Observational studyEuropean radiology2016
Normalizing computed tomography data reconstructed with different filter kernels: effect on emphysema quantification.
Observational study in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.
- The Use of Computed Tomography Densitometry for the Assessment of Emphysema in Clinical Trials: A Position Paper from the Fleischner Society.American journal of respiratory and critical care medicine · 2025Pooled it
- Trial
- Segmentation-based deep learning emphysema quantification using chest CT: improved accuracy and robustness vs LAA-950.European radiology · 2026Article
- Intra-vendor inter-scanner agreement of negative-HU measurements on fast kV-switching dual-energy CT virtual monoenergetic imaging: a phantom study.Radiological physics and technology · 2026Article
- Precise Lung Density Quantification with a Physics-based CT Harmonizer.Radiology. Cardiothoracic imaging · 2026Observational
- Harmonizing the National Lung Screening Trial: Kernel resolution and field of view compensation.PloS one · 2026Article
- Investigating the impact of kernel harmonization and deformable registration on inspiratory and expiratory chest CT images for people with COPD.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Histopathological correlations of CT-based radiomics imaging biomarkers in native kidney biopsy.BMC medical imaging · 2024Article
- Leveraging Computed Tomography Imaging to Detect Chronic Obstructive Pulmonary Disease and Concomitant Chronic Diseases.American journal of respiratory and critical care medicine · 2024Article
- Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.Medical physics · 2024Article
- ROBUST QUANTIFICATION OF PERCENT EMPHYSEMA ON CT VIA DOMAIN ATTENTION: THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA) LUNG STUDY.Proceedings. IEEE International Symposium on Biomedical Imaging · 2024Article
- Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study.Radiology. Cardiothoracic imaging · 2024Article
- Development and Application of a Virtual Imaging Trial Framework for Longitudinal Quantification of Emphysema in CT.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Lung Imaging in COPD Part 2: Emerging Concepts.Chest · 2023Review
- Harmonizing CT Images via Physics-based Deep Neural Networks.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT.RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin · 2023Article
- Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer.European radiology · 2022Article
- Single-material beam hardening correction via an analytical energy response model for diagnostic CT.Medical physics · 2022Article
- AI-Driven Model for Automatic Emphysema Detection in Low-Dose Computed Tomography Using Disease-Specific Augmentation.Journal of digital imaging · 2022Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
Abstract
objectivesTo propose and evaluate a method to reduce variability in emphysema quantification among different computed tomography (CT) reconstructions by normalizing CT data reconstructed with varying kernels.
methodsWe included 369 subjects from the COPDGene study. For each subject, spirometry and a chest CT reconstructed with two kernels were obtained using two different scanners. Normalization was performed by frequency band decomposition with hierarchical unsharp masking to standardize the energy in each band to a reference value. Emphysema scores (ES), the percentage of lung voxels below -950 HU, were computed before and after normalization. Bland-Altman analysis and correlation between ES and spirometry before and after normalization were compared. Two mixed cohorts, containing data from all scanners and kernels, were created to simulate heterogeneous acquisition parameters.
resultsThe average difference in ES between kernels decreased for the scans obtained with both scanners after normalization (7.7 ± 2.7 to 0.3 ± 0.7; 7.2 ± 3.8 to -0.1 ± 0.5). Correlation coefficients between ES and FEV1, and FEV1/FVC increased significantly for the mixed cohorts.
conclusionsNormalization of chest CT data reduces variation in emphysema quantification due to reconstruction filters and improves correlation between ES and spirometry. KEY POINTS: • Emphysema quantification is sensitive to the reconstruction kernel used. • Normalization allows comparison of emphysema quantification from images reconstructed with varying kernels. • Normalization allows comparison of emphysema quantification obtained with scanners from different manufacturers. • Normalization improves correlation of emphysema quantification with spirometry. • Normalization can be used to compare data from different studies and centers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.