, R01 LM010033, R01 EB013248, and P30 HD018655 and by a research grant from the Boston Children’s Hospital Translational Research Program.

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Author information

Authors and Affiliations

  1. Computational Radiology Laboratory, Boston Children’s Hospital, Harvard Medical School, MA, USA

    M. Freiman & Simon K. Warfield

  2. Department of Radiology, Boston Children’s Hospital, Harvard Medical School, MA, USA

    S. D. Voss, R. V. Mulkern, J. M. Perez-Rossello & M. J. Callahan

Authors
  1. M. Freiman
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  2. S. D. Voss
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  3. R. V. Mulkern
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  4. J. M. Perez-Rossello
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  5. M. J. Callahan
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  6. Simon K. Warfield
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Editor information

Editors and Affiliations

  1. Inria Sophia Antipolis, Project Team Asclepios, 06902, Sophia-Antipolis, France

    Nicholas Ayache & Hervé Delingette & 

  2. MIT, CSAIL, 02139,, Cambridge,, MA, USA

    Polina Golland

  3. Information and Communication, Nagoya University, 464-8603, Headquarters, Nagoya, Japan

    Kensaku Mori

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Freiman, M., Voss, S.D., Mulkern, R.V., Perez-Rossello, J.M., Callahan, M.J., Warfield, S.K. (2012). Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33415-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-33415-3_1

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  • Print ISBN: 978-3-642-33414-6

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