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Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

Identifieur interne : 000023 ( Main/Exploration ); précédent : 000022; suivant : 000024

Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

Auteurs : Pablo Hernández-Morera [Espagne] ; Irene Casta O-González [Espagne] ; Carlos M. Travieso-González [Espagne] ; Blanca Mompe Corredera [Espagne] ; Francisco Ortega-Santana [Espagne]

Source :

RBID : PMC:4711946

Abstract

Purpose

To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson’s trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained.

Methods

The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time.

Results

The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes.

Conclusion

The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met.


Url:
DOI: 10.1371/journal.pone.0146954
PubMed: 26761643
PubMed Central: 4711946


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<p>The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time.</p>
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<p>The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes.</p>
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<p>The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met.</p>
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<name sortKey="Hernandez Morera, Pablo" sort="Hernandez Morera, Pablo" uniqKey="Hernandez Morera P" first="Pablo" last="Hernández-Morera">Pablo Hernández-Morera</name>
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<name sortKey="Travieso Gonzalez, Carlos M" sort="Travieso Gonzalez, Carlos M" uniqKey="Travieso Gonzalez C" first="Carlos M." last="Travieso-González">Carlos M. Travieso-González</name>
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</record>

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