Late gadolinium enhancement of colorectal liver metastases post-chemotherapy is associated with tumour fibrosis and overall survival post-hepatectomy
Bibliographic record
Abstract
PURPOSE: To determine whether late gadolinium MRI enhancement of colorectal liver metastases (CRCLM) post-chemotherapy is associated with tumour fibrosis and survival post-hepatectomy. MATERIALS AND METHODS: The institutional review board approved this retrospective cohort study and waived the requirement for informed consent. A cohort of 121 surgical patients who received preoperative MRI after chemotherapy between 2006-2012 was included in this study. Target tumour enhancement (TTE), defined as the mean contrast-to-noise ratio of up to two target lesions on late-phase gadobutrol-enhanced MRI, was determined by two independent raters. The average TTE was correlated with tumour fibrosis on post-hepatectomy specimens using Spearman correlation and with survival post-hepatectomy using Kaplan-Meier and Cox regression. Inter-rater reliability was determined using relative intra-class correlation coefficients. RESULTS: In the surgical cohort (mean age: 63.0 years; male: 58%), TTE was associated with tumour fibrosis (r = 0.43, p < 0.001). Strong TTE was associated with improved survival compared to weak TTE (3-year survival: 88.4% vs. 58.8%, p = 0.003) with a hazard ratio of 0.32 (95% CI: 0.14-0.75, p = 0.008), after taking into account known prognostic variables. Inter-rater reliability was very good with a relative intraclass correlation of 0.84 (95% CI: 0.77-0.89). CONCLUSION: Late gadolinium MRI enhancement of CRCLM post-chemotherapy is associated with tumour fibrosis and survival. KEY POINTS: • MRI enhancement of colorectal liver metastases is associated with survival post-hepatectomy • MRI enhancement of chemotherapy-treated colorectal liver metastases correlates with tumour fibrosis • Measuring late MRI enhancement using target tumour enhancement is reliable.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 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".