Automated 3D interstitial lung disease extent quantification: Performance evaluation and correlation to PFTs

Alexandra Kazantzi, Lena Costaridou, Spyros Skiadopoulos, Panayiotis Korfiatis, Anna Karahaliou, Dimitris Daoussis, Andreas Andonopoulos, Christina Kalogeropoulou

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In this study, the performance of a recently proposed computer-aided diagnosis (CAD) scheme in detection and 3D quantification of reticular and ground glass pattern extent in chest computed tomography of interstitial lung disease (ILD) patients is evaluated. CAD scheme performance was evaluated on a dataset of 37 volumetric chest scans, considering five representative axial anatomical levels per scan. CAD scheme reliability analysis was performed by estimating agreement (intraclass correlation coefficient, ICC) of automatically derived ILD pattern extent to semi-quantitative disease extent assessment in terms of 29-point rating scale provided by two expert radiologists. Receiver operating characteristic (ROC) analysis was employed to assess CAD scheme accuracy in ILD pattern detection in terms of area under ROC curve (A z ). Correlation of reticular and ground glass volumetric pattern extent to pulmonary function tests (PFTs) was also investigated. CAD scheme reliability was substantial for ILD extent (ICC∈=∈0.809) and distinct reticular pattern extent (0.806) and moderate for distinct ground glass pattern extent (0.543), performing within inter-observer agreement. CAD scheme demonstrated high accuracy in detecting total ILD (A z ∈=∈0.950∈±∈0.018), while accuracy in detecting distinct reticular and ground glass patterns was 0.920∈±∈0.023 and 0.883∈±∈0.024, respectively. Moderate and statistically significant negative correlation was found between reticular volumetric pattern extent and diffusing capacity, forced expiratory volume in 1 s, forced vital capacity, and total lung capacity (R∈=∈-0.581, -0.513, -0.494, and -0.446, respectively), similar to correlations found between radiologists' semi-quantitative ratings with PFTs. CAD-based quantification of disease extent is in agreement with radiologists' semi-quantitative assessment and correlates to specific PFTs, suggesting a potential imaging biomarker for ILD staging and management.

Original languageEnglish (US)
Pages (from-to)380-391
Number of pages12
JournalJournal of Digital Imaging
Issue number3
StatePublished - Jun 2014


  • Automated 3D disease extent quantification
  • Disease extent assessment
  • Interstitial lung disease
  • Pulmonary function tests
  • Semi-quantitative scoring

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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