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Automated Grading of Renal Cell Carcinoma Using Whole Slide Imaging by Fang-Cheng Yeh; Anil V. Parwani; Liron Pantanowitz; Chien Ho is a Computer Science article available to read on EtoBox.

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## Introduction: Recent technology developments have demonstrated the benefit of using whole slide imaging (WSI) in computer-aided diagnosis. In this paper, we explore the feasibility of using automatic WSI analysis to assist grading of clear cell renal cell carcinoma (RCC), which is a manual task traditionally performed by pathologists. ## Materials and Methods: Automatic WSI analysis was applied to 39 hematoxylin and eosin-stained digitized slides of clear cell RCC with varying grades. Kernel regression was used to estimate the spatial distribution of nuclear size across the entire slides. The analysis results were correlated with Fuhrman nuclear grades determined by pathologists. ## Results: The spatial distribution of nuclear size provided a panoramic view of the tissue sections. The distribution images facilitated locating regions of interest, such as high-grade regions and areas with necrosis. The statistical analysis showed that the maximum nuclear size was significantly different (__P__ < 0.001) between low-grade (Grades I and II) and high-grade tumors (Grades III and IV). The receiver operating characteristics analysis showed that the maximum nuclear size distinguished hig

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Author

Fang-Cheng Yeh; Anil V. Parwani; Liron Pantanowitz; Chien Ho

Published

2014

Language

EN

Field

Computer Science (Physical Sciences)