Volumetric evaluation of lumbar epidural fat distribution in epidural lipomatosis and back pain in patients who are obese: introducing a novel technique (Fat Finder algorithm)
Why this work is in the frame
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Bibliographic record
Abstract
Objective: Spinal epidural lipomatosis (EL) represents an excessive deposition of unencapsulated adipose tissue in the spinal canal that can result in chronic back pain in patients who are obese with and without diabetes. We aim to calculate the total volumetric epidural fat on lumbar spine MRI in a predominately obese population and correlate total epidural fat to lower back pain (LBP) and body mass index (BMI). Research design and methods: We developed a program (Fat Finder) to quantify volumetric distribution of epidural fat throughout the lumbar spine. Eleven patients with LBP were imaged using two MRI protocols: parallel axial slices and conventional clinical protocol. The distribution of epidural fat per level was analyzed and normalized to the spinal canal size. Results: (815.0-2717.5) in the age-similar non-EL group. A higher percentage of fat volume in the canal was associated with higher LBP scores. The fat percentage was 32.2% among patients with EL versus 15.4% for age-similar non-EL with LBP score of 6.1 and 4.0, respectively. Conclusions: The Fat Finder is a novel volumetric method to quantify epidural lumbar spinal fat. The epidural fat favors the lower spinal segment with direct proportionality between the fat volume and LBP score, independent of BMI.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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