<i>In vivo</i><sup>1</sup>H MRS of human gallbladder bile at 3 T in one and two dimensions: detection and quantification of major biliary lipids
Bibliographic record
Abstract
In vitro (1)H MRS of human bile has shown potential in the diagnosis of various hepatopancreatobiliary (HPB) diseases. Previously, in vivo (1)H MRS of human bile in gallbladder using a 1.5 T scanner demonstrated the possibility of quantification of choline-containing phospholipids (chol-PLs). However, other lipid components such as bile acids play an important role in the pathophysiology of the HPB system. We have employed a higher magnetic field strength (3 T), and a custom-built receive array coil, to improve the quality of in vivo (1)H MRS of human bile in the gallbladder. We obtained significant improvement in the quality of 1D spectra (17 healthy volunteers) using a respiratory-gated PRESS sequence with well distinguished signals for total bile acids (TBAs) plus cholesterol resonating at 0.66 ppm, taurine-conjugated bile acids (TCBAs) at 3.08 ppm, chol-PLs at 3.22 ppm, glycine-conjugated bile acids (GCBAs) at 3.74 ppm, and the amide proton (-NH) arising from GCBAs and TCBAs in the region 7.76-8.05 ppm. The peak areas of these signals were measured by deconvolution, and subsequently the molar concentrations of metabolites were estimated with good accuracy, except for that of TBAs plus cholesterol. The concentration of TBAs plus cholesterol was overestimated in some cases, which could be due to lipid contamination. In addition, we report the first 2D L-COSY spectra of human gallbladder bile in vivo (obtained in 15 healthy volunteers). 2D L-COSY spectra will be helpful in differentiating various biliary chol-PLs in pathological conditions of the HPB system.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".