MRI has limited agreement with CT in the evaluation of vertebral fractures of the canine trauma patient
Bibliographic record
Abstract
Complete assessment of vertebral trauma in dogs currently requires CT and MRI for evaluation of the osseous and soft tissue structures that contribute to vertebral stability. Some studies in people have suggested that MRI may be sensitive and specific at detecting vertebral fractures making this potentially a single modality that could be used in spinal trauma evaluation. This study aimed to assess the ability for observers to evaluate vertebral fractures using MRI when compared to CT, which was used as the reference standard. Twenty-nine dogs with previously diagnosed acute vertebral fractures and four dogs with no vertebral fracture that had undergone sequential CT and MRI were included into the study. One hundred twenty-eight vertebrae were evaluated for the presence of fractures. Imaging studies were read by two observers blinded to the history. While both observers had similarly high sensitivity and specificity for simple detection of any fractured vertebrae, interobserver agreement was only moderate (κ = 0.584). When evaluations were specifically limited to detection of structurally unstable fractured vertebrae both observers showed improved specificity and interobserver agreement became substantial (κ = 0.650). Complete agreement for exact fracture location between MRI and CT results was only achieved in 14.3-32.6% of fractured vertebra with up to 79% of fractures being missed in some vertebral structures. This suggests that although MRI may be able to detect the presence of fractured vertebrae, it is not able to replace CT for the complete evaluation of the traumatized spine and documentation of fracture morphology.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".