Affiliations 

  • 1 Faculty of Engineering, Multimedia University, 63100, Cyberjaya, SGR, Malaysia. [email protected]
  • 2 Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
  • 3 Department of Internal Medicine, Division of Human Genetics, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
  • 4 Center for Biomedical Informatics, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA
J Med Syst, 2019 Dec 18;44(2):38.
PMID: 31853654 DOI: 10.1007/s10916-019-1515-y

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.