An Advanced Image Analysis Tool for the Quantification and Characterization of Breast Cancer in Microscopy Images

2015 ◽  
Vol 39 (3) ◽  
Author(s):  
Theodosios Goudas ◽  
Ilias Maglogiannis
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Analysis Tool ◽  
Microscopy Images

scholarly journals Quantitation of HER2/neu Expression in Primary Gastroesophageal Adenocarcinomas Using Conventional Light Microscopy and Quantitative Image Analysis

2012 ◽  
Vol 136 (6) ◽  
pp. 610-617 ◽  
Author(s):  
Jennifer Jeung ◽  
Roshan Patel ◽  
Lizette Vila ◽  
Dara Wakefield ◽  
Chen Liu
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Light Microscopy ◽  
Scoring System ◽  
Growth Factor Receptor ◽  
Tumor Grade ◽  
Quantitative Image ◽  
Epidermal Growth ◽  
Conventional Light Microscopy

Context.—Human epidermal growth factor receptor 2 (HER2/neu) is overexpressed in a proportion of gastroesophageal (GE) adenocarcinomas, and trastuzumab treatment results in significant improvement in overall survival in patients with HER2/neu-overexpressing GE tumors. Grading of HER2/neu expression in GE tumors and its clinical application is different from that of breast cancer. HER2/neu immunohistochemistry (IHC) image analysis (IA), widely used in breast cancer, has not been studied in GE tumors. Objective.—To evaluate the correlation between manual HER2/neu IHC scoring and HER2/neu IHC image analysis in GE adenocarcinomas with characterization of associated clinicopathologic features. Design.—Tumor grade, growth pattern, and stage were evaluated in 116 cases of primary GE adenocarcinoma biopsy and resection specimens. Using anti-HER2/neu antibody and the proposed HER2/neu scoring system for gastric cancer, HER2/neu IHC expression was recorded after manual scoring and automated IA interpretation. Results.—HER2/neu overexpression (IHC 3+) was detected in 19% (10 of 54) of gastric tumors, and overall correlation between manual HER2/neu IHC interpretation and IA interpretation was 78% (42 of 54). HER2/neu overexpression (IHC 3+) was detected in 26% (16 of 62) of GE junction tumors, and the overall correlation between manual HER2/neu IHC interpretation and IA interpretation was 84% (52 of 62). Conclusions.—The HER2/neu IHC scoring system for GE adenocarcinomas differs from that of breast carcinoma. Automated IA, validated for scoring of HER2/neu IHC in breast cancer, has a low correlation between HER2/neu IHC 2+ and IHC 3+ cases scored by conventional light microscopy and cannot be reliably used in the interpretation of HER2/neu IHC expression in GE adenocarcinomas.

scholarly journals Novel Image Analysis Approach Quantifies Morphological Characteristics of 3D Breast Culture Acini with Varying Metastatic Potentials

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Lindsey McKeen Polizzotti ◽  
Basak Oztan ◽  
Chris S. Bjornsson ◽  
Katherine R. Shubert ◽  
Bülent Yener ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Three Dimensional ◽  
Morphological Characteristics ◽  
Tissue Samples ◽  
Metastatic Cascade ◽  
Automated Grading

Prognosis of breast cancer is primarily predicted by the histological grading of the tumor, where pathologists manually evaluate microscopic characteristics of the tissue. This labor intensive process suffers from intra- and inter-observer variations; thus, computer-aided systems that accomplish this assessment automatically are in high demand. We address this by developing an image analysis framework for the automated grading of breast cancer inin vitrothree-dimensional breast epithelial acini through the characterization of acinar structure morphology. A set of statistically significant features for the characterization of acini morphology are exploited for the automated grading of six (MCF10 series) cell line cultures mimicking three grades of breast cancer along the metastatic cascade. In addition to capturing both expected and visually differentiable changes, we quantify subtle differences that pose a challenge to assess through microscopic inspection. Our method achieves 89.0% accuracy in grading the acinar structures as nonmalignant, noninvasive carcinoma, and invasive carcinoma grades. We further demonstrate that the proposed methodology can be successfully applied for the grading ofin vivotissue samples albeit with additional constraints. These results indicate that the proposed features can be used to describe the relationship between the acini morphology and cellular function along the metastatic cascade.

scholarly journals EpiGraph: an open-source platform to quantify epithelial organization

2019 ◽  
Author(s):  
Pablo Vicente-Munuera ◽  
Pedro Gómez-Gálvez ◽  
Robert J Tetley ◽  
Cristina Forja ◽  
Antonio Tagua ◽  
...  
Keyword(s):  
Image Analysis ◽  
Open Access ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Distribution Analysis ◽  
Supplementary Data ◽  
Programming Skills ◽  
User Friendly ◽  
Degree Of Order

Abstract Summary Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform Fiji. This makes EpiGraph very user friendly, with no programming skills required. Availability and implementation EpiGraph is available at https://imagej.net/EpiGraph and the code is accessible (https://github.com/ComplexOrganizationOfLivingMatter/Epigraph) under GPLv3 license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals RootAnalyzer: A Cross-Section Image Analysis Tool for Automated Characterization of Root Cells and Tissues

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137655 ◽  
Author(s):  
Joshua Chopin ◽  
Hamid Laga ◽  
Chun Yuan Huang ◽  
Sigrid Heuer ◽  
Stanley J. Miklavcic
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Analysis Tool ◽  
Root Cells

scholarly journals EpiGraph: an open-source platform to quantify epithelial organization

2017 ◽  
Author(s):  
Pablo Vicente-Munuera ◽  
Pedro Gómez-Gálvez ◽  
Robert J. Tetley ◽  
Cristina Forja ◽  
Antonio Tagua ◽  
...  
Keyword(s):  
Image Analysis ◽  
Open Access ◽  
Analysis Tool ◽  
Distribution Analysis ◽  
Form Complex ◽  
Programming Skills ◽  
User Friendly ◽  
Degree Of Order ◽  
Different Tissues

SUMMARYDuring development, cells must coordinate their differentiation with their growth and organization to form complex multicellular structures such as tissues and organs. Healthy tissues must maintain these structures during homeostasis. Epithelia are packed ensembles of cells from which the different tissues of the organism will originate during embryogenesis. A large barrier to the analysis of the morphogenetic changes in epithelia is the lack of simple tools that enable the quantification of cell arrangements. Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform FIJI. This makes EpiGraph very user friendly, with no programming skills required.

Characterization of Platelet Adhesion under Flow using Microscopic Image Sequence Analysis

2005 ◽  
Vol 28 (7) ◽  
pp. 678-685 ◽  
Author(s):  
M. Machin ◽  
A. Santomaso ◽  
M.R. Cozzi ◽  
M. Battiston ◽  
M. Mazzucato ◽  
...  
Keyword(s):  
Image Analysis ◽  
Blood Platelets ◽  
Lower Surface ◽  
Video Camera ◽  
Flow Chamber ◽  
Artificial Organs ◽  
Analysis Tool ◽  
Glass Coverslip ◽  
Platelet Surface

A method for quantitative analysis of platelet deposition under flow is discussed here. The model system is based upon perfusion of blood platelets over an adhesive substrate immobilized on a glass coverslip acting as the lower surface of a rectangular flow chamber. The perfusion apparatus is mounted onto an inverted microscope equipped with epifluorescent illumination and intensified CCD video camera. Characterization is based on information obtained from a specific image analysis method applied to continuous sequences of microscopical images. Platelet recognition across the sequence of images is based on a time-dependent, bidimensional, gaussian-like pdf. Once a platelet is located, the variation of its position and shape as a function of time (i.e., the platelet history) can be determined. Analyzing the history we can establish if the platelet is moving on the surface, the frequency of this movement and the distance traveled before its resumes the velocity of a non-interacting cell. Therefore, we can determine how long the adhesion would last which is correlated to the resistance of the platelet-substrate bond. This algorithm enables the dynamic quantification of trajectories, as well as residence times, arrest and release frequencies for a high numbers of platelets at the same time. Statistically significant conclusions on platelet-surface interactions can then be obtained. An image analysis tool of this kind can dramatically help the investigation and characterization of the thrombogenic properties of artificial surfaces such as those used in artificial organs and biomedical devices.

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