<scp>USPIO</scp>‐related T1 and T2 mapping <scp>MRI</scp> of cartilage in a rabbit model of blood‐induced arthritis: a pilot study
Bibliographic record
Abstract
Ultrasmall paramagnetic iron oxide (USPIO)-enhanced MRI is promising for evaluating inflammation. The aims of this study were to investigate the effect of USPIO on cartilage T1 and T2 mapping, and to evaluate a proposed rapid vs. conventional T2 map method for imaging cartilage in a blood-induced arthritis model. Knees of nine arthritic (induction by intra-articular autologous blood injection) and six control rabbits were imaged over time (baseline, weeks 1, 5, 10) by 1.5 T MRI. All rabbits had USPIO (35-75 μmol Fe/kg)-enhanced MRI at each time point. T1 and T2 (conventional and rapid) maps and signal-to-noise ratios (SNR) were obtained pre- and post-USPIO administration. Cartilage biochemistry and histology were compared with MRI. Excellent correlations were noted between T1 map values and histologic scores at week 10 pre-USPIO (medial, r = 0.93, P = 0.0007; lateral, r = 0.87, P = 0.005) in the arthritic group, but not between T2 map and histology. Marginally and significant differences were observed between pre- and post-USPIO T2 values at weeks 5 (P = 0.06) and 10 (P = 0.02), but only with the administration of high USPIO doses in the arthritic group using the conventional method. No significant differences were noted between pre- and post-USPIO T1 values at any imaging time points. Cartilage T2 maps with short-TR and conventional protocols provided similar T2 values [(decreased trend)] (P > 0.05). Concomitant use of USPIO to T1 and T2 mapping of cartilage would not impair the identification of interval changes of T1 and T2 maps. Rapid T2 map provides similar results compared to conventional method, but its validation warrants further investigation.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".