Low dose contrast enhancement of biodegradable low-density stents by an approach balancing radiopaque coatings and beam filtration
Bibliographic record
Abstract
Abstract Objective. Biodegradable cardiovascular stents made of thin, low atomic number metals (e.g. Zn, Mg, Fe) are now approved for clinical use. However, poor contrast under x-ray imaging leads to longer surgical times, high patient exposure, and sometimes stent misplacement. This study aimed at enhancing the visibility of low- Z metal stents under x-ray imaging, by combining high- Z metal coatings and beam filtration. Approach. Photon energy spectra from W-anode x-ray beams operated at 80 and 120 kVp, were generated by the SpekCalc and BEAMnrc softwares. The contrast produced by Fe stent struts (50–10 μ m W coatings), as well as dose and air kerma values (by BEAMnrc), were simulated. Several types of beam hardening filters (Sn: 0.1, 0.2 mm; Cu: 0.2, 0.7 mm) were also applied. Then, Fe foils (50 µ m) with W coatings (2–3 µ m-thick) were fabricated by magnetosputtering. These samples were x-ray visualized, for quantification of contrast between W-coated and uncoated Fe samples. Fe struts (50 µ m) were also coated with W (3.8 ± 0.2 µ m), and stent-like objects were x-ray visualized. Main results. Fe samples attenuate 6.4% (120 kVp) and 10.1% (80 kVp) spectra photons, and 25% and 34.5% for W-coated Fe samples (SpekCalc). BEAMnrc calculations revealed the highest contrast improvement in a 120 kVp beam (36.4%, and 38.5%) for W-coated and uncoated Fe samples with Sn (0.2 mm), and Cu + Sn (0.2 + 0.2 mm) filters. Experimentally, the highest contrasts between Fe and W–Fe foils, were obtained with 0.2 mm Sn (77 ± 7% contrast increase at 80 kV). The dose was also strongly reduced (70% and 75%, for 80 and 120 kVp beams). Finally, for 3D Fe stents visualized at 80 kVp, the highest CNR and CNRD values were achieved with 0.1 mm Sn (18.5 × and 20.1 mGy −1 ; compared to 15.0 × and 12.0 mGy −1 in no-filter condition). Significance. The contrast of Fe-based stents in x-ray imaging is improved by addition of a thin layer of W and beam filtration with Sn. The precision and rapidity of biodegradable stents implantation would be improved thereby, as well as the dose to patients.
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.
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 | 0.000 | 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 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".