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Feasibility of <i>in vivo</i> 3D microCT imaging of cortical bone vascular porosity in the rat

2013· article· en· W3173659431 on OpenAlexafffundabout
Isaac Pratt, David M. L. Cooper

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIn vivoCortical boneBiomedical engineeringX-ray microtomographyEx vivoSynchrotronMaterials scienceCortex (anatomy)Nuclear medicineAnatomyMedicineRadiologyBiologyOpticsNeurosciencePhysics

Abstract

fetched live from OpenAlex

Cortical bone is a dynamic tissue which undergoes adaptive and pathological changes through life. An improved understanding of the spatio‐temporal nature of these changes holds great promise for aiding the study of bone development, maintenance and senescence. Commercial in vivo microCT scanners operate with maximal resolutions in the 10–20 um range producing doses of 0.5–1 Gy for trabecular bone imaging. As dose scales exponentially with resolution, in vivo visualization of cortical microarchitecture remains beyond the reach of these systems. This study explored the feasibility of utilizing synchrotron propagation phase contrast microCT to resolve vascular porosity in the cortex of rat bone with doses suitable for in vivo imaging. We imaged ex vivo rat distal limbs at the Canadian Light Source synchrotron, determined the optimal propagation distance and used ion chamber and thermoluminescent dosimetry to measure dose. We found that 10 um resolution with 0.6 m of propagation distance at 37 keV was sufficient to visualize cortical pores with doses in the range of 2–4 Gy. Further optimization of the scan protocol promises to reduce dose to levels comparable to conventional trabecular bone scans. Grant Funding Source : NSERC

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.009
GPT teacher head0.226
Teacher spread0.216 · 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 teacher head, 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

Citations0
Published2013
Admission routes3
Has abstractyes

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