Usefulness of MRI T1 Mapping in Predicting Postoperative Pancreatic Fistula After Distal Pancreatectomy
Bibliographic record
Abstract
OBJECTIVES: Postoperative pancreatic fistula (POPF) is the most significant and potentially lethal complication of pancreatectomy. This study evaluated the association between MRI pancreatic T1 mapping and POPF and developed a new, useful, and noninvasive predictor of distal pancreatectomy (DP). METHODS: The study included 39 patients who underwent preoperative MRI T1 mapping using the Modified Look-Locker Inversion Recovery Sequence (MOLLI) followed by DP between January 2018 and July 2024. Patients with [POPF (+), n=15] and those without POPF [POPF (-), n=24] were compared for their characteristics, perioperative outcomes, and parameters derived from MRI. The circular region of interest was positioned on the pancreatic head, ventral side of the portal vein, and transection site to measure the T1 mapping value. The data were analyzed using R1 values (R1=1/T1), and the cutoff values were calculated using the receiver operating characteristic (ROC) curve. RESULTS: The R1 value of the pancreatic transection site in the POPF (+) group was significantly higher than that in the POPF (-) group (1.180 vs. 1.066 s - 1 ; P <0.001). The R1 value of the pancreatic transection site was an independent risk factor for grade B/C POPF (odds ratio, 5.01; P =0.005). To predict POPF, a cutoff R1 value of 1.116 s -1 at the transection site was obtained by maximizing the Youden index. CONCLUSIONS: High R1 values at the pancreatic transection site indicate a higher possibility of developing grade B/C POPF. Preoperative MRI T1 mapping may be valuable for predicting POPF after DP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".