BRAIN TUMOR INFORMATICS
IN SILICO SCIENCE
CLINICAL AND TRANSLATIONAL INFORMATICS
HIGH END COMPUTING
IMAGING INFORMATICS

Pathology Imaging

Share Last Updated: October 23, 2012


GBM Subclassification Results

Morphologic variations of disease observed at microscopic resolution are often linked to underlying molecular events and patient outcome, suggesting that quantitative morphometric analysis may provide further insight into disease mechanisms. There is currently intense interest in developing subclassifications of disease, with the hope that finer distinctions will lead to improved personalized therapies. However most, if not all, of these efforts have focused on genomics. Using image analysis techniques, we develop signatures to represent patient-specific tumor morphology through the analysis of hundreds of millions of cells in digitized whole slide images. Clustering of these signatures aggregates tumors into groups with cohesive morphological characteristics. We demonstrate this methodology with an analysis of glioblastoma, using data from The Cancer Genome Atlas to identify a prognostically-significant morphology-driven subclassification, in which clusters are correlated with transcriptional, genetic and epigenetic events.

 

Related Projects

Keeneland

 

References

  1. Lee A.D. Cooper, Jung Kong, David A. Gutman, Fusheng Wang, Jingjing Gao, Christina Appin, Sharath Cholleti, Tony Pan, Ashish Sharma, Lisa Scarpace, Tom Mikkelsen, Tahsin Kurc, Carlos S. Moreno, Daniel J. Brat, Joel H. Saltz. "Integrated Morphologic Analysis for the Identification and Characterization of Disease Subtypes." Journal of the American Medical Informatics Association. Vol. 19, Issue 2. January 24, 2012.

     
  2. Lee Cooper, Jun Kong, David Gutman, Fusheng Wang, Sharath Cholleti, Tony Pan, Patrick Widener, Ashish Sharma, Tom Mikkelsen, Adam Flanders, Daniel Rubin, Erwin Van Meir, Tahsin Kurc, Carlos Moreno, Daniel Brat, Joel Saltz, “An Integrative Approach for In Silico Glioma Research”, IEEE Transactions on Biomedical Engineering, Vol. 57, No. 10, pp. 2617-2621, October 2010.

     
  3. Lee Cooper, Jun Kong, Fusheng Wang, Tahsin Kurc, Carlos Moreno, Daniel Brat, Joel Saltz, “Morphological Signatures and Genomic Correlates in Glioblastoma,” The 8th International Symposium on Biomedical Imaging (ISBI), pp. 1624-1627, Chicago, Illinois, March, 2011.

     
  4. Jun Kong, Lee A.D. Cooper, Fusheng Wang, David A. Gutman, Jingjing Gao, Candace Chisolm, Ashish Sharma, Tony C. Pan, Erwin G. Van Meir, Tahsin M. Kurc, Carlos S. Moreno, Joel H. Saltz and Daniel J. Brat, “Integrative, Multi-modal Analysis of Glioblastoma Using TCGA Molecular Data, Pathology Images and Clinical Outcomes”, Special Issue of IEEE Transactions on Biomedical Engineering LETTERS on “Multi-scale Modeling and Analysis for Computational Biology and Medicine”, 2011.

     
  5. Lee Cooper, Jun Kong, Tahsin Kurc, Tom Mikkelsen, Lisa Scarpace, Daniel Brat, and Joel Saltz, "Nuclear Morphometry Analysis with Whole-Slide Microscopy Images of Low-grade Glioma", the Microscopic Image Analysis with Applications in Biology (MIAAB) co-hosted with ACM Conference on Bioinformatics, Computational Biology and Biomedicine (BCBB) 2011.

     
  6. Jun Kong, Lee Cooper, Carlos Moreno, Fusheng Wang, Tahsin Kurc, Joel Saltz, Daniel Brat, “In Silico Analysis of Nuclei in Glioblastoma using Large-scale Microscopy Images Improves Prediction of Treatment Response,” The 33rd International Conference of the IEEE Engineering in Medicine and Biology Society(EMBC), Boston, MA, August, 2011.

     
  7. Jun Kong, Lee Cooper, Tahsin Kurc, Daniel Brat, Joel Saltz, “Towards Building Computerized Image Analysis Framework for Nucleus Discrimination in Microscopy Images of Diffuse Glioma,” The 33rd International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Boston, MA, August, 2011.

     
  8. Jun Kong, Lee Cooper, Fusheng Wang, Candace Chisolm, Carlos Moreno, Tahsin Kurc, Patrick Widener, Daniel Brat, Joel Saltz, “A Comprehensive Framework for Classification of Nuclei in Digital Microscopy Imaging: An Application to Diffuse Gliomas,” The 8th International Symposium on Biomedical Imaging (ISBI), pp. 2128-2131, Chicargo, Illinois, March, 2011.

HOME | CONTACTS | EMERGENCY | EMPLOYMENT | MAKE A GIFT | EMORY'S WEB | SITE MAP | A-Z INDEX

Copyright © 2017 Emory University - All Rights Reserved | 201 Dowman Drive, Atlanta, Georgia 30322 USA 404.727.6123