Radioembolization for the Treatment of Liver Tumors
Bibliographic record
Abstract
Radioembolization aims to selectively target radiation to all liver tumors while limiting the dose to normal liver parenchyma. The deposition of yttrium-90 ((90)Y) microspheres delivered through the hepatic artery are preferentially implanted within liver tumors in a 3:1 to 20:1 ratio compared with a normal liver. The principles and mode of action of radioembolization are fundamentally different from the conventional embolization of liver tumors through transarterial embolization or chemoembolization. A meticulous work-up, involving computed tomography scanning, contrast-enhanced magnetic resonance imaging, and transfemoral hepatic angiogram, is essential to assess the appropriateness of the patient for treatment. A simulation of the treatment, done with technetium-99m-labeled macroaggregated albumin particles, which approximate the size of microspheres, is used to identify the shunting of microparticles to the lungs or gastrointestinal tract, thus helping to determine patient selection. Whole-liver or unilobar treatment approaches are chosen according to the anatomic distribution of the tumors, concomitant factors affecting liver function, and institutional preferences. Optimal periprocedural care, discharge planning, and follow-up care are essential to assess treatment response and ensure that short-term side effects of radioembolization are adequately managed. The expanding literature on radioembolization shows that this is an effective treatment for the management of both primary and metastatic tumors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".