Claudio Vinegoni, Ph.D. | Fluorescence microscopy tensor imaging representations for large-scale dataset analysis

Sci. Rep.
Fluorescence microscopy tensor imaging representations for large-scale dataset analysis

Vinegoni^#†, C., Feruglio^†, P. F., Courties, G., Schmidt, S., Hulsmans, M., Lee, S., Wang, R., Sosnovik, D., Nahrendorf, M., and Weissleder, R.

Scientific Reports 2020

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Understanding complex biological systems requires the system-wide characterization of cellular and molecular features. Recent advances in optical imaging technologies and chemical tissue clearing have facilitated the acquisition of whole-organ imaging datasets, but automated tools for their quantitative analysis and visualization are still lacking. We have here developed a visualization technique capable of providing whole-organ tensor imaging representations of local regional descriptors based on fluorescence data acquisition. This method enables rapid, multiscale, analysis and virtualization of large-volume, high-resolution complex biological data while generating 3D tractographic representations. Using the murine heart as a model, our method allowed us to analyze and interrogate the cardiac microvasculature and the tissue resident macrophage distribution and better infer and delineate the underlying structural network in unprecedented detail.
@article{2020-SCIREP, author= {Vinegoni<sup>#†</sup>, C. and Feruglio<sup>†</sup>, P. F. and Courties, G. and Schmidt, S. and Hulsmans, M. and Lee, S. and Wang, R. and Sosnovik, D. and Nahrendorf, M. and Weissleder, R.}, title= {Fluorescence microscopy tensor imaging representations for large-scale dataset analysis}, journal= {Scientific Reports}, alternatejournal = {Sci. Rep.}, year = {2020}, volume = {10}, number = {1}, pages = {15}, issn = {2045-2322}, doi = {10.1038/s41598-020-62233-2}, pmcid = {PMC7101442}, pmid= {32221334} }
32221334

PMC7101442

10.1038/s41598-020-62233-2

Abstract

"Understanding complex biological systems requires the system-wide characterization of cellular and molecular features. Recent advances in optical imaging technologies and chemical tissue clearing have facilitated the acquisition of whole-organ imaging datasets, but automated tools for their quantitative analysis and visualization are still lacking. We have here developed a visualization technique capable of providing whole-organ tensor imaging representations of local regional descriptors based on fluorescence data acquisition. This method enables rapid, multiscale, analysis and virtualization of large-volume, high-resolution complex biological data while generating 3D tractographic representations. Using the murine heart as a model, our method allowed us to analyze and interrogate the cardiac microvasculature and the tissue resident macrophage distribution and better infer and delineate the underlying structural network in unprecedented detail."

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Vinegoni^#†, C., Feruglio^†, P. F., Courties, G., Schmidt, S., Hulsmans, M., Lee, S., Wang, R., Sosnovik, D., Nahrendorf, M., & Weissleder, R. (2020). Fluorescence microscopy tensor imaging representations for large-scale dataset analysis. Scientific Reports, 10(1), 15. https://doi.org/10.1038/s41598-020-62233-2