Inter-Rater Reliability between Musculoskeletal Radiologists and Orthopedic Surgeons on Computed Tomography Imaging Features of Spinal Metastases
Bibliographic record
Abstract
INTRODUCTION: The primary objective of this pilot study was to examine the inter-rater reliability in scoring the computed tomography (ct) imaging features of spinal metastases in patients referred for radiotherapy (rt) for bone pain. METHODS: In a retrospective review, 3 musculoskeletal radiologists and 2 orthopedic spinal surgeons independently evaluated ct imaging features for 41 patients with spinal metastases treated with rt in an outpatient radiation clinic from January 2007 to October 2008. The evaluation used spinal assessment criteria that had been developed in-house, with reference to osseous and soft tissue tumour extent,presence of a pathologic fracture,severity of vertebral height loss, andpresence of kyphosis.The Cohen kappa coefficient between the two specialties was calculated. RESULTS: Mean patient age was 69.2 years (30 men, 11 women). The mean total daily oral morphine equivalent was 73.4 mg. Treatment dose-fractionation schedules included 8 Gy/1 (n = 28), 20 Gy/5 (n = 12), and 20 Gy/8 (n = 1). Areas of moderate agreement in identifying the ct imaging appearance of spinal metastasis included extent of vertebral body involvement (κ = 0.48) and soft-tissue component (κ = 0.59). Areas of fair agreement included extent of pedicle involvement (κ = 0.28), extent of lamina involvement (κ = 0.35), and presence of pathologic fracture (κ = 0.20). Areas of poor agreement included nerve-root compression (κ = 0.14) and vertebral body height loss (κ = 0.19). CONCLUSIONS: The range of agreement between musculoskeletal radiologists and orthopedic surgeons for most spinal assessment criteria is moderate to poor. A consensus for managing challenging vertebral injuries secondary to spinal metastases needs to be established so as to best triage patients to the most appropriate therapeutic modality.
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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 | 0.053 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".