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Conf Proc IEEE Eng Med Biol Soc. 2011;2011:87-90. doi: 10.1109/IEMBS.2011.6089903.

In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response.

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  • 1Emory University, Center for Comprehensive Informatics, Atlanta, GA 30322, USA.


In this paper, we present a complete and novel workflow for quantitative nuclear feature analysis of glioblastoma using high-throughput whole-slide microscopy image processing as it relates to treatment response and patient survival. With a complete suite of computer algorithms, large numbers of micro-anatomical structures, in this case nuclei, are analyzed and represented efficiently from whole-slide digitized images with numerical features. With regard to endpoints of treatment response, the computerized analysis presents a better discrimination than traditional neuropathologic review. As a result, this analysis method shows potential to facilitate a better understanding of disease progression and patients' response to therapy for glioblastoma.

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