Stereotactic body radiation therapy for colorectal cancer liver metastases
Bibliographic record
Abstract
The management of colorectal cancer liver metastases requires a multidisciplinary approach, which may incorporate systemic therapy, surgery, or local ablative therapies. Stereotactic body radiation therapy (SBRT) is a non-invasive highly conformal radiation technique that enables the delivery of large doses of radiation in a few fractions to well-defined targets using image-guidance and motion management. For selected patients with colorectal cancer liver metastases, stereotactic body radiation therapy can be delivered safely, with excellent long-term local control and overall survival. The purpose of this clinical practice review is to review the background, indications, and treatment details of stereotactic body radiation therapy for the treatment of colorectal liver metastases. SBRT for colorectal cancer liver metastases may be considered for patients with oligometastatic colorectal cancer in combination with surgery or other locally ablative therapies; for patients who are not candidates for surgical resection; or after failure of resection or other ablative therapies. When planning SBRT both a computed tomography and magnetic resonance imaging simulation may be obtained, where feasible, for target delineation. One or 3 fraction SBRT can be considered for lesions away from the central liver and luminal organs at risk, whereas 5 fraction SBRT is preferred otherwise. Image-guidance and motion management strategies are essential components of liver SBRT and will guide the creation of relevant internal and planning target volume margins. For lesions in close proximity to or overlapping with organs-at-risk, the balance between adequate local control and potential for cure with potential acute and late toxicity must be carefully considered.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".