Objectives: This study aimed to describe a method of reducing interobserver variation associated with the visual quantitation of high-resolution computed tomographic (HRCT) signs of airways and interstitial lung disease (ILD).
Methods: The HRCT scans of 2 cohorts of patients with airways disease (n = 144) and ILD (n = 109) were evaluated by 2 observers. Selected signs of airways disease were evaluated: (1) bronchial wall thickness and (2) the extent of the decreased attenuation. In the ILD group, the total extent of disease was scored. These 3 HRCT signs were scored by 2 observers independently using a standard method. The observers rescored the CT scans with a new scoring system (continuous learning method, CLM).
Results: Observer agreement for CT signs was superior for CLM: bronchial wall thickness κw increased from 0.51 to 0.76; for decreased attenuation, κw increased from 0.34 to 0.81; and for ILD extent, κw increased from 0.53 to 0.87.
Conclusions: The CLM reduces noise from observer variation in studies that require visual quantitation of HRCT signs of lung disease.