MRI biomarkers of liver disease are robust and reproducible alternatives to liver biopsy. Emerging data suggest that absolute reduction in iron corrected T1 (cT1) of ≥ 80 ms and relative reduction in liver fat content of 30% reflect histological improvement. We aimed to validate the associations of changes to these noninvasive biomarkers with histological improvement, specifically the resolution of steatohepatitis. A retrospective analysis of participants from three interventional clinical trials who underwent multiparametric MRI to measure liver cT1 and liver fat content (LFC) (LiverMultiScan) alongside biopsies at baseline and end of study. Responders were defined as those achieving resolution of steatohepatitis with no worsening in fibrosis. Differences in the magnitude of change in cT1 and LFC between responders and non-responders was assessed. Individual patient data from 150 participants were included. There was a significant decrease in liver cT1 (-119 ms vs. -49 ms) and liver fat content (-65% vs. -29%) in responders compared to non-responders (P < .001) respectively. The diagnostic accuracy to identify responders was 0.72 (AUC) for both. The Youden's index for cT1 to separate responders from non-responders was -82 ms and for liver fat was a 58% relative reduction. Those achieving a ≥ 80 ms reduction in cT1 were 5-times more likely to achieve histological response (sens 0.68; spec 0.70). Those achieving a 30% relative reduction in liver fat were ∼4 times more likely to achieve a histological response (sens 0.77; spec 0.53). These results, from three combined drug trials, demonstrate that changes in multiparametric MRI markers of liver health (cT1 and PDFF) can predict histological response for steatohepatitis following therapeutic intervention. There is great interest in identifying suitable biomarkers that can be used to replace liver biopsy, or to identify those patients who would benefit from one, in both the clinical management of MASH and in drug development. We investigated the utility of two MRI-derived non-invasive tests, iron corrected T1 mapping (cT1) and liver fat content from proton density fat fraction (PDFF), to predict histological improvement in patients who had undergone experimental treatment for MASH. Using data from 150 people who participated in one of three clinical trials, we observed that a reduction in cT1 by over 80 ms and a relative reduction in PDFF of over 58% were the optimal thresholds for change that predicted resolution of steatohepatitis. PDFF as a marker of liver fat, and cT1 as a specific measure of liver disease activity, are both effective at identifying those who are likely responding to drug interventions and experiencing improvements in overall liver health. NCT02443116, NCT03976401, NCT03551522.

Background: Serum liver tests (serum tests) and histological assessment for T-cell mediated (TcM) rejection are essential for post-liver transplant monitoring. Liver biopsy carries risk of complications which are preferably avoided in low-risk patients. Multiparametric MRI (mpMRI) is a reliable non-invasive diagnostic method which quantifies liver disease activity and has prognostic utility. Our aim was to determine whether using mpMRI in combination with serum tests could noninvasively identify low-risk post-liver transplant patients who are eligible to avoid invasive liver biopsies. Methods: In a multicentre prospective study (RADIcAL2), including 131 adult and paediatric (children and adolescent) patients with previous liver transplant from the Netherlands, Portugal, and UK, concomitant mpMRI and liver biopsies were performed. Biopsies were centrally read by two expert pathologists. TcM rejection was assessed using BANFF global assessment (BANFF-GA). Diagnostic accuracy to discriminate no rejection vs. indeterminate or TcM liver transplant rejection was performed using area under the receiver operating characteristic curve (AUC). Results: In this study, 52% of patients received a routine (protocol) biopsy whilst 48% had a biopsy for suspicion of pathology. 38% of patients had no rejection, while 62% had either indeterminate (21%) or TcM rejection (41%). However, there was a high inter-observer variability (0<Cohen’s Kappa<0.85) across all histology scores. The combined score of mpMRI and serum tests had AUC 0.7 (NPV: 0.8) to identify those without either indeterminate or TcM rejection. Conclusion: Combining both imaging and serum biomarkers into a composite biomarker (imaging and serum biomarkers) has potential in monitoring the liver graft to effectively risk stratify patients and identify those most likely to benefit from a non-invasive diagnostic approach, reducing the need for liver biopsy. Export

Background: Multiparametric MRI markers of liver health corrected T1 (cT1) and proton density fat fraction (PDFF) have shown utility in the management of various chronic liver diseases. We assessed the normal population reference range of both cT1 and PDFF in healthy child and adult volunteers without any known liver disease. Methods: A retrospective multi-centre pooled analysis of 102 child and young adult (9.1 years (6–18)) volunteers from three centres: Children’s Memorial Health Institute (N = 21), University Hospital Southampton (N = 28) and Hospital Infantil de Mexico (N = 53). Sex and ethnic differences were investigated for both cT1 and PDFF. Age effects were investigated with comparison to a pooled adult cohort from the UK Biobank (N = 500) and CoverScan (N = 71), covering an age range of 21 to 81 years. Results: cT1 values were normally distributed with a median of 748 ms (IQR: 725–768 ms; 2.5–97.5 percentiles: 683–820 ms). PDFF values followed a normal distribution with a median of 1.7% (IQR: 1.3–1.9%; 2.5–97.5 percentiles: 1–4.4%). There were no significant age and sex differences in cT1 and PDFF between children and young adults. No differences in cT1 and PDFF were found between ethnicities. Age comparisons showed statistically significant, but clinically negligible, cT1 (748 ms vs. 732 ms) and PDFF (2.4% vs. 1.9%) differences between paediatric and adult groups, respectively. Conclusions: Median healthy cT1 and PDFF reference ranges in children and young adults fall within the reported limits for normal of 800 ms and 5%, respectively.

The US Food and Drug Administration (FDA) recently approved the first treatment for metabolic dysfunction-associated steatohepatitis (MASH), resmetirom, without clarifying the most effective strategy for diagnosing or monitoring response to therapy. Current standards-of-care (SoC) for Veterans Health Administration [VHA] and Medicare largely rely on vibration-controlled transient elastography (VCTE) and/or liver biopsy. Multiparametric MRI corrected T1 (cT1) is a cost-effective, noninvasive liver disease assessment (NILDA) tool in MASH. We evaluated the budgetary impact of pathways using cT1 versus SoC (liver biopsy or VCTE) to assign suspected MASH patients to resmetirom and for those assigned treatment, monitor response. A model of the VHA and Medicare populations was used to derive a budget impact model comparing cT1, VCTE and liver biopsy. Clinical and cost data were taken from publicly available sources and used to estimate the number of patients prescribed resmetirom, the identification of those benefiting from therapy, the budgetary impact of each diagnosis and monitoring strategy and the cost of medication prescribed. For the VHA, cT1 resulted in the lowest per-patient costs (cT1: $7,022 vs liver biopsy: $7,268 vs VCTE: $28,509). cT1 was ∼4% less expensive than liver biopsy ($7,168 vs $7,085). This was consistent across scenario analyses. In the Medicare population, cT1 resulted in the lowest per-patient costs ($11,866 (cT1) vs $15,488 (biopsy) vs $27,539 (VCTE)), and this was maintained across scenario analyses. The use of cT1 to assign and monitor resmetirom treatment improves treatment allocation and reduces health system cost vs VCTE and liver biopsy.

Background & Aims: Annotation of liver biopsies, for disease staging is increasingly aided by digital pathology, however existing systems do not quantify inflammation and steatosis within an anatomical framework. We developed an AI system to quantify portal tracts (PT) and disease features and their regional distribution in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)/Metabolic Dysfunction-Associated Steatohepatitis (MASH) and Autoimmune Hepatitis (AIH). Methods: Digitised images of haematoxylin and eosin-stained specimens were pooled from 4 clinical cohorts (n=390: 89 MASLD, 238 MASH, 63 AIH). Portal tracts, regional steatosis, interface hepatitis, portal and lobular inflammation were quantified using a proprietary AI system and scored by expert pathologists. Results: The percentage of steatosis was higher in MASH (7.5%) compared to MASLD (3.2%, p<0.0001). Lobular regions had larger steatotic vesicles (260 vs 190mm ² , p<0.0001). AI-derived steatosis quantification correlated with manual grading (r _s =0.72; p<0.0001). The inflammatory cell number (ICN) was 2-fold higher in AIH compared to MASLD/MASH in interface [390 vs 140; p<0.0001], portal [4600 vs 1500], and lobular [1500 vs 650] regions. Severity of portal inflammation from manual grading correlated well with ICN count at PT (r _s =0.71; p<0.0001) but not lobular regions (r _s =<0.1). For equivalent grades of portal inflammation, the ICN was up to 3-fold higher in AIH than in MASLD/MASH (r _s =0.71; p<0.0001). Conclusion: Despite equivalent pathologist portal inflammation grades, the digital burden of inflammation was significantly higher in AIH than MASLD/MASH. This digital system quantifies PT, inflammation, and steatosis, providing powerful decision support for pathologists in AIH diagnosis and MASH staging. LAY SUMMARY: The detection of portal tracts is an important part of liver biopsy sample quality control and histological scoring. Using artificial intelligence, this study demonstrates a system that automatically detects and quantifies portal tracts and surrounding patterns of inflammation and steatosis. AI found that inflammation was in similar regions but was higher in autoimmune hepatitis than in metabolic dysfunction-associated steatohepatitis, despite similar grading from manual scoring. This AI system provides granular information that can aid biopsy grading and provide insights into liver disease progression and diagnosis.