Therapeutic procedures in liver metastases: Conventional and future measures
Bibliographic record
Abstract
1. Background Resection of liver metastases from colorectal carcinoma (CRC) is associated with 5-year survival rates of 30–40%, with the possibility of cure, even in the absence of systemic therapy. This demonstration of a local therapy improving outcomes for ‘oligo-metastatic’ CRC is well accepted. Long-term survivors have also been reported following resection of liver metastases from sarcoma, renal-cell carcinoma, breast cancer and melanoma, with 5-year survival rates of 23–36% in a series of non-CRC liver metastases. Resection of neuroendocrine liver metastases has also been associated with favourable survival. Stereotactic body radiation therapy (SBRT) is an attractive option for patients with liver metastases. Liver SBRT requires a planning computed tomography (CT) simulation scan with intravenous (IV) contrast for target definition. Multimodal imaging with contrast-enhanced magnetic resonance imaging (MRI) or positron emission tomography (PET) may improve target delineation. Breathing-related liver motion should be assessed by respiratory-correlated (or 4D) CT, cine-MRI or 2D kV fluoroscopy to determine appropriate planning target volume (PTV) margins. Highly conformal dose distributions are desirable using multiple beams or arcs in coplanar or non-coplanar geometries. The nominal prescribed dose should reflect the isodose that encompasses the PTV (or 95% of the PTV) with hotspots within the PTV. Immobilization of the liver using controlled breath holds, shallow breathing, abdominal compression and gating of the RT (radiation therapy) beam during specified phases of the respiratory cycle, medications and tumour tracking of implanted fiducial markers may help reduce the adverse effects of breathing motion. Image-guided RT (IGRT) based on orthogonal imaging, ultrasound or volumetric imaging such as MV or kV cone beam CT, is required at every fraction in order to reduce PTV margins for setup uncertainty. MR IGRT is an area of active research that may benefit patients requiring liver SBRT. Advantages of SBRT include increased convenience for patients. Furthermore, there are preclinical data demonstrating dose-per-fraction effects (e.g. endothelial and immune effects), with a threshold of approximately 8 Gray (Gy). Clinical experience in SBRT for liver metastases is rapidly increasing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".