Magnusson, Marine M M; Schüpbach-Regula, Gertraud; Rieger, Juliane; Plendl, Johanna; Marin, Ilka; Drews, Barbara; Kässmeyer, Sabine (2024). Application of an artificial intelligence for quantitative analysis of endothelial capillary beds in vitro. (In Press). Clinical hemorheology and microcirculation IOS Press 10.3233/CH-242157
Full text not available from this repository. (Request a copy)OBJECTIVE
BACKGROUND: The use of endothelial cell cultures has become fundamental to study angiogenesis. Recent advances in artificial intelligences (AI) offer opportunities to develop automated assessment methods in medical research, analyzing larger datasets.
OBJECTIVE
OBJECTIVE: The aim of this study was to compare the application of AI with a manual method to morphometrically quantify in vitro angiogenesis.
OBJECTIVE
METHODS: Co-cultures of human microvascular endothelial cells and fibroblasts were incubated mimicking endothelial capillary-beds. An AI-software was trained for segmentation of endothelial capillaries on anti-CD31-labeled light microscope crops. Number of capillaries and branches and average capillary diameter were measured by the AI and manually on 115 crops.
OBJECTIVE
RESULTS: The crops were analyzed faster by the AI than manually (3 minutes vs 1 hour per crop). Using the AI, systematically more capillaries (mean 48/mm2 vs 27/mm2) and branches (mean 23/mm2 vs 11/mm2) were counted than manually. Both methods had a strong linear relationship in counting capillaries and branches (r-capillaries = 0.88, r-branches = 0.89). No correlation was found for measurements of the diameter (r-diameter = 0.15).
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CONCLUSIONS: The present AI reduces the time required for quantitative analysis of angiogenesis on large datasets, and correlates well with manual analysis.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Public Health Institute 05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Anatomy 05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) |
UniBE Contributor: |
Magnusson, Marine Morgane Marie, Schüpbach-Regula, Gertraud Irene, Drews, Barbara, Kässmeyer, Sabine |
Subjects: |
600 Technology > 630 Agriculture 500 Science > 570 Life sciences; biology |
ISSN: |
1386-0291 |
Publisher: |
IOS Press |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
23 Apr 2024 10:23 |
Last Modified: |
23 Apr 2024 10:23 |
Publisher DOI: |
10.3233/CH-242157 |
PubMed ID: |
38640146 |
Uncontrolled Keywords: |
Artificial intelligence HMVEC angiogenesis endothelial cells machine learning |
URI: |
https://boris.unibe.ch/id/eprint/196124 |
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