Parenchymal sparing liver resection for cytoreduction of neuroendocrine tumors metastases
Bibliographic record
Abstract
BackgroundDue to unique indolent biology, neuroendocrine tumours (NETs) can be managed for many years with prolonged survival. Goals of NETs therapy differ from other more common solid malignancies. Cytoreductive surgery plays an important role in the multidisciplinary management of NETs. It offers an opportunity to reduce both tumor burden and hormonal load to improve symptom-free survival and quality of life, and spare systemic therapy options. Parenchyma-sparing liver cytoreduction is recommended technique to preserve liver parenchyma for future treatments upon progression or recurrence.MethodsThis video reviews parenchyma-sparing cytoreductive surgery for NETs liver metastases. Approaches and techniques, and their rationale are reviewed.ResultsWe focus on the management of hepatic metastases in well differentiated low grade intestinal neuroendocrine neoplasm (or NET). The video reviews the steps of parenchyma-sparing liver metastases with enucleation for NETs. Considering the goal for cytoreduction for an indolent disease, wide margins are not aimed for. We highlight the technical aspects of enucleations to avoid anatomical resection and preserve parenchyma, which is critical in minimizing morbidity and optimizing long-term sequencing of therapies for a chronic malignancy.ConclusionWe herein illustrate the steps and rationale for hepatic parenchyma-sparing cytoreduction for metastatic NETs. This approach can lead to significant tumoral and hormonal control, with favorable long-term outcomes. Parenchyma-sparing resection should be used over anatomical resection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".