International recommendations for personalised selective internal radiation therapy of primary and metastatic liver diseases with yttrium-90 resin microspheres
Bibliographic record
Abstract
Abstract Purpose A multidisciplinary expert panel convened to formulate state-of-the-art recommendations for optimisation of selective internal radiation therapy (SIRT) with yttrium-90 ( 90 Y)-resin microspheres. Methods A steering committee of 23 international experts representing all participating specialties formulated recommendations for SIRT with 90 Y-resin microspheres activity prescription and post-treatment dosimetry, based on literature searches and the responses to a 61-question survey that was completed by 43 leading experts (including the steering committee members). The survey was validated by the steering committee and completed anonymously. In a face-to-face meeting, the results of the survey were presented and discussed. Recommendations were derived and level of agreement defined (strong agreement ≥ 80%, moderate agreement 50%–79%, no agreement ≤ 49%). Results Forty-seven recommendations were established, including guidance such as a multidisciplinary team should define treatment strategy and therapeutic intent (strong agreement); 3D imaging with CT and an angiography with cone-beam-CT, if available, and 99m Tc-MAA SPECT/CT are recommended for extrahepatic/intrahepatic deposition assessment, treatment field definition and calculation of the 90 Y-resin microspheres activity needed (moderate/strong agreement). A personalised approach, using dosimetry (partition model and/or voxel-based) is recommended for activity prescription, when either whole liver or selective, non-ablative or ablative SIRT is planned (strong agreement). A mean absorbed dose to non-tumoural liver of 40 Gy or less is considered safe (strong agreement). A minimum mean target-absorbed dose to tumour of 100–120 Gy is recommended for hepatocellular carcinoma, liver metastatic colorectal cancer and cholangiocarcinoma (moderate/strong agreement). Post-SIRT imaging for treatment verification with 90 Y-PET/CT is recommended (strong agreement). Post-SIRT dosimetry is also recommended (strong agreement). Conclusion Practitioners are encouraged to work towards adoption of these recommendations.
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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 | 0.097 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".