Quantitative CT Imaging of the Spatial and Temporal Distribution of Liposomes in a Rabbit Tumor Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Successful employment of noninvasive imaging techniques to quantitatively assess the in vivo pharmacokinetics and biodistribution of nanoparticle drug delivery systems will facilitate the rational design of novel targeted drug carriers. This study reports on the bulk organ/tissue (liver, kidneys, spleen, tumor and blood) and intratumoral distribution of liposomes containing iohexol and gadoteridol over a 14-day period in VX2 sarcoma-bearing New Zealand White rabbits using computed tomography (CT). The vascular half-life of the liposomes was found to be 63.6 +/- 5.8 h and the maximum tumor-to-muscle iodine concentration ratio of 11.9 +/- 6.0 was measured 7 days postinjection with 1.13 +/- 0.29% ID of liposomes accumulating at the tumor site. The liposomes achieved their highest intratumoral distribution volume ratio at 48 h postadministration, occupying 72 +/- 5% of the total tumor volume. This investigation demonstrated the feasibility of using CT to perform quantitative, volumetric and longitudinal assessment of the pharmacokinetics and biodistribution of iodinated liposomes with sensitivities in the range of microg/cm3 while maintaining the ability to identify boundaries of anatomical structures at submillimeter resolution and with imaging time of less than one minute per scan. If successfully approved for clinical adoption, the use of CT imaging to monitor nanoparticulate drug delivery will provide an opportunity for online adjustment of therapeutic regimens and implementation of personalized medicine.
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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 it