Comparison of qualitative and quantitative measurements on unenhanced T1‐weighted fat saturation MR images in predicting pancreatic pathology
Bibliographic record
Abstract
PURPOSE: To evaluate the accuracy of signal intensity (SI) analysis on unenhanced fat-suppressed T1-weighted MR images in the diagnosis of pancreatic disease and to compare subjective interpretation with different quantitative measurements. MATERIALS AND METHODS: The pancreas was evaluated in 159 patients (86 normal and 73 with pancreatic disease) with spoiled gradient echo (GRE) T1-weighted fat saturation MR images. The relative SI of the pancreas to liver and spleen was quantitatively measured using regions of interest (ROIs) and qualitatively assessed by two independent observers. RESULTS: The mean values between a normal and an abnormal pancreas with pancreas-liver ratios of 0.14 +/- 0.37 vs. -0.32 +/- 0.24, respectively, and pancreas-spleen ratios of 0.89 +/- 0.55 vs. 0.02 +/- 0.43, respectively, were significantly different (P < 0.001). The pancreas-liver SI ratio was significantly better than the pancreas-spleen ratio throughout the disease group (area under the receiver operating characteristic (ROC) curve +/- SD; 0.92 +/- 0.02 for pancreas-liver vs. 0.86 +/- 0.03 for pancreas-spleen, P < 0.01), and after excluding cases of acute pancreatitis (0.96 +/- 0.02 for pancreas-liver vs. 0.89 +/- 0.03 for pancreas-spleen, P < 0.01). There was no statistically significant difference between quantitative and qualitative analysis (area under the ROC curve +/- SD; 0.93 +/- 0.02 vs. 0.93 +/- 0.02 for the entire disease group; excluding acute pancreatitis 0.96 +/- 0.02 vs 0.97 +/- 0.02) for the diagnosis of pancreatic disease when using liver as internal standard. The interobserver concordance was very good (kappa > 0.71). The sensitivity of visual liver comparison was 80% in the entire disease group and 91% after the cases of acute pancreatitis were excluded, while specificity was 93%. CONCLUSION: The pancreas-liver ratio is the best quantitative means of distinguishing normal from abnormal pancreas. Visual observation by experienced observers (qualitative measurement) was just as accurate as quantitative measurement. Detection of pancreatic pathology can be made with high accuracy by visually comparing the SI of the pancreas with that of the normal liver.
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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 | 0.000 | 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) | 0.000 | 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".