Measurement of Midfemoral Shaft Geometry: Repeatability and Accuracy Using Magnetic Resonance Imaging and Dual-Energy X-ray Absorptiometry
Bibliographic record
Abstract
Although macroscopic geometric architecture is an important determinant of bone strength, there is limited published information relating to the validation of the techniques used in its measurement. This study describes new techniques for assessing geometry at the midfemur using magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA) and examines both the repeatability and the accuracy of these and previously described DXA methods. Contiguous transverse MRI (Philips 1.5T) scans of the middle one-third femur were made in 13 subjects, 3 subjects with osteoporosis. Midpoint values for total width (TW), cortical width (CW), total cross-sectional area (TCSA), cortical cross-sectional area (CCSA), and volumes from reconstructed three-dimensional (3D) images (total volume [TV] and cortical volume [CVol]) were derived. Midpoint TW and CW also were determined using DXA (Lunar V3.6, lumbar software) by visual and automated edge detection analysis. Repeatability was assessed on scans made on two occasions and then analyzed twice by two independent observers (blinded), with intra- and interobserver repeatability expressed as the CV (CV +/- SD). Accuracy was examined by comparing MRI and DXA measurements of venison bone (and Perspex phantom for MRI), against "gold standard" measures made by vernier caliper (width), photographic image digitization (area) and water displacement (volume). Agreement between methods was analyzed using mean differences (MD +/- SD%). MRI CVs ranged from 0.5 +/- 0.5% (TV) to 3.1 +/- 3.1% (CW) for intraobserver and 0.55 +/- 0.5% (TV) to 3.6 +/- 3.6% (CW) for interobserver repeatability. DXA results ranged from 1.6 +/- 1.5% (TW) to 4.4 +/- 4.5% (CW) for intraobserver and 3.8 +/- 3.8% (TW) to 8.3 +/- 8.1% (CW) for interobserver variation. MRI accuracy was excellent for TV (3.3 +/- 6.4%), CVol (3.5 +/- 4.0%), TCSA (1.8 +/- 2.6%), and CCSA (1.6 +/- 4.2%) but not TW (4.1 +/- 1.4%) or CW (16.4 +/14.9%). DXA results were TW (6.8 +/- 2.7%) and CW (16.4 +/- 17.0%). MRI measures of geometric parameters of the midfemur are highly accurate and repeatable, even in osteoporosis. Both MRI and DXA techniques have limited value in determining cortical width. MRI may prove valuable in the assessment of surface-specific bone accrual and resorption responses to disease, therapy, and variations in mechanical loading.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".