Picture archiving and communications systems: a study of reliability of orthodontic cephalometric analysis
Bibliographic record
Abstract
The objectives of this study were to investigate the possibility of using a picture archiving and communications system (PACS) for basic chairside cephalometric analysis and to compare PACS with hand-tracing and on-screen digitization using a commercial program (Dolphin Imaging Plus Version 10.0). One hundred digital lateral cephalometric radiographs were selected and analysed using the Eastman analysis. Angular and linear measurements were recorded and a single operator traced each radiograph twice, using each of the following methods: PACS, hand-tracing, and Dolphin Imaging. The British Standards Institution Coefficient of Repeatability was used to investigate repeatability within each method and the Bland and Altman method to investigate systematic and random errors between methods. The PACS was more repeatable than Dolphin for measuring the angle between the upper incisors and the maxillary plane but was less repeatable than hand-tracing for measuring percentage lower anterior face height (LAFH). There were statistically significant systematic differences between PACS, hand-tracing, and Dolphin for measurement of lower incisor inclination. However, all three methods agreed, on average, and differences between methods were all within clinically acceptable limits. PACS was found to be clinically acceptable to be used chairside, without the need for hand-tracing or involvement of any orthodontic software. This offers the freedom to analyse digital cephalograms within a clinical area at the same appointment as when the digital radiograph is taken.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".