Functional colonography of <i>Min</i> mice using dark lumen dynamic contrast‐enhanced MRI
Bibliographic record
Abstract
Dark lumen MRI colonography detects colonic polyps by minimization of the intestinal lumen signal intensity. Here we validate the use of perfluorinated oil as an intestinal-filling agent for dark lumen MRI studies in mice, enabling the physiological characterization of colonic polyps by dynamic contrast-enhanced MRI. In control and Min (multiple intestinal neoplasia) mice with and without pretreatment with oral dextran sodium sulfate (DSS), polyps as small as 0.94 mm diameter were consistently identified using standard 2D gradient echo imaging (voxel size, 0.23 x 0.16 x 0.5 mm). In serial studies, polyp growth rates were heterogeneous with an average approximately 5% increase in polyp volume per day. In DSS-treated control mice the colon wall contrast agent extravasation rate constant, K(trans), and extravascular extracellular space volume fraction, v(e), values were measured for the first time and found to be 0.10 +/- 0.03 min(-1) and 0.23 +/- 0.09, respectively. In DSS-treated Min mice, polyp K(trans) values (0.09 +/- 0.04 min(-1)) were similar to those in the colon wall but the v(e) values were substantially lower (0.16 +/- 0.03), suggesting increased cellular density. The functional dark-lumen colonography approach described herein provides new opportunities for the noninvasive assessment of gastrointestinal disease pathology and treatment response in mouse models.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".