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Tumor Budding Detection System in Whole Slide Pathology Images

  • Image & Signal Processing
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Tumor budding is defined as the presence of single tumor cells or small tumor clusters (less than five cells) that ‘bud’ from the invasive front of the main tumor. Tumor budding (TB) has recently emerged as an important adverse prognostic factor for many different cancer types. In colorectal carcinoma (CRC), tumor budding has been independently associated with lymph node metastasis and poor outcome. Pathologic assessment of tumor budding by light microscopy requires close evaluation of tumor invasive front on intermediate to high power magnification, entailing locating the ‘hotspot’ of tumor budding, counting all TB in one high power field, and generating a tumor budding score. By automating these time-consuming tasks, computer-assisted image analysis tools can be helpful for daily pathology practice, since tumor budding reporting is now recommended on select cases. In this paper, we report our work on the development of a tumor budding detection system in CRC from whole-slide Cytokeratin AE1/3 images, based on de novo computer algorithm that automates morphometric analysis of tumor budding.

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Acknowledgements

The first author would like to thank the Fulbright program, the Malaysian Communications and Multimedia Commission, the Fundamental Research Grant Scheme of the Ministry of Higher Education Malaysia (FRGS 2015-1), and the Ohio State University Wexner Medical Center for providing support to conduct this research project.

Funding

This study was supported in part by OSU CCC Pelotonia Award. Mohammad Faizal Ahmad Fauzi also received support from the Fulbright program, the Malaysian Communications and Multimedia Commission and the Fundamental Research Grant Scheme of the Ministry of Higher Education Malaysia (FRGS 2015–1) to conduct this research at the Ohio State University Wexner Medical Center.

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Authors and Affiliations

  1. Faculty of Engineering, Multimedia University, 63100, Cyberjaya, SGR, Malaysia

    Mohammad F. A. Fauzi

  2. Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA

    Wei Chen, Debbie Knight & Wendy L. Frankel

  3. Department of Internal Medicine, Division of Human Genetics, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA

    Heather Hampel

  4. Center for Biomedical Informatics, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA

    Metin N. Gurcan

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  1. Mohammad F. A. Fauzi
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Correspondence to Mohammad F. A. Fauzi.

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Mohammad Faizal Ahmad Fauzi declares that he has no conflict of interest. Wei Chen declares that she has no conflict of interest. Debbie Knight declares that she has no conflict of interest. Heather Hampel declares that she has no conflict of interest. Wendy L. Frankel declares that she has no conflict of interest. Metin N. Gurcan declares that he has no conflict of interest.

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Fauzi, M.F.A., Chen, W., Knight, D. et al. Tumor Budding Detection System in Whole Slide Pathology Images. J Med Syst 44, 38 (2020). https://doi.org/10.1007/s10916-019-1515-y

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  • DOI: https://doi.org/10.1007/s10916-019-1515-y

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