Spirometry is a common primary or secondary endpoint in respiratory clinical trials. Ensuring high-quality spirometry is therefore of paramount importance to deliver reliable outcomes.
While the quantitative criteria put forward by the American Thoracic Society and European Respiratory Society (ATS/ERS) are usually numeric thresholds, the qualitative criteria require visual inspection of the curve by an expert. In clinical trials, such experts perform over-reading which is both a manual, time-consuming and costly process.
To address these problems we developed ArtiQ.QC.
WHAT is ARTIQ.QC?
ArtiQ.QC is an AI-based software that automatically analyses spirometry data and provides a quality evaluation at the session and curve level.
By applying both the quantitative and qualitative ATS/ERS 2005 and 2019 criteria, ArtiQ.QC is supporting consideration of acceptance and usability of spirometry curves in clinical trials, epidemiological studies and beyond.
In a comparison study, ArtiQ.QC has shown to be at least equivalent to traditional over-reading (ATS 2021).
APPLYING ARTIQ.QC COULD ALLOW FOR:
- Faster turn-around time to complete quality control (QC) and evaluation of spirometry endpoints
- Immediate results with reduced subject burden as another effort can be done while subjects are still at the site
- High-quality data collection with potential reduction in sample size or study duration
- Reduced inter- and intra-rater variability when assessing spirometry quality
HOW DOES ARTIQ.QC WORK?
Based on data from the spirometry device an automated analysis is done and a PDF is immediately generated. Other data formats can also be made available, e.g. for dedicated study dashboards and beyond.
The ArtiQ.QC report contains three main sections:
1. Session Evaluation: Overall session grading (A-F ATS/ERS 2005, A-U ATS/ERS 2019), display of best test results as well as flow-volume and volume-time curves for best trial.
2. Trial Overview: Acceptability and Usability labels for manoeuvres in all trials displayed in an easy-to-interpret table view.
3. Trial Evaluation Details: Complete quality evaluation per trial, including the reason for acceptability results, evaluation of all criteria from the guidelines separately, and descriptive feedback.
quality and science
ArtiQ.QC is developed in accordance with the latest standards relevant to the development, testing and validation of medical software (EN IEC 62304:2006/A1:2015, EN 82304-1:2017). ArtiQ is ISO 13485 certified.
- Eva Topole, Sonia Biondaro, Isabella Montagna, Sandrine Corre, Kevin Ray, Nilakash Das, Marko Topalovic (2021). Artificial Intelligence Assists in Quality Assessment of Spirometry in Clinical Trials. American Journal of Respiratory and Critical Care Medicine 2021;203:A4606; DOI: 10.1164/ajrccm-conference.2020.201.1_MeetingAbstracts.A6423
- Nilakash Das, Kenneth Verstraete, Sanja Stanojevic, Marko Topalovic, Jean-Marie Aerts, Wim Janssens. Deep learning algorithm helps to standardise ATS/ERS spirometric acceptability and usability criteria. European Respiratory Journal 2020; DOI: 10.1183/13993003.00603-2020