Optimized algorithm for speed-of-sound-based infant sulfur hexafluoride multiple-breath washout measurements.

Area of Science:

• Pediatric Pulmonology
• Respiratory Physiology
• Medical Device Technology

Background:

• Existing WBreath algorithm for infant sulfur hexafluoride (SF₆) multiple-breath washout (MBW) measurements has significant methodological flaws.
• These flaws lead to inaccurate results and hinder comparisons across different infant age groups and research institutions.

Purpose of the Study:

• To develop and validate OASIS, a novel algorithm for analyzing speed-of-sound-based infant SF₆ MBW measurements.
• To overcome the limitations of the WBreath algorithm and improve the accuracy and comparability of infant lung function data.

Main Methods:

• Developed the OASIS algorithm, which utilizes measurement context instead of relying on WBreath's model input parameters.
• Validated OASIS's functional residual capacity (FRC) measurement accuracy in vitro.
• Applied OASIS to existing infant MBW datasets from diverse cohorts in Switzerland and South Africa.

Main Results:

• OASIS demonstrated superior in vitro FRC measurement accuracy compared to WBreath, reducing mean absolute error from 5.1(3.2)% to 2.1(1.6)%.
• OASIS showed improved longitudinal tracking and measurement stability for lung clearance index (LCI), and enhanced comparability between centers.
• Unlike WBreath, OASIS results were not significantly impacted by changes in input parameters.

Conclusions:

• OASIS represents a significant advancement for analyzing legacy lung function measurement systems.
• The algorithm enables consistent analysis of MBW data across various infant age groups and research centers.
• This facilitates more reliable and comparable insights into infant respiratory health.