Thyroid Arterial Embolization for the Management of Benign and Malignant Thyroid Disease: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Thyroid arterial embolization (TAE) is a minimally invasive procedure that reduces blood flow to the thyroid gland by injecting particles into the superior and/or inferior thyroid artery. It has been sporadically used for goiter, Graves' disease, thyrotoxicosis, and thyroid cancers, but no reviews have assessed its safety and efficacy. METHODS: Databases were searched until January 2024. English-language studies on TAE were included. Studies using TAE for arterial aneurysms or lacking full text were excluded. No meta-analyses were performed. RESULTS: Among 1203 retrieved articles, 24 studies met inclusion criteria: TAE was used for goiter (8 studies), Graves' disease (8), thyroid malignancy (5), and thyrotoxicosis (4). The primary outcome was safety and efficacy. Limited evidence suggested benefits, including goiter size reduction and symptom relief with minimal complications like neck pain and hematoma. In Graves' disease, TAE induced hormonal and immunologic changes, normalizing thyroid function in some patients. In thyroid cancer, it alleviated symptoms and facilitated safer surgery. However, serious risks, including nontarget embolization and mortality, require caution. CONCLUSION: This review presents an overview of the literature regarding safety and efficacy of TAE. The lack of robust data, significant risk of serious complications (including nontarget embolization and mortality), and absence of a standardized, safe protocol preclude recommending TAE as a routine treatment option. Given the high efficacy and lower complication rates of current established therapies, TAE should only be considered in exceptional circumstances, when standard treatments have failed or are contraindicated, and then only at specialized centers with extensive embolization expertise.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".