TY - GEN
T1 - Exploring relationships between multivariate radiological phenotypes and genetic features
T2 - 2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
AU - Rao, Arvind
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Glioblastoma is a form of brain cancer with extremely poor prognosis. While comprehensive genomic profiling is routinely done to identify genetic determinants of pathological grade, a finer-course evaluation of genetic determinants of radiology-specific phenotype remains to be done. This is essential since radiological characterization is a key component of GBM diagnosis in the clinic. In this work, we seek to understand the relationship between genetic features (miRNA and mRNA) with radio-phenotypic features associated with GBM progression. Using genomics data from the Cancer Genome atlas (TCGA) as well as image-derived phenotypes from the Cancer Imaging archive (TCIA), we investigate a multi-task lasso framework to discover associations between gene expression and multivariate image phenotypes. Our study reveals that such integrated imaging-genomic analysis implicates several key molecules involved in glioma biology.
AB - Glioblastoma is a form of brain cancer with extremely poor prognosis. While comprehensive genomic profiling is routinely done to identify genetic determinants of pathological grade, a finer-course evaluation of genetic determinants of radiology-specific phenotype remains to be done. This is essential since radiological characterization is a key component of GBM diagnosis in the clinic. In this work, we seek to understand the relationship between genetic features (miRNA and mRNA) with radio-phenotypic features associated with GBM progression. Using genomics data from the Cancer Genome atlas (TCGA) as well as image-derived phenotypes from the Cancer Imaging archive (TCIA), we investigate a multi-task lasso framework to discover associations between gene expression and multivariate image phenotypes. Our study reveals that such integrated imaging-genomic analysis implicates several key molecules involved in glioma biology.
UR - http://www.scopus.com/inward/record.url?scp=84897728477&partnerID=8YFLogxK
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U2 - 10.1109/GlobalSIP.2013.6736815
DO - 10.1109/GlobalSIP.2013.6736815
M3 - Conference contribution
AN - SCOPUS:84897728477
SN - 9781479902484
T3 - 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
SP - 69
EP - 72
BT - 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Y2 - 3 December 2013 through 5 December 2013
ER -