Title
Preliminary Radiomic Texture Analysis Of High-Channel Fluorescence Confocal Images Of Triple-Negative Breast Cancer Biopsies
Abstract
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by a high level of inflammation In this work, we present a computational method for assessing immune activity across many populations of immune cells. For this analysis, we have a dataset of 18 TNBC biopsies, each stained with a 'strip-and-reprobe' approach consisting of multiple rounds of staining and imaging the tissue. Each sample is stained with 8 separate antibody panels, resulting in similar to 20 different stains per sample, plus tissue autofluorescence images. Biopsy sections are imaged across a similar to 4mm x 5mm area on a Caliber ID confocal microscope with a pixel size of 221 nm, resulting in image composites of similar to 27,000x27,000x20 pixels per sample. Using radiomic texture analysis, we have analyzed a subset of these images to determine which texture features are predictive of inflammation From 3 of these samples, we have selected inflamed and uninflamed regions of interest (ROIs) for three lymphocyte markers: 1) CD4, 2) CD3, and 3) CD8. We have computed 20 texture features, specifically gray level co-occurrence matrix features, for each of these 42 ROIs and their corresponding tissue autofluorescence images. From this analysis, we have found multiple features that successfully differentiate inflamed tissue from uninflamed tissue. These features will be calculated across the full dataset to analyze the overall TNBC immune architecture of these samples as diffuse or compartmentalized, and which cell populations tend to co - aggregate.
Year
DOI
Venue
2020
10.1117/12.2549755
MEDICAL IMAGING 2020: DIGITAL PATHOLOGY
Keywords
DocType
Volume
radiomics, texture analysis, breast cancer, high-throughput image analysis
Conference
11320
ISSN
Citations 
PageRank 
1605-7422
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Madeleine S. Durkee100.68
Bradie M. Ferguson200.34
Rebecca Abraham300.34
Li Lan46918.36
Hui Li54515.48
Marcus R. Clark600.34
Maryellen L. Giger739385.89