Feasibility and Safety of Silicone Rubber Contrast-Enhanced Microcomputed Tomography in Evaluating the Angioarchitecture of Prostatectomy Specimens
Bibliographic record
Abstract
This ethics committee-approved pilot study was carried out with informed consent. A protocol was developed to assess the feasibility of in vitro Microfil injection of prostate cancer specimens followed by analysis with micro-computed tomography (microCT) to characterize the functional vascularity of prostatic tissue and evaluate its safety with respect to the preservation of a specimen for pathologic examination. The visible prostatic arteries of two surgically resected prostates frompatients with known prostate cancer (PCa) were injected with MicrofilMV-122 contrast medium immediately after removal. The specimens were scanned using microCT and were qualitatively examined using three-dimensional analysis software (MicroView; GE Healthcare Biosciences). The Microfil perfusion in the two samples was sufficient to view the functional vascularity arising from a major prostatic artery, up to a resolution of 17.626 µm without any indication of adverse effects due to Microfil injection. Malignant prostatic regions showed a greater vascular density on histology but decreased vascular perfusion compared with benign prostatic regions. The use of microCT on Microfil-injected prostates seems to be a feasible and specimen-preserving method for visualizing the three-dimensional vessel patterns present in resected human prostates.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".