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Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy
Stereological methods for estimating the 3D particle size and density from 2D projections are essential to many research fields. These methods are, however, prone to errors arising from undetected particle profiles due to sectioning and limited resolution, known as ‘lost caps’. A potential solution...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10022809/ https://www.ncbi.nlm.nih.gov/pubmed/36930689 http://dx.doi.org/10.1371/journal.pone.0277148 |
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author | Rothman, Jason Seth Borges-Merjane, Carolina Holderith, Noemi Jonas, Peter Silver, R. Angus |
author_facet | Rothman, Jason Seth Borges-Merjane, Carolina Holderith, Noemi Jonas, Peter Silver, R. Angus |
author_sort | Rothman, Jason Seth |
collection | PubMed |
description | Stereological methods for estimating the 3D particle size and density from 2D projections are essential to many research fields. These methods are, however, prone to errors arising from undetected particle profiles due to sectioning and limited resolution, known as ‘lost caps’. A potential solution developed by Keiding, Jensen, and Ranek in 1972, which we refer to as the Keiding model, accounts for lost caps by quantifying the smallest detectable profile in terms of its limiting ‘cap angle’ (ϕ), a size-independent measure of a particle’s distance from the section surface. However, this simple solution has not been widely adopted nor tested. Rather, model-independent design-based stereological methods, which do not explicitly account for lost caps, have come to the fore. Here, we provide the first experimental validation of the Keiding model by comparing the size and density of particles estimated from 2D projections with direct measurement from 3D EM reconstructions of the same tissue. We applied the Keiding model to estimate the size and density of somata, nuclei and vesicles in the cerebellum of mice and rats, where high packing density can be problematic for design-based methods. Our analysis reveals a Gaussian distribution for ϕ rather than a single value. Nevertheless, curve fits of the Keiding model to the 2D diameter distribution accurately estimate the mean ϕ and 3D diameter distribution. While systematic testing using simulations revealed an upper limit to determining ϕ, our analysis shows that estimated ϕ can be used to determine the 3D particle density from the 2D density under a wide range of conditions, and this method is potentially more accurate than minimum-size-based lost-cap corrections and disector methods. Our results show the Keiding model provides an efficient means of accurately estimating the size and density of particles from 2D projections even under conditions of a high density. |
format | Online Article Text |
id | pubmed-10022809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100228092023-03-18 Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy Rothman, Jason Seth Borges-Merjane, Carolina Holderith, Noemi Jonas, Peter Silver, R. Angus PLoS One Research Article Stereological methods for estimating the 3D particle size and density from 2D projections are essential to many research fields. These methods are, however, prone to errors arising from undetected particle profiles due to sectioning and limited resolution, known as ‘lost caps’. A potential solution developed by Keiding, Jensen, and Ranek in 1972, which we refer to as the Keiding model, accounts for lost caps by quantifying the smallest detectable profile in terms of its limiting ‘cap angle’ (ϕ), a size-independent measure of a particle’s distance from the section surface. However, this simple solution has not been widely adopted nor tested. Rather, model-independent design-based stereological methods, which do not explicitly account for lost caps, have come to the fore. Here, we provide the first experimental validation of the Keiding model by comparing the size and density of particles estimated from 2D projections with direct measurement from 3D EM reconstructions of the same tissue. We applied the Keiding model to estimate the size and density of somata, nuclei and vesicles in the cerebellum of mice and rats, where high packing density can be problematic for design-based methods. Our analysis reveals a Gaussian distribution for ϕ rather than a single value. Nevertheless, curve fits of the Keiding model to the 2D diameter distribution accurately estimate the mean ϕ and 3D diameter distribution. While systematic testing using simulations revealed an upper limit to determining ϕ, our analysis shows that estimated ϕ can be used to determine the 3D particle density from the 2D density under a wide range of conditions, and this method is potentially more accurate than minimum-size-based lost-cap corrections and disector methods. Our results show the Keiding model provides an efficient means of accurately estimating the size and density of particles from 2D projections even under conditions of a high density. Public Library of Science 2023-03-17 /pmc/articles/PMC10022809/ /pubmed/36930689 http://dx.doi.org/10.1371/journal.pone.0277148 Text en © 2023 Rothman et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Rothman, Jason Seth Borges-Merjane, Carolina Holderith, Noemi Jonas, Peter Silver, R. Angus Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title | Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title_full | Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title_fullStr | Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title_full_unstemmed | Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title_short | Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy |
title_sort | validation of a stereological method for estimating particle size and density from 2d projections with high accuracy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10022809/ https://www.ncbi.nlm.nih.gov/pubmed/36930689 http://dx.doi.org/10.1371/journal.pone.0277148 |
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