Diffusion coefficients of articular cartilage for different CT and MRI contrast agents
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.
Bibliographic record
Abstract
In contrast enhanced magnetic resonance imaging (MRI) and computed tomography (CT), the equilibrium distribution of anionic contrast agent is expected to reflect the fixed charged density (FCD) of articular cartilage. Diffusion is mainly responsible for the transport of contrast agents into cartilage. In osteoarthritis, cartilage composition changes at early stages of disease, and solute diffusion is most likely affected. Thus, investigation of contrast agent diffusion could enable new methods for imaging of cartilage composition. The aim of this study was to determine the diffusion coefficient of four contrast agents (ioxaglate, gadopentetate, iodide, gadodiamide) in bovine articular cartilage. The contrast agents were different in molecular size and charge. In peripheral quantitative CT experiments, penetration of contrast agent into the tissue was allowed either through the articular surface or through deep cartilage. To determine diffusion coefficients, a finite element model based on Fick's law was fitted to experimental data. Diffusion through articular surface was faster than through deep cartilage with every contrast agent. Iodide, being of atomic size, diffused into the cartilage significantly faster (q<0.05) than the other three contrast agents, for either transport direction. The diffusion coefficients of all clinical contrast agents (ioxaglate, gadopentetate and gadodiamide) were relatively low (142.8-253.7 μm(2)/s). In clinical diagnostics, such slow diffusion may not reach equilibrium and this jeopardizes the determination of FCD by standard methods. However, differences between diffusion through articular surface and deep cartilage, that are characterized by different tissue composition, suggest that diffusion coefficients may correlate with cartilage composition. Present method could therefore enable image-based assessment of cartilage composition by determination of diffusion coefficients within cartilage tissue.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it