Tracking pleural sliding motion to assess lung overdistention using an open source algorithm: a proof-of-concept...

Area of Science:

• Pulmonology
• Medical Imaging
• Critical Care Medicine

Background:

• Lung ultrasound (LUS) assesses pleural line (PL) movement for pneumothorax detection.
• Quantitative tools for PL movement analysis are lacking, limiting research.
• This study explores quantitative PL movement analysis using motion tracking software.

Purpose of the Study:

• To determine if open-source motion tracking software can quantify PL movement.
• To investigate if quantified PL movement can identify lung overdistention.
• To validate motion tracking as an accurate estimation of lung sliding.

Main Methods:

• Utilized LUS video clips from healthy volunteers, ICU patients, and severe COVID-19 patients.
• Employed open-source 'Channel and Spatial Reliability Tracking' software for PL motion tracking.
• Normalized motion-time curves and defined PL movement as maximum lateral displacement.

Main Results:

• PL movement significantly increased in healthy volunteers and ICU patients with lung sliding (p < 0.01).
• Motion tracking achieved 71% balanced accuracy in predicting absent lung sliding.
• Quantified PL movement correlated with overdistention (Spearman-rho=-0.6) and decreased with increasing PEEP levels (p < 0.01).

Conclusions:

• Pleural line motion tracking is a feasible method for quantitative PL movement analysis.
• This technique provides valuable insights into lung sliding and overdistention.
• Motion tracking offers an accurate, quantitative assessment tool for mechanical ventilation.