Effect of Picture Archiving and Communication System Image Manipulation on the Agreement of Chest Radiograph Interpretation in the Neonatal Intensive Care Unit
Bibliographic record
Abstract
OBJECTIVE: Variability in image interpretation has been attributed to differences in the interpreters' knowledge base, experience level, and access to the clinical scenario. Picture archiving and communication system (PACS) has allowed the user to manipulate the images while developing their impression of the radiograph. The aim of this study was to determine the agreement of chest radiograph (CXR) impressions among radiologists and neonatologists and help determine the effect of image manipulation with PACS on report impression. MATERIALS AND METHODS: Prospective cohort study included 60 patients from the Neonatal Intensive Care Unit undergoing CXRs. Three radiologists and three neonatologists reviewed two consecutive frontal CXRs of each patient. Each physician was allowed manipulation of images as needed to provide a decision of "improved," "unchanged," or "disease progression" lung disease for each patient. Each physician repeated the process once more; this time, they were not allowed to individually manipulate the images, but an independent radiologist presets the image brightness and contrast to best optimize the CXR appearance. Percent agreement and opposing reporting views were calculated between all six physicians for each of the two methods (allowing and not allowing image manipulation). RESULTS: One hundred percent agreement in image impression between all six observers was only seen in 5% of cases when allowing image manipulation; 100% agreement was seen in 13% of the cases when there was no manipulation of the images. CONCLUSION: Agreement in CXR interpretation is poor; the ability to manipulate the images on PACS results in a decrease in agreement in the interpretation of these studies. New methods to standardize image appearance and allow improved comparison with previous studies should be sought to improve clinician agreement in interpretation consistency and advance patient care.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".