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Comparison of manual and digital microvascular density counting of RECK expression in glioma
Author(s) -
Rahmah Nunung Nur,
Sakai Keiichi,
Li Yuhui,
Sano Kenji,
Hongo Kazuhiro
Publication year - 2012
Publication title -
neuropathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.701
H-Index - 61
eISSN - 1440-1789
pISSN - 0919-6544
DOI - 10.1111/j.1440-1789.2011.01265.x
Subject(s) - magnification , glioma , computer science , rgb color model , expression (computer science) , artificial intelligence , pathology , medicine , cancer research , programming language
A microvascular density (MVD) counting method for reversion‐inducing cysteine‐rich protein with Kazal motifs (RECK) expression, using a digital image analysis tool, has advantages over manual counting by microscope. Thirty glioma cases with RECK staining were photographed at a magnification of 200× high power field and the photographs in RGB images were analyzed, and stained vessels were captured and were counted automatically. MVD with RECK expression using a digital image analysis tool showed comparable results to those of the manual method. RECK intensity expression could show linear correlation with grades of glioma by the digital method, which was superior compared to the manual method. The present method is recommended to researchers undertaking MVD study for glioma.