Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction.

Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method. Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis. SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r =  - 0.69 vs. r =  - 0.49/r =  - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r =  - 0.77 vs. r =  - 0.69/r =  - 0.65, p = 0.03/p = 0.002), and in the random sample (r =  - 0.39 vs. r =  - 0.26/r =  - 0.25, p = 0.001/p = 0.007). The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores. The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores. • A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research. © 2023. The Author(s).

Citation

Mats Lidén, Antoine Spahr, Ola Hjelmgren, Simone Bendazzoli, Josefin Sundh, Magnus Sköld, Göran Bergström, Chunliang Wang, Per Thunberg. Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction. European radiology. 2024 Jan;34(1):39-49

Mesh Tags

PMID: 37552259

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