Urinary excretion of Yttrium-90 following intra-arterial microsphere treatment for liver tumours
Bibliographic record
Abstract
1744 Objectives To measure the urinary excretion of Yttrium-90 (90Y) following intra-arterial (IA) treatment with 90Y-microspheres for liver tumours. Methods Urine was collected over 12h. 3 samples of 2 ml were analysed in a gamma counter (Cobra 5003, Packard, Meriden). The energy window was set at 15-300 keV. Following correction for decay, background and total volume of urine, measurements were normalized to the administered activity of 90Y. From a 90Y solution a calibration curve was constructed to assess the correlation between activity and counts per minute. Results are compared between patients treated with TheraSphere (Nordion, Canada)-mainly suffering HCC- and patients treated with SIR-Spheres (SIRTEX, Australia) for colorectal liver metastasis. Results 15 patients were treated with TheraSphere, with an activity ranging from 977-6537 MBq (mean 2541). In 13 of 15 treatments it concerned primary liver cancer. 6 patients treated with SIR-Spheres were included. The mean activity was 1785 MBq (range: 1145-3212). The 12h urine collection contained on average a total activity of 52 kBq (range: 8-113) for TheraSphere and 1128 kBq (range: 438-2118) for SIR-Spheres. Approximately 0,0025% of the total activity was excreted in the urine during the first 12h following treatment with TheraSphere versus 0,0641% in case of SIR-Spheres. Microscopy did not reveal presence of microspheres in the urine. Conclusions Activity measurements in urine yielded consistent results, with a significant difference between SIR-Spheres and TheraSphere (26 times lower). However, the overall excreted activities for both products remain low. In case of urinary incontinence a short hospital stay is not strictly essential but can be considered in individual cases when treated with SIR-Spheres. No specific guidelines seem necessary in case of TheraSphere
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".