Mechanisms of Intraductal Tumor Spread

Abstract

During the administrative funding period of this grant, we have developed a system that permits three-dimensional reconstruction of intraductal tumors (DCIS) from physical tissue sections. The system reduces the interaction required for low-resolution imaging of H&E stained sections, registration of images of consecutive sections and annotation of tissue structures -i.e. morphologically normal ducts and intraductal tumors-in the images. In addition, we have developed fully automatic tools for image registration and annotation that are now being integrated in our system and used in the reconstruction of the latest tissue specimens. Complementing morphological H&E based reconstructon, our system can be used for morphologically driven acquisition of high-resolution images from immunostained intermediate sections, both using fluorescence and brightfield microscopy. We are using our system to characterize the cellular differences between malignant transformed cells and morphologically normal cells of ducts either in continuum or in the proximity of DCIS tumors. Under the no-cost extension requested, we expect to complete the characterization, which includes the following markers: Her2, ER and PR status Ki67 (proliferation), Caspase 3 (apoptosis) and a marker of dedifferentiation of stemness, CD49f.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2003
Accession Number
ADA420771

Entities

People

  • Carlos O. De Solorzano

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Biological Sciences
  • Breast Cancer
  • Carcinoma
  • Computational Science
  • Computer Programs
  • Differential Equations
  • Graphical User Interface
  • High Resolution
  • Histology
  • Image Processing
  • Low Resolution
  • Medical Personnel
  • Microscopy
  • Optics
  • Stem Cells
  • Three Dimensional

Fields of Study

  • Medicine
  • Physics

Readers

  • Computer Vision.
  • Oncology (Cancer Research).
  • Oncology and Biomarker-Based Cancer Detection.