TubuleTracker: a high-fidelity shareware software to quantify angiogenesis architecture and maturity

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Mahmood, Danish, Buczkowski, Stephanie, Shah, Sahaj, Anthony, Autumn, Desetty, Rohini, Bartoli, Carlo R
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916823980572672
author Mahmood, Danish
Buczkowski, Stephanie
Shah, Sahaj
Anthony, Autumn
Desetty, Rohini
Bartoli, Carlo R
author_facet Mahmood, Danish
Buczkowski, Stephanie
Shah, Sahaj
Anthony, Autumn
Desetty, Rohini
Bartoli, Carlo R
contents Background: In vitro endothelial cell culture is widely used to study angiogenesis. Histomicrographic images of cell networks are often analyzed manually, a process that is time-consuming and subjective. Automated tools like ImageJ (NIH) can assist, but are often slow and inaccurate. Additionally, as endothelial networks grow more complex, traditional architectural metrics may not fully reflect network maturity. To address these limitations, we developed tubuleTracker, a software tool that quantifies endothelial network architecture and maturity rapidly and objectively. Methods: Human umbilical vein endothelial cells were cultured in an extracellular matrix, and 54 images were acquired using phase contrast microscopy. Each image was analyzed manually by three independent reviewers, and by both ImageJ and tubuleTracker. Key metrics included tubule count, total length, node count, tubule area, and vessel circularity. In parallel, trained scientists rated each image for angiogenesis maturity on a 1-5 scale (1 = most mature). Results: Analysis time per image differed significantly: manual (8 min), ImageJ (58+/-4 s), and tubuleTracker (6+/-2 s) (p<0.0001). Significant differences were also found in tubule count (manual 168+/-SD, tubuleTracker 92+/-SD, ImageJ 433+/-SD), length, and node count (all p<0.0001). tubuleTracker's metrics varied significantly across angiogenesis maturity scores, including tubule count, length, node count, area, and circularity (all p<0.0001). Conclusions: tubuleTracker was faster and more consistent than both manual and ImageJ-based analysis. Vessel circularity proved especially effective in capturing angiogenesis maturity. tubuleTracker is available as free shareware for the biomedical research community.
format Preprint
id arxiv_https___arxiv_org_abs_2507_02024
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle TubuleTracker: a high-fidelity shareware software to quantify angiogenesis architecture and maturity
Mahmood, Danish
Buczkowski, Stephanie
Shah, Sahaj
Anthony, Autumn
Desetty, Rohini
Bartoli, Carlo R
Quantitative Methods
Computer Vision and Pattern Recognition
Cell Behavior
Background: In vitro endothelial cell culture is widely used to study angiogenesis. Histomicrographic images of cell networks are often analyzed manually, a process that is time-consuming and subjective. Automated tools like ImageJ (NIH) can assist, but are often slow and inaccurate. Additionally, as endothelial networks grow more complex, traditional architectural metrics may not fully reflect network maturity. To address these limitations, we developed tubuleTracker, a software tool that quantifies endothelial network architecture and maturity rapidly and objectively. Methods: Human umbilical vein endothelial cells were cultured in an extracellular matrix, and 54 images were acquired using phase contrast microscopy. Each image was analyzed manually by three independent reviewers, and by both ImageJ and tubuleTracker. Key metrics included tubule count, total length, node count, tubule area, and vessel circularity. In parallel, trained scientists rated each image for angiogenesis maturity on a 1-5 scale (1 = most mature). Results: Analysis time per image differed significantly: manual (8 min), ImageJ (58+/-4 s), and tubuleTracker (6+/-2 s) (p<0.0001). Significant differences were also found in tubule count (manual 168+/-SD, tubuleTracker 92+/-SD, ImageJ 433+/-SD), length, and node count (all p<0.0001). tubuleTracker's metrics varied significantly across angiogenesis maturity scores, including tubule count, length, node count, area, and circularity (all p<0.0001). Conclusions: tubuleTracker was faster and more consistent than both manual and ImageJ-based analysis. Vessel circularity proved especially effective in capturing angiogenesis maturity. tubuleTracker is available as free shareware for the biomedical research community.
title TubuleTracker: a high-fidelity shareware software to quantify angiogenesis architecture and maturity
topic Quantitative Methods
Computer Vision and Pattern Recognition
Cell Behavior
url https://arxiv.org/abs/2507.02024