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Workshop on Clinical Image-Based Procedures

CLIP 2013: Clinical Image-Based Procedures. Translational Research in Medical Imaging pp 134–142Cite as

Modelling Smooth Intensity Changes in the Putamen for Diagnosis of Sporadic Creutzfeldt-Jakob Disease

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8361))

Abstract

The putamen, one of the deep grey matter structures in the brain, is unusual in that MRI intensities vary smoothly within the structure. We develop a geometric and intensity model of the putamen, and in averaged images from 60 CJD patients and non-CJD clinical controls we show these smooth changes clearly. In the axial plane, there is a linear decrease of T2 intensity from anterior to posterior in the central part of the putamen. The gradient is significantly higher in sporadic CJD, but not in variant CJD, than controls. We show that gradient quantification would give good sensitivity and specificity, making this suitable as a simple screening test for sporadic CJD. However, the data are preliminary; a wider database of patients and further statistical analyses are needed for a robust definition of the clinical role of the test.

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References

  1. Tschampa, H.J., Kallenberg, K., Urbach, H., Meissner, B., Nicolay, C., Kretzschmar, H.A., Knauth, M., Zerr, I.: MRI in the diagnosis of sporadic Creutzfeldt-Jakob disease: a study on inter-observer agreement. Brain 128, 2026–2033 (2005)

    Article  Google Scholar 

  2. Kallenberg, K., Schulz-Schaeffer, W.J., Jastrow, U., et al.: Creutzfeldt-Jakob disease: comparative analysis of MR imaging sequences. Am. J. Neuroradiol. 27, 1459–1462 (2006)

    Google Scholar 

  3. Coulthard, A., Hall, K., English, P.T.: Quantitative analysis of MRI signal intensity in new variant Creutzfeldt-Jakob disease. Brit. J. Radiol. 72, 742–748 (1999)

    Google Scholar 

  4. Fulbright, R.K., Kingsley, P.B., Guo, X., et al.: The imaging appearance of Creutzfeldt-Jakob disease caused by the E200K mutation. Magn. Reson. Imag. 24, 1121–1129 (2006)

    Article  Google Scholar 

  5. Linguraru, M.G., Ayache, N., Bardinet, E., et al.: Differentiation of sCJD and vCJD forms by automated analysis of Basal Gagnlia intensity distribution in multisequence MRI of the brain - definition and evaluation of new MRI-based rations. IEEE Trans. Med. Imag. 25, 1052–1067 (2006)

    Article  Google Scholar 

  6. Hojjat, A., Collie, D., Colchester, A.C.F.: The putamen intensity gradient in CJD diagnosis. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002, Part I. LNCS, vol. 2488, pp. 524–531. Springer, Heidelberg (2002)

    Google Scholar 

  7. Murata, T., Shiga, Y., Higano, S., et al.: Conspicuity and evolution of lesions in Creutzfeldt-Jakob disease at diffusion-weighted imaging. Am. J. Neuroradiol. 23, 1164–1172 (2002)

    Google Scholar 

  8. Romano, A., Bozzao, A., Tisei, P., et al.: Emerging patterns of diffusion, perfusion-weighted MRI and spectroscopy in Creutzfeldt-Jacob disease. Neuroradiol. J. 20, 56–60 (2007)

    Google Scholar 

  9. Collie, D.A., Summers, D.M., Sellar, R.J., et al.: Diagnosing variant Creutzfeldt-Jakob disease with the pulvinar sign: MR imaging findings in 86 Neuropathologically confirmed cases. Am. J. Neuroradiol. 24, 1560–1569 (2003)

    Google Scholar 

  10. Heckel, F., Konrad, O., Karl Hahn, H., et al.: Interactive 3D medical image segmentation with energy-minimizing implicit functions. Comput. Graph. 35, 275–287 (2011)

    Article  Google Scholar 

  11. Bookstein, F.L.: Principal Warps: thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Mach. Intell. 11, 567–585 (1989)

    Article  MATH  Google Scholar 

  12. Schnabel, J.A., Rueckert, D., Quist, M., Blackall, J.M., Castellano-Smith, A.D., Hartkens, T., Penney, G.P., Hall, W.A., Liu, H., Truwit, C.L., Gerritsen, F.A., Hill, D.L.G., Hawkes, David J.: A generic framework for non-rigid registration based on non-uniform multi-level free-form deformations. In: Niessen, Wiro J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 573–581. Springer, Heidelberg (2001)

    Google Scholar 

  13. McGuire, L.I., Peden, A.H., Orrú, C.D., et al.: Real time quaking-induced conversion analysis of cerebrospinal fluid in sporadic Creutzfeldt-Jakob disease. Ann. Neurol. 72, 278–285 (2012)

    Article  Google Scholar 

  14. Aljabar, P., Heckemann, R.A., Hammers, A., et al.: Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy. Neuroimage 46, 726–738 (2009)

    Article  Google Scholar 

  15. Cabezas, M., Oliver, A., Lladó, X., et al.: A review of atlas-based segmentation for magnetic resonance brain images. Comput. Methods Programs Biomed. 104, e158–e177 (2011)

    Article  Google Scholar 

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Acknowledgements

This work was supported by an NHS R&D grant [East Kent Hospitals University Trust].

Author information

Authors and Affiliations

  1. East Kent Hospitals University Foundation Trust, Canterbury, UK

    S. Bouyagoub, Y. H. Mah & A. C. F. Colchester

  2. University of Kent, Canterbury, UK

    I. C. Cimpan, S. A. Hojjatoleslami, A. Kume & A. C. F. Colchester

Authors
  1. S. Bouyagoub
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  2. I. C. Cimpan
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  3. S. A. Hojjatoleslami
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  4. A. Kume
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  5. Y. H. Mah
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  6. A. C. F. Colchester
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Corresponding author

Correspondence to S. Bouyagoub .

Editor information

Editors and Affiliations

  1. Fraunhofer IDM@NTU, Singapore, Singapore

    Marius Erdt

  2. Children’s National Medical Center, Washington, District of Columbia, USA

    Marius George Linguraru

  3. Fraunhofer IGD, Darmstadt, Germany

    Cristina Oyarzun Laura

  4. Children's National Medical Center, Washington, D.C., USA

    Raj Shekhar

  5. Fraunhofer IGD, Darmstadt, Germany

    Stefan Wesarg

  6. ICREA -- Universitat Pompeu Fabra, Barcelona, Spain

    Miguel Angel González Ballester

  7. Fraunhofer IGD, Darmstadt, Germany

    Klaus Drechsler

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© 2014 Springer International Publishing Switzerland

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Bouyagoub, S., Cimpan, I.C., Hojjatoleslami, S.A., Kume, A., Mah, Y.H., Colchester, A.C.F. (2014). Modelling Smooth Intensity Changes in the Putamen for Diagnosis of Sporadic Creutzfeldt-Jakob Disease. In: Erdt, M., et al. Clinical Image-Based Procedures. Translational Research in Medical Imaging. CLIP 2013. Lecture Notes in Computer Science(), vol 8361. Springer, Cham. https://doi.org/10.1007/978-3-319-05666-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-05666-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05665-4

  • Online ISBN: 978-3-319-05666-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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