A new radiopaque embolizing agent for the treatment of endoleaks after endovascular repair: Influence of contrast agent on chitosan thermogel properties
Bibliographic record
Abstract
A new injectable radiopaque embolizing agent has been developed, based on chitosan thermogelling properties. Different commercial contrast agents (Isovue®, Visipaque®, and Conray®) were associated with chitosan-β-glycerophosphate. Their impact on gelation kinetic, mechanical properties, radiopacity, and cytotoxicity was tested to evaluate the best candidate and its feasibility for the treatment of endoleaks after endovascular aneurysm repair (EVAR). Addition of contrast agents did not prevent gelation at body temperature, but it significantly increased the viscosity of the solution before gelation, delayed gelation, and reduced the gelation rate. However, using chitosan with a high degree of deacetylation and 20 vol % contrast agent made it possible to obtain a gel with rapid gelation that was visible during X-ray based guided intervention. Hydrogels exhibit relatively low mechanical properties, which are only slightly modified by the addition of contrast agents. In vitro studies have demonstrated rapid release of contrast agents from hydrogels when immersed in a saline solution (>50% within 4 h). This is suitable for embolization, as radiopacity is required only to follow the embolization procedure, while long-term radiopacity would hamper further imaging and endoleak detection. Cytotoxicity and osmolality testing of extracts demonstrated some toxicity of products released by the gel during the first few hours, which is mainly related to their hypertonicity. After the first 24 h incubation, hydrogels released no more cytotoxic compounds, suggesting that the hydrogel rapidly becomes biocompatible. Altogether, this study suggests that the new radiopaque thermogels present interesting characteristics as embolizing agents for EVAR, although their mechanical properties require improvement.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".