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Wilms’ Tumor in Childhood: Can Pattern Recognition Help for Classification?

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Medical Image Understanding and Analysis (MIUA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1065))

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Abstract

Wilms’ tumor or nephroblastoma is a kidney tumor and the most common renal malignancy in childhood. Clinicians assume that these tumors develop from embryonic renal precursor cells - sometimes via nephrogenic rests or nephroblastomatosis. In Europe, chemotherapy is carried out prior to surgery, which downstages the tumor. This results in various pathological subtypes with differences in their prognosis and treatment.

First, we demonstrate that the classical distinction between nephroblastoma and its precursor lesion is error prone with an accuracy of 0.824. We tackle this issue with appropriate texture features and improve the classification accuracy to 0.932.

Second, we are the first to predict the development of nephroblastoma under chemotherapy. We use a bag of visual model and show that visual clues are present that help to approximate the developing subtype.

Last but not least, we provide our data set of 54 kidneys with nephroblastomatosis in conjunction with 148 Wilms’ tumors.

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Notes

  1. 1.

    The data set can be accessed at www.mia.uni-saarland.de/nephroblastomatosis.

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Acknowledgements

J. Weickert has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 741215, ERC Advanced Grant INCOVID).

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Authors and Affiliations

  1. Department of Pediatric Oncology and Hematology, Saarland University Medical Center, Homburg, Germany

    Sabine Müller & Norbert Graf

  2. Mathematical Image Analysis Group, Saarland University, Campus E1.7, Saarbrücken, Germany

    Sabine Müller & Joachim Weickert

Authors
  1. Sabine Müller
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  2. Joachim Weickert
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  3. Norbert Graf
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Correspondence to Sabine Müller .

Editor information

Editors and Affiliations

  1. University of Liverpool, Liverpool, UK

    Yalin Zheng

  2. University of Liverpool, Liverpool, UK

    Bryan M. Williams

  3. University of Liverpool, Liverpool, UK

    Ke Chen

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Müller, S., Weickert, J., Graf, N. (2020). Wilms’ Tumor in Childhood: Can Pattern Recognition Help for Classification?. In: Zheng, Y., Williams, B., Chen, K. (eds) Medical Image Understanding and Analysis. MIUA 2019. Communications in Computer and Information Science, vol 1065. Springer, Cham. https://doi.org/10.1007/978-3-030-39343-4_4

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  • DOI: https://doi.org/10.1007/978-3-030-39343-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39342-7

  • Online ISBN: 978-3-030-39343-4

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