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Journal of Computer Assisted Tomography:
doi: 10.1097/RCT.0b013e3182277d05
Thoracic Imaging

Method for Minimizing Observer Variation for the Quantitation of High-Resolution Computed Tomographic Signs of Lung Disease

Sverzellati, Nicola MD, PhD*; Devaraj, Anand MD†‡; Desai, Sujal R. MD§; Quigley, Maureen MBBS‡; Wells, Athol U. MD, FRACP∥; Hansell, David M. DM, MD, FRCP‡

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Abstract

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.

© 2011 Lippincott Williams & Wilkins, Inc.

 

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