Reliability of lower extremity alignment measurement using radiographs and PACS
Bibliographic record
Abstract
PURPOSE: Lower extremity alignment is an important consideration prior to cartilage surgery and/or osteotomy about the knee. This is measured on full length standing hip to ankle radiographs, which has traditionally been done using hard copy radiographs. However, the advent of PACS (Picture Archiving and Communication Systems) has allowed these measurements to be done on computer based digital radiographs. The objectives of this study were to evaluate the intra- and inter-observer reliability of lower limb alignment measures manually obtained from hard copy radiographs versus using the Philips Easy Vision system, and to assess the subjective ease of use for the two methods. METHODS: Forty-two patients who underwent surgery and who had a standing hip to ankle radiograph on file were identified. Four raters, including two radiologists and two orthopaedic surgeons, measured each hard copy radiograph and computer image on two separate occasions. Three measurements were recorded for each hard copy radiograph and computer image-width of tibial plateau, the distance from the medial aspect of the tibial plateau to the weight-bearing line, and the mechanical axis. RESULTS: All correlations for this study were high. For tibial plateau data, the hard copy radiographs compared to PACS demonstrated intra-class correlation coefficients (ICC) ranging from 0.93 to 0.99 for inter-rater reliability for the four raters. The ICC for intra-rater reliability for hard copies ranged from 0.90 to 0.99 and for PACS from 0.94 to 0.99. The inter-rater data comparing raters ranged from 0.87 to 0.98 for hard copy radiographs and from 0.98 to 0.99 for PACS. For mechanical axis data, the ICC for hard copy radiograph compared to PACS ranged from 0.93 to 0.97 for the intra-rater reliability for the four raters. The intra-rater reliability for mechanical axis data on hard copy radiograph ranged from an ICC of 0.86 to 0.96, and for PACS the ICC ranged from 0.93 to 0.99. The inter-observer data for hard copy radiographs using the mechanical axis ranged from 0.88 to 0.94 and for PACS ranged from 0.93 to 0.97. The physicians rated PACS as statistically significantly easier to use when compared to hard copy (P = 0.03). CONCLUSION: Evaluation of lower extremity alignment using two techniques prior to knee surgery was found to have higher inter- and intra-observer reliability using PACS software. PACS is now used prior to cartilage surgery and/or osteotomy to measure both alignment and the location of the weight bearing line on the tibial plateau both before and after surgery. LEVEL OF EVIDENCE: Diagnostic study, Level I.
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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 | 0.001 | 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".