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Biomedical subjects

Rodrigo Fernandez-Gonzalez

Publications and source records attributed to Rodrigo Fernandez-Gonzalez.

4 recordsLinked to original sources

High-throughput analysis of multispectral images of breast cancer tissue.

Statistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast.

Algorithms↗

A tool for the quantitative spatial analysis of complex cellular systems.

Spatial events largely determine the biology of cells, tissues, and organs. In this paper, we present a tool for the quantitative spatial analysis of heterogeneous cell populations, and we show experimental validation of this tool using both artificial and real (mammary gland tissue) data, in two and three dimensions. We present the refined relative neighborhood graph as a means to establish neighborhood between cells in an image while modeling the topology of the tissue. Then, we introduce the M function as a method to quantitatively evaluate the existence of spatial patterns within one cell population or the relationship between the spatial distributions of multiple cell populations. Finally, we show a number of examples that demonstrate the feasibility of our approach.

Algorithms↗

Quantitative image analysis in mammary gland biology.

In this paper we present a summary of recent quantitative approaches used for the analysis of macro and microscopic images in mammary gland biology. The advantages and disadvantages of whole mount analysis, reconstruction of serial tissue sections and nucleus/cell segmentation of either conventional and confocal images are discussed, as are applications of quantitative image analysis, such as quantification of protein levels or vasculature measurements in normal tissue and cancer. Integration of quantitative imaging into the further study of the mammary gland holds the promise of better understanding its tissue complexity that evolves during development, differentiation and disease.

Animals↗

System for combined three-dimensional morphological and molecular analysis of thick tissue specimens.

We present a new system for simultaneous morphological and molecular analysis of thick tissue samples. The system is composed of a computer-assisted microscope and a JAVA-based image display, analysis, and visualization program that allows acquisition, annotation, meaningful storage, three-dimensional reconstruction, and analysis of structures of interest in thick sectioned tissue specimens. We describe the system in detail and illustrate its use by imaging, reconstructing, and analyzing two complete tissue blocks that were differently processed and stained. One block was obtained from a ductal carcinoma in situ (DCIS) lumpectomy specimen and stained alternatively with Hematoxilyn and Eosin (H&E), and with a counterstain and fluorescence in situ hybridization (FISH) to the ERB-B2 gene. The second block contained a fully sectioned mammary gland of a mouse, stained for histology with H&E. We show how the system greatly reduces the amount of interaction required for the acquisition and analysis and is, therefore, suitable for studies that require morphologically driven, wide-scale (e.g., whole gland) analysis of complex tissue samples or cultures.

Animals↗