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Record W4405409642 · doi:10.1093/jbmrpl/ziae158

Bone imaging modality precision and agreement between DXA, pQCT, and HR-pQCT

2024· article· en· W4405409642 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJBMR Plus · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersNational Health and Medical Research CouncilMedical Research CouncilDavid and Elaine Potter Foundation
KeywordsQuantitative computed tomographyNuclear medicineModality (human–computer interaction)RadiologyMedicineComputer scienceInternal medicineBone densityOsteoporosisArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Quantifying precision error for DXA, peripheral QCT (pQCT), and HR-pQCT is crucial for monitoring longitudinal changes in body composition and musculoskeletal outcomes. Agreement and associations between bone variables assessed using pQCT and second-generation HR-pQCT are unclear. This study aimed to determine the precision of, and agreement and associations between, bone variables assessed via DXA, pQCT, and second-generation HR-pQCT. Thirty older adults (mean age: 64.2 ± 8.0 yr; women: 67%) were recruited. DXA scans were performed at the total hip, lumbar spine, and whole body. Distal (4%) and proximal (30%/33%/66%) skeletal sites at the radius and tibia were scanned with pQCT and/or HR-pQCT. Root-mean-squared coefficients of variation (%CVRMS) were calculated to define precision errors, and Bland–Altman plots assessed agreement between densitometric estimates. Pearson correlations and linear regression explored relationships between bone variables at different skeletal sites and proportional bias, respectively. Precision errors ranged between 0.55% and 1.6% for DXA, 0.40% and 4.8% for pQCT, and 0.13% and 30.7% for HR-pQCT. Systematic bias was identified between pQCT- and HR-pQCT-determined radius and tibia volumetric BMD (vBMD) estimates (all p<.001). Proportional bias was not observed between vBMD measures at any skeletal site (all p>.05). pQCT- and HR-pQCT-determined total, trabecular, and cortical vBMD and estimates of bone strength at the radius and tibia were strongly correlated (all p<.05). Precision error was low for most bone variables and within the expected range for all imaging modalities. We observed significant systematic bias, but no proportional bias, between pQCT- and second-generation HR-pQCT-determined vBMD estimates at the radius and tibia. Nevertheless, measures of bone density and strength were strongly correlated at all skeletal sites. These findings suggest that although bone density and strength estimates from both imaging modalities are not interchangeable, they are strongly related and likely have similar fracture prediction capabilities.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.353
Teacher spread0.325 · 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