Virtual Microscopy on the Stony Way to Revolutionize Anatomic Pathology
Within the last decade the technical prerequisites for reliable and functional virtual microscopy (VM) have improved dramatically. For example, a wide range of novel digital slide scanners and software solutions have been developed for various virtual microscopy applications in education and research. However, a breakthrough also in diagnostic pathology is...
Somatic Evolution of Cancer Probed by Multiparametric Feature Analysis of Histology
Mark Lloyd, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
This project uses advanced microscopy, image analysis and computational modeling to investigate how the somatic evolution of breast cancer can be characterized and measured. We have evaluated multiparametric morphological features of single cells in histology sections. Our specific hypothesis for this project proposes that single cell features will distinguish subpopulations...
Image Analysis to Discover New Prognostic Features in Breast Cancer
Andrew Beck, Beth Israel Deaconess Medical Center, Boston, MA
The morphological interpretation of histologic sections forms the basis of diagnosis and prognostication for cancer. In the diagnosis of carcinomas, pathologists perform a semi-quantitative analysis of a small set of morphological features to determine the cancer’s histologic grade. However, the determination of grade in breast cancer examines only a small...
Digital Pathology and Image Analysis: The Window to Personalized Medicine
Jared Schwartz, Aperio, Vista, CA
The medical media is awash in reports of how personalized medicine will revolutionize the practice of medicine and that genomics may replace traditional diagnostic pathology and cytology. The reality as more scientific knowledge becomes available is the real promise in personalized medicine will have as its‟ foundation tools the rapidly...
Multiplex Fluorescence in situ Cancer Prognosis Testing in a Clinical Laboratory using Definiens Developer
Tom Nifong, Metamark Genetics, Cambridge, MA
Cancer prognostication depends on both biomarker discovery and accurate quantification of the appropriate biomarkers within the region of interest. In situ biomarker analysis is optimally performed on the fewest number of tissue sections to minimize inter-section heterogeneity. We identified a set of protein biomarkers proven to be drivers of metastasis...