Does Tumour Contrast Retention on CT Immediately Post Chemoembolization Predict Tumour Metabolic Response on FDG-PET in Patients with Hepatic Metastases from Colorectal Cancer?
Bibliographic record
Abstract
Purpose . The exact mechanism of action of chemoembolization with drug eluting beads loaded with irinotecan (DEBIRI) in colorectal cancer is undetermined. Posttreatment tumour contrast retention often seen on CT immediately post procedure is of indeterminate significance. This study is aimed at assessing if metabolic response on PET-CT can be related to posttreatment tumour contrast retention. Materials and Methods . In this retrospective study, a total of 17 patients with a total of 55 marker lesions were recruited. Results . The area of tumour contrast retention can be matched to a hypometabolic area on subsequent PET-CT in over 36 lesions (65.5%). Out of the 55 lesions, a total of 38 marker lesions in 11 patients who also had pre-DEBIRI PET-CT were analyzed for disease response. 10 out of 10 lesions that had a complete response on PET-CT were found to demonstrate contrast retention throughout the tumour. 12 out of 13 (92.3%) tumours that had a partial metabolic response on PET-CT were found to demonstrate contrast uptake in the hypometabolic area only. In the 15 lesions that had progression/no response, 13 (86.6%) demonstrated no relationship between tumour contrast retention and tumour response. There was a significant correlation between contrast retention and disease response (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.001</mml:mn></mml:math>). Conclusion . Our study showed that PET-CT response can be associated with post embolization contrast retention. The data suggests blood stasis, for which tumour contrast retention is a surrogate marker, is important for the PET-CT metabolic response. The authors propose that tumour contrast retention is an important embolization endpoint in DEBIRI.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".