A Tracer Dose of Technetium-99m–Labeled Liposomes Can Estimate the Effect of Hyperthermia on Intratumoral Doxil Extravasation
Bibliographic record
Abstract
PURPOSE: A noninvasive method to monitor intratumoral Doxil delivery in individual patients during targeted tumor therapy is important to predict treatment response. The purpose of this study was to determine if a small tracer dose of technetium-99m (99mTc)-labeled liposomes could be used to quantify the effect of local hyperthermia on intratumoral Doxil extravasation. EXPERIMENTAL DESIGN: Experiments were carried out in a rat fibrosarcoma model with transplanted thigh tumors. Liposomes of approximately same size and composition as Doxil were radiolabeled using [technetium-99m (99mTc)]exametazime. Eight treatment groups received either Doxil, a tracer dose or a large dose of 99mTc-labeled liposomes, or a combination of tracer and Doxil, with or without hyperthermia. This design was chosen to assure that coadministration of both liposomal formulations did not influence their intratumoral distribution. Hyperthermia was done for 45 minutes. Scintigraphic images were obtained at 5 and 18 hours. At 18 hours, tumors were removed and gamma counts as well as doxorubicin concentrations were measured. RESULTS: Intratumoral extravasation of the 99mTc-labeled tracer could be imaged scintigraphically under normothermic and hyperthermic conditions. The thermal enhancement ratio was slightly higher for radiolabeled liposomes than for doxorubicin concentration. However, there was a significant positive correlation of intratumoral doxorubicin concentration and intratumoral uptake of the radiolabeled tracer (expressed as percentage of the injected dose per gram of tissue). Coadministration of radiolabeled liposomes did not negatively influence the amount of drug delivered with Doxil. CONCLUSIONS: The use of a radiolabeled tracer has potential value to monitor drug delivery and estimate the effect of an intervention aimed to increase liposomal accumulation, such as local hyperthermia.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".