Technical Note: Bone mineral density measurements of strontium‐rich trabecular bone‐mimicking phantoms using quantitative ultrasound
Bibliographic record
Abstract
PURPOSE: Bone quantity, as determined by the current gold standard, dual energy X-ray absorptiometry (DXA), through measured areal bone mineral density (aBMD), is subject to positive biases if bone strontium levels are high. This is of particular concern for populations administered strontium-based compounds for the treatment of osteoporosis. This study investigated the dependence of bone mineral density (BMD) determinations, and associated ultrasound-determined indices, obtained by quantitative ultrasound (QUS), on bone strontium content using a new generation of trabecular bone-mimicking phantoms. METHODS: A new generation of bone-mimicking phantoms, consisting of hydroxyapatite (HA) and gelatin, was developed. Castor oil layers were included in these phantoms to create a multilayer bone-mimicking phantom. These phantoms were prepared using a bone mineral fraction consisting of varying strontium concentrations in the range of 0-2.5% mol/mol as strontium-substituted HA. The effect of varying bone strontium content on determined quality indices was evaluated based on determined speed of sound (SOS), broadband ultrasound attenuation (BUA) and determined quantitative ultrasound index (QUI) for phantoms with varying BMD values and varying strontium concentration using two QUS systems: a clinical Sahara® system and an in-house research system with two identical transducers with center frequency of 1 MHz. The two QUS systems were also compared through a Bland-Altman analysis. RESULTS: Both the clinical system and the research QUS systems showed a strong dependency between BMD and BUA, indicating a potential for QUS to be used as a means of estimating BMD (p = 0.001). SOS was found to have no correlation to BMD (p = 0.546). There was no correlation observed between BUA and increasing bone strontium concentrations for the research (p = 0.749) and clinical (p = 0.609) QUS systems. Similarly, no dependency was observed between the SOS and bone strontium levels up to 2.5 mol/mol [Sr/(Sr+Ca)]% for the research (p = 0.862) and clinical (p = 0.481) QUS systems. No effect on the QUI values was observed with changing strontium levels with either research (p = 0.939) or clinical QUS systems (p = 0.931). A Bland-Altman analysis showed that there was a clear offset in determined QUI values for both systems but they are in agreement with one another. CONCLUSIONS: Bone quality can be assessed through the use of QUS while increasing bone strontium concentration was found to have no effect on QUS-determined quality indices. This study concludes that QUS can potentially be used for the determination of bone quality without introducing biases due to bone strontium levels as is known to be the case with DXA determined aBMD.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".