AUTHOR=Oestreich Marc-Alexander , Doswald Isabelle , Salem Yasmin , Künstle Noëmi , Wyler Florian , Frauchiger Bettina S. , Kentgens Anne-Christianne , Latzin Philipp , Yammine Sophie TITLE=A computerized tool for the systematic visual quality assessment of infant multiple-breath washout measurements JOURNAL=Frontiers in Pediatrics VOLUME=12 YEAR=2024 URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2024.1393291 DOI=10.3389/fped.2024.1393291 ISSN=2296-2360 ABSTRACT=Background

Multiple-breath washout (MBW) is a sensitive method for assessing lung volumes and ventilation inhomogeneity in infants, but remains prone to artefacts (e.g., sighs). There is a lack of tools for systematic retrospective analysis of existing datasets, and unlike N2-MBW in older children, there are few specific quality control (QC) criteria for artefacts in infant SF6-MBW.

Aim

We aimed to develop a computer-based tool for systematic evaluation of visual QC criteria of SF6-MBW measurements and to investigate interrater agreement and effects on MBW outcomes among three independent examiners.

Methods

We developed a software package for visualization of raw Spiroware (Eco Medics AG, Switzerland) and signal processed WBreath (ndd Medizintechnik AG, Switzerland) SF6-MBW signal traces. Interrater agreement among three independent examiners (two experienced, one novice) who systematically reviewed 400 MBW trials for visual artefacts and the decision to accept/reject the washin and washout were assessed.

Results

Our tool visualizes MBW signals and provides the user with (i) display options (e.g., zoom), (ii) options for a systematic QC assessment [e.g., decision to accept or reject, identification of artefacts (leak, sigh, irregular breathing pattern, breath hold), and comments], and (iii) additional information (e.g., automatic identification of sighs). Reviewer agreement was good using pre-defined QC criteria (κ 0.637–0.725). Differences in the decision to accept/reject had no substantial effect on MBW outcomes.

Conclusion

Our visual quality control tool supports a systematic retrospective analysis of existing data sets. Based on predefined QC criteria, even inexperienced users can achieve comparable MBW results.