Novel Method to Improve Radiologist Agreement in Interpretation of Serial Chest Radiographs in the ICU
Bibliographic record
Abstract
OBJECTIVES: To determine whether a novel method and device, called a variable attenuation plate (VAP), which equalizes chest radiographic appearance and allows for synchronization of manual image windowing with comparison studies, would improve consistency in interpretation. MATERIALS AND METHODS: Research ethics board approved the prospective cohort pilot study, which included 50 patients in the intensive care unit (ICU) undergoing two serial chest radiographs with a VAP placed on each one of them. The VAP allowed for equalization of density and contrast between the patients' serial chest radiographs. Three radiologists interpreted all the studies with and without the use of VAP. Kappa and percent agreement was used to calculate agreement between radiologists' interpretations with and without the plate. RESULTS: Radiologist agreement was substantially higher with the VAP method, as compared to that with the non-VAP method. Kappa values between Radiologists A and B, A and C, and B and C were 46%, 55%, and 51%, respectively, which improved to 73%, 81%, and 66%, respectively, with the use of VAP. Discrepant report impressions (i.e., one radiologist's impression of unchanged versus one or both of the other radiologists stating improved or worsened in their impression) ranged from 24 to 28.6% without the use of VAP and from 10 to 16% with the use of VAP (χ (2) = 7.454, P < 0.01). Opposing views (i.e., one radiologist's impression of improved and one of the others stating disease progression or vice versa) were reported in 7 (12%) cases in the non-VAP group and 4 (7%) cases in the VAP group (χ (2) = 0.85, P = 0.54). CONCLUSION: Numerous factors play a role in image acquisition and image quality, which can contribute to poor consistency and reliability of portable chest radiographic interpretations. Radiologists' agreement of image interpretation can be improved by use of a novel method consisting of a VAP and associated software and has the potential to improve patient care.
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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 | 0.027 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".