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=Volume 12 - 2024

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.