Local tumor progression patterns after radiofrequency ablation of colorectal cancer liver metastases
Bibliographic record
Abstract
PURPOSE: We aimed to evaluate patterns of local tumor progression (LTP) after radiofrequency ablation (RF ablation) of colorectal cancer liver metastases (CRCLM) and to highlight the percentage of LTP not attributable to lesion size or RF ablation procedure-related factors (heat sink or insufficient ablation margin). METHODS: CRCLM treated by RF ablation at a single tertiary care center from 2004-2012, with a minimum of six months of postprocedure follow-up, were included in this retrospective study. LTP morphology was classified as focal nodular (<90° of ablation margin), circumferential (>270°), or crescentic (90°-270°). Initial metastasis size, minimum ablation margin size, morphology of LTP, presence of a heat sink, and time to progression were recorded independently by two radiologists. RESULTS: Thirty-two of 127 RF ablation treated metastases (25%) with a mean size of 23 mm (standard deviation 12 mm) exhibited LTP. Fifteen of 32 LTPs (47%) were classified as focal nodular, with seven having no procedure-related factor to explain recurrence. Ten of 32 LTPs (31%) were circumferential, with four having no procedure-related factor to explain recurrence. Seven of 32 LTPs (22%) were crescentic, with two having no procedure-related factor to explain recurrence. Of the 13 lesions without any obvious procedure-related reason for LTP, six (46%) were <3 cm in size. CONCLUSION: Although LTP in RF ablation treated CRCLM can often be explained by procedure-related factors or size of the lesion, in this study up to six (5%) of the CRCLM we treated showed LTP without any reasonable cause.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".