Can negligible hepatic steatosis determined by magnetic resonance imaging–proton density fat fraction obviate the need for liver biopsy in potential liver donors?
Bibliographic record
Abstract
The purpose of this study is to determine whether magnetic resonance (MR)-proton density fat fraction (PDFF) estimate of negligible hepatic fat percentage (<5%) can exclude significant hepatic steatosis (≥10%) in living liver donor candidates obviating the need for liver biopsy and to perform intraindividual comparisons between MR-PDFF techniques for hepatic steatosis quantification. In an ethics-approved retrospective study, 144 liver donor candidates with magnetic resonance spectroscopy (MRS) and 6-echo Dixon magnetic resonance imaging (MRI) between 2013 and 2015 were included. A subset of 32 candidates underwent liver biopsy. Hepatic fat percentage was determined using MR-PDFF and histopathology-determined fat fraction as the reference standard. A receiver operating characteristic analysis with positive predictive value, negative predictive value (NPV), sensitivity, and specificity was performed to discriminate between clinically significant steatosis (≥10%) or not (<10%) at MRS-PDFF and MRI-PDFF thresholds of 5% and 10%. Pearson correlation and Bland-Altman analyses between MRS-PDFF and MRI-PDFF were performed for intraindividual comparison of hepatic steatosis estimation. There was significant association between MRS-PDFF and MRI-PDFF with HP-FP. High NPV of 95% (95% confidence interval [CI], 78%-99%) and 100% (95% CI, 76%-100%) as well as an area under the curve of 0.90 (95% CI, 0.79-1.0) and 0.93 (95% CI, 0.84-1.0) were obtained with a cutoff threshold of 5% MRI-PDFF and MRS-PDFF, respectively, to exclude clinically significant steatosis (≥10%). Intraindividual comparison between MRS-PDFF and MRI-PDFF showed a Pearson correlation coefficient of 0.83. Bland-Altman analysis showed a mean difference of 1% with 95% limits of agreement between -1% and 3%. MR-PDFF estimate of negligible hepatic fat percentage (<5%) has sufficient NPV for excluding clinically significant hepatic steatosis (≥10%) in living liver donor candidates obviating the need for liver biopsy. It may be sufficient to acquire only the multiecho Dixon MRI-PDFF for hepatic steatosis estimation. Liver Transplantation 24 470-477 2018 AASLD.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".