MRI Virtual Biopsies: Analysis of an Explanted Endovascular Device and Perspectives for the Future
Bibliographic record
Abstract
Information that can be obtained by magnetic resonance imaging (MRI) of explanted endovascular devices must be validated as this method is non-destructive. Histology of such a device together with its encroached tissues can be elegantly performed after polymethymethacrylate (PMMA) embedding, but this approach requires destruction of the specimen. The issue is therefore to determine if the MRI is sufficient to fully validate an explanted device based upon the characterization of an explanted specimen. An AneuRx device deployed percutaneously 25 months earlier in a 75-year-old patient was removed en bloc at autopsy together with the surrounding aneurysmal sac and segments of the upstream and downstream arteries. Macroscopic pictures were taken and a slice of the cross-section was processed for histology after polymethylmethacrylate (PMMA) embedding. For the magnetic resonance imaging investigation, the device was inserted in a Biospec 4.7 T MRI system with a 20 mm diameter birdcage resonator used for both emission and reception. A Spin-Echo (SE) was used to acquire both T1 proton density (PD) and T2 weighted images. A gradient-echo (GE) sampling of a free induction decay (GESFID) was used to generate multiple GE images using a single excitation pulse so that four images at different TE were obtained in the same acquisition. The selected explanted device was outstandingly well-healed compared to most devices harvested from humans. No inflammatory process was observed in contact or at distance of the materials. In MRI T1 images display no specific contrast and were homogeneous in the different tissues. The contrast was improved on proton density weighed images. On the T2 weighed images, the different areas were well identified. The diffusion images displayed in the surrounding B region had the greatest diffusion coefficient and the greatest anisotropy. The MRI analysis of the explanted AneuRx device illustrates the possibilities of this technique to characterize the interaction of the endovascular graft with the surrounding tissues. MRI is a breakthrough to investigate explanted medical devices but it also can be advantageously used in vivo to obtain virtual biopsies, because real biopsies to determine the 3 Bs (biocompatibility, biofunctionality and bioresilience) cannot be carried out as they could obviously initiate infection and degradation of the foreign materials.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".