An Integrative Approach for In Silico Glioma Research

被引：44

作者：

Cooper, Lee A. D. ^{[1
,2
]}

Kong, Jun ^{[2
]}

Gutman, David A. ^{[2
]}

Wang, Fusheng ^{[2
]}

Cholleti, Sharath R. ^{[2
]}

Pan, Tony C. ^{[2
]}

Widener, Patrick M. ^{[2
]}

Sharma, Ashish ^{[2
]}

Mikkelsen, Tom ^{[3
]}

Flanders, Adam E. ^{[4
]}

Rubin, Daniel L. ^{[5
]}

Van Meir, Erwin G. ^{[2
]}

Kurc, Tahsin M. ^{[2
]}

Moreno, Carlos S. ^{[2
]}

Brat, Daniel J. ^{[2
]}

Saltz, Joel H. ^{[2
]}

机构：

[1] Ctr Comprehens Informat, Atlanta, GA 30322 USA

[2] Emory Univ, Atlanta, GA 30322 USA

[3] Henry Ford Hosp, Dept Neurol & Neurosurg, Detroit, MI 48202 USA

[4] Thomas Jefferson Univ, Dept Radiol, Philadelphia, PA 19107 USA

[5] Stanford Univ, Med Ctr, Stanford, CA 94305 USA

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2010年 / 57卷 / 10期

基金：

美国国家卫生研究院;

关键词：

Biology; brain tumor; image analysis; in silico; microscopy;

D O I：

10.1109/TBME.2010.2060338

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The integration of imaging and genomic data is critical to forming a better understanding of disease. Large public datasets, such as The Cancer Genome Atlas, present a unique opportunity to integrate these complementary data types for in silico scientific research. In this letter, we focus on the aspect of pathology image analysis and illustrate the challenges associated with analyzing and integrating large-scale image datasets with molecular characterizations. We present an example study of diffuse glioma brain tumors, where the morphometric analysis of 81 million nuclei is integrated with clinically relevant transcriptomic and genomic characterizations of glioblastoma tumors. The preliminary results demonstrate the potential of combining morphometric and molecular characterizations for in silico research.

引用

页码：2617 / 2621

页数：5

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