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Alveolar microscopy: on the automatic determination of alveolar size during ventilation

Introduction

Alveolar microscopy seems to provide important insight into alveolar dynamics during mechanical ventilation [1, 2]. The utility of this method is limited due to high efforts needed to evaluate sequences of images with respect to alveolar geometry. The evaluation – done by hand – is time consuming, places a high cognitive load on the examiner and is error prone. Reproducibility of results is low. This project aims to establish a computer-assisted tool that provides semi-automatic evaluation of video sequences acquired with alveolar endoscopy.

Methods

We developed a computer program based on Matlab (Mathworks, Natick, MA, USA), which analyses video sequences acquired with an alveolar endoscope (Schölly, Denzlingen, Germany) [2]. The user has to provide a pointer to the alveoli that shall be traced and whose changes in size and shape are to be determined. Filters, smoothing splines and expectation-driven fine tuning is performed to achieve robust and predictable results of the intratidal change in alveolar geometry.

Results

Animal studies related to alveolar mechanics during artificial ventilation were conducted. Figure 1a shows a plot of a frame taken from a video obtained during an experiment performed on a healthy anesthetized rat. Overlaid circles indicate identified boundaries of a selected alveolus. Figure 1b presents a trace of alveolar diameter during a tidal breath. Evaluation of successive frames allows one to compensate for motion artifacts and to analyze the intratidal changes in alveolar geometry.

Figure 1
figure1

(a) Marked areas of a traced alveolus. (b) Changes in diameter during ventilation.

Conclusion

Given a synchronization with respiratory data, this tool will allow one to quantify pressure-related changes of alveolar size. Thus it will allow one to monitor the alveolar distension in a variety of animal models (for example, lavage-induced ARDS) and to correlate these findings, for example, with outcome.

References

  1. 1.

    Schiller , et al.: Crit Care Med. 2001, 29: 1049-1055. 10.1097/00003246-200105000-00036

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  2. 2.

    Stahl CA, et al.: Crit Care. 2006,10(Suppl 1):S2. 10.1186/cc4349

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Schwenninger, D., Moeller, K., Stahl, C. et al. Alveolar microscopy: on the automatic determination of alveolar size during ventilation. Crit Care 11, P191 (2007). https://doi.org/10.1186/cc5351

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Keywords

  • Video Sequence
  • Cognitive Load
  • Analysis Video
  • High Effort
  • Artificial Ventilation