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Record W2013195869 · doi:10.1359/jbmr.2001.16.12.2251

Measurement of Midfemoral Shaft Geometry: Repeatability and Accuracy Using Magnetic Resonance Imaging and Dual-Energy X-ray Absorptiometry

2001· article· en· W2013195869 on OpenAlexaff
Helen J. Woodhead, Allan Kemp, Cameron J. R. Blimkie, Julie Briody, Craig Duncan, Madeleine Thompson, Albert Lam, Robert Howman-Giles, Christopher T. Cowell

Bibliographic record

VenueJournal of Bone and Mineral Research · 2001
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcMaster University
FundersNational Health and Medical Research Council
KeywordsRepeatabilityCalipersNuclear medicineDual-energy X-ray absorptiometryReproducibilityMagnetic resonance imagingImaging phantomMedicineMathematicsOsteoporosisRadiologyGeometryBone mineral

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.088
GPT teacher head0.391
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations54
Published2001
Admission routes1
Has abstractyes

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