Quantitative Ultrasound and the Pancreas: Demonstration of Early Detection Capability
Bibliographic record
Abstract
OBJECTIVES: To show that quantitative ultrasound biomarkers attenuation (AC) and backscatter (BSC) coefficients are effective tools to detect early changes in acute pancreatitis, using a cerulein-induced pancreatitis rat model. METHODS: Sprague-Dawley rats (n = 68) were divided into 8 groups: uninjected cage controls, saline-injected controls, and cerulein-injected rats euthanized at 2, 4, 15, 24, 48, and 60 hours after injection. Pancreatic AC and BSC (25-55 MHz) were estimated in vivo (Vevo 2100, VisualSonics, Toronto, CA) and ex vivo (40-MHz transducer). The pancreas of each rat was evaluated histopathologically. RESULTS: Changes in both in vivo and ex vivo AC and BSC relative to controls reflected temporal histomorphologic changes. Overall, there were decreased AC and BSC at early time points and then rebound toward control values over time. Maximal in vivo AC and BSC decreases occurred at 2 hours after cerulein injection. Attenuation coefficient changes corresponded well with early pancreatic edema and acinar cell vacuolation, with rebound as edema decreased, autophagy/cellular death occurred, and histiocytic infiltrates and fibrosis manifested. Backscatter coefficient decreased early but rebounded as autophagy and apoptosis increased, only to fall as acinar atrophy peaked, and fibrosis and histiocytic infiltration increased. CONCLUSIONS: Cerulein-induced pancreatitis is an excellent model for studying ultrasonic AC and BSC biomarkers during the early stages of acute pancreatitits, reflecting microscopic structural changes. Edema followed by cell shrinkage and apoptosis, then histiocytic infiltration and fibrosis, has certain similarities with the morphologies of some forms of pancreatic carcinoma. This suggests that quantitative ultrasound may be very useful for early detection of disease onset or response to therapy for not only acute pancreatitis but also pancreatic cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".