TY - JOUR
T1 - Automated 3D interstitial lung disease extent quantification
T2 - Performance evaluation and correlation to PFTs
AU - Kazantzi, Alexandra
AU - Costaridou, Lena
AU - Skiadopoulos, Spyros
AU - Korfiatis, Panayiotis
AU - Karahaliou, Anna
AU - Daoussis, Dimitris
AU - Andonopoulos, Andreas
AU - Kalogeropoulou, Christina
N1 - Funding Information:
This work is supported in part by the Caratheodory Programme (C.591) of the University of Patras, Greece.
PY - 2014/6
Y1 - 2014/6
N2 - 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.
AB - 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.
KW - Automated 3D disease extent quantification
KW - Disease extent assessment
KW - Interstitial lung disease
KW - Pulmonary function tests
KW - Semi-quantitative scoring
UR - http://www.scopus.com/inward/record.url?scp=84901499082&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901499082&partnerID=8YFLogxK
U2 - 10.1007/s10278-013-9670-z
DO - 10.1007/s10278-013-9670-z
M3 - Article
C2 - 24448918
AN - SCOPUS:84901499082
SN - 0897-1889
VL - 27
SP - 380
EP - 391
JO - Journal of Digital Imaging
JF - Journal of Digital Imaging
IS - 3
ER -