REGIONAL DEPTH-SPECIFIC SUBCHONDRAL BONE DENSITY IN OA AND NORMAL DISTAL FEMORA: PRECISION AND PRELIMINARY COMPARISONS
Bibliographic record
Abstract
INTRODUCTION The exact role of altered subchondral bone in OA pathogenesis and pain is unclear. Clinical quantitative CT (QCT) combined with depth-specific image processing has been previously used to study subchondral bone mineral density (BMD) at the proximal tibia and patella. Limited depth-specific QCT research has been completed at the OA distal femur. OBJECTIVES To 1) assess the short-term precision of automated, regional, depth-specific subchondral BMD measures at the distal femur in individuals with and without OA; and 2) determine whether regional and focal BMD metrics were able to discriminate differences in subchondral bone density patterns between normal and OA distal femora. METHODS Fourteen participants (3M:11F; mean age: 49.9 (SD: 11.9) years) were recruited and classified as normal (n=7) or OA (n=7). Each participant was scanned three times over two days using clinical QCT. Two BMD assessments were evaluated at the distal femur: mean regional density and peak focal density. BMD measures were assessed across three depths (0-2.5, 2.5-5, 5-7.5 mm) and six sub-regions of the distal femur (medial/lateral, anterior/central/posterior), as per the MOAKS approach (Fig.1). We assessed precision using root mean square coefficients of variation (CV% RMS ). To explore potential differences between OA and normal distal femora, we performed parametric t-tests and non-parametric Mann-Whitney statistical analyses and also determined Cohen’s d effect sizes, with an absolute d > 0.8 considered clinically significant. RESULTS CV% RMS ranged from 1.6% to 3.6% (average: 2.2%) for measures of regional BMD while CV% RMS ranged from 1.6% to 6.9% (average: 2.7%) for measures of focal BMD. Statistical comparisons indicated lower BMD in OA distal femoral in the medial-anterior region at depths of 2.5-5 mm (regional: -17%; focal: -19%) and 5-7.5 mm (regional: -21%; focal: -25%) (Fig. 2). All other BMD measures were similar between normal and OA distal femora (p > 0.05). Cohen's d effect sizes ranged from -1.7 to 0.76. CONCLUSION This automated technique offers precise measures of subchondral BMD at the distal femur. This approach has potential to quantify and distinguish OA-related alterations in subchondral BMD at the distal femur.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".