Hepatitis E virus (HEV) infection is increasingly recognized as a clinically significant disease with two distinct presentations— acute self-limiting infection and chronic infection in immunosuppressed patients . Acute HEV is usually mild and requires only supportive management , including hydration, avoidance of hepatotoxic drugs, and monitoring. However, certain groups need special attention. Pregnant women (especially 2nd–3rd trimester) and patients with pre-existing liver disease are at high risk of acute liver failure (ALF) or ACLF . In such severe cases, ribavirin may be considered , although it is not routinely recommended and is contraindicated in pregnancy. Chronic HEV is now well established, particularly in solid organ transplant recipients and other immunosuppressed individuals . It should be suspected in patients with persistent elevation of liver enzymes , and diagnosis relies on HEV RNA testing , as serology may be unreliable. The first step in management is cautious reduction of immunosuppression , which alone can lead to viral clearance in some cases. If viremia persists beyond 3 months, ribavirin monotherapy for ~12 weeks is the treatment of choice, achieving high sustained virological response rates. Treatment should be guided by HEV RNA monitoring , with extension of therapy if viral clearance is incomplete. Key Message: HEV is no longer just an acute infection—clinicians must recognize and actively treat chronic HEV , especially in immunosuppressed patients, while reserving antivirals in acute disease for selected severe cases only .
Hepatitis E virus (HEV) infection is increasingly recognized as a clinically significant disease with two distinct presentations—acute self-limiting infection and chronic infection in immunosuppressed patients.
Acute HEV is usually mild and requires only supportive management, including hydration, avoidance of hepatotoxic drugs, and monitoring. However, certain groups need special attention. Pregnant women (especially 2nd–3rd trimester)and patients with pre-existing liver disease are at high risk of acute liver failure (ALF) or ACLF. In such severe cases, ribavirin may be considered, although it is not routinely recommended and is contraindicated in pregnancy.
Chronic HEV is now well established, particularly in solid organ transplant recipients and other immunosuppressed individuals. It should be suspected in patients with persistent elevation of liver enzymes, and diagnosis relies on HEV RNA testing, as serology may be unreliable.
The first step in management is cautious reduction of immunosuppression, which alone can lead to viral clearance in some cases. If viremia persists beyond 3 months, ribavirin monotherapy for ~12 weeks is the treatment of choice, achieving high sustained virological response rates. Treatment should be guided by HEV RNA monitoring, with extension of therapy if viral clearance is incomplete.
Key Message:
HEV is no longer just an acute infection—clinicians must recognize and actively treat chronic HEV, especially in immunosuppressed patients, while reserving antivirals in acute disease for selected severe cases only.
This APASL 2026 topic focuses on how artificial intelligence (AI) is changing cirrhosis care from a late, reactive approach to an early, predictive, and personalized model . In the APASL 2026 program, this lecture is listed under cirrhosis-focused academic content, reflecting the growing role of AI in hepatology. In diagnosis , AI can combine clinical data, laboratory parameters, imaging, elastography, and endoscopic findings to detect cirrhosis earlier and identify patients at risk of clinically significant portal hypertension . This is important because many patients remain clinically silent until decompensation occurs. Recent reviews suggest AI-based models may improve diagnostic precision and support earlier recognition of advanced liver disease. In outcome prediction , AI can analyze multiple variables simultaneously and continuously, often outperforming static conventional scores alone in predicting hepatic decompensation, hospitalization, variceal bleeding, and mortality . This allows clinicians to identify high-risk patients earlier, intensify follow-up, optimize therapy, and improve transplant referral timing. In patient management , the real value of AI lies in supporting decisions such as surveillance intensity, early intervention, and prioritization of resources. However, AI should be seen as a decision-support tool , not a substitute for hepatology expertise. Current limitations include data heterogeneity, limited external validation, interpretability issues, and challenges in routine clinical integration . Key message: AI has the potential to make cirrhosis care more accurate, proactive, and individualized , but its future depends on strong validation and careful clinical adoption.
This APASL 2026 topic focuses on how artificial intelligence (AI) is changing cirrhosis care from a late, reactive approach to an early, predictive, and personalized model. In the APASL 2026 program, this lecture is listed under cirrhosis-focused academic content, reflecting the growing role of AI in hepatology.
In diagnosis, AI can combine clinical data, laboratory parameters, imaging, elastography, and endoscopic findingsto detect cirrhosis earlier and identify patients at risk of clinically significant portal hypertension. This is important because many patients remain clinically silent until decompensation occurs. Recent reviews suggest AI-based models may improve diagnostic precision and support earlier recognition of advanced liver disease.
In outcome prediction, AI can analyze multiple variables simultaneously and continuously, often outperforming static conventional scores alone in predicting hepatic decompensation, hospitalization, variceal bleeding, and mortality. This allows clinicians to identify high-risk patients earlier, intensify follow-up, optimize therapy, and improve transplant referral timing.
In patient management, the real value of AI lies in supporting decisions such as surveillance intensity, early intervention, and prioritization of resources. However, AI should be seen as a decision-support tool, not a substitute for hepatology expertise. Current limitations include data heterogeneity, limited external validation, interpretability issues, and challenges in routine clinical integration.
Key message: AI has the potential to make cirrhosis care more accurate, proactive, and individualized, but its future depends on strong validation and careful clinical adoption.
Metabolic dysfunction–associated fatty liver disease (MAFLD) is now understood as a systemic metabolic disorder rather than a purely hepatic condition. Its pathophysiology is best explained by a “multiple-hit” model , where several parallel mechanisms drive disease progression from steatosis to steatohepatitis, fibrosis, and cirrhosis. The central driver is insulin resistance , which increases lipolysis in adipose tissue, leading to excess free fatty acid (FFA) flux to the liver . This results in hepatic triglyceride accumulation and lipotoxicity , particularly from toxic lipid intermediates rather than simple fat deposition. A key second component is mitochondrial dysfunction and oxidative stress , which promote hepatocyte injury through reactive oxygen species and impaired β-oxidation. This is accompanied by endoplasmic reticulum stress and activation of inflammatory pathways. Inflammation plays a pivotal role, with activation of Kupffer cells and recruitment of immune cells driven by cytokines such as TNF-α and IL-6. In parallel, gut–liver axis dysfunction —including increased intestinal permeability and dysbiosis—contributes to endotoxemia and further hepatic inflammation. Progression to fibrosis is mediated by hepatic stellate cell activation , triggered by chronic inflammation and oxidative stress, leading to extracellular matrix deposition. Genetic and epigenetic factors (e.g., PNPLA3, TM6SF2 variants) modulate susceptibility and disease severity, explaining inter-individual variability. Key Message: MAFLD is a multifactorial, systemic disease driven by insulin resistance, lipotoxicity, inflammation, and gut–liver interactions, with genetics influencing progression—making it an ideal target for multi-pathway therapeutic strategies .
Metabolic dysfunction–associated fatty liver disease (MAFLD) is now understood as a systemic metabolic disorderrather than a purely hepatic condition. Its pathophysiology is best explained by a “multiple-hit” model, where several parallel mechanisms drive disease progression from steatosis to steatohepatitis, fibrosis, and cirrhosis.
The central driver is insulin resistance, which increases lipolysis in adipose tissue, leading to excess free fatty acid (FFA) flux to the liver. This results in hepatic triglyceride accumulation and lipotoxicity, particularly from toxic lipid intermediates rather than simple fat deposition.
A key second component is mitochondrial dysfunction and oxidative stress, which promote hepatocyte injury through reactive oxygen species and impaired β-oxidation. This is accompanied by endoplasmic reticulum stress and activation of inflammatory pathways.
Inflammation plays a pivotal role, with activation of Kupffer cells and recruitment of immune cells driven by cytokines such as TNF-α and IL-6. In parallel, gut–liver axis dysfunction—including increased intestinal permeability and dysbiosis—contributes to endotoxemia and further hepatic inflammation.
Progression to fibrosis is mediated by hepatic stellate cell activation, triggered by chronic inflammation and oxidative stress, leading to extracellular matrix deposition.
Genetic and epigenetic factors (e.g., PNPLA3, TM6SF2 variants) modulate susceptibility and disease severity, explaining inter-individual variability.
Key Message:
MAFLD is a multifactorial, systemic disease driven by insulin resistance, lipotoxicity, inflammation, and gut–liver interactions, with genetics influencing progression—making it an ideal target for multi-pathway therapeutic strategies.
Metabolic dysfunction–associated fatty liver disease (MAFLD) is now recognized as the hepatic manifestation of systemic metabolic syndrome , tightly linked with multiple metabolic complications that drive both liver-related and cardiovascular outcomes. The strongest association is with type 2 diabetes mellitus (T2DM) . MAFLD and T2DM share a bidirectional relationship—insulin resistance promotes hepatic steatosis, while MAFLD itself increases the risk of incident diabetes and worsens glycemic control. Importantly, the presence of T2DM significantly accelerates progression to steatohepatitis, fibrosis, and cirrhosis . MAFLD is also closely associated with obesity , particularly visceral adiposity , which increases free fatty acid flux to the liver and promotes lipotoxicity. In addition, dyslipidemia —characterized by elevated triglycerides, low HDL, and atherogenic LDL particles—is common and contributes to both liver disease progression and cardiovascular risk. The most critical clinical implication is the strong link with cardiovascular disease (CVD) , which remains the leading cause of mortality in MAFLD patients. Endothelial dysfunction, chronic inflammation, and a pro-atherogenic state all contribute to this risk. Other important associations include chronic kidney disease (CKD) , polycystic ovary syndrome (PCOS) , and obstructive sleep apnea (OSA) , reflecting the systemic nature of MAFLD. Key Message: MAFLD is not just a liver disease—it is a multisystem metabolic disorder . Effective management requires a holistic approach , targeting metabolic risk factors (diabetes, obesity, dyslipidemia) to improve both hepatic outcomes and overall survival , especially by reducing cardiovascular risk.
Metabolic dysfunction–associated fatty liver disease (MAFLD) is now recognized as the hepatic manifestation of systemic metabolic syndrome, tightly linked with multiple metabolic complications that drive both liver-related and cardiovascular outcomes.
The strongest association is with type 2 diabetes mellitus (T2DM). MAFLD and T2DM share a bidirectional relationship—insulin resistance promotes hepatic steatosis, while MAFLD itself increases the risk of incident diabetes and worsens glycemic control. Importantly, the presence of T2DM significantly accelerates progression to steatohepatitis, fibrosis, and cirrhosis.
MAFLD is also closely associated with obesity, particularly visceral adiposity, which increases free fatty acid flux to the liver and promotes lipotoxicity. In addition, dyslipidemia—characterized by elevated triglycerides, low HDL, and atherogenic LDL particles—is common and contributes to both liver disease progression and cardiovascular risk.
The most critical clinical implication is the strong link with cardiovascular disease (CVD), which remains the leading cause of mortality in MAFLD patients. Endothelial dysfunction, chronic inflammation, and a pro-atherogenic state all contribute to this risk.
Other important associations include chronic kidney disease (CKD), polycystic ovary syndrome (PCOS), and obstructive sleep apnea (OSA), reflecting the systemic nature of MAFLD.
Key Message:
MAFLD is not just a liver disease—it is a multisystem metabolic disorder. Effective management requires a holistic approach, targeting metabolic risk factors (diabetes, obesity, dyslipidemia) to improve both hepatic outcomes and overall survival, especially by reducing cardiovascular risk.
Hepatic stellate cells (HSCs) are central regulators of liver homeostasis and fibrosis , acting as the key effector cells in chronic liver disease progression. In the healthy liver , HSCs exist in a quiescent state , located in the space of Disse, where they function primarily as vitamin A–storing cells and help maintain extracellular matrix (ECM) balance. They also contribute to normal sinusoidal architecture and hepatic microcirculation. In liver injury , HSCs undergo a critical transformation into an activated, myofibroblast-like phenotype . This activation is triggered by signals from injured hepatocytes, Kupffer cells, and inflammatory mediators such as TGF-β, PDGF, and reactive oxygen species . Once activated, HSCs proliferate, lose vitamin A stores, and produce large amounts of collagen and extracellular matrix , leading to fibrosis. HSC activation is not a single-step process but involves initiation, perpetuation, and resolution phases . Persistent activation drives progressive fibrosis and ultimately cirrhosis, while resolution may occur through HSC apoptosis, senescence, or reversion to an inactive phenotype . Beyond fibrosis, HSCs also play roles in immune modulation, angiogenesis, and portal hypertension , making them central to multiple aspects of chronic liver disease. Key Message: Hepatic stellate cells are the master regulators of liver fibrosis —understanding their activation and reversibility provides a critical therapeutic target for antifibrotic strategies in diseases such as MAFLD, viral hepatitis, and alcoholic liver disease.
Hepatic stellate cells (HSCs) are central regulators of liver homeostasis and fibrosis, acting as the key effector cells in chronic liver disease progression.
In the healthy liver, HSCs exist in a quiescent state, located in the space of Disse, where they function primarily as vitamin A–storing cells and help maintain extracellular matrix (ECM) balance. They also contribute to normal sinusoidal architecture and hepatic microcirculation.
In liver injury, HSCs undergo a critical transformation into an activated, myofibroblast-like phenotype. This activation is triggered by signals from injured hepatocytes, Kupffer cells, and inflammatory mediators such as TGF-β, PDGF, and reactive oxygen species. Once activated, HSCs proliferate, lose vitamin A stores, and produce large amounts of collagen and extracellular matrix, leading to fibrosis.
HSC activation is not a single-step process but involves initiation, perpetuation, and resolution phases. Persistent activation drives progressive fibrosis and ultimately cirrhosis, while resolution may occur through HSC apoptosis, senescence, or reversion to an inactive phenotype.
Beyond fibrosis, HSCs also play roles in immune modulation, angiogenesis, and portal hypertension, making them central to multiple aspects of chronic liver disease.
Key Message:
Hepatic stellate cells are the master regulators of liver fibrosis—understanding their activation and reversibility provides a critical therapeutic target for antifibrotic strategies in diseases such as MAFLD, viral hepatitis, and alcoholic liver disease.
Extracellular vesicles (EVs) are emerging as key mediators of intercellular communication in the liver , playing critical roles in both physiological homeostasis and disease progression. EVs include exosomes, microvesicles, and apoptotic bodies , released by hepatocytes, Kupffer cells, hepatic stellate cells, and cholangiocytes. In the healthy liver , EVs help maintain homeostasis by facilitating communication between liver cells, regulating metabolism, immune tolerance, and tissue repair . They carry bioactive cargo such as proteins, lipids, mRNA, and microRNA , allowing precise signaling across the hepatic microenvironment. In liver disease , EVs become pathogenic mediators. Injured hepatocytes release EVs enriched with inflammatory signals that activate Kupffer cells and hepatic stellate cells , promoting inflammation and fibrosis. In MAFLD and alcoholic liver disease, EVs contribute to lipotoxicity, oxidative stress, and immune activation , accelerating progression to steatohepatitis and fibrosis. EVs also play a role in viral hepatitis , where they can modulate immune responses and even facilitate viral persistence. In hepatocellular carcinoma (HCC) , tumor-derived EVs promote angiogenesis, immune evasion, and metastasis , highlighting their role in cancer biology. Clinically, EVs are gaining attention as non-invasive biomarkers , as they can be detected in blood and reflect disease activity. They also represent potential therapeutic targets and drug delivery vehicles . Key Message: Liver extracellular vesicles are not just bystanders—they are active drivers of liver disease and promising tools for diagnosis, prognosis, and targeted therapy in hepatology.
Extracellular vesicles (EVs) are emerging as key mediators of intercellular communication in the liver, playing critical roles in both physiological homeostasis and disease progression. EVs include exosomes, microvesicles, and apoptotic bodies, released by hepatocytes, Kupffer cells, hepatic stellate cells, and cholangiocytes.
In the healthy liver, EVs help maintain homeostasis by facilitating communication between liver cells, regulating metabolism, immune tolerance, and tissue repair. They carry bioactive cargo such as proteins, lipids, mRNA, and microRNA, allowing precise signaling across the hepatic microenvironment.
In liver disease, EVs become pathogenic mediators. Injured hepatocytes release EVs enriched with inflammatory signals that activate Kupffer cells and hepatic stellate cells, promoting inflammation and fibrosis. In MAFLD and alcoholic liver disease, EVs contribute to lipotoxicity, oxidative stress, and immune activation, accelerating progression to steatohepatitis and fibrosis.
EVs also play a role in viral hepatitis, where they can modulate immune responses and even facilitate viral persistence. In hepatocellular carcinoma (HCC), tumor-derived EVs promote angiogenesis, immune evasion, and metastasis, highlighting their role in cancer biology.
Clinically, EVs are gaining attention as non-invasive biomarkers, as they can be detected in blood and reflect disease activity. They also represent potential therapeutic targets and drug delivery vehicles.
Key Message:
Liver extracellular vesicles are not just bystanders—they are active drivers of liver disease and promising tools for diagnosis, prognosis, and targeted therapy in hepatology.
Liver macrophages are central to maintaining hepatic homeostasis, immune surveillance, and tissue repair , while also driving inflammation and fibrosis in chronic liver disease. They exist as two major populations: resident Kupffer cells and monocyte-derived macrophages recruited during injury. In the healthy liver , Kupffer cells reside within the sinusoids and maintain immune tolerance despite constant exposure to gut-derived antigens. They clear pathogens, apoptotic cells, and debris, and regulate inflammation through anti-inflammatory cytokines such as IL-10, thereby preserving hepatic balance. During liver injury , macrophage dynamics change dramatically. Damage-associated signals and gut-derived endotoxins activate Kupffer cells and recruit circulating monocytes, which differentiate into inflammatory macrophages. These cells release cytokines such as TNF-α, IL-1β, and IL-6 , amplifying inflammation and contributing to hepatocyte injury. Macrophages also play a pivotal role in fibrosis by interacting with hepatic stellate cells. Pro-inflammatory macrophages promote stellate cell activation via mediators like TGF-β , leading to extracellular matrix deposition. Conversely, during resolution, a shift toward anti-inflammatory (pro-resolving) macrophages facilitates fibrosis regression by promoting matrix degradation and tissue repair. Emerging concepts highlight macrophage plasticity , with dynamic switching between pro-inflammatory and restorative phenotypes depending on the microenvironment. Key Message: Liver macrophages are double-edged regulators —essential for defense and repair, yet central drivers of inflammation and fibrosis. Targeting macrophage activation and polarization offers a promising therapeutic strategy in chronic liver diseases such as MAFLD, viral hepatitis, and cirrhosis.
Liver macrophages are central to maintaining hepatic homeostasis, immune surveillance, and tissue repair, while also driving inflammation and fibrosis in chronic liver disease. They exist as two major populations: resident Kupffer cellsand monocyte-derived macrophages recruited during injury.
In the healthy liver, Kupffer cells reside within the sinusoids and maintain immune tolerance despite constant exposure to gut-derived antigens. They clear pathogens, apoptotic cells, and debris, and regulate inflammation through anti-inflammatory cytokines such as IL-10, thereby preserving hepatic balance.
During liver injury, macrophage dynamics change dramatically. Damage-associated signals and gut-derived endotoxins activate Kupffer cells and recruit circulating monocytes, which differentiate into inflammatory macrophages. These cells release cytokines such as TNF-α, IL-1β, and IL-6, amplifying inflammation and contributing to hepatocyte injury.
Macrophages also play a pivotal role in fibrosis by interacting with hepatic stellate cells. Pro-inflammatory macrophages promote stellate cell activation via mediators like TGF-β, leading to extracellular matrix deposition. Conversely, during resolution, a shift toward anti-inflammatory (pro-resolving) macrophages facilitates fibrosis regression by promoting matrix degradation and tissue repair.
Emerging concepts highlight macrophage plasticity, with dynamic switching between pro-inflammatory and restorative phenotypes depending on the microenvironment.
Key Message:
Liver macrophages are double-edged regulators—essential for defense and repair, yet central drivers of inflammation and fibrosis. Targeting macrophage activation and polarization offers a promising therapeutic strategy in chronic liver diseases such as MAFLD, viral hepatitis, and cirrhosis.
The extracellular matrix (ECM) of the liver is a dynamic scaffold that maintains structural integrity, cell signaling, and microvascular architecture . In the normal liver, the ECM is minimal and well organized, composed of collagens (types I, III, IV), laminin, fibronectin, and proteoglycans , particularly within the space of Disse, allowing efficient exchange between hepatocytes and sinusoidal blood. In health , ECM turnover is tightly regulated by a balance between matrix synthesis and degradation , primarily controlled by hepatic stellate cells and matrix metalloproteinases (MMPs) with their inhibitors (TIMPs). This balance ensures tissue homeostasis and normal liver function. In liver injury , this balance is disrupted. Chronic insults such as MAFLD, viral hepatitis, or alcohol lead to activation of hepatic stellate cells into fibrogenic myofibroblasts , resulting in excessive deposition of collagen-rich ECM. This causes sinusoidal capillarization , impaired hepatocyte function, and increased intrahepatic resistance, contributing to portal hypertension . Progressive ECM accumulation leads to fibrosis and ultimately cirrhosis , characterized by architectural distortion and formation of regenerative nodules. Importantly, ECM is not merely structural—it actively modulates cell behavior, inflammation, and fibrosis progression through signaling pathways. During disease resolution , ECM remodeling can occur via degradation by MMPs, and fibrosis may partially regress if the injurious stimulus is removed. Key Message: The liver ECM is a dynamic and biologically active system —its dysregulation is central to fibrosis and cirrhosis, making it a critical target for antifibrotic therapies in chronic liver disease.
The extracellular matrix (ECM) of the liver is a dynamic scaffold that maintains structural integrity, cell signaling, and microvascular architecture. In the normal liver, the ECM is minimal and well organized, composed of collagens (types I, III, IV), laminin, fibronectin, and proteoglycans, particularly within the space of Disse, allowing efficient exchange between hepatocytes and sinusoidal blood.
In health, ECM turnover is tightly regulated by a balance between matrix synthesis and degradation, primarily controlled by hepatic stellate cells and matrix metalloproteinases (MMPs) with their inhibitors (TIMPs). This balance ensures tissue homeostasis and normal liver function.
In liver injury, this balance is disrupted. Chronic insults such as MAFLD, viral hepatitis, or alcohol lead to activation of hepatic stellate cells into fibrogenic myofibroblasts, resulting in excessive deposition of collagen-rich ECM. This causes sinusoidal capillarization, impaired hepatocyte function, and increased intrahepatic resistance, contributing to portal hypertension.
Progressive ECM accumulation leads to fibrosis and ultimately cirrhosis, characterized by architectural distortion and formation of regenerative nodules. Importantly, ECM is not merely structural—it actively modulates cell behavior, inflammation, and fibrosis progression through signaling pathways.
During disease resolution, ECM remodeling can occur via degradation by MMPs, and fibrosis may partially regress if the injurious stimulus is removed.
Key Message:
The liver ECM is a dynamic and biologically active system—its dysregulation is central to fibrosis and cirrhosis, making it a critical target for antifibrotic therapies in chronic liver disease.
Acute liver failure (ALF) is a rapidly progressive syndrome characterized by coagulopathy (INR ≥1.5) and hepatic encephalopathy in patients without prior cirrhosis. The clinical course is unpredictable, with potential for either spontaneous recovery or rapid deterioration , making timely transplant decision-making critical . The cornerstone of management is early identification of patients unlikely to survive without transplantation . Prognostic models such as King’s College Criteria (KCC) and dynamic markers like serum lactate, INR trends, and ammonia levels are widely used to guide listing decisions. However, no single model is perfect— continuous reassessment is essential. Etiology matters. Patients with paracetamol (acetaminophen) toxicity often have better spontaneous recovery rates with optimal medical therapy (including N-acetylcysteine), whereas non-acetaminophen ALF (e.g., viral, autoimmune, indeterminate) more frequently requires transplantation. The timing of transplant listing is the most crucial determinant of outcome. Delayed referral may result in irreversible multi-organ failure or cerebral edema , precluding transplantation. Conversely, premature listing risks unnecessary transplant in patients who may recover. Liver transplantation offers a survival benefit of >70–80% in appropriately selected ALF patients, transforming an otherwise fatal condition into a treatable one. Both deceased donor and living donor transplantation play important roles, especially in regions with limited organ availability. Key Message: In ALF, success depends on early referral, dynamic prognostic assessment, and optimal timing of transplantation —balancing the window between potential recovery and irreversible deterioration to maximize survival benefit.
Acute liver failure (ALF) is a rapidly progressive syndrome characterized by coagulopathy (INR ≥1.5) and hepatic encephalopathy in patients without prior cirrhosis. The clinical course is unpredictable, with potential for either spontaneous recovery or rapid deterioration, making timely transplant decision-making critical.
The cornerstone of management is early identification of patients unlikely to survive without transplantation. Prognostic models such as King’s College Criteria (KCC) and dynamic markers like serum lactate, INR trends, and ammonia levels are widely used to guide listing decisions. However, no single model is perfect—continuous reassessment is essential.
Etiology matters. Patients with paracetamol (acetaminophen) toxicity often have better spontaneous recovery rates with optimal medical therapy (including N-acetylcysteine), whereas non-acetaminophen ALF (e.g., viral, autoimmune, indeterminate) more frequently requires transplantation.
The timing of transplant listing is the most crucial determinant of outcome. Delayed referral may result in irreversible multi-organ failure or cerebral edema, precluding transplantation. Conversely, premature listing risks unnecessary transplant in patients who may recover.
Liver transplantation offers a survival benefit of >70–80% in appropriately selected ALF patients, transforming an otherwise fatal condition into a treatable one. Both deceased donor and living donor transplantation play important roles, especially in regions with limited organ availability.
Key Message:
In ALF, success depends on early referral, dynamic prognostic assessment, and optimal timing of transplantation—balancing the window between potential recovery and irreversible deterioration to maximize survival benefit.
Liver transplantation (LT) is a curative option for hepatocellular carcinoma (HCC) as it treats both the tumor and the underlying cirrhotic liver. The key challenge is appropriate patient selection to maximize survival while minimizing post-transplant recurrence. The benchmark remains the Milan Criteria (single tumor ≤5 cm or up to 3 tumors each ≤3 cm, no vascular invasion or metastasis), achieving 5-year survival >70% with low recurrence rates. Over time, expanded criteria such as the UCSF Criteria and Up-to-7 Criteria have allowed inclusion of selected patients with larger tumor burden while maintaining acceptable outcomes. Modern selection has evolved beyond size and number alone to include tumor biology . Biomarkers such as alpha-fetoprotein (AFP) , radiologic response to therapy, and absence of vascular invasion help identify patients with favorable disease. This has shifted practice toward a “biology-based selection” approach. Bridging and downstaging therapies—such as transarterial chemoembolization (TACE) , radiofrequency ablation, and newer locoregional strategies—play a critical role. Successful downstaging into Milan criteria is now an accepted pathway to transplantation in many centers. Recent advancements include improved imaging, allocation policies, and living donor liver transplantation (LDLT) , particularly relevant in regions with limited deceased donors. Emerging areas include immunotherapy and targeted therapy as neoadjuvant or bridging strategies, though concerns about post-transplant rejection remain. Key Message: Liver transplantation for HCC has evolved from strict size-based criteria to a comprehensive model integrating tumor biology, response to therapy, and dynamic assessment , enabling safe expansion of transplant eligibility while preserving excellent outcomes.
Liver transplantation (LT) is a curative option for hepatocellular carcinoma (HCC) as it treats both the tumor and the underlying cirrhotic liver. The key challenge is appropriate patient selection to maximize survival while minimizing post-transplant recurrence.
The benchmark remains the Milan Criteria (single tumor ≤5 cm or up to 3 tumors each ≤3 cm, no vascular invasion or metastasis), achieving 5-year survival >70% with low recurrence rates. Over time, expanded criteria such as the UCSF Criteria and Up-to-7 Criteria have allowed inclusion of selected patients with larger tumor burden while maintaining acceptable outcomes.
Modern selection has evolved beyond size and number alone to include tumor biology. Biomarkers such as alpha-fetoprotein (AFP), radiologic response to therapy, and absence of vascular invasion help identify patients with favorable disease. This has shifted practice toward a “biology-based selection” approach.
Bridging and downstaging therapies—such as transarterial chemoembolization (TACE), radiofrequency ablation, and newer locoregional strategies—play a critical role. Successful downstaging into Milan criteria is now an accepted pathway to transplantation in many centers.
Recent advancements include improved imaging, allocation policies, and living donor liver transplantation (LDLT), particularly relevant in regions with limited deceased donors. Emerging areas include immunotherapy and targeted therapy as neoadjuvant or bridging strategies, though concerns about post-transplant rejection remain.
Key Message:
Liver transplantation for HCC has evolved from strict size-based criteria to a comprehensive model integrating tumor biology, response to therapy, and dynamic assessment, enabling safe expansion of transplant eligibility while preserving excellent outcomes.
The management of chronic hepatitis B (HBV) is shifting from simple viral suppression to the goal of functional cure , creating a need for more precise biomarkers beyond HBV DNA and ALT. One of the most important advances is quantitative HBsAg , which reflects cccDNA transcriptional activity and helps in treatment monitoring and prediction of response, particularly in interferon-based therapy. Declining HBsAg levels are associated with a higher likelihood of functional cure (HBsAg loss) . Another key marker is HBV core-related antigen (HBcrAg) , which correlates closely with intrahepatic cccDNA and remains detectable even when HBV DNA is suppressed. It is particularly useful in assessing residual viral activity , risk of relapse after stopping therapy, and long-term disease progression. Emerging biomarkers include serum HBV RNA , which reflects active viral replication and transcription. It is increasingly used to evaluate treatment response and risk of viral rebound , especially in patients on nucleos(t)ide analogues. Novel approaches also include quantitative anti-HBc , which provides insight into host immune response, and circulating microRNAs and immune markers , which may help predict disease activity and treatment outcomes. Key Message: New HBV biomarkers—especially HBsAg quantification, HBcrAg, and HBV RNA —are transforming clinical practice by providing deeper insights into viral activity, host response, and treatment endpoints , paving the way toward personalized therapy and functional cure strategies .
The management of chronic hepatitis B (HBV) is shifting from simple viral suppression to the goal of functional cure, creating a need for more precise biomarkers beyond HBV DNA and ALT.
One of the most important advances is quantitative HBsAg, which reflects cccDNA transcriptional activity and helps in treatment monitoring and prediction of response, particularly in interferon-based therapy. Declining HBsAg levels are associated with a higher likelihood of functional cure (HBsAg loss).
Another key marker is HBV core-related antigen (HBcrAg), which correlates closely with intrahepatic cccDNA and remains detectable even when HBV DNA is suppressed. It is particularly useful in assessing residual viral activity, risk of relapse after stopping therapy, and long-term disease progression.
Emerging biomarkers include serum HBV RNA, which reflects active viral replication and transcription. It is increasingly used to evaluate treatment response and risk of viral rebound, especially in patients on nucleos(t)ide analogues.
Novel approaches also include quantitative anti-HBc, which provides insight into host immune response, and circulating microRNAs and immune markers, which may help predict disease activity and treatment outcomes.
Key Message:
New HBV biomarkers—especially HBsAg quantification, HBcrAg, and HBV RNA—are transforming clinical practice by providing deeper insights into viral activity, host response, and treatment endpoints, paving the way toward personalized therapy and functional cure strategies.
Hepatitis B research is entering a transformative phase, shifting focus from lifelong viral suppression to achieving a functional or complete cure . The key unmet need remains elimination of cccDNA and integrated HBV DNA, which sustain viral persistence despite therapy. A major research priority is the development of novel antiviral agents targeting different steps of the viral life cycle. These include entry inhibitors, capsid assembly modulators, siRNA therapies, antisense oligonucleotides, and agents targeting cccDNA transcriptional activity . Combination strategies are being actively explored to enhance efficacy. Equally important is immune restoration . Chronic HBV is characterized by immune exhaustion; therefore, therapies such as therapeutic vaccines, checkpoint inhibitors, and T-cell–based approaches aim to restore antiviral immunity and achieve durable viral control. Another emerging area is the identification and validation of novel biomarkers (e.g., HBcrAg, HBV RNA) to better define treatment endpoints, predict relapse, and guide safe discontinuation of therapy. Research is also expanding into HBV-related hepatocellular carcinoma (HCC) , focusing on early detection, risk stratification, and prevention strategies, even in patients with low viral loads. Finally, implementation science and public health strategies —including improved screening, vaccination coverage, and linkage to care—are critical to achieving global HBV elimination goals. Key Message: The future of HBV lies in combination antiviral and immunomodulatory strategies , guided by novel biomarkers, with the ultimate goal of achieving a functional cure and global disease elimination .
Hepatitis B research is entering a transformative phase, shifting focus from lifelong viral suppression to achieving a functional or complete cure. The key unmet need remains elimination of cccDNA and integrated HBV DNA, which sustain viral persistence despite therapy.
A major research priority is the development of novel antiviral agents targeting different steps of the viral life cycle. These include entry inhibitors, capsid assembly modulators, siRNA therapies, antisense oligonucleotides, and agents targeting cccDNA transcriptional activity. Combination strategies are being actively explored to enhance efficacy.
Equally important is immune restoration. Chronic HBV is characterized by immune exhaustion; therefore, therapies such as therapeutic vaccines, checkpoint inhibitors, and T-cell–based approaches aim to restore antiviral immunity and achieve durable viral control.
Another emerging area is the identification and validation of novel biomarkers (e.g., HBcrAg, HBV RNA) to better define treatment endpoints, predict relapse, and guide safe discontinuation of therapy.
Research is also expanding into HBV-related hepatocellular carcinoma (HCC), focusing on early detection, risk stratification, and prevention strategies, even in patients with low viral loads.
Finally, implementation science and public health strategies—including improved screening, vaccination coverage, and linkage to care—are critical to achieving global HBV elimination goals.
Key Message:
The future of HBV lies in combination antiviral and immunomodulatory strategies, guided by novel biomarkers, with the ultimate goal of achieving a functional cure and global disease elimination.
Assessment of liver fibrosis is central to chronic liver disease management, yet traditional tools like liver biopsy are invasive, and non-invasive scores (FIB-4, APRI) have limited precision. AI-based fibrosis stage estimators are emerging as powerful tools that integrate clinical, laboratory, and imaging data to provide accurate, non-invasive fibrosis staging . AI models—particularly machine learning and deep learning algorithms —can analyze large datasets including routine blood tests, elastography, radiologic imaging, and even histology slides . These models identify complex patterns that are not captured by conventional scoring systems, enabling improved differentiation between early fibrosis (F1–F2) and advanced fibrosis (F3–F4) . A major advantage is dynamic risk prediction . Unlike static scores, AI models can continuously update fibrosis estimates over time, allowing better monitoring of disease progression or regression in response to therapy. Some models also predict clinical outcomes , such as risk of cirrhosis, decompensation, and liver-related mortality. In clinical practice, AI-based tools have the potential to reduce the need for biopsy , optimize patient selection for therapy, and improve screening strategies in high-risk populations such as MAFLD and viral hepatitis. However, challenges remain, including lack of standardization, need for external validation, data heterogeneity, and integration into routine workflows . Key Message: AI-based fibrosis estimators represent the next step in hepatology—offering accurate, non-invasive, and dynamic assessment of fibrosis , with the potential to transform disease monitoring and personalized patient care.
Assessment of liver fibrosis is central to chronic liver disease management, yet traditional tools like liver biopsy are invasive, and non-invasive scores (FIB-4, APRI) have limited precision. AI-based fibrosis stage estimators are emerging as powerful tools that integrate clinical, laboratory, and imaging data to provide accurate, non-invasive fibrosis staging.
AI models—particularly machine learning and deep learning algorithms—can analyze large datasets including routine blood tests, elastography, radiologic imaging, and even histology slides. These models identify complex patterns that are not captured by conventional scoring systems, enabling improved differentiation between early fibrosis (F1–F2) and advanced fibrosis (F3–F4).
A major advantage is dynamic risk prediction. Unlike static scores, AI models can continuously update fibrosis estimates over time, allowing better monitoring of disease progression or regression in response to therapy. Some models also predict clinical outcomes, such as risk of cirrhosis, decompensation, and liver-related mortality.
In clinical practice, AI-based tools have the potential to reduce the need for biopsy, optimize patient selection for therapy, and improve screening strategies in high-risk populations such as MAFLD and viral hepatitis.
However, challenges remain, including lack of standardization, need for external validation, data heterogeneity, and integration into routine workflows.
Key Message:
AI-based fibrosis estimators represent the next step in hepatology—offering accurate, non-invasive, and dynamic assessment of fibrosis, with the potential to transform disease monitoring and personalized patient care.
The gut microbiota is increasingly recognized as a key driver in the pathogenesis and progression of metabolic dysfunction–associated fatty liver disease (MAFLD) . The concept of the gut–liver axis highlights the close anatomical and functional link between the intestine and liver via the portal circulation. In MAFLD, gut dysbiosis —an imbalance in microbial composition—leads to increased intestinal permeability (“leaky gut”), allowing translocation of bacterial products such as lipopolysaccharide (LPS) into the portal vein. This triggers hepatic inflammation through activation of Kupffer cells and innate immune pathways, promoting progression from steatosis to steatohepatitis. Microbiota also influence metabolic pathways . Altered microbial profiles can increase energy harvest , promote insulin resistance , and generate harmful metabolites such as ethanol, secondary bile acids, and trimethylamine (TMA) , all of which contribute to hepatic fat accumulation and inflammation. Another key mechanism involves bile acid signaling . The microbiota modulate bile acid composition, influencing receptors such as FXR and TGR5, which regulate lipid metabolism, glucose homeostasis, and inflammation. Therapeutically, modulation of the microbiota is an area of intense research. Strategies include dietary interventions, probiotics, prebiotics, antibiotics, and fecal microbiota transplantation (FMT) , though robust clinical evidence is still evolving. Key Message: The microbiota is not just a bystander—it is a central player in MAFLD pathogenesis , influencing inflammation, metabolism, and disease progression. Targeting the gut–liver axis may offer novel therapeutic opportunities in the future.
The gut microbiota is increasingly recognized as a key driver in the pathogenesis and progression of metabolic dysfunction–associated fatty liver disease (MAFLD). The concept of the gut–liver axis highlights the close anatomical and functional link between the intestine and liver via the portal circulation.
In MAFLD, gut dysbiosis—an imbalance in microbial composition—leads to increased intestinal permeability (“leaky gut”), allowing translocation of bacterial products such as lipopolysaccharide (LPS) into the portal vein. This triggers hepatic inflammation through activation of Kupffer cells and innate immune pathways, promoting progression from steatosis to steatohepatitis.
Microbiota also influence metabolic pathways. Altered microbial profiles can increase energy harvest, promote insulin resistance, and generate harmful metabolites such as ethanol, secondary bile acids, and trimethylamine (TMA), all of which contribute to hepatic fat accumulation and inflammation.
Another key mechanism involves bile acid signaling. The microbiota modulate bile acid composition, influencing receptors such as FXR and TGR5, which regulate lipid metabolism, glucose homeostasis, and inflammation.
Therapeutically, modulation of the microbiota is an area of intense research. Strategies include dietary interventions, probiotics, prebiotics, antibiotics, and fecal microbiota transplantation (FMT), though robust clinical evidence is still evolving.
Key Message:
The microbiota is not just a bystander—it is a central player in MAFLD pathogenesis, influencing inflammation, metabolism, and disease progression. Targeting the gut–liver axis may offer novel therapeutic opportunities in the future.
Computed tomography (CT) provides a widely available, objective method for assessing hepatic steatosis, especially when imaging is performed for other indications. CT quantifies liver fat based on attenuation values measured in Hounsfield Units (HU) . In normal liver, attenuation is typically higher than spleen due to protein and glycogen content. With increasing fat accumulation, hepatic attenuation decreases . The most commonly used approach is the liver-to-spleen (L/S) attenuation ratio . An L/S ratio <1.0 or an absolute liver attenuation <40 HU (on non-contrast CT) suggests significant steatosis (≥30% fat content). CT allows quantitative and reproducible assessment , and can detect moderate-to-severe steatosis with good accuracy. It is particularly useful in retrospective evaluation , population studies, and opportunistic screening in patients undergoing CT for other reasons. However, CT has important limitations. It is less sensitive for mild steatosis (<20–30%) , and accuracy can be affected by factors such as iron overload, edema, or fibrosis . Additionally, it involves radiation exposure , limiting its role in routine screening or longitudinal follow-up. Compared to newer modalities like MRI-PDFF , CT is less precise for fat quantification but remains practical and accessible in many clinical settings. Key Message: CT-based assessment is a simple, objective, and widely available tool for detecting moderate-to-severe hepatic steatosis, but its limitations in sensitivity and radiation exposure restrict its use as a primary screening or monitoring modality.
Computed tomography (CT) provides a widely available, objective method for assessing hepatic steatosis, especially when imaging is performed for other indications. CT quantifies liver fat based on attenuation values measured in Hounsfield Units (HU).
In normal liver, attenuation is typically higher than spleen due to protein and glycogen content. With increasing fat accumulation, hepatic attenuation decreases. The most commonly used approach is the liver-to-spleen (L/S) attenuation ratio. An L/S ratio <1.0 or an absolute liver attenuation <40 HU (on non-contrast CT) suggests significant steatosis (≥30% fat content).
CT allows quantitative and reproducible assessment, and can detect moderate-to-severe steatosis with good accuracy. It is particularly useful in retrospective evaluation, population studies, and opportunistic screening in patients undergoing CT for other reasons.
However, CT has important limitations. It is less sensitive for mild steatosis (<20–30%), and accuracy can be affected by factors such as iron overload, edema, or fibrosis. Additionally, it involves radiation exposure, limiting its role in routine screening or longitudinal follow-up.
Compared to newer modalities like MRI-PDFF, CT is less precise for fat quantification but remains practical and accessible in many clinical settings.
Key Message:
CT-based assessment is a simple, objective, and widely available tool for detecting moderate-to-severe hepatic steatosis, but its limitations in sensitivity and radiation exposure restrict its use as a primary screening or monitoring modality.
Hepatocellular carcinoma (HCC) is driven not only by genetic mutations but also by epigenetic alterations , which regulate gene expression without changing the DNA sequence. These changes are reversible and dynamic , making them important in both carcinogenesis and therapeutic targeting. One major mechanism is DNA methylation , particularly hypermethylation of tumor suppressor gene promoters, leading to gene silencing. Conversely, global hypomethylation can activate oncogenes and promote genomic instability. Histone modifications —including acetylation and methylation—alter chromatin structure and gene accessibility. Dysregulation of histone-modifying enzymes leads to abnormal activation of pathways involved in cell proliferation, survival, and metastasis . Another key layer involves non-coding RNAs , especially microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). These molecules regulate gene expression post-transcriptionally and are frequently dysregulated in HCC, contributing to tumor growth, angiogenesis, and immune evasion. Epigenetic changes are influenced by chronic liver injury , such as viral hepatitis, MAFLD, and alcohol, linking environmental factors to cancer development. Clinically, epigenetic alterations have potential as biomarkers for early detection, prognosis, and treatment response . Therapeutically, epigenetic drugs (e.g., DNA methyltransferase inhibitors, histone deacetylase inhibitors) are being explored, often in combination with immunotherapy. Key Message: Epigenetic dysregulation is central to HCC pathogenesis—offering promising avenues for early diagnosis, risk stratification, and targeted therapy , with the advantage of being potentially reversible.
Hepatocellular carcinoma (HCC) is driven not only by genetic mutations but also by epigenetic alterations, which regulate gene expression without changing the DNA sequence. These changes are reversible and dynamic, making them important in both carcinogenesis and therapeutic targeting.
One major mechanism is DNA methylation, particularly hypermethylation of tumor suppressor gene promoters, leading to gene silencing. Conversely, global hypomethylation can activate oncogenes and promote genomic instability.
Histone modifications—including acetylation and methylation—alter chromatin structure and gene accessibility. Dysregulation of histone-modifying enzymes leads to abnormal activation of pathways involved in cell proliferation, survival, and metastasis.
Another key layer involves non-coding RNAs, especially microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). These molecules regulate gene expression post-transcriptionally and are frequently dysregulated in HCC, contributing to tumor growth, angiogenesis, and immune evasion.
Epigenetic changes are influenced by chronic liver injury, such as viral hepatitis, MAFLD, and alcohol, linking environmental factors to cancer development.
Clinically, epigenetic alterations have potential as biomarkers for early detection, prognosis, and treatment response. Therapeutically, epigenetic drugs (e.g., DNA methyltransferase inhibitors, histone deacetylase inhibitors) are being explored, often in combination with immunotherapy.
Key Message:
Epigenetic dysregulation is central to HCC pathogenesis—offering promising avenues for early diagnosis, risk stratification, and targeted therapy, with the advantage of being potentially reversible.
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