Steatotic donor livers: Where is the risk-benefit maximized?

Automated liver volumetry and hepatic steatosis quantification with magnetic resonance imaging proton density fat fraction

BACKGROUND

Preoperative imaging evaluation of liver volume and hepatic steatosis for the donor affects transplantation outcomes. However, computed tomography (CT) for liver volumetry and magnetic resonance spectroscopy (MRS) for hepatic steatosis are time consuming. Therefore, we investigated the correlation of automated 3D-multi-echo-Dixon sequence magnetic resonance imaging (ME-Dixon MRI) and its derived proton density fat fraction (MRI-PDFF) with CT liver volumetry and MRS hepatic steatosis measurements in living liver donors.

METHODS

This retrospective cross-sectional study was conducted from December 2017 to November 2022. We enrolled donors who received a dynamic CT scan and an MRI exam within 2 days. First, the CT volumetry was processed semiautomatically using commercial software, and ME-Dixon MRI volumetry was automatically measured using an embedded sequence. Next, the signal intensity of MRI-PDFF volumetric data was correlated with MRS as the gold standard.

RESULTS

We included the 165 living donors. The total liver volume of ME-Dixon MRI was significantly correlated with CT (r = 0.913, p < 0.001). The fat percentage measured using MRI-PDFF revealed a strong correlation between automatic segmental volume and MRS (r = 0.705, p < 0.001). Furthermore, the hepatic steatosis group (MRS ≥5%) had a strong correlation than the non-hepatic steatosis group (MRS <5%) in both volumetric (r = 0.906 vs. r = 0.887) and fat fraction analysis (r = 0.779 vs. r = 0.338).

CONCLUSION

Automated ME-Dixon MRI liver volumetry and MRI-PDFF were strongly correlated with CT liver volumetry and MRS hepatic steatosis measurements, especially in donors with hepatic steatosis.

Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms

BACKGROUND & AIMS

The Banff Liver Working Group recently published consensus recommendations for steatosis assessment in donor liver biopsy, but few studies reported their use and no automated deep-learning algorithms based on the proposed criteria have been developed so far. We evaluated Banff recommendations on a large monocentric series of donor liver needle biopsies by comparing pathologists' scores with those generated by convolutional neural networks (CNNs) we specifically developed for automated steatosis assessment.

METHODS

We retrospectively retrieved 292 allograft liver needle biopsies collected between January 2016 and January 2020 and performed steatosis assessment using a former intra-institution method (pre-Banff method) and the newly introduced Banff recommendations. Scores provided by pathologists and CNN models were then compared, and the degree of agreement was measured with the intraclass correlation coefficient (ICC).

RESULTS

Regarding the pre-Banff method, poor agreement was observed between the pathologist and CNN models for small droplet macrovesicular steatosis (ICC: 0.38), large droplet macrovesicular steatosis (ICC: 0.08), and the final combined score (ICC: 0.16) evaluation, but none of these reached statistically significance. Interestingly, significantly improved agreement was observed using the Banff approach: ICC was 0.93 for the low-power score (p <0.001), 0.89 for the high-power score (p <0.001), and 0.93 for the final score (p <0.001). Comparing the pre-Banff method with the Banff approach on the same biopsy, pathologist and CNN model assessment showed a mean (±SD) percentage of discrepancy of 26.89 (±22.16) and 1.20 (±5.58), respectively.

CONCLUSIONS

Our findings support the use of Banff recommendations in daily practice and highlight the need for a granular analysis of their effect on liver transplantation outcomes.

IMPACT AND IMPLICATIONS

We developed and validated the first automated deep-learning algorithms for standardized steatosis assessment based on the Banff Liver Working Group consensus recommendations. Our algorithm provides an unbiased automated evaluation of steatosis, which will lay the groundwork for granular analysis of steatosis's short- and long-term effects on organ viability, enabling the identification of clinically relevant steatosis cut-offs for donor organ acceptance. Implementing our algorithm in daily clinical practice will allow for a more efficient and safe allocation of donor organs, improving the post-transplant outcomes of patients.

Integrated multi-omic analysis identifies fatty acid binding protein 4 as a biomarker and therapeutic target of ischemia-reperfusion injury in steatotic liver transplantation

BACKGROUND AND AIMS

Due to a lack of donor grafts, steatotic livers are used more often for liver transplantation (LT). However, steatotic donor livers are more sensitive to ischemia-reperfusion (IR) injury and have a worse prognosis after LT. Efforts to optimize steatotic liver grafts by identifying injury targets and interventions have become a hot issue.

METHODS

Mouse LT models were established, and 4D label-free proteome sequencing was performed for four groups: normal control (NC) SHAM, high-fat (HF) SHAM, NC LT, and HF LT to screen molecular targets for aggravating liver injury in steatotic LT. Expression detection of molecular targets was performed based on liver specimens from 110 donors to verify its impact on the overall survival of recipients. Pharmacological intervention using small-molecule inhibitors on an injury-related target was used to evaluate the therapeutic effect. Transcriptomics and metabolomics were performed to explore the regulatory network and further integrated bioinformatics analysis and multiplex immunofluorescence were adopted to assess the regulation of pathways and organelles.

RESULTS

HF LT group represented worse liver function compared with NC LT group, including more apoptotic hepatocytes (P < 0.01) and higher serum transaminase (P < 0.05). Proteomic results revealed that the mitochondrial membrane, endocytosis, and oxidative phosphorylation pathways were upregulated in HF LT group. Fatty acid binding protein 4 (FABP4) was identified as a hypoxia-inducible protein (fold change > 2 and P < 0.05) that sensitized mice to IR injury in steatotic LT. The overall survival of recipients using liver grafts with high expression of FABP4 was significantly worse than low expression of FABP4 (68.5 vs. 87.3%, P < 0.05). Adoption of FABP4 inhibitor could protect the steatotic liver from IR injury during transplantation, including reducing hepatocyte apoptosis, reducing serum transaminase (P < 0.05), and alleviating oxidative stress damage (P < 0.01). According to integrated transcriptomics and metabolomics analysis, cAMP signaling pathway was enriched following FABP4 inhibitor use. The activation of cAMP signaling pathway was validated. Microscopy and immunofluorescence staining results suggested that FABP4 inhibitors could regulate mitochondrial membrane homeostasis in steatotic LT.

CONCLUSIONS

FABP4 was identified as a hypoxia-inducible protein that sensitized steatotic liver grafts to IR injury. The FABP4 inhibitor, BMS-309403, could activate of cAMP signaling pathway thereby modulating mitochondrial membrane homeostasis, reducing oxidative stress injury in steatotic donors.

Liver Transplant in Patients with Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence

Hepatocellular carcinoma is the most common primary malignant hepatic tumor and occurs most often in the setting of chronic liver disease. Liver transplantation is a curative treatment option and is an ideal solution because it solves the chronic underlying liver disorder while removing the malignant lesion. However, due to organ shortages, this treatment can only be applied to carefully selected patients according to clinical guidelines. Artificial intelligence is an emerging technology with multiple applications in medicine with a predilection for domains that work with medical imaging, like radiology. With the help of these technologies, laborious tasks can be automated, and new lesion imaging criteria can be developed based on pixel-level analysis. Our objectives are to review the developing AI applications that could be implemented to better stratify liver transplant candidates. The papers analysed applied AI for liver segmentation, evaluation of steatosis, sarcopenia assessment, lesion detection, segmentation, and characterization. A liver transplant is an optimal treatment for patients with hepatocellular carcinoma in the setting of chronic liver disease. Furthermore, AI could provide solutions for improving the management of liver transplant candidates to improve survival.

Hyperspectral imaging for quantitative assessment of hepatic steatosis in human liver allografts

INTRODUCTION

In liver transplantation (LT), steatosis is commonly judged to be a risk factor for graft dysfunction, and quantitative assessment of hepatic steatosis remains crucial. Liver biopsy as the gold standard for evaluation of hepatic steatosis has certain drawbacks, i.e. invasiveness, and intra- and inter-observer variability. A non-invasive, quantitative modality could replace liver biopsy and eliminate these disadvantages, but has not yet been evaluated in human LT.

METHODS

We performed a pilot study to evaluate the feasibility and accuracy of hyperspectral imaging (HSI) in the assessment of hepatic steatosis of human liver allografts for transplantation. Thirteen deceased donor liver allografts were included in the study. The degree of steatosis was assessed by means of conventional liver biopsy as well as HSI, performed at the end of backtable preparation, during normothermic machine perfusion (NMP), and after reperfusion in the recipient.

RESULTS

Organ donors were 51 [30-83] years old, and 61.5% were male. Donor body mass index was 24.2 [16.5-38.0] kg/m2. The tissue lipid index (TLI) generated by HSI at the end of back-table preparation correlated significantly with the histopathologically assessed degree of overall hepatic steatosis (R2 = 0.9085, p<0.0001); this was based on a correlation of TLI and microvesicular steatosis (R2 = 0.8120; p<0.0001). There is also a linear relationship between the histopathologically assessed degree of overall steatosis and TLI during NMP (R2 = 0.5646; p = 0.0031) as well as TLI after reperfusion (R2 = 0.6562; p = 0.0008).

CONCLUSION

HSI may safely be applied for accurate assessment of hepatic steatosis in human liver grafts. Certainly, TLI needs further assessment and validation in larger sample sizes. This article is protected by copyright. All rights reserved.

Noninvasive, quantitative evaluation of hepatic steatosis of donor livers by reference frequency method: A preliminary study

PURPOSE

Evaluating degree of hepatic steatosis is of great value for prognosis of liver transplantation. There is an urgent need for a non-invasive method to assess hepatic steatosis grade of donor livers. Purpose of our study was to evaluate diagnostic accuracy of attenuation coefficient estimation (ACE) by reference frequency method (RFM) in detecting hepatic steatosis of donor livers.

METHOD

We retrospectively enrolled 62 potential liver donors which underwent ACE by RFM ex-vivo, in-vivo or both. We acquired raw data of B-mode images of liver parenchyma and offline-processes for attenuation estimation. Finally, we calculated and compared diagnostic performance of ACEs for steatosis grade detection and used histological results as the gold standard.

RESULTS

ACEs with none, mild and moderate hepatic steatosis were 0.57, 0.73 and 0.80 dB/cm/MHz in potential donor livers. The cutoff value to diagnose mild hepatic steatosis was 0.63 dB/cm/MHz and 0.77 dB/cm/MHz for moderate hepatic steatosis, and values for the area under the receiver operating characteristic curve for diagnosis of mild and moderate hepatic steatosis were 0.92 and 0.90, respectively.

CONCLUSIONS

According to our results, ACE by RFM is an accurate non-invasive method in detecting hepatic steatosis, which may be of great help for clinical evaluation of donor livers before liver transplantation.

CT and MR imaging evaluation of living liver donors

Preoperative cross-sectional imaging evaluation of potential living liver donors allows to exclude donors with an increased risk for morbidity and mortality, and to assure that a suitable graft for the recipient can be obtained, minimizing the risk of complications in both the donor and the recipient. CT is routinely performed to delineate the anatomy of the liver, relevant vasculature, and liver volumes in whole right or left lateral segment donation. MR imaging is the gold standard for the assessment of biliary anatomy and allows a better quantification of hepatic steatosis compared to CT. Knowledge of normal and variant vascular and biliary anatomy and their surgical relevance for liver transplantation is of paramount importance for the radiologist. The purpose of this review is to outline the current role of CT and MR imaging in the assessment of hepatic parenchyma, hepatic vascular anatomy, biliary anatomy, and hepatic volumetry in the potential living liver donor with short notes on acquisition protocols and the relevant reportable findings.

Necroptosis in Hepatosteatotic Ischaemia-Reperfusion Injury

While liver transplantation remains the sole treatment option for patients with end-stage liver disease, there are numerous limitations to liver transplantation including the scarcity of donor livers and a rise in livers that are unsuitable to transplant such as those with excess steatosis. Fatty livers are susceptible to ischaemia-reperfusion (IR) injury during transplantation and IR injury results in primary graft non-function, graft failure and mortality. Recent studies have described new cell death pathways which differ from the traditional apoptotic pathway. Necroptosis, a regulated form of cell death, has been associated with hepatic IR injury. Receptor-interacting protein kinase 3 (RIPK3) and mixed-lineage kinase domain-like pseudokinase (MLKL) are thought to be instrumental in the execution of necroptosis. The study of hepatic necroptosis and potential therapeutic approaches to attenuate IR injury will be a key factor in improving our knowledge regarding liver transplantation with fatty donor livers. In this review, we focus on the effect of hepatic steatosis during liver transplantation as well as molecular mechanisms of necroptosis and its involvement during liver IR injury. We also discuss the immune responses triggered during necroptosis and examine the utility of necroptosis inhibitors as potential therapeutic approaches to alleviate IR injury.

CREBZF as a Key Regulator of STAT3 Pathway in the Control of Liver Regeneration in Mice

BACKGROUND AND AIMS

STAT3, a member of the signal transducer and activator of transcription (STAT) family, is strongly associated with liver injury, inflammation, regeneration, and hepatocellular carcinoma development. However, the signals that regulate STAT3 activity are not completely understood.

APPROACH AND RESULTS

Here we characterize CREB/ATF bZIP transcription factor CREBZF as a critical regulator of STAT3 in the hepatocyte to repress liver regeneration. We show that CREBZF deficiency stimulates the expression of the cyclin gene family and enhances liver regeneration after partial hepatectomy. Flow cytometry analysis reveals that CREBZF regulates cell cycle progression during liver regeneration in a hepatocyte-autonomous manner. Similar results were observed in another model of liver regeneration induced by intraperitoneal injection of carbon tetrachloride (CCl₄ ). Mechanistically, CREBZF potently associates with the linker domain of STAT3 and represses its dimerization and transcriptional activity in vivo and in vitro. Importantly, hepatectomy-induced hyperactivation of cyclin D1 and liver regeneration in CREBZF liver-specific knockout mice was reversed by selective STAT3 inhibitor cucurbitacin I. In contrast, adeno-associated virus-mediated overexpression of CREBZF in the liver inhibits the expression of the cyclin gene family and attenuates liver regeneration in CCl₄ -treated mice.

CONCLUSIONS

These results characterize CREBZF as a coregulator of STAT3 to inhibit regenerative capacity, which may represent an essential cellular signal to maintain liver mass homeostasis. Therapeutic approaches to inhibit CREBZF may benefit the compromised liver during liver transplantation.

The role of deceased donor liver biopsy: An analysis of 5449 liver transplant recipients

BACKGROUND

No standard exists for the use of deceased donor liver biopsy during procurement. We sought to evaluate liver biopsy and the impact of findings on outcomes and graft utilization.

METHODS

A prospective observational study of donors after neurologic determination of death was conducted from 02/2012-08/2017 (16 OPOs). Donor data were collected through the UNOS Donor Management Goals Registry Web Portal and linked to the Scientific Registry of Transplant Recipients (SRTR) for recipient outcomes. Recipients of biopsied donor livers (BxDL) were studied and a Cox proportional hazard analysis was used to identify independent predictors of 1-year graft survival.

RESULTS

Data from 5449 liver transplant recipients were analyzed, of which 1791(33%) received a BxDL. There was no difference in graft or patient survival between the non-BxDL and BxDL recipient groups. On adjusted analysis of BxDL recipients, macrosteatosis (21%-30%[n = 148] and >30%[n = 92]) was not found to predict 1-year graft survival, whereas increasing donor age (HR1.02), donor Hispanic ethnicity (HR1.62), donor INR (HR1.18), and recipient life support (HR2.29) were.

CONCLUSIONS

Excellent graft and patient survival can be achieved in recipients of BxDL grafts. Notably, as demonstrated by the lack of effect of macrosteatosis on survival, donor to recipient matching may contribute to these outcomes.

Autofluorescence-based optical biopsy: An effective diagnostic tool in hepatology

Autofluorescence emission of liver tissue depends on the presence of endogenous biomolecules able to fluoresce under suitable light excitation. Overall autofluorescence emission contains much information of diagnostic value because it is the sum of individual autofluorescence contributions from fluorophores involved in metabolism, for example, NAD(P)H, flavins, lipofuscins, retinoids, porphyrins, bilirubin and lipids, or in structural architecture, for example, fibrous proteins, in close relationship with normal, altered or diseased conditions of the liver. Since the 1950s, hepatocytes and liver have been historical models to study NAD(P)H and flavins as in situ, real-time autofluorescence biomarkers of energy metabolism and redox state. Later investigations designed to monitor organ responses to ischaemia/reperfusion were able to predict the risk of dysfunction in surgery and transplantation or support the development of procedures to ameliorate the liver outcome. Subsequently, fluorescent fatty acids, lipofuscin-like lipopigments and collagen were characterized as optical biomarkers of liver steatosis, oxidative stress damage, fibrosis and disease progression. Currently, serum AF is being investigated to improve non-invasive optical diagnosis of liver disease. Validation of endogenous fluorophores and in situ discrimination of cancerous from non-cancerous tissue belong to the few studies on liver in human subjects. These reports along with other optical techniques and the huge work performed on animal models suggest many optically based applications in hepatology. Optical diagnosis is currently offering beneficial outcomes in clinical fields ranging from the respiratory and gastrointestinal tracts, to dermatology and ophthalmology. Accordingly, this review aims to promote an effective bench to bedside transfer in hepatology.