<scp>In Vivo MRI</scp> Tracking of Degradable Polyurethane Hydrogel Degradation In Situ Using a Manganese Porphyrin Contrast Agent
Bibliographic record
Abstract
BACKGROUND: A noninvasive method to track implanted biomaterials is desirable for real-time monitoring of material interactions with host tissues and assessment of efficacy and safety. PURPOSE: To explore quantitative in vivo tracking of polyurethane implants using a manganese porphyrin (MnP) contrast agent containing a covalent binding site for pairing to polymers. STUDY TYPE: Prospective, longitudinal. ANIMAL MODEL: Rodent model of dorsal subcutaneous implants (10 female Sprague Dawley rats). FIELD STRENGTH/SEQUENCE: A 3-T; two-dimensional (2D) T1-weighted spin-echo (SE), T2-weighted turbo SE, three-dimensional (3D) spoiled gradient-echo T1 mapping with variable flip angles. ASSESSMENT: A new MnP-vinyl contrast agent to covalently label polyurethane hydrogels was synthesized and chemically characterized. Stability of binding was assessed in vitro. MRI was performed in vitro on unlabeled hydrogels and hydrogels labeled at different concentrations, and in vivo on rats with unlabeled and labeled hydrogels implanted dorsally. In vivo MRI was performed at 1, 3, 5, and 7 weeks postimplantation. Implants were easily identified on T1-weighted SE, and fluid accumulation from inflammation was distinguished on T2-weighted turbo SE. Implants were segmented on contiguous T1-weighted SPGR slices using a threshold of 1.8 times the background muscle signal intensity; implant volume and mean T1 values were then calculated at each timepoint. Histopathology was performed on implants in the same plane as MRI and compared to imaging results. STATISTICAL TESTS: Unpaired t-tests and one-way analysis of variance (ANOVA) were used for comparisons. A P value <0.05 was considered to be statistically significant. RESULTS: Hydrogel labeling with MnP resulted in a significant T1 reduction in vitro (T1 = 517 ± 36 msec vs. 879 ± 147 msec unlabeled). Mean T1 values of labeled implants in rats increased significantly by 23% over time, from 1 to 7 weeks postimplantation (651 ± 49 msec to 801 ± 72 msec), indicating decreasing implant density. DATA CONCLUSION: Polymer-binding MnP enables in vivo tracking of vinyl-group coupling polymers. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 1.
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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 | 0.000 | 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) | 0.001 | 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 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".