Selective Internal Radiation Therapy with Yttrium-90 for Intrahepatic Cholangiocarcinoma: A Systematic Review on Post-Treatment Dosimetry and Concomitant Chemotherapy
Bibliographic record
Abstract
Y)-loaded microspheres is increasingly used for the treatment of Intrahepatic Cholangiocarcinoma (ICC). Dosimetry verifications post-treatment are required for a valid assessment of any dose-response relationship. We performed a systematic review of the literature to determine how often clinics conducted post-treatment dosimetry verification to measure the actual radiation doses delivered to the tumor and to the normal liver in patients who underwent SIRT for ICC, and also to explore the corresponding dose-response relationship. We also investigated other factors that potentially affect treatment outcomes, including the type of microspheres used and concomitant chemotherapy. Out of the final 47 studies that entered our study, only four papers included post-treatment dosimetry studies after SIRT to quantitatively assess the radiation doses delivered. No study showed that one microsphere type provided a benefit over another, one study demonstrated better imaging-based response rates associated with the use of glass-based TheraSpheres, and two studies found similar toxicity profiles for different types of microspheres. Gemcitabine and cisplatin were the most common chemotherapeutic drugs for concomitant administration with SIRT. Future studies of SIRT for ICC should include dosimetry to optimize treatment planning and post-treatment radiation dosage measurements in order to reliably predict patient responses and liver toxicity.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".