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Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT
Jeremias B Klaus1,2, Stergios Christodoulidis3, Alan A Peters1
1Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
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|September 6, 2022
Summary
This study found no significant difference between lung and soft CT kernel reconstructions for identifying interstitial lung disease (ILD) patterns. Results suggest soft kernels may slightly improve accuracy, challenging current ILD imaging recommendations.
Area of Science:
- Radiology
- Medical Imaging
- Pulmonary Medicine
Background:
- Current recommendations for CT reconstruction kernels in interstitial lung disease (ILD) lack recent comparative scientific evidence.
- The influence of different CT reconstruction kernels on the diagnostic accuracy of ILD patterns remains under-investigated.
Purpose of the Study:
- To evaluate and compare the sensitivity of lung (i70) and soft (i30) CT kernel algorithms for the accurate diagnosis of ILD patterns.
- To assess the impact of CT reconstruction kernel choice on radiologist performance in ILD pattern recognition.
Main Methods:
- Retrospective analysis of 408 annotation stacks from 23 ILD subjects, comparing lung and soft kernel reconstructions.
- Blinded readout by radiologists of varying experience levels (residents, fellows, consultants) with consensus ground truth established by subspecialized radiologists.
- Statistical analysis using a generalized linear mixed model (GLMM) to account for data clustering and evaluate kernel and experience effects.
Main Results:
- No statistically significant difference was found in the odds of correct ILD pattern recognition between lung and soft kernels (OR 0.88, p=0.187).
- A non-significant trend suggested higher odds of correct pattern recognition with soft kernels compared to lung kernels.
- Radiologist experience showed a non-significant trend towards improved performance with higher experience levels (OR 1.78, p=0.283).
- Substantial intra-rater agreement (κ=0.63) and moderate inter-rater agreement (κ=0.37-0.38) were observed for both kernels.
Conclusions:
- There is no significant difference in ILD pattern recognition accuracy between lung and soft kernel CT reconstructions.
- Non-significant trends suggest potential benefits of soft kernels and higher radiologist experience for improved diagnostic accuracy in ILD.
- These findings challenge the routine use of separate lung kernel reconstructions for ILD parenchyma analysis and current clinical guidelines.
