Early diagnosis of liver graft steatosis and fibrosis: are non-invasive tests the answer?

Introduction

Survival rates of liver transplant recipients have risen over the last decades (1). New concerns in terms of managing post-transplant and immunosuppressive complications and avoiding graft loss are challenging the transplantation teams worldwide.

With increasing prevalence of obesity and metabolic syndrome worldwide and specifically post liver transplantation (LT), detection and quantification of new-onset graft steatosis is becoming a new subject of investigation. Evolution and outcome of this condition seem to be different from recurrent metabolic dysfunction-associated steatotic liver disease (MASLD), with reduced cardiovascular and metabolic complications and mortality (2). Several risk factors influence the occurrence of MASLD after LT, including donor genetic (3-5), environmental (rapid weight gain after LT, alcohol abuse) (6,7), and immunosuppressive therapy, including steroids and calcineurin inhibitors (8).

Fibrosis is one of the main forms of graft injury and emerges much earlier than altered liver function tests. A correlation between chronic inflammation and fibrosis development has been established (9). Multiple triggers have been identified including recurrence of the primary disease, viral diseases, idiopathic post-transplantation hepatitis (10,11), immunomodulatory mechanisms, biliary and vascular post-surgical complications, graft particularities (age of donor, partial graft transplantation) (12), and even dysbiosis (13). Timely detection and good assessment of fibrosis are essential steps forward to a better management of graft and recipient.

Liver biopsy (LB) is the gold standard for histological evaluation after LT (14). The histological analysis of LB offers a comprehensive picture, largely exceeding the sole quantitation of fibrosis and steatosis, which includes assessment of inflammation, rejection, biliary changes, and vascular alterations. However, LB is fraught with procedural risks that include serious post-punction complications, important discomfort for the patient, hospitalisation costs. Additionally, the quality of reports depends on specimen size and inter-observer variations (14). The role of LB in the follow-up of the graft is evolving with the emergence of non-invasive tests, including patented and non-patented fibrosis scores, transient elastography (TE) and other imaging techniques (acoustic radiation force impulse, shear wave elastography and magnetic resonance elastography). However, no recommendation of non-invasive methods is currently available concerning the usefulness of these assessment methods after LT (15). Only a few studies about the role of TE in the screening and the diagnosis of fibrosis recurrence after LT have been published, the majority being retrospective. Evidence is even weaker for the non-invasive evaluation of steatosis after LT.

The aims of our study are to ascertain factors associated with graft fibrosis and graft steatosis, to determine if TE is correlated to histological scores and to evaluate the accuracy of TE in predicting steatosis and fibrosis grade in the post-LT period. We present this article in accordance with the STARD reporting checklist (available at https://tgh.amegroups.com/article/view/10.21037/tgh-24-131/rc).

Methods

Study design

This prospective analysis was performed on a monocentric cohort including all consecutive liver transplant recipients admitted in the Department of Abdominal Surgery and Transplantation of the University Hospital Saint-Luc, Brussels, Belgium, from February 2021 to September 2022, who underwent per-protocol LB. Patients with history of heart failure (16) and unresolved biliary complications were excluded. In our institution, per-protocol LBs are scheduled 6 months, 1 year, and every 5 years after LT. This study was performed according to the Good Clinical Practice recommendations and the Helsinki Declaration and its subsequent amendments, and was approved by the Ethical Committee of the University Hospital Saint-Luc (EC No. 2021/07JUI/265). All patients signed an informed consent form prior to enrollment into the study.

We recorded all demographic and transplant-related data, including etiology of the native liver disease, its severity according to the Child-Pugh Classification and Model for End-Stage Liver Disease (MELD) (17) at the time of LT, recipient and donor characteristics [ABO blood group, gender, age and body mass index (BMI)], graft and surgical features, post-LT complications, and relevant comorbidities (cardiovascular diseases, renal impairment, concomitant kidney transplantation, active alcohol use and neoplasia). A panel of laboratory parameters were also documented.

Liver biopsy

Liver sampling was obtained either by percutaneous or transvenous biopsy depending on the risks of bleeding. LB specimens with a minimum of five complete portal tracts were considered suitable for inclusion. Each histological sample was evaluated by one of our two trained liver-expert pathologists, who were blinded to TE results.

Our pathologists classified histological fibrosis according to both the Metavir score (18) and the liver allograft fibrosis semiquantitative scoring system (LAFSc or Venturi score) (19). Steatosis was classified in three categories (S0 <3%, S1 =3–33%, S2 >33%). Other histological modifications including acute and chronic T-cell-mediated rejection portal tract inflammatory cells infiltration, sinusoidal dilatation, de novo autoimmune hepatitis and steatohepatitis were reported.

TE

Controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) were assessed in each patients using Fibroscan^® (Echosens^®, Paris, France), with an adult M probe or an XL probe (following device recommendation). One out of three independent investigators performed the said measurements a few hours before LB during all the inclusion time. The probe was placed in the standard position (patient laid on the back, positioned in a right intercostal space on the anterior axillary line). An ultrasound probe was used in case of unusual anatomy of the graft. Ten validated measurements were performed in each patient. The mean CAP was indicated in decibel per meter (dB/m). The median LSM was indicated in kilopascal (kPa). Interquartile range (IQR) had to be <30% to validate the measurements (20).

Statistical analysis

Data were processed using the software packages SPSS version 29 (SPSS Inc., Chicago, IL, USA). Numerical variables were expressed as mean ± standard deviation (SD). We tested for differences in categorical variables using Fisher’s exact test or χ² test, and in continuous variables using the Mann-Whitney U test, Kruskal-Wallis test, or logistic regression were used. Spearman’s rank correlation coefficient was used to assess the relationship between quantitated histological scores and non-invasive methods. To assess the performance of the TE measurement in identifying significant fibrosis and steatosis, the receiver operating characteristic (ROC) curves were conducted and the area under the curve (AUC) along with 95% confidence intervals (CIs) were calculated. The null hypothesis of AUC =0.5 was tested. The cut-off value was set to obtain a minimal specificity of 0.80. The probability level of P<0.05 was considered for statistical significance.

Results

Out of the 173 patients hospitalized for per-protocol LB during the inclusion period, 15 patients were excluded: 10 due to lack of LT history data, 1 due to heart failure, and 4 due to unreliable LSM (<10 valid results or IQR/median >30%). Finally, 158 patients were considered for subsequent analysis. No side effect of TE was noticed. One patient suffered from liver hematoma after LB and needed a hospital readmission a few days after discharge. One hundred and thirty-two liver biopsies with adequate number of portal tracts were included in the uni- and multivariate analyses, correlation, and accuracy analysis of non-invasive methods. Thus, 26 liver biopsies were ultimately excluded because the specimens contained fewer than 5 portal tracts.

Population characteristics

The overall population comprised 95 men (60.1%). The mean age at the time of protocolar LB was 59 years (SD, ±15 years). The first two major indications for LT were alcohol-related liver disease (19.6%) and liver congenital disorders (19.6%), including congenital biliary atresia, Alagille syndrome, familial intrahepatic cholestasis and metabolic disorders. The third most frequent indication was hepatitis C (7.6%). Hepatocellular carcinoma was detected in 38.0% of surgical specimens, including known and incidental cases. The mean time since transplantation was 5 years (SD, ±8.1 years). The mean current BMI was 24.68 kg/m² (SD, ±4.2 kg/m²). Diabetes mellitus (DM) was present in 29.7% of patients and arterial hypertension in 41.8%. Tacrolimus was used as a single immunosuppressive agent in 67.7% of cases. Specific data regarding donors and grafts were only recorded for the 140 patients who underwent LT as adults (over 16 years). The most frequent recipient blood group was A (49.3%) and we did not observe any ABO mismatch. Gender mismatch between recipient and donor was present in 42.9% of LT. The mean donor BMI was 24.69 kg/m² (SD, ±7.3 kg/m²). Grafts came from donors after brain death in 65.5% of cases. All the population characteristics are presented in Tables 1,2.

Factors associated with graft steatosis

Steatosis was present in 39.4% of the LB specimens (90.4% in up to one-third of the hepatocytes and 9.6% in one to two-thirds of the hepatocytes). Histological findings of steatohepatitis were present in 30.7%. Factors independently associated with the presence of histological steatosis in logistic regression were LT for metabolic dysfunction-associated steatohepatitis (MASH) [odds ratio (OR) 11.951, 95% confidence interval (CI): 1.251–114.609, P=0.03], current recipient BMI (OR 1.121, 95% CI: 1.101–1.257, P=0.04) and low-density lipoproteins-cholesterol (LDL-cholesterol) level (OR 1.016, 95% CI: 1.002–1.030, P=0.03). We found no correlation with donor BMI and the presence of DM. Details of the uni- and multivariate analyses are displayed in Table 3. Finally, we compared de novo steatosis and recurrence of MASLD. The group with recurrent MASLD included patients who underwent transplantation due to complications of MASLD. All these patients had a confirmed MASLD/MASH before LT, based on histological evidence from LB and/or liver explant. On the contrary, the de novo steatosis group consisted of patients who underwent a LT for complications of liver disease not related to MASLD, but subsequently developed steatosis during the post-LT follow-up period. In the 52 patients with significant steatosis, 44 were classified with de novo steatosis, and 8 were classified with recurrent MASLD. We did not find any significant difference between the groups regarding BMI, hypertension, age, LDL-cholesterol and triglyceride levels. The only statistically significant difference between the two groups was the higher prevalence of DM in the recurrent MASLD group (31.6% vs. 6.1%, P=0.04). Rates of significant fibrosis and steatohepatitis were not different in the two groups.

Factors associated with graft fibrosis

Through univariate analysis, the following factors were found to be associated with significant histological fibrosis (Metavir ≥ F2): LT for autoimmune liver disease (P=0.01), low serum LDL-cholesterol level (P=0.03) and low serum triglyceride level (P=0.01). Factors associated with significant histological fibrosis (LAFSc ≥4) were LT for auto-immune liver diseases (P=0.03), second LT (P=0.04), low serum LDL-cholesterol (P=0.04) and low serum triglyceride level (P=0.03). We also performed subgroup analysis for LAFSc. Concerning the portal tract (P), LT for auto-immunes diseases were associated with fibrosis development (15.7% with P-score =2 or 3 vs. 2.8% with P-score =1) (P=0.01). No association was demonstrated with sinusoidal tract (S). Fibrosis in the centrilobular tract (C-score) was associated with median time since LT (8 years in C-score =2–3 vs. 5 years in C-score =1) (P=0.02) and with history of previous LT (31.3% with C-score =2–3 vs. 9.2% with C-score =1) (P=0.02).

In the multivariate analysis, factors associated with significant fibrosis (Metavir ≥ F2) were LT for autoimmune liver diseases (OR 8.618, 95% CI: 1.546–47.939, P=0.01) and low serum triglyceride level (OR 0.989, 95% CI: 0.980–0.999, P=0.03). We did not identify any factors associated with significant fibrosis, defined as LAFSc ≥4, although autoimmune liver diseases showed a trend toward significance. We found no significant correlation between the presence of significant fibrosis and the subsequent variables assessed: recipient characteristics [age, positive cytomegalovirus polymerase chain reaction (CMV PCR)], graft quality (donor age, donor/recipient weight ratio, donor/recipient age ratio), surgery (graft type, prolonged ischemia time), and complications (biliary, vascular, infectious complications and rejection episodes). Details of the uni- and multivariate analyses are displayed in Table 4.

Performance of non-invasive techniques

Correlation between CAP (dB/m) and histologically graded steatosis was tested and we observed a better positive correlation (rho =0.37, 95% CI: 0.21–0.51, P<0.001; r²=0.13, P<0.001) (Figure 1). Regarding the assessment of graft fibrosis, we observed a weak positive correlation between Metavir score and TE (kPa) (rho =0.26, 95% CI: 0.09–0.42, P=0.01; r²=0.12, P<0.001), and between LAFSc and TE (kPa) (rho =0.29, 95% CI: 0.12–0.45, P<0.001; r²=0.10, P<0.001). We found no correlation between serum marker models [Fibrosis-4 Index for Liver Fibrosis (FIB-4) and Aspartate Aminotransferase to Platelet Ratio Index (APRI)] and Metavir score or LAFSc. Fibrosis correlation analyses are presented in Figure 2.

Figure 1 Spearman’s correlation between CAP and histological steatosis. CAP, controlled attenuation parameter.

Figure 2 Spearman’s correlations of non-invasive assessment techniques of graft fibrosis. APRI, Aspartate Aminotransferase to Platelet Ratio Index; FIB-4, Fibrosis-4 Index for Liver Fibrosis; LAFSc, the liver allograft fibrosis semiquantitative scoring system.

The distribution of the CAP and LSM for each steatosis and fibrosis grades are represented in the Figure 3. Using CAP, AUC were 0.872 (95% CI: 0.791–0.953, P=0.01) and 0.708 (95% CI: 0.614–0.801, P<0.001) for the diagnosis of graft steatosis ≥ S2 and ≥ S1, respectively. Using LSM, AUC were 0.588 (95% CI: 0.486–0.691, P=0.10) and 0.651 (95% CI: 0.480–0.822, P=0.10) for the diagnosis of graft fibrosis ≥ F2 and F3-F4, respectively. ROC curves and the AUC between each steatosis and fibrosis stage are illustrated in Figure 4. The optimal cut-off values for CAP were 246.5 dB/m for S1 and 275.5 dB/m for S2. The cut-offs for LSM were 7.65 for ≥ F2 and 9.25 for ≥ F3. Performance of CAP and LSM for the diagnostic of steatosis and fibrosis are resumed in Table 5. The performance of FIB-4 and APRI were poor in the diagnosis of significant fibrosis (≥ F2) with an AUC of 0.5 and 0.60, respectively.

Figure 3 Distribution of LSM and CAP. CAP, controlled attenuation parameter; LSM, liver stiffness measurement.

Figure 4 ROC curves and the AUC between each fibrosis and steatosis stage. (A) ROC curves and AUC between fibrosis stages F0-F1 and F2-F3-F4; (B) ROC curves and AUC between fibrosis stages F0-F1-F2 and F3-F4; (C) ROC curves and AUC between steatosis stages S0 and S1-S2; (D) ROC curves and AUC between steatosis stage S0-S1 and S2. AUC, area under the ROC curve; CAP, controlled attenuation parameter; ROC, receiver operating characteristic.

Discussion

Nowadays, LT yields remarkable long-term outcomes. Nevertheless, liver fibrosis persists as a prominent contributor to graft dysfunction (21). The improvement of the knowledge of its physiopathology, detection and assessment is needed.

With 132 graft biopsies, we present here one of the largest prospective cohort of histological post-LT specimens in an adult population. Della-Guardia et al. published in 2017 the results from a cohort of 276 post-LT biopsies, in predominantly hepatitis C virus (HCV) patients, with 46% of significant fibrosis (≥ F2) (22). To date, HCV cohorts have mainly been found in the literature (21,23). Our strength is the inclusion of a larger non-HCV population, in line with the current evolution of hepatology. The proportion of significant fibrosis we detected (32.6% of patients ≥ F2) was lower compared to other publications, while mean recipient age was comparable (24). Risk factors for fibrosis development after LT are poorly investigated. The pathophysiology of post-LT fibrosis has been studied mostly in pediatric transplant populations (9,25-27). LAFSc was created and validated to better assess graft fibrosis in a pediatric population. This scoring system was conceived to quantify and discriminate fibrosis in the three areas of the hepatic acinus: the portal tract, the sinusoids and the centrilobular veins. Venturi et al. (19) showed a better correlation between LAFSc and morphometric analysis of the allograft fibrosis, compared to Metavir or Ishak (28) scoring systems. The use of LAFSc, with its finer description of histological fibrosis, offers clinical translational potential and has given us insights into fibrosis risk factors even in our adult population.

Autoimmune liver diseases are correlated with histological graft fibrosis. Profound immunosuppression, including the use of multiple immunosuppressive drugs, is associated with less fibrosis occurrence. Koshiba et al. have already demonstrated that fibrosis develops more extensively in the grafts of immunotolerant patients compared to patients who are still under immunosuppressive therapy (29). This probably suggests the need for a careful follow-up of autoimmune diseases and patients with operational tolerance. Further correlations could be identified by increasing the population size and obtaining a higher rate of significant fibrosis. This also raises the question of the impact of auto- and allo-immune activity on the development of graft fibrosis. Low triglyceride levels have been linked to advanced fibrosis in other studies involving patients with MASH (30). However, it remains unclear whether this is a cause or a consequence of the progression to more advanced liver disease.

The rates of recurrence for both MASLD and MASH, as well as the rates of new-onset MASLD/MASH, vary significantly across different studies (7). The variability can be attributed to several factors, such as the retrospective nature of most of the studies, their single-centre design, and the absence of a universally applied post-LT biopsy regimen, standardized histological criteria, and consistent inclusion/exclusion criteria in these studies. Dumortier et al. published a series where the prevalence of histological steatosis was comparable to that of our cohort (31.10%) (6). Definition of histological steatosis, studied population (including age, comorbidities, BMI, immunosuppressive medications), and median delay between LT and LB were also similar to our study. However, the severity of steatosis was milder in our population. Based on our multivariate regression analysis, we found that obesity, LDL-cholesterol level and MASLD cirrhosis, as the primary indication for LT, are risk factors for the occurrence of post-LT steatosis. Vallin et al. showed different natural courses for new-onset or recurrent MASLD, with earlier and more rapid onset for recurrent MASLD and more frequent progression to MASH (31). We could not reach a similar conclusion, likely due to a small cohort concerning MASH and significant fibrosis, as well as because of a random inclusion follow-up after LT. The performance of a more extensive study, with long-term follow-up and biopsies at different time points after LT, might as well have added power to find similar evidence.

Because of the potential for severe complications and the high cost of the procedure needing in-hospital surveillance, there is a strong interest in exploring alternatives to LB for detection and follow-up of fibrosis and steatosis. In addition, per-protocol LB cannot be performed too frequently, as opposed to other non-invasive techniques. Studies examining serum markers to detect significant fibrosis after LT have primarily focused on two scores: APRI (AST/platelet ratio) and FIB-4 (based on age, AST, ALT, and platelet count) (21). We found AUC values similar to a recent meta-analysis, in which AUC ranged from 0.50 to 0.83, for APRI, and from 0.66 to 0.81, for FIB-4 (24). Important limitations hinder the utilisation of serum markers after LT. Evidences and cut-offs are lacking (15). Another significant concern is the impact of other post-LT factors on biological scores. Splenomegaly and thrombocytopenia may persist after LT, even if portal hypertension is resolved, and this can have a negative influence on the biological assessment of liver fibrosis (32). Based on the available literature, it seems that TE outperforms biological markers in the detection of fibrosis and the evaluation of its progression (21,24). Research on the post-LT period is limited. Most studies involve only a small number of patients and intend to evaluate the recurrence of HCV in recipients (33). On this score, we included a large and heterogeneous population of liver transplant recipients. We excluded all patients with biliary complications where effective drainage was not achieved. TE was feasible in 97.5% of our patients. Notably, in our study, TE failed to effectively differentiate between different stages of hepatic fibrosis when compared to the widely accepted gold standard LB. Various confounding factors may play a role in the estimation of fibrosis degree using TE, including diaphragm elevation, mismatch between the graft and the abdominal cavity, hepatic inflammation, and outflow obstruction (34).

To our knowledge, this is the second but largest study that prospectively and systematically assesses the performance of CAP in evaluating graft steatosis after LT in comparison with gold standard LB. The occurrence of steatosis after LT is soaring, and, therefore, non-invasive diagnostic and quantification methods are critically needed (35). Regarding ROC curves, CAP demonstrates an adequate performance in detecting steatosis from 3%. Additionally, the technique well discriminates between two grades of steatosis, suggesting that CAP could be a reliable semi-quantitative method for assessing steatosis. Cut-offs for the detection of S1 and S2, respectively of 246 dB/m and 276 dB/m are distinct. Other non-invasive techniques are employed to evaluate steatosis in the native liver. Abdominal ultrasound offers adequate sensitivity but lacks precision in providing quantitative information (36,37). Magnetic resonance imaging-proton density fat fraction (MRI-PDFF) showed excellent results in detecting steatosis, but is not accessible in daily practice and not yet described in post-LT (38). CAP presents the advantages of repeatability, cost-effectiveness, and ease of execution. It is essential to bear in mind the strong correlation between MASLD and other complications of the metabolic syndrome, including cardiovascular diseases, DM, and kidney dysfunction. CAP could become a tool to track graft metabolic dysfunction and to propose lifestyle interventions and follow their impact on the liver graft.

Our study suffers from some limitations that could potentially weaken the results. Firstly, we observed a large number of “healthy” grafts, showing either no or very mild fibrosis. Secondly, there was a lack of standardization in the interpretation of LB by different pathologists, particularly in the interpretation of the degree of inflammation and sinusoidal congestion. Thirdly, another weakness of our study is the use of LB at different post-LT times. Additionally, there might have been inter-observer variability in estimating fibrosis on the LB. Lastly, the involvement of multiple investigators in performing TE can have affected the quality of the results despite standardization.

Conclusions

In conclusion, the effective management of post-LT complications, immunosuppressive-related issues, and the prevention of graft loss is still challenging. LB remains unmatched in identifying underlying causes of allograft dysfunction and in grading the severity of pathological pictures. Nonetheless, logistics, costs, and potential complications of LB trigger a need for alternative non-invasive tools for routine graft monitoring. As such, TE might help identify, in routine follow-up, liver transplant recipient who exhibit normal liver tests but are at risk for histological abnormalities. Additionally, while our study emphasizes the importance of careful interpretation of non-invasive tests, particularly for fibrosis detection and grading, CAP could find a place in screening and monitoring post-LT metabolic dysfunction.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://tgh.amegroups.com/article/view/10.21037/tgh-24-131/rc

Data Sharing Statement: Available at https://tgh.amegroups.com/article/view/10.21037/tgh-24-131/dss

Peer Review File: Available at https://tgh.amegroups.com/article/view/10.21037/tgh-24-131/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tgh.amegroups.com/article/view/10.21037/tgh-24-131/coif). E.B.R. is a member of the Belgium Liver Intestine Advisory Committee (BeLIAC) and a board member of the European Liver Intestine Transplant Association (ELITA). N.L. received research grants from Gilead Sciences, Echosens, AstraZeneca, UCLouvain, BASL and FNRS (for other research); acted as a consultant for Ipsen and have received honoraria for presentations for Gilead Sciences, Orphalan and Fresenius Kabi; and received support for attending scientific meetings from AbbVie, Gilead Sciences and Norgine. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was performed according to the Good Clinical Practice recommendations, the Helsinki Declaration and its subsequent amendments, and was approved by our Ethical committee of University Hospital Saint-Luc (EC No. 2021/07JUI/265). All patients signed an informed consent form prior to enrollment into the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Adam R, Karam V, Cailliez V, et al. 2018 Annual Report of the European Liver Transplant Registry (ELTR) - 50-year evolution of liver transplantation. Transpl Int 2018;31:1293-317. [Crossref] [PubMed]
2. Narayanan P, Mara K, Izzy M, et al. Recurrent or De novo Allograft Steatosis and Long-term Outcomes After Liver Transplantation. Transplantation 2019;103:e14-21. [Crossref] [PubMed]
3. Míková I, Neřoldová M, Hubáček JA, et al. Donor PNPLA3 and TM6SF2 Variant Alleles Confer Additive Risks for Graft Steatosis After Liver Transplantation. Transplantation 2020;104:526-34. [Crossref] [PubMed]
4. Trunečka P, Míková I, Dlouhá D, et al. Donor PNPLA3 rs738409 genotype is a risk factor for graft steatosis. A post-transplant biopsy-based study. Dig Liver Dis 2018;50:490-5. [Crossref] [PubMed]
5. Iacob S, Beckebaum S, Iacob R, et al. Genetic and Life Style Risk Factors for Recurrent Non-alcoholic Fatty Liver Disease Following Liver Transplantation. Front Nutr 2022;8:787430. [Crossref] [PubMed]
6. Dumortier J, Giostra E, Belbouab S, et al. Non-alcoholic fatty liver disease in liver transplant recipients: another story of “seed and soil”. Am J Gastroenterol 2010;105:613-20. [Crossref] [PubMed]
7. Saeed N, Glass L, Sharma P, et al. Incidence and Risks for Nonalcoholic Fatty Liver Disease and Steatohepatitis Post-liver Transplant: Systematic Review and Meta-analysis. Transplantation 2019;103:e345-54. [Crossref] [PubMed]
8. Burra P, Becchetti C, Germani G. NAFLD and liver transplantation: Disease burden, current management and future challenges. JHEP Rep 2020;2:100192. [Crossref] [PubMed]
9. Kelly D, Verkade HJ, Rajanayagam J, et al. Late graft hepatitis and fibrosis in pediatric liver allograft recipients: Current concepts and future developments. Liver Transpl 2016;22:1593-602. [Crossref] [PubMed]
10. Hübscher SG. What is the long-term outcome of the liver allograft? J Hepatol 2011;55:702-17. [Crossref] [PubMed]
11. Hübscher S. What does the long-term liver allograft look like for the pediatric recipient? Liver Transpl 2009;15:S19-24. [Crossref] [PubMed]
12. Peeters PM, Sieders E. Predictive factors for portal fibrosis in pediatric liver transplant recipients. Transplantation 2000;70:1581-7. [Crossref] [PubMed]
13. Qin T, Fu J, Verkade HJ. The role of the gut microbiome in graft fibrosis after pediatric liver transplantation. Hum Genet 2021;140:709-24. [Crossref] [PubMed]
14. EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis - 2021 update. J Hepatol 2021;75:659-89. [Crossref] [PubMed]
15. Dumont C, Lanthier N, Dahlqvist G. Fibrosis and steatosis of the liver graft: Are non-invasive tests useful? A short review. Clin Res Hepatol Gastroenterol 2023;47:102194. [Crossref] [PubMed]
16. Millonig G, Friedrich S, Adolf S, et al. Liver stiffness is directly influenced by central venous pressure. J Hepatol 2010;52:206-10. [Crossref] [PubMed]
17. Malinchoc M, Kamath PS, Gordon FD, et al. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864-71. [Crossref] [PubMed]
18. Bedossa P, Poynard T. An algorithm for the grading of activity in chronic hepatitis C. The METAVIR Cooperative Study Group. Hepatology 1996;24:289-93. [Crossref] [PubMed]
19. Venturi C, Sempoux C, Bueno J, et al. Novel histologic scoring system for long-term allograft fibrosis after liver transplantation in children. Am J Transplant 2012;12:2986-96. [Crossref] [PubMed]
20. Lanthier N, Rodriguez J, Nachit M, et al. Microbiota analysis and transient elastography reveal new extra-hepatic components of liver steatosis and fibrosis in obese patients. Sci Rep 2021;11:659. [Crossref] [PubMed]
21. Conti F. The challenge of non-invasive evaluation of fibrosis after liver transplantation. Clin Res Hepatol Gastroenterol 2013;37:314-5. [Crossref] [PubMed]
22. Della-Guardia B, Evangelista AS, Felga GE, et al. Diagnostic Accuracy of Transient Elastography for Detecting Liver Fibrosis After Liver Trannsplantation: A Specific Cut-Off Value Is Really Needed? Dig Dis Sci 2017;62:264-72. [Crossref] [PubMed]
23. Adebajo CO, Talwalkar JA, Poterucha JJ, et al. Ultrasound-based transient elastography for the detection of hepatic fibrosis in patients with recurrent hepatitis C virus after liver transplantation: a systematic review and meta-analysis. Liver Transpl 2012;18:323-31. [Crossref] [PubMed]
24. Bhat M, Tazari M, Sebastiani G. Performance of transient elastography and serum fibrosis biomarkers for non-invasive evaluation of recurrent fibrosis after liver transplantation: A meta-analysis. PLoS One 2017;12:e0185192. [Crossref] [PubMed]
25. Evans HM, Kelly DA, McKiernan PJ, et al. Progressive histological damage in liver allografts following pediatric liver transplantation. Hepatology 2006;43:1109-17. [Crossref] [PubMed]
26. Venturi C, Sempoux C, Quinones JA, et al. Dynamics of allograft fibrosis in pediatric liver transplantation. Am J Transplant 2014;14:1648-56. [Crossref] [PubMed]
27. Angelico R, Spada M, Liccardo D, et al. Allograft Fibrosis After Pediatric Liver Transplantation: Incidence, Risk Factors, and Evolution. Liver Transpl 2022;28:280-93. [Crossref] [PubMed]
28. Ishak K, Baptista A, Bianchi L, et al. Histological grading and staging of chronic hepatitis. J Hepatol 1995;22:696-9. [Crossref] [PubMed]
29. Koshiba T, Li Y, Takemura M, et al. Clinical, immunological, and pathological aspects of operational tolerance after pediatric living-donor liver transplantation. Transpl Immunol 2007;17:94-7. [Crossref] [PubMed]
30. Kogiso T, Hashimoto E. Are low triglyceride levels the cause or an outcome of advanced liver fibrosis in elderly patients with nonalcoholic fatty liver disease? J Gastroenterol Hepatol 2020;35:1459-60. [Crossref] [PubMed]
31. Vallin M, Guillaud O, Boillot O, et al. Recurrent or de novo nonalcoholic fatty liver disease after liver transplantation: natural history based on liver biopsy analysis. Liver Transpl 2014;20:1064-71. [Crossref] [PubMed]
32. Mikolasevic I, Stojsavljevic S, Blazic F, et al. Noninvasive markers of liver steatosis and fibrosis after liver transplantation - Where do we stand? World J Transplant 2021;11:37-53. [Crossref] [PubMed]
33. Beckebaum S, Iacob S, Klein CG, et al. Assessment of allograft fibrosis by transient elastography and noninvasive biomarker scoring systems in liver transplant patients. Transplantation 2010;89:983-93. [Crossref] [PubMed]
34. Winters AC, Mittal R, Schiano TD. A review of the use of transient elastography in the assessment of fibrosis and steatosis in the post-liver transplant patient. Clin Transplant 2019;33:e13700. [Crossref] [PubMed]
35. Mikolasevic I, Hauser G, Mijic M, et al. Assessment of Steatosis and Fibrosis in Liver Transplant Recipients Using Controlled Attenuation Parameter and Liver Stiffness Measurements. Can J Gastroenterol Hepatol 2021;2021:6657047. [Crossref] [PubMed]
36. Hernaez R, Lazo M, Bonekamp S, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology 2011;54:1082-90. [Crossref] [PubMed]
37. Saadeh S, Younossi ZM, Remer EM, et al. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology 2002;123:745-50. [Crossref] [PubMed]
38. Stine JG, Munaganuru N, Barnard A, et al. Change in MRI-PDFF and Histologic Response in Patients With Nonalcoholic Steatohepatitis: A Systematic Review and Meta-Analysis. Clin Gastroenterol Hepatol 2021;19:2274-2283.e5. [Crossref] [PubMed]