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Automated Area Calculation of Histopathologic Features Using SIVQ

Authors :
Jason Hipp
Jerome Cheng
Stephanie Daignault
Jefferey Sica
Michael C. Dugan
David Lucas
Yukako Yagi
Stephen Hewitt
Ulysses J. Balis
Source :
Analytical Cellular Pathology, Vol 34, Iss 5, Pp 265-275 (2011)
Publication Year :
2011
Publisher :
Hindawi Limited, 2011.

Abstract

Recently, with the advent of the 7th edition of the AJCC Cancer Staging manual, at least one set of criteria (e.g. breast) were modified to now require the measurement of maximal depth of stromal invasion. With the current manual interpretive morphological approaches typically employed by surgical pathologists to assess tumor extent, the specialty now potentially has stumbled upon a crossroads of practice, where the diagnostic criteria have exceeded the capabilities of our commonly available tools. While whole slide imaging (WSI) technology holds the potential to offer many improvements in clinical workflow over conventional slide microscopy including unambiguous utility for facilitating quantitative diagnostic tasks with one important example being the determination of both linear dimension and surface area. However, the availability of histology data in digital form is of little utility if time-consuming and cumbersome manual workflow steps are necessarily imposed upon the pathologist in order to generate such measurements, especially as encountered with the complex and ill-defined shapes inherent to infiltrative tumors. In this communication, we demonstrate the utility of the recently described SIVQ algorithm to serve as the basis of a highly accurate, precise and semi-automated tool for direct surface area measurement of tumor infiltration from WSI data sets. By anticipating the current trend in cancer staging that emphasizes increasingly precise feature characterization, as witnessed by the recent publication of AJCC's 7th edition of the Cancer Staging Manual, this tool holds promise to will be of value to pathologists for clinical utility.

Details

Language :
English
ISSN :
22107177 and 22107185
Volume :
34
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Analytical Cellular Pathology
Publication Type :
Academic Journal
Accession number :
edsdoj.6a14f16f40554fd09a1148fcea2f7a85
Document Type :
article
Full Text :
https://doi.org/10.3233/ACP-2011-0025