VNA
VNA analyzes vascular networks from microcomputed tomography (µCT) scans to quantify vessel diameter and vessel volume within bone structures for studies of angiogenesis in orthopedic research.
Key Features:
- Software Integration: VNA processes µCT data using two Fiji ImageJ modules and a custom MATLAB program.
- Measurements: VNA extracts quantitative vascular metrics including vessel diameter and vessel volume from reconstructed vascular networks.
- Validation and Performance: Validated against in silico models of varying complexity and homogeneity, VNA produced most outcomes with percent error <10% relative to true values.
- Comparison with Existing Tools: Benchmarking against a µCT trabecular analysis software (MicroCT) showed similar volume measurements but large differences in average vessel diameter, with MicroCT overestimating diameter by approximately 650% on heterogeneous models while VNA remained within 1% of true values.
- Robustness to Network Homogeneity: VNA's measurements are insensitive to network homogeneity, maintaining accuracy across homogeneous and heterogeneous vascular models.
Scientific Applications:
- Orthopedic research: Quantitative analysis of angiogenesis during bone repair and regeneration using µCT-derived vessel diameter and volume metrics.
- Method comparison: Benchmarking and comparison of vascular quantification methods against trabecular analysis software such as MicroCT.
- Model validation: Validation of vascular network reconstruction and measurement accuracy using in silico models of varying complexity and homogeneity.
Methodology:
VNA processes µCT scan data through two Fiji ImageJ modules and a custom MATLAB program to generate vascular network metrics.
Topics
Details
- License:
- GPL-3.0
- Programming Languages:
- MATLAB
- Added:
- 1/14/2020
- Last Updated:
- 11/24/2024
Operations
Publications
Peters J, Vest L, Schuelke M, Zustiak SP, Hall AF, McBride‐Gagyi S. MicroCT vascular network analysis program: Development, validation, and comparison to manufacturer software. Journal of Orthopaedic Research. 2019;38(6):1340-1350. doi:10.1002/jor.24568. PMID:31840849. PMCID:PMC7790441.
DOI: 10.1002/jor.24568
PMID: 31840849
PMCID: PMC7790441
Funding: - National Institutes of Health: P30 AR074992