Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma

Ju Han; Yunfu Wang; Weidong Cai; Alexander D Borowsky; Bahram Parvin; Hang Chang

doi:10.1007/978-3-319-46720-7_9

Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma

Ju Han, Yunfu Wang, Weidong Cai, Alexander D Borowsky, Bahram Parvin, Hang Chang

Pathology and Laboratory Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Integrative analysis based on quantitative representation of whole slide images (WSIs) in a large histology cohort may provide predictive models of clinical outcome. On one hand,the efficiency and effectiveness of such representation is hindered as a result of large technical variations (e.g.,fixation,staining) and biological heterogeneities (e.g.,cell type,cell state) that are always present in a large cohort. On the other hand,perceptual interpretation/validation of important multi-variate phenotypic signatures are often difficult due to the loss of visual information during feature transformation in hyperspace. To address these issues,we propose a novel approach for integrative analysis based on cellular morphometric context,which is a robust representation of WSI,with the emphasis on tumor architecture and tumor heterogeneity,built upon cellular level morphometric features within the spatial pyramid matching (SPM) framework. The proposed approach is applied to The Cancer Genome Atlas (TCGA) lower grade glioma (LGG) cohort,where experimental results (i) reveal several clinically relevant cellular morphometric types,which enables both perceptual interpretation/validation and further investigation through gene set enrichment analysis; and (ii) indicate the significantly increased survival rates in one of the cellular morphometric context subtypes derived from the cellular morphometric context.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
Publisher	Springer Verlag
Pages	72-80
Number of pages	9
Volume	9900 LNCS
ISBN (Print)	9783319467191
DOIs	https://doi.org/10.1007/978-3-319-46720-7_9
State	Published - 2016
Event	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: Oct 21 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9900 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country	Greece
City	Athens
Period	10/21/16 → 10/21/16

Keywords

Cellular morphometric context
Cellular morphometric type
Consensus clustering
Gene set enrichment analysis
Lower grade glioma
Spatial pyramid matching
Survival analysis

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-46720-7_9

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Cite this

Han, J., Wang, Y., Cai, W., Borowsky, A. D., Parvin, B., & Chang, H. (2016). Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (Vol. 9900 LNCS, pp. 72-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_9

Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma. / Han, Ju; Wang, Yunfu; Cai, Weidong; Borowsky, Alexander D; Parvin, Bahram; Chang, Hang.

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9900 LNCS Springer Verlag, 2016. p. 72-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Han, J, Wang, Y, Cai, W, Borowsky, AD, Parvin, B & Chang, H 2016, Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma. in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. vol. 9900 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9900 LNCS, Springer Verlag, pp. 72-80, 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 10/21/16. https://doi.org/10.1007/978-3-319-46720-7_9

Han J, Wang Y, Cai W, Borowsky AD, Parvin B, Chang H. Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9900 LNCS. Springer Verlag. 2016. p. 72-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-46720-7_9

Han, Ju ; Wang, Yunfu ; Cai, Weidong ; Borowsky, Alexander D ; Parvin, Bahram ; Chang, Hang. / Integrative analysis of cellular morphometric context reveals clinically relevant signatures in lower grade glioma. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9900 LNCS Springer Verlag, 2016. pp. 72-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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