Affiliation:
1. Department of Applied Mathematics, Wrocław University of Environmental and Life Sciences, 50-357 Wroclaw, Poland.
2. Department of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
Abstract
Objective
The aim of the study is to assess the correlation between artificial intelligence (AI)–based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysema grades in routine chest computed tomography (CT). Furthermore, optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or moderate to more extensive visual emphysema grades were calculated.
Methods
In a retrospective study of 298 consecutive patients who underwent routine chest CT and spirometry examinations, LAV% was quantified using an AI-based software with a threshold < −950 HU. The FEV1/FVC was derived from spirometry, with FEV1/FVC < 70% indicating airway obstruction. The mean time interval of CT from spirometry was 3.87 ± 4.78 days. Severity of emphysema was visually graded by an experienced chest radiologist using an established 5-grade ordinal scale (Fleischner Society classification system). Spearman correlation coefficient between LAV% and FEV1/FVC was calculated. Receiver operating characteristic determined the optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or a visual emphysema grade of moderate or higher (Fleischner grade 3–5).
Results
Significant correlation between LAV% and FEV1/FVC was found (ϱ = −0.477, P < 0.001). Increasing LAV% corresponded to higher visual emphysema grades. For patients with absent visual emphysema, mean LAV% was 2.98 ± 3.30, for patients with trace emphysema 3.22 ± 2.75, for patients with mild emphysema 3.90 ± 3.33, for patients with moderate emphysema 6.41 ± 3.46, for patients with confluent emphysema 9.02 ± 5.45, and for patients with destructive emphysema 16.90 ± 8.19. Optimal LAV% cutoff value for predicting a FEV1/FVC < 70 was 6.1 (area under the curve = 0.764, sensitivity = 0.773, specificity = 0.665), while for predicting a visual emphysema grade of moderate or higher, it was 4.7 (area under the curve = 0.802, sensitivity = 0.766, specificity = 0.742). Furthermore, correlation between visual emphysema grading and FEV1/FVC was found. In patients with FEV1/FVC < 70% a high proportion of subjects had emphysema grade 3 (moderate) or higher, whereas in patients with FEV1/FVC ≥ 70%, a larger proportion had emphysema grade 3 (moderate) or lower. The sensitivity for visual emphysema grading predicting a FEV1/FVC < 70% was 56.3% with an optimal cutoff point at a visual grade of 4 (confluent), demonstrating a lower sensitivity compared with LAV% (77.3%).
Conclusions
A significant correlation between AI-based LAV% and FEV1/FVC as well as visual CT emphysema grades can be found in routine chest CT suggesting that AI-based LAV% measurement might be integrated as an add-on functional parameter in the evaluation of chest CT in the future.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Radiology, Nuclear Medicine and imaging