Potential of propagation-based synchrotron X-ray phase-contrast computed tomography for cardiac tissue engineering
Bibliographic record
Abstract
Hydrogel-based cardiac tissue engineering offers great promise for myocardial infarction repair. The ability to visualize engineered systems in vivo in animal models is desired to monitor the performance of cardiac constructs. However, due to the low density and weak X-ray attenuation of hydrogels, conventional radiography and micro-computed tomography are unable to visualize the hydrogel cardiac constructs upon their implantation, thus limiting their use in animal systems. This paper presents a study on the optimization of synchrotron X-ray propagation-based phase-contrast imaging computed tomography (PCI-CT) for three-dimensional (3D) visualization and assessment of the hydrogel cardiac patches. First, alginate hydrogel was 3D-printed into cardiac patches, with the pores filled by fibrin. The hydrogel patches were then surgically implanted on rat hearts. A week after surgery, the hearts including patches were excised and embedded in a soft-tissue-mimicking gel for imaging by using PCI-CT at an X-ray energy of 25 keV. During imaging, the sample-to-detector distances, CT-scan time and the region of interest (ROI) were varied and examined for their effects on both imaging quality and radiation dose. The results showed that phase-retrieved PCI-CT images provided edge-enhancement fringes at a sample-to-detector distance of 147 cm that enabled visualization of anatomical and microstructural features of the myocardium and the implanted patch in the tissue-mimicking gel. For visualization of these features, PCI-CT offered a significantly higher performance than the dual absorption-phase and clinical magnetic resonance (3 T) imaging techniques. Furthermore, by reducing the total CT-scan time and ROI, PCI-CT was examined for lowering the effective dose, meanwhile without much loss of imaging quality. In effect, the higher soft tissue contrast and low-dose potential of PCI-CT has been used along with an acceptable overall animal dose to achieve the high spatial resolution needed for cardiac implant visualization. As a result, PCI-CT at the identified imaging parameters offers great potential for 3D assessment of microstructural features of hydrogel cardiac patches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".