Magnetic Resonance Imaging of Human Tissue-Engineered Adipose Substitutes
Bibliographic record
Abstract
Adipose tissue (AT) substitutes are being developed to answer the strong demand in reconstructive surgery. To facilitate the validation of their functional performance in vivo, and to avoid resorting to excessive number of animals, it is crucial at this stage to develop biomedical imaging methodologies, enabling the follow-up of reconstructed AT substitutes. Until now, biomedical imaging of AT substitutes has scarcely been reported in the literature. Therefore, the optimal parameters enabling good resolution, appropriate contrast, and graft delineation, as well as blood perfusion validation, must be studied and reported. In this study, human adipose substitutes produced from adipose-derived stem/stromal cells using the self-assembly approach of tissue engineering were implanted into athymic mice. The fate of the reconstructed AT substitutes implanted in vivo was successfully followed by magnetic resonance imaging (MRI), which is the imaging modality of choice for visualizing soft ATs. T1-weighted images allowed clear delineation of the grafts, followed by volume integration. The magnetic resonance (MR) signal of reconstructed AT was studied in vitro by proton nuclear magnetic resonance ((1)H-NMR). This confirmed the presence of a strong triglyceride peak of short longitudinal proton relaxation time (T1) values (200 ± 53 ms) in reconstructed AT substitutes (total T1=813 ± 76 ms), which establishes a clear signal difference between adjacent muscle, connective tissue, and native fat (total T1 ~300 ms). Graft volume retention was followed up to 6 weeks after implantation, revealing a gradual resorption rate averaging at 44% of initial substitute's volume. In addition, vascular perfusion measured by dynamic contrast-enhanced-MRI confirmed the graft's vascularization postimplantation (14 and 21 days after grafting). Histological analysis of the grafted tissues revealed the persistence of numerous adipocytes without evidence of cysts or tissue necrosis. This study describes the in vivo grafting of human adipose substitutes devoid of exogenous matrix components, and for the first time, the optimal parameters necessary to achieve efficient MRI visualization of grafted tissue-engineered adipose substitutes.
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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".