RATIONALE AND OBJECTIVES: The aim of this study was to compare the performance of various image-based metrics computed from thoracic high-resolution computed tomography (HRCT) with data from pulmonary function testing (PFT) in characterizing interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: Fourteen patients with ILD and 11 with COPD had undergone both PFT and HRCT within 3 days. For each patient, 93 image-based metrics were computed, and their relationships with the 21 clinically used PFT parameters were analyzed using a minimal-redundancy-maximal-relevance statistical framework. The first 20 features were selected among the total of 114 mixed image metrics and PFT values in the characterization of ILD and COPD. RESULTS: Among the best-performing 20 features, 14 were image metrics, derived from attenuation histograms and texture descriptions. The highest relevance value computed from PFT parameters was 0.47, and the highest from image metrics was 0.52, given the theoretical bound as [0, 0.69]. The ILD or COPD classifier using the first four features achieved a 1.92% error rate. CONCLUSIONS: Some image metrics are not only as good discriminators as PFT for the characterization of ILD and COPD but are also not redundant when PFT values are provided. Image metrics of attenuation histogram statistics and texture descriptions may be valuable for further investigation in computer-assisted diagnosis.
RATIONALE AND OBJECTIVES: The aim of this study was to compare the performance of various image-based metrics computed from thoracic high-resolution computed tomography (HRCT) with data from pulmonary function testing (PFT) in characterizing interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: Fourteen patients with ILD and 11 with COPD had undergone both PFT and HRCT within 3 days. For each patient, 93 image-based metrics were computed, and their relationships with the 21 clinically used PFT parameters were analyzed using a minimal-redundancy-maximal-relevance statistical framework. The first 20 features were selected among the total of 114 mixed image metrics and PFT values in the characterization of ILD and COPD. RESULTS: Among the best-performing 20 features, 14 were image metrics, derived from attenuation histograms and texture descriptions. The highest relevance value computed from PFT parameters was 0.47, and the highest from image metrics was 0.52, given the theoretical bound as [0, 0.69]. The ILD or COPD classifier using the first four features achieved a 1.92% error rate. CONCLUSIONS: Some image metrics are not only as good discriminators as PFT for the characterization of ILD and COPD but are also not redundant when PFT values are provided. Image metrics of attenuation histogram statistics and texture descriptions may be valuable for further investigation in computer-assisted diagnosis.
Authors: Sang Cheol Park; Jun Tan; Xingwei Wang; Dror Lederman; Joseph K Leader; Soo Hyung Kim; Bin Zheng Journal: Phys Med Biol Date: 2011-01-25 Impact factor: 3.609
Authors: Surya P Bhatt; Jessica C Sieren; Mark T Dransfield; George R Washko; John D Newell; Douglas S Stinson; Gideon K D Zamba; Eric A Hoffman Journal: Thorax Date: 2013-03-23 Impact factor: 9.139