Abstract
Prostate cancer is the second most common cause of cancer deaths and is the most frequently detected form of cancer of males in the United States. Death rates can be greatly reduced by early treatment. Consequently, it is important to understand the cause and progression of this disease in order to improve detection and treatment methods. As part of the Cancer Genome Anatomy Project (CGAP) work is underway to produce a `molecular finger print' of prostate cancer. Collaboration between scientists at the National Cancer Institute (NCI), the University of Pittsburgh Medical Center (UPMC), and the Pittsburgh Supercomputing Center (PSC) has begun to produce 3D models of gene expression within diseased prostates. Using special preparation methods, tissue sections in the form of microscope slides can be formed with their mRNA intact. Laser capture microdissection (LCM) allows very precise areas of the section can be sampled for gene expression based on mRNA. Three dimensional imaging based on serial tissue sections allows the LMD samples and the genomic information they contain to targeted and understood in the appropriate morphologic context. We are currently determining the details of reconstruction model and functional requirements of the reconstruction tools for this application. Our goal is to provide data exploration methods that will allow tissue sampling decisions to be made, and cancer gene expression understood, in the context of traditional morphologic markers such as invasion, angiogenesis, cancer-in-situ and hyperplasia.
Original language | English |
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Pages (from-to) | 204-212 |
Number of pages | 9 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 3905 |
State | Published - 2000 |
Event | 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making - Washington, DC, USA Duration: Oct 13 1999 → Oct 15 1999 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering