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Related Experiment Video

Updated: Nov 10, 2025

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
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Evaluation of automated microvascular flow analysis software AVA 4: a validation study.

Christian S Guay1,2, Mariam Khebir2,3, T Shiva Shahiri4

  • 1Department of Anesthesiology, Washington University School of Medicine in St. Louis, 660 S. Euclid Avenue, St Louis, MO, 63110, USA.

Intensive Care Medicine Experimental
|April 2, 2021
PubMed
Summary

The automated microvascular analysis software AVA 4.1 showed poor agreement with the gold standard and could not replicate findings from AVA 3.2 in human studies, deeming it unsuitable for clinical use.

Keywords:
AnesthesiaAutomated analysisHumanMicrocirculationSublingualValidation

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Area of Science:

  • Critical care medicine
  • Biomedical engineering
  • Medical imaging analysis

Background:

  • Automated analysis of microvasculature videos is crucial for developing research protocols and clinical algorithms.
  • This study addresses the European Society of Intensive Care Medicine's call for validation of automated microvascular analysis software.
  • It builds upon a previous validation study conducted in sheep, extending it to human subjects.

Purpose of the Study:

  • To perform the first human validation study of AVA 4.1, a new automated microvascular analysis software.
  • To assess the agreement between AVA 4.1 and the gold standard semi-automated method (AVA 3.2).
  • To evaluate AVA 4.1's ability to discriminate between microcirculatory states before and after general anesthesia.

Main Methods:

  • Utilized two retrospective perioperative datasets (P1, P2) and one prospective healthy volunteer dataset (V1) of human microcirculation videos.
  • Assessed video quality using the modified Microcirculation Image Quality Selection (MIQS) score.
  • Compared AVA 4.1 automated analysis with AVA 3.2 semi-automated analysis, measuring perfused vessel density (PVD), total vessel density (TVD), and proportion of perfused vessels (PPV) using Bland-Altman analysis and intraclass correlation coefficients (ICC).

Main Results:

  • Analysis included 52 videos (P1), 128 videos (P2), and 26 videos (V1).
  • Revealed poor agreement and no correlation between AVA 4.1 and AVA 3.2.
  • AVA 3.2 detected significant increases in TVD and PVD post-anesthesia in P1 and P2, but AVA 4.1 failed to replicate these findings.

Conclusions:

  • AVA 4.1 is currently not suitable for research or clinical applications.
  • Future validation studies should focus on agreement with gold standards, clinical discrimination ability, and performance thresholds.
  • Further research is needed to validate automated microvascular analysis software for reliable clinical integration.