Spatial Dependence of CT Emphysema in Chronic Obstructive Pulmonary Disease Quantified by Using Join-Count Statistics
Bibliographic record
Abstract
Background Existing CT emphysema measurements quantify the extent or clustering of emphysema voxels in chronic obstructive pulmonary disease (COPD); however, these measurements do not quantify how those voxels are clustered. Purpose To develop a CT measurement to quantify the “compactness” of emphysema voxels, called the normalized join count (NJC), and to determine whether the NJC measurement differentiates COPD disease severity and correlates with lung function and visual emphysema scores. Materials and Methods In this secondary analysis of a prospective study, lung function and CT images were obtained from the Canadian Cohort Obstructive Lung Disease study visit 1 from 2009 to 2013. Participants were categorized as never-smokers, at risk, mild COPD, or moderate-severe COPD. Diffusion capacity for carbon monoxide/alveolar volume was measured. CT emphysema was scored visually by radiologists. CT measurements included the percentage low-attenuation area with attenuation less than –950 HU (%LAA–950insp), low-attenuation cluster (LAC), and lowest 15th percentile point of the CT lung density histogram. NJC was developed to measure compactness of CT emphysema voxels. An analysis of variance determined differences between groups. Multivariable ridge regression determined association between CT measurements with lung function and radiologist scores. Results A total of 1294 participants (750 men; mean age, 67 years ± 10) were analyzed (277 never-smokers, 306 at risk, 427 mild COPD, and 284 moderate-severe COPD). NJC, %LAA–950insp, and LAC measurements were higher in moderate-severe COPD than in never-smokers and at-risk participants (P < .05 for all comparisons), but only NJC was different between mild and ;moderate-severe COPD (mean, 1.98% ± 3.61 vs 1.44% ± 2.14; P < .05). In multivariable regression analysis, among all CT measurements NJC had the greatest relative contribution to diffusion capacity for carbon monoxide/alveolar volume (P = .002) and visual emphysema score (P < .001). Conclusion The relationship of normalized join count with severity of chronic obstructive pulmonary disease may indicate that the assessment of this disease is dependent on the number of low attenuating voxels or the size of clusters and the spatial arrangement of such voxels. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".