2021
DOI: 10.1038/s41598-021-89469-w
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Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy

Abstract: Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging proces… Show more

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Cited by 7 publications
(7 citation statements)
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“…Although the intravital microscopic observations were made in the EDL, a skeletal muscle in the hind limb of a rat, the results in our study also indicate that other microvascular beds may be affected as well. It is important to note that the machine learning algorithm used to assess the overall maldistribution of blood flow to assesses the tissue’s overall perfusion 41 , and does not analyze local hemodynamic changes in microvascular vessel segments in the tissue. As such, it cannot be excluded that the observed microvascular disruption later in the HD procedure may be preceded by hemodynamic changes in the individual vessel segments.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Although the intravital microscopic observations were made in the EDL, a skeletal muscle in the hind limb of a rat, the results in our study also indicate that other microvascular beds may be affected as well. It is important to note that the machine learning algorithm used to assess the overall maldistribution of blood flow to assesses the tissue’s overall perfusion 41 , and does not analyze local hemodynamic changes in microvascular vessel segments in the tissue. As such, it cannot be excluded that the observed microvascular disruption later in the HD procedure may be preceded by hemodynamic changes in the individual vessel segments.…”
Section: Discussionmentioning
confidence: 99%
“…For this, the algorithm analyzes each individual intersection with the associated recorded video to assess if blood flow is present or not. Not only does this significantly expedite the analysis of the large video data sets associated with intravital video microscopy, it also ensures a more consistent analysis of the video data compared to a manual analysis step 41 .…”
Section: Methodsmentioning
confidence: 99%
“…First, they used a vessel segmentation algorithm to identify the vasculature and in a second step the trained neural network analyzed the three-dimensional imaging data to determine whether the vessel showed blood flow or not. 112 We expect advances in the development of imaging hardware and analysis software tools to further increase the productivity and accessibility of imaging systems and that these systems will soon become standard technology in most thrombosis and hemostasis research laboratories.…”
Section: Conclusion/outlookmentioning
confidence: 99%
“…In the last decade, several promising microfluidic systems have been developed to assess the flow properties of RBCs 33,35,40,41 by the measurement of transit time, velocity, electrical impedance, transit pressure, or the microcapillary occlusion index 37 of cells passing through artificial microvascular networks, along with image processing algorithms and machine learning techniques for the functional characterization of captured microscopic images. 42 Microfluidic biochips can be combined with microsphiltration (microsphere filtration) devices 43 to further assess the deformation capacity of RBCs to pass through the inter-endothelial slits of the spleen. Some of them have proved to be more sensitive compared to the ektacytometry in detecting small differences between RBCs stored under hypoxic or standard conditions, even after the first week of storage.…”
mentioning
confidence: 99%
“…Consequently, a need has emerged for methods to perform highly sensitive assessments of RBC deformability at the single cell level to allow full characterization of RBC populations and aid clinical decision‐making. In the last decade, several promising microfluidic systems have been developed to assess the flow properties of RBCs 33,35,40,41 by the measurement of transit time, velocity, electrical impedance, transit pressure, or the microcapillary occlusion index 37 of cells passing through artificial microvascular networks, along with image processing algorithms and machine learning techniques for the functional characterization of captured microscopic images 42 . Microfluidic biochips can be combined with microsphiltration (microsphere filtration) devices 43 to further assess the deformation capacity of RBCs to pass through the inter‐endothelial slits of the spleen.…”
mentioning
confidence: 99%