Cell Reports MethodsBioinformaticsPeer-reviewed journal article
Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs
Philippa SpangenbergiD, Nina HagemanniD, Anthony SquireiD, Nils FörsteriD, Sascha D. KraußiD, Yachao QiiD, Ayan Mohamud YusufiD, Jing WangiD, Anika GrüneboomiD, Lennart Kowitz, Sebastian KorsteiD, Matthias TotzeckiD, Zülal Cibir, Ali Ata TuziD, Vikramjeet SinghiD, Devon SiemesiD, Laura Struensee, Daniel Robert EngeliD, Peter LudewigiD, Luiza Martins Nascentes MeloiD, Iris HelfrichiD, Jianxu CheniD, Matthias GunzeriD, Dirk Matthias HermanniD, Axel Mosig AiD
Abstract
Blood vasculature represents a complex network of vessels with varying lengths and diameters that are precisely organized in space to allow proper tissue function. Light-sheet fluorescence microscopy (LSFM) is very useful to generate tomograms of tissue vasculature with high spatial accuracy. Yet, quantitative LSFM analysis is still cumbersome and available methods are restricted to single organs and advanced computing hardware. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ~100 times faster than other existing vessel analysis tools, requires no user interaction, integrates batch processing, and parallelization. Employing an innovative dual Frangi filter approach we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool.
- organism: mouse
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: clustering
- research focus: dimensionality reduction
- approach: experimental assay
- Citations
- 49
- FWCI
- 5.68
- Field percentile
- top 2%
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