High-Resolution Computed Tomography Features of Nonspecific Interstitial Pneumonia and Usual Interstitial Pneumonia
Bibliographic record
Abstract
OBJECTIVE: To assess the accuracy of high-resolution computed tomography (HRCT) in the diagnosis of nonspecific interstitial pneumonia (NSIP). We hypothesized that the computed tomography (CT) features of NSIP could be distinguished from those of usual interstitial pneumonia (UIP). METHODS: The HRCT images of 47 patients with surgical lung biopsy-proven NSIP (n = 25) and UIP (n = 22) were independently reviewed by 2 thoracic radiologists. Predominant imaging patterns, most likely diagnosis, and diagnostic level of confidence were recorded. A confident HRCT diagnosis of NSIP was based on the presence of spatially uniform, bilateral, basal-predominant ground-glass and/or reticular opacities with little if any honeycombing, whereas UIP was confidently diagnosed if a spatially inhomogeneous, bilateral, peripheral, basal-predominant pattern of reticular opacities and honeycombing with little if any ground-glass attenuation was identified. RESULTS: A predominant pattern of ground-glass and/or reticular opacity with minimal to no honeycombing was demonstrated in 48 (96%) of 50 readings in patients with NSIP. Conversely, the presence of honeycombing as a predominant feature had a predictive value of 90% for UIP (P < 0.001). Usual interstitial pneumonia was more likely than NSIP to be subpleural and patchy (P < 0.001). A confident CT diagnosis of NSIP and UIP was correct in 73% and 88% of cases, respectively. The correctness of a CT diagnosis made at intermediate or high confidence was 68% and 88%, respectively. The kappa value for distinction of NSIP from UIP was 0.72. CONCLUSION: In contrast to previous reports, NSIP can be separated from UIP in most cases. The presence of honeycombing as a predominant imaging finding is highly specific for UIP and can be used to differentiate it from NSIP, particularly when the distribution is patchy and subpleural predominant. The presence of predominant ground-glass and reticular opacity is highly characteristic of NSIP, but there is a subset of patients with UIP who have this pattern and may require biopsy for differentiation from NSIP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".