Correlations Between MRI Biomarkers PDFF and cT1 With Histopathological Features of Non-Alcoholic Steatohepatitis
Bibliographic record
Abstract
Introduction Late stage clinical trials in non-alcoholic steatohepatitis (NASH) are currently required by the FDA to use liver biopsy as a primary endpoint. The well-reported limitations with biopsy, such as associated risks and sampling error, coupled with patient preference, are driving investigation into non-invasive alternatives. MRI-derived biomarkers proton density fat fraction (PDFF) and iron-corrected T1 mapping (cT1) are gaining traction as emerging alternatives to biopsy for NASH. Our aim was to explore the correlations between cT1 and PDFF (from Liver MultiScan ®), with the histological components on the NAFLD-NASH spectrum in a large cohort of cross-sectional data, in order to calibrate the measurement to histology, and to infer what might constitute a clinically meaningful change when related to the FDA’s criteria. Materials and Methods In a retrospective analysis of data combined from three previously published observational NASH studies, in which adult participants who underwent liver biopsy on suspicion of NAFLD or NASH and had an MRI scan measuring cT1 and PDFF (Liver MultiScan ®, Perspectum Ltd, UK), associations between imaging biomarkers and histology were tested using Spearman’s rank correlation coefficient (r s ), and further exploration of the relationships between the imaging variables and histology were performed using linear regression. Results N = 264 patients with mean age of 54 (SD:9.9), 39% female, and 69% with BMI ≥ 30kg.m −2 were included in the analysis. cT1 and PDFF both correlated with all features of the NAFLD activity score (NAS). cT1 was also positively correlated with Kleiner-Brunt fibrosis. Partial correlations, adjusting for steatosis, revealed cT1 correlated with inflammation and fibrosis, whereas PDFF did not, and both were still associated with the NAS, but correlation was weaker with PDFF than cT1. An estimated difference of 88 ms in cT1, or 21% relative difference in PDFF was related to a two-point difference in overall NAS. Conclusion The correlations between cT1 and PDFF with the histopathological hallmarks of NASH demonstrate the potential utility of both cT1 and PDFF as non-invasive biomarkers to detect a pharmacodynamic change in NASH, with cT1 showing superiority for detecting changes in inflammation and fibrosis, rather than liver fat alone.
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) | 0.000 | 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) | 0.000 | 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".