MRI cine‐tagging of cardiac‐induced motion for noninvasive staging of liver fibrosis
Bibliographic record
Abstract
BACKGROUND: MR elastography is a noninvasive technique that provides high diagnostic accuracy for the staging of liver fibrosis; however, it requires external hardware and mainly assesses the right lobe. PURPOSE: To evaluate the diagnostic performance of MRI cine-tagging for staging fibrosis in the left liver lobe, using biopsy as the reference standard. STUDY TYPE: Institutional Review Board (IRB)-approved two-center prospective study. POPULATION: Seventy-six patients with chronic liver disease who underwent an MRI cine-tagging examination and a liver biopsy within a 6-week interval. FIELD STRENGTH/SEQUENCE: 2D-GRE multislice sequence at 3.0T with spatial modulation of the magnetization preparation sequence and peripheral pulse-wave triggering on two coronal slices chosen underneath the heart apex to capture maximal deformation with consecutive breath-holds adapted to patient cardiac frequency. ASSESSMENT: A region of interest was selected in the liver close to the heart apex. Maximal strain was evaluated with the harmonic phase (HARP) technique. STATISTICAL TESTS: Spearman's correlation, Kruskal-Wallis test, Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were performed. RESULTS: Liver strain measured on tagged images decreased with higher histological fibrosis stage (ρ = -0.68, P < 0.0001). Strain values were significantly different between all fibrosis stages (P < 0.0001), and between groups of fibrosis stages ≤F3 vs. F4 (P < 0.05). Areas under the ROC curves were 0.95 (95% confidence interval: 0.89-1.00) to distinguish fibrosis stages F0 vs. F4, 0.81 (0.70-0.92) for stages F0 vs. ≥F1, 0.84 (0.76-0.93) for stages ≤F1 vs. ≥F2, 0.86 (0.78-0.94) for stages ≤F2 vs. ≥F3, and 0.87 (0.77-0.96) for stages ≤F3 vs. F4. DATA CONCLUSION: MRI cine-tagging is a promising technique for measuring liver strain without additional elastography hardware. It could be used to assess the left liver lobe as a complement to current techniques assessing the right lobe. LEVEL OF EVIDENCE: 1 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;51:1570-1580.
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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 | 0.001 | 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 | 0.000 | 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 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".