A Fast, Robust Method for Quantitative Assessment of Collagen Fibril Architecture from Transmission Electron Micrographs.

collagen extracellular matrix image segmentation transmission electron microscopy

Journal

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
ISSN: 1435-8115
Titre abrégé: Microsc Microanal
Pays: England
ID NLM: 9712707

Informations de publication

Date de publication:
19 Oct 2023
Historique:
received: 03 05 2023
revised: 21 09 2023
accepted: 25 09 2023
medline: 19 10 2023
pubmed: 19 10 2023
entrez: 19 10 2023
Statut: aheadofprint

Résumé

Collagen is the most abundant protein in mammals; it exhibits a hierarchical organization and provides structural support to a wide range of soft tissues, including blood vessels. The architecture of collagen fibrils dictates vascular stiffness and strength, and changes therein can contribute to disease progression. While transmission electron microscopy (TEM) is routinely used to examine collagen fibrils under normal and pathological conditions, computational tools that enable fast and minimally subjective quantitative assessment remain lacking. In the present study, we describe a novel semi-automated image processing and statistical modeling pipeline for segmenting individual collagen fibrils from TEM images and quantifying key metrics of interest, including fibril cross-sectional area and aspect ratio. For validation, we show first-of-their-kind illustrative results for adventitial collagen in the thoracic aorta from three different mouse models.

Identifiants

pubmed: 37856696
pii: 7323808
doi: 10.1093/micmic/ozad116
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Commentaires et corrections

Type : UpdateOf

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the Microscopy Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Bruno V Rego (BV)

Department of Biomedical Engineering, Yale University, 55 Prospect Street, New Haven, CT 06511, USA.
Department of Biological & Agricultural Engineering, Louisiana State University, 149 E. B. Doran Building, Baton Rouge, LA 70803, USA.

Dar Weiss (D)

Department of Biomedical Engineering, Yale University, 55 Prospect Street, New Haven, CT 06511, USA.

Jay D Humphrey (JD)

Department of Biomedical Engineering, Yale University, 55 Prospect Street, New Haven, CT 06511, USA.
Vascular Biology and Therapeutics Program, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06520, USA.

Classifications MeSH