Proposal for an Objective and Concrete Definition for Determining Anatomic Resectability in Pancreatic Cancer: The Concept of the “Suitable Target”
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma with extensive peripancreatic vessel involvement is classified as locally advanced pancreatic cancer (LAPC). For this group of patients, the current standard of care does not include considering a potentially curative oncologic resection. However, recent advances in multiagent chemotherapy and surgical techniques are challenging this paradigm. The current determination of anatomic resectability is vague and unreliable. Here, we propose a definition of local resectability based on pre- and intraoperative assessment. This anatomic definition of resectability assumes careful patient selection based on tumor biology and patient condition. The preoperative evaluation of vascular anatomy and tumor involvement is conducted using 3-dimensional rendering of the pancreas protocol CT. Identifying a disease-free arterial or venous segment above and below the tumor ("suitable target") is the single critical factor determining anatomic resectability. Intraoperative isolation of these target vessels confirms the feasibility of vascular reconstruction before resection. This approach, which focuses on identifying target vessels rather than circumferential involvement, offers a more straightforward and clinically relevant method for assessing surgical eligibility in patients with LAPC at centers of excellence. In summary, reconstructability-based on surgical expertise and guided by tumor biology-now defines the modern paradigm of resectability in LAPC.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".