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Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids

In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more phy...

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Autores principales: Barbier, Michaël, Jaensch, Steffen, Cornelissen, Frans, Vidic, Suzana, Gjerde, Kjersti, de Hoogt, Ronald, Graeser, Ralph, Gustin, Emmanuel, Chong, Yolanda T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909318/
https://www.ncbi.nlm.nih.gov/pubmed/27303813
http://dx.doi.org/10.1371/journal.pone.0156942
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author Barbier, Michaël
Jaensch, Steffen
Cornelissen, Frans
Vidic, Suzana
Gjerde, Kjersti
de Hoogt, Ronald
Graeser, Ralph
Gustin, Emmanuel
Chong, Yolanda T.
author_facet Barbier, Michaël
Jaensch, Steffen
Cornelissen, Frans
Vidic, Suzana
Gjerde, Kjersti
de Hoogt, Ronald
Graeser, Ralph
Gustin, Emmanuel
Chong, Yolanda T.
author_sort Barbier, Michaël
collection PubMed
description In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.
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spelling pubmed-49093182016-07-06 Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids Barbier, Michaël Jaensch, Steffen Cornelissen, Frans Vidic, Suzana Gjerde, Kjersti de Hoogt, Ronald Graeser, Ralph Gustin, Emmanuel Chong, Yolanda T. PLoS One Research Article In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation. Public Library of Science 2016-06-15 /pmc/articles/PMC4909318/ /pubmed/27303813 http://dx.doi.org/10.1371/journal.pone.0156942 Text en © 2016 Barbier et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Barbier, Michaël
Jaensch, Steffen
Cornelissen, Frans
Vidic, Suzana
Gjerde, Kjersti
de Hoogt, Ronald
Graeser, Ralph
Gustin, Emmanuel
Chong, Yolanda T.
Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title_full Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title_fullStr Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title_full_unstemmed Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title_short Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids
title_sort ellipsoid segmentation model for analyzing light-attenuated 3d confocal image stacks of fluorescent multi-cellular spheroids
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909318/
https://www.ncbi.nlm.nih.gov/pubmed/27303813
http://dx.doi.org/10.1371/journal.pone.0156942
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