Extraspinal Findings at Lumbar Spine CT Examinations: Prevalence and Clinical Importance
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To prospectively determine the prevalence and clinical importance of extraspinal abnormalities in adult outpatients undergoing computed tomography (CT) of the lumbar spine. MATERIALS AND METHODS: Institutional review board approval was obtained for this prospective study. Informed consent was obtained from 400 consecutive adult outpatients (mean age, 49 years; 212 male and 188 female patients) undergoing lumbar spine CT for low back pain and/or radiculopathy. Those with known malignancy were excluded. Dedicated spinal and abdominal full-field-of-view (FOV) images for each patient were reviewed by at least one neuroradiologist and two body radiologists. Extraspinal abnormalities were classified according to the CT Colonography Reporting and Data System (C-RADS). The electronic medical record of the patients with C-RADS E3 and E4 extraspinal findings were reviewed to assess how many of these findings were previously unknown, and the patients were followed up 24-36 months after the initial CT to determine their work-up and outcome. RESULTS: Extraspinal findings were present on images in 162 (40.5%) of 400 lumbar spine CT examinations; 59 (14.8%) patients had indeterminate or clinically important findings requiring clinical correlation or further evaluation. After review of the electronic medical record, the prevalence of clinically important findings was 4.3%, comprising an early-stage renal cell carcinoma and transitional cell carcinoma, chronic lymphocytic leukemia, sarcoidosis, and 13 abdominal aortic aneurysms. Excluding anatomic variants, the full FOV was required to best visualize extraspinal abnormalities in 127 (79.4%) of 160 patients. CONCLUSION: Reviewing the full-FOV images from lumbar spine CT examinations will result in the detection of a small number of substantial extraspinal pathologic findings in addition to many benign incidental findings.
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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 | 0.002 |
| 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 it