Using magnetic resonance imaging to accurately assess injury to the posterior ligamentous complex of the spine: a prospective comparison of the surgeon and radiologist
Bibliographic record
Abstract
OBJECT: Magnetic resonance imaging has been proposed as a powerful technique for assessing the integrity of the posterior ligamentous complex (PLC) in spinal trauma. Because MR imaging is often used to determine appropriate treatment, it is important to determine the accuracy and reliability of MR imaging in diagnosing PLC disruption. The purpose of this study is to compare the ability of the radiologist and surgeon to assess disruption of the PLC in the setting of acute cervical and thoracolumbar trauma using MR imaging. METHODS: The components of the PLC in 89 consecutive patients with cervical or thoracolumbar fractures following acute spinal trauma were evaluated using MR imaging by both a musculoskeletal radiologist and an independent spine surgeon and assessed intraoperatively under direct visualization by the treating surgeon. The MR imaging interpretations of the musculoskeletal radiologist and surgeon were compared with the intraoperative report for accuracy, sensitivity, specificity, and positive and negative predictive values. A comparison between the radiologist's and spine surgeon's accuracy of MR imaging interpretation was performed. RESULTS: The agreement between both the spine surgeon's and radiologist's MR imaging interpretation and the actual intraoperative findings was moderate for most components of the PLC. Overall, the MR imaging interpretation of the surgeon was more accurate than that of the radiologist. The interpretation of MR imaging by the surgeon had negative predictive value and sensitivity of up to 100%. However, the specificity of MR imaging for both the surgeon and radiologist was lower, ranging from 51.5 to 80.5%. CONCLUSIONS: Comparison of the MR imaging interpretations between surgeon and radiologist indicates that the surgeon was more accurate for some PLC components. The relatively low positive predictive value and specificity for MR imaging in assessing PLC integrity suggests that both the surgeon and radiologist tend to overdiagnose PLC injury using MR imaging. This can lead to unnecessary surgeries if only MR imaging is used for treatment decision making.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".