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Segmentation of Dynamic Contrast-Enhanced MR-Images of Post Chemotherapy Ewing’s Sarcoma with a Pharmacokinetic Model and a Neural Network

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Book cover Bildverarbeitung für die Medizin 1999

Part of the book series: Informatik aktuell ((INFORMAT))

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Abstract

Most patients with Ewing’s sarcoma undergo neoadjuvant (preoperative) chemotherapy before surgery is performed. Generally, chemotherapy reduces the size of the tumor which makes the subsequent treatment more successful. MR-imaging aims at monitoring the effect of chemotherapy by identifying areas of vital remnant tumor. An MR-examination includes static T1- and T2-weighted MR-images as well as dynamic, contrast-enhanced T1-weighted MR-images. Whereas the static MR-images are used to estimate the volume of intra- and extra-osseous bone tumor, the dynamic contrast-enhanced MR-sequence indicates which parts of the tumor are highly perfused by blood. In general, malignant bone tumors are highly perfused. Moreover, these lesions are heterogenuous (sometimes multifocal) containing viable as well as nonviable (necrotic) parts. The only way to reliably distinguish viable from nonviable tumor tissue is by performing a perfusion study by dynamic contrast-enhanced MRI [1].

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Author information

Authors and Affiliations

  1. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, P.O.B. 9600, 2300, RC Leiden, The Netherlands

    M. Egmont-Petersen, R. J. van der Geest, H. A. Vrooman, J. P. Janssen & J. H. C. Reiber

  2. Leiden University Medical Center, Department of Radiology, P.O.B. 9600, 2300, RC Leiden, The Netherlands

    H. J. van der Woude & J. L. Bloem

  3. Leiden University Medical Center, Department of Pathology, P.O.B. 9600, 2300, RC Leiden, The Netherlands

    P. C. W. Hogendoorn

Authors
  1. M. Egmont-Petersen
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  2. R. J. van der Geest
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  3. H. A. Vrooman
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  4. P. C. W. Hogendoorn
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  5. H. J. van der Woude
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  6. J. P. Janssen
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  7. J. L. Bloem
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  8. J. H. C. Reiber
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Editor information

Editors and Affiliations

  1. Abteilung für Medizinische und Biologische Informatik / H0100, Deutsches Krebsforschungszentrum, D-69120, Heidelberg, Deutschland

    Harald Evers , Gerald Glombitza  & Hans-Peter Meinzer ,  & 

  2. Institut für Medizinische Informatik, Universitätsklinikum der RWTH Aachen, D-52057, Aachen, Deutschland

    Thomas Lehmann

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© 1999 Springer-Verlag Berlin Heidelberg

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Egmont-Petersen, M. et al. (1999). Segmentation of Dynamic Contrast-Enhanced MR-Images of Post Chemotherapy Ewing’s Sarcoma with a Pharmacokinetic Model and a Neural Network. In: Evers, H., Glombitza, G., Meinzer, HP., Lehmann, T. (eds) Bildverarbeitung für die Medizin 1999. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60125-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-60125-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65627-2

  • Online ISBN: 978-3-642-60125-5

  • eBook Packages: Springer Book Archive

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