Development and Evaluation of a Small Airway Disease Index Derived From Modeling the Late-Expiratory Flattening of the Flow-Volume Loop.

Chen, Hengji

Joshi, Sangeeta

Oberle, Amber J

Wong, An-Kwok

Shaz, David

Thapamagar, Suman

Tan, Laren

Anholm, James D

Giri, Paresh C

Henriquez, Craig

Huang, Yuh-Chin T

2022-10-04T14:16:42Z

2022-10-04T14:16:42Z

2022-01

2022-10-04T14:16:40Z

Excessive decrease in the flow of the late expiratory portion of a flow volume loop (FVL) or "flattening", reflects small airway dysfunction. The assessment of the flattening is currently determined by visual inspection by the pulmonary function test (PFT) interpreters and is highly variable. In this study, we developed an objective measure to quantify the flattening. We downloaded 172 PFT reports in PDF format from the electronic medical records and digitized and extracted the expiratory portion of the FVL. We located point A (the point of the peak expiratory flow), point B (the point corresponding to 75% of the expiratory vital capacity), and point C (the end of the expiratory portion of the FVL intersecting with the x-axis). We did a linear fitting to the A-B segment and the B-C segment. We calculated: 1) the AB-BC angle (∠ABC), 2) BC-x-axis angle (∠BCX), and 3) the log ratio of the BC slope over the vertical distance between point A and x-axis [log (BC/A-x)]. We asked an expert pulmonologist to assess the FVLs and separated the 172 PFTs into the flattening and the non-flattening groups. We defined the cutoff value as the mean minus one standard deviation using data from the non-flattening group. ∠ABC had the best concordance rate of 80.2% with a cutoff value of 149.7°. We then asked eight pulmonologists to evaluate the flattening with and without ∠ABC in another 168 PFTs. The Fleiss' kappa was 0.320 (lower and upper confidence intervals [CIs]: 0.293 and 0.348 respectively) without ∠ABC and increased to 0.522 (lower and upper CIs: 0.494 and 0.550) with ∠ABC. There were 147 CT scans performed within 6 months of the 172 PFTs. Twenty-six of 55 PFTs (47.3%) with ∠ABC <149.7° had CT scans showing small airway disease patterns while 44 of 92 PFTs (47.8%) with ∠ABC ≥149.7° had no CT evidence of small airway disease. We concluded that ∠ABC improved the inter-rater agreement on the presence of the late expiratory flattening in FVL. It could be a useful addition to the assessment of small airway disease in the PFT interpretation algorithm and reporting.

914972

1664-042X

1664-042X

https://hdl.handle.net/10161/26054

eng

Frontiers Media SA

Frontiers in physiology

10.3389/fphys.2022.914972

CT scan

machine learning

pulmonary function test

small airway disease

spirometry

Development and Evaluation of a Small Airway Disease Index Derived From Modeling the Late-Expiratory Flattening of the Flow-Volume Loop.

Journal article

Joshi, Sangeeta|0000-0002-5012-4082

Wong, An-Kwok|0000-0001-5668-4251

914972

Duke

School of Medicine

Clinical Science Departments

Medicine

Medicine, Pulmonary, Allergy, and Critical Care Medicine

Published

13