Autoimmune Hepatitis (AIH) is a liver disease with a wide clinical spectrum, driven by an abnormal immune response against the liver parenchyma. Challenges persist especially in terms of accurate diagnosis of acute onsets and differential diagnosis, outlined by the European Association for the Study of Liver guidelines. Our training cohort comprised 170 untreated AIH and 232 control cases with a variety of differential diagnosis. Ground Truth was the integrative diagnosis of the clinical, histological, biological and treatment response data. We trained a multiple-instance deep-learning model (DLM) from Whole Slide Images alone for the initial diagnosis of AIH. The model was then tested on an external dataset of 61 AIH and 124 controls. Prospective real-life testing of the model was conducted between January and June 2025. Our DLM “Artificial Intelligence On Liver Immunity (AIOLI)” achieved an AUC of 0,92 ± 0,02 on the training dataset and an AUC of 0,74 on the external dataset; in detail, it achieved an AUC of 0,89 for the differential diagnosis of AIH vs. acute alcoholic hepatitis, 0,98 vs. MASH, 0,42 vs. Hepatitis B Virus and 0,76 vs. drug-induced liver injuries. Retrieval of the five most predictive tiles allowed to identify patterns used by the model for prediction and provided interpretability. In the prospective setting, AIOLI achieved a Sensibility of 0.86, a Specificity of 0.76, a F1-score of 0.69 and an AUC of 0.73. AIOLI is an interpretable DLM able to segregate AIH from a variety of control cases with performances comparable to those of an expert liver pathologist, setting a benchmark for future research. We plan to enhance our performances by enriching our dataset, and to validate this approach with a multicentric deployment.

BACKGROUND & AIMS:Unresectable intrahepatic cholangiocarcinoma (iCCA) has a poor prognosis, with limited curative options. Chemotherapy combined with selective internal radiation therapy (SIRT) has shown promising results in tumor response and survival. We evaluated liver transplantation (LT) outcomes following this neoadjuvant approach in patients with liver-limited iCCA in our center. METHOD:We retrospectively included all patients who underwent LT in the Rennes University Hospital for unresectable, locally advanced iCCA following neoadjuvant treatment with a combination of chemotherapy and SIRT. RESULTS:Six patients underwent transplantation between 2010 and 2024. The median timeframe from diagnosis to listing was 351 days (IQR 250-558 days). The median time from listing to LT was 114 days (44-192 days). Age was 50.7 years (39.9-59.3 years) with a sex ratio of 1:1. The initial total tumor size was 100 mm (65-115 mm), with one tumoral lesion (1-1). Neoadjuvant treatment consisted of a gemcitabine-cisplatin regimen in four of six patients (66.7%), while one patient received cisplatin combined with 5-fluorouracil. The median follow-up was 4.9 years (1.8-8.8 years). The median length of hospitalization following LT was 12 days (10-20 days). Five-year overall survival was 100%, while 5-year progression-free survival was 44.4% (95% CI 8.9-88.0%) with three patients who experienced iCCA recurrence on Days 573, 577, and 1,180 after LT. No patient has yet died from tumor progression. CONCLUSIONS:This study presents one of the first series of unresectable iCCA cases treated with a neoadjuvant combination of SIRT and chemotherapy. Very selected patients (six patients over 15 years) who underwent LT demonstrated high long-term survival rates and an acceptable recurrence rate, even in the presence of large tumor sizes. Prospective trials evaluating this neoadjuvant combination are awaited. IMPACT AND IMPLICATIONS:Liver transplantation is not currently considered a standard therapeutic option for patients with unresectable, liver-limited intrahepatic cholangiocarcinoma because of historically poor outcomes. This study provides a scientific rationale for reconsidering transplantation in a highly selected subgroup of patients who achieve sustained disease control after neoadjuvant chemotherapy combined with selective internal radiation therapy. The results are particularly relevant for transplant hepatologists, oncologists, and surgeons, as they suggest that treatment response and prolonged disease stability may better predict post-transplant outcomes than tumor size alone. Clinically, these findings support a multidisciplinary, response-based selection strategy with a 'test-of-time' approach, while acknowledging the small sample size and retrospective design, and highlight the need for prospective studies and structured allocation frameworks to safely expand this approach.

BACKGROUND:Normothermic machine perfusion (NMP) enables metabolic restoration and viability testing of liver grafts, but current viability criteria incompletely predict post-transplant outcomes. The molecular basis of graft resilience or biliary vulnerability remains unclear. This study aimed to characterise tissue-level proteomic trajectories during NMP and early reperfusion to identify molecular signatures associated with biliary complications after liver transplantation (LT). METHODS:This prospective, single-centre study was conducted at Rennes University Hospital. Twenty donation-after-brain-death (DBD) livers underwent NMP; sixteen transplanted grafts with complete sequential biopsies and ≥ 6 months of follow-up were analysed. Biopsies were collected after cold storage (B1), at the end of NMP (B2), and 1 h after graft reperfusion (B3). Proteins were quantified by high-resolution LC-MS/MS and analysed with Proteome Discoverer 3.1/Chimerys. Pathway enrichment used Ingenuity Pathway Analysis to compare grafts with and without biliary complications. RESULTS:Principal component analysis revealed distinct proteomic profiles between grafts with and without complications at all biopsy time points. During NMP (B2/B1), uncomplicated grafts showed glycolytic activation with attenuation of oxidative phosphorylation, whereas complicated grafts showed blunted glycolysis and mild OXPHOS upregulation. At reperfusion (B3/B2), complicated grafts displayed induction of translational and endoplasmic-reticulum-stress pathways, while resilient grafts maintained proteasome-related protein turnover and enrichment of a hypoxia-response signature driven by ELOC and proteasome subunits. CONCLUSIONS:Sequential tissue proteomics during NMP reveals divergent metabolic and proteostatic adaptations linked to biliary outcomes. Glycolytic activation with preserved protein turnover characterises resilient grafts, whereas translational and ER-stress programmes predominate in complicated ones. These insights may refine viability assessment beyond biochemical criteria.

Understanding tumor heterogeneity by examining how cells are organized in tissues is essential to better decipher the biological processes involved in cancer and to improve therapeutic management. Here, we present a protocol for a multiplex immunofluorescence (mIF) technique that enables the detection of an array of protein markers and allows immunophenotyping on a single section of human hepatocellular carcinoma. We describe the procedures for antibody labeling, mIF image acquisition using Cell DIVE, and preliminary analysis using QuPath software.

Background: Transient elastography (TE) can be used to accurately screen for severe liver fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD). However, some studies suggest that steatosis influences liver stiffness measurement (LSM). Thus, treatment that modifies steatosis might impact the relevance of TE in the management of patients. The use of magnetic resonance imaging (MRI)-proton density fat fraction (PDFF) has shown good reliability and accuracy for quantifying hepatic steatosis. Therefore, the aim of our study was to evaluate the performance of TE combined with MRI-PDFF for the diagnosis of severe fibrosis in patients with MASLD. The study is registered at ClinicalTrials.gov (NCT03245606). Methods: In this prospective multicenter study, patients with MASLD and indication for biopsy underwent MRI and TE within the same month. Biopsies were centrally reviewed using the steatosis, activity, and fibrosis (SAF) score. PDFF was centrally quantified using MRQuantif software. AUROCs for the diagnosis of fibrosis ≥F2 and ≥F3 were determined for LSM alone and LSM combined with PDFF as a continuous or categorical variable in a logistic regression. Results: In total, 208 patients were studied. The median age was 59 years, 63.9% were men, the median body mass index (BMI) was 31.2 kg/m2, and 47.6% had diabetes. Of these patients, 56.3% had fibrosis ≥F2 and 30.3% had fibrosis F3–F4 on biopsy. Based on the SAF score, 35.7% of patients had MASH. The AUROC of LSM for fibrosis ≥F3 was 0.78 (95% CI 0.72–0.85), with no significant difference compared with the AUROC of LSM combined with PDFF (0.78; 95% CI 0.72–0.85; p = 0.96). The AUROC of LSM for fibrosis ≥F2 was 0.67 (95 % CI 0.60–0.74), with no significant difference compared with the AUROC of LSM combined with PDFF (0.66; 95% CI 0.59–0.73, p = 0.48). Conclusions: TE performance for the diagnosis of liver fibrosis does not appear to be affected by the level of liver steatosis. Thus, quantifying hepatic steatosis using MRI-PDFF allows a comprehensive and accurate assessment of liver steatosis. Impact and implications: TE is a reliable tool for screening severe liver fibrosis in patients with MASLD. However, some studies suggest that the severity of steatosis influences LSM. Thus, treatment that modifies steatosis might impact the relevance of TE in the management of patients. This prospective multicenter study evaluated whether combining TE with MRI-PDFF, a precise method for measuring liver fat, could improve diagnostic accuracy for severe fibrosis in patients with MASLD. Our results show that TE performance in fibrosis diagnosis remains consistent regardless of steatosis levels, reinforcing the use of non-invasive methods, particularly TE, for regular patient monitoring, even as steatosis levels fluctuate.

In this proof-of-concept study, we devised a calibration method with matrix-matched samples (phantoms) and performed quantitative LASER Ablation Inductively Coupled Mass Spectrometry (LA-ICP-MS) on 16 paraffin embedded human liver samples with genetic hemochromatosis (GH) and 5 liver resection specimens with hepatocellular carcinoma arising on GH, with correlation to histology and integration into our lab's workflow. LA-ICP-MS enables easy recognition of histological structures including portal tracts, fibrous septa and centrilobular veins. Compared to adjacent non-tumoral liver, hepatocellular carcinoma presented a decreased iron concentration (p = 0.034) and no significant difference in copper concentration. This profile was similar to that of three Iron Free Foci identified on genetic hemochromatosis liver biopsies which showed decreased concentration of iron compared to the adjacent parenchyma (p = 0.013) and no significant difference in copper concentration. LA-ICP-MS outperformed Perls' stain for iron detection in liver achieving a detection limit below 1 µg.g-1 and a lateral resolution of 5 μm and can be performed on 3 μm-thick paraffin-embedded slides with few pre-analytics constraints, enabling topographical analysis and quantification, overlay with histological stains and a preservation of the histological material contrary to classic ICP-MS. This new approach opens retrospective analysis of archived histological samples and may prove a tool in the evaluation of metal-related afflictions.

Background & Aims: Owing to unexplained interpatient variation and treatment failure in hepatocellular carcinoma (HCC), novel therapeutic approaches remain an urgent clinical need. Hepatic neurons, belonging to the autonomic nervous system (ANS), mediate liver/whole body crosstalk. Pathological innervation of the ANS has been identified in cancer, nurturing tumor stroma and conferring stronger carcinogenic properties. Methods: We characterized the innervation of liver tumors from the French Liver Biobank, then applied bioinformatics to TCGA (The Cancer Genome Atlas), several other datasets and a European validation cohort, to re-evaluate patient stratification. Cell biology and pharmacology studies were also performed. Results: Densely packed nucleated DCX+, synaptophysin+, NeuN+, VAChT+, TH-, CD31-, CD45- clusters, to date undetected, were identified in human HCCs, and independently confirmed by single-cell RNA sequencing data. Using the new concept of a neuronal score, human and rat HCCs displayed tightly netrin-1-associated neural reconfiguration towards cholinergic polarity, which was associated with chronic liver disease progression, cancer onset and many features of aggressive (proliferative class) HCC, including shortened survival. This score was conditioned by tumoral hepatocytes, and predicted sorafenib efficacy in the STORM HCC phase III trial. Conversely, intratumoral adrenergic lymphocytes were enriched in TEMRA and cytotoxic phenotypes. Amongst all cholinergic transcripts, the medically targeted CHRM3 receptor was enriched and associated with pathogenic traits in HCC, as well as poor prognosis in HCC stages 1-2, while its level dropped upon experimental re-differentiation. Its pharmacological inhibition with low concentrations of anticholinergic drugs, but not cholinomimetics, decreased anchorage-independent growth and anoikis, synergized with sorafenib and lenvatinib in HCC class 1 to 3 lines, yet not in primary human hepatocytes, and preserved mature hepatocyte functions. Conclusion: These data identify cholinergic processes as instrumental in liver carcinogenesis and support the use of EMA/FDA-approved cholinergic drugs in HCC research. Impact and implications:: Hepatocellular carcinoma (HCC) care has long been hampered by the enigmatic nature of disease evolution, as well as of response or resistance to treatment. Hepatic neurons are likely the least studied liver cell type and mediate patients singularities from the ANS to the organ in real-time. Cholinergic inputs identified in this study as pathogenic may be targeted with the well charted pharmacopoeia of neurotropic drugs already available, for basic or clinical research purposes, with an expected high level of safety.

Langerhans cell histiocytosis (LCH) is a disease whose physiopathology remains unclear, involving both inflammatory processes and clonal proliferation. It is observable at any given age, although about ten times more frequent in children than adults. Hepatic involvement is not rare, mostly part of a systemic disease, and linked to a poor prognosis. We report here a case of LCH with solitary hepatic involvement in a 74 year -old patient. This case demonstrated molecular anomaly of the MAPK pathway, BRAF N486 P490del. Through this observation, we precise the epidemiological and histological aspects and diagnostic criteria of this rare disease. (c) 2023 Elsevier Masson SAS. All rights reserved.

Iron is essential for functioning of cells and of the body as a whole. Perls staining allows the histopathological identification of iron deposits. By classifying hepatic siderosis as parenchymal, mesenchymal or mixed, it may guide the search for its etiology. HFE1 hemochromatosis is the most common siderosis. Its diagnosis is currently based on genetic analysis. Its expressivity being variable and its penetrance incomplete, the demonstration of hepatic siderosis may represent a mode of discovery.

Le fer est indispensable au fonctionnement cellulaire et de l’organisme dans son ensemble. La coloration de Perls permet l’identification histopathologique de dépôts sidériques. En classant les sidéroses hépatiques en parenchymateuse, mésenchymateuse ou mixte, il est possible d’orienter la recherche étiologique. L’hémochromatose HFE1 est la sidérose la plus fréquente. Son diagnostic repose actuellement sur l’analyse génétique. Son expressivité étant variable et sa pénétrance incomplète, la mise en évidence d’une sidérose hépatique peut représenter un mode de découverte.

L’histiocytose langerhansienne (LCH) est une maladie de physiopathologie encore incertaine, impliquant à la fois des processus inflammatoires et une prolifération clonale. Elle est observable à tout âge, bien que dix fois plus fréquente chez les enfants que chez les adultes. Une atteinte hépatique n’est pas rare, s’intégrant le plus souvent dans une maladie systémique, et considérée péjorative. Nous rapportons ici un cas d’histiocytose langerhansienne de localisation hépatique exclusive chez un patient de 74ans. Ce cas présentait une anomalie moléculaire de la voie des MAPK, BRAF N486_P490del. À travers cette observation, nous préciserons les aspects épidémiologiques et histologiques ainsi que la démarche diagnostique à effectuer devant ce type de pathologie rare.

To validate the proton density fat fraction (PDFF) obtained by the MRQuantif software from 2D chemical shift encoded MR (CSE–MR) data in comparison with the histological steatosis data. This study, pooling data from 3 prospective studies spread over time between January 2007 and July 2020, analyzed 445 patients who underwent 2D CSE–MR and liver biopsy. MR derived liver iron concentration (MR–LIC) and PDFF was calculated using the MRQuantif software. The histological standard steatosis score (SS) served as reference. In order to get a value more comparable to PDFF, histomorphometry fat fraction (HFF) were centrally determined for 281 patients. Spearman correlation and the Bland and Altman method were used for comparison. Strong correlations were found between PDFF and SS (rs = 0.84, p < 0.001) or HFF (rs = 0.87, p < 0.001). Spearman’s coefficients increased to 0.88 (n = 324) and 0.94 (n = 202) when selecting only the patients without liver iron overload. The Bland and Altman analysis between PDFF and HFF found a mean bias of 5.4

The diagnosis of alcoholic steatohepatitis (ASH) is based on liver biopsy, which is costly and invasive with non-negligible morbidity. The aim of this study was to evaluate the accuracy of circulating cytokeratin 18 M65 fragment (K18-M65) alone or in association with other markers for the non-invasive diagnosis of ASH in patients ongoing alcohol withdrawal. This study examined the serum level of K18-M65 in a test cohort of 196 patients. All patients underwent liver biopsy, transient elastography (TE) and serum collection. The diagnostic accuracy of K18-M65 alone or combined with clinico-biological data was assessed and the best defined cut-offs were validated in an independent validation cohort of 58 patients. K18-M65 had an area under the curve (AUC) of 0.82 (test cohort) and 0.90 (validation cohort). Using two cut-off decision points, K18-M65 was able to classify 46.9% (test cohort) and 34.5% (validation cohort) of patients with 95% sensitivity or specificity. Combining K18-M65, alpha-2-macroglobulin, TE, body mass index, and age, we created a score allowing accurate diagnosis of ASH with an AUC of 0.93 (test cohort) and 0.94 (validation cohort). This new score was able to rule out or rule in the diagnosis of steatohepatitis for probability ≤0.135 or ≥0.667 respectively in more than two-thirds of patients. We propose a new validated non-invasive score for the diagnosis of ASH in patients ongoing alcohol withdrawal. This score can help to identify patients that may benefit from potential therapeutics or motivate them to reduce alcohol consumption.

Background & Aims:Metabolic dysfunction-associated steatotic liver disease (MASLD) results in steatosis, inflammation (steatohepatitis), and fibrosis. Patients with MASLD more likely develop liver injury in coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As viral RNA has been identified in liver tissues, we studied expression levels and cellular sources of the viral receptor angiotensin-converting enzyme 2 (ACE2) and coreceptors in MASLD and fibroinflammatory liver diseases. Methods:We built a transcriptomic MASLD meta-dataset (N = 243) to study SARS-CoV-2 receptor expression and verified results in 161 additional cases of fibroinflammatory liver diseases. We assessed the fibroinflammatory microenvironment by deconvoluting immune cell populations. We studied the cellular sources of ACE2 by multiplex immunohistochemistry followed by high-resolution confocal microscopy (N = 9 fatty livers; N = 7 controls), meta-analysis of two single-cell RNA sequencing datasets (N = 5 cirrhotic livers; N = 14 normal livers), and bulk transcriptomics from 745 primary cell samples. In vitro, we tested ACE2 mRNA expression in primary human hepatocytes treated with inflammatory cytokines, bacterial lipopolysaccharides, or long-chain fatty acids. Results:We detected ACE2 at the apical and basal poles of hepatocyte chords, in CLEC4M+ liver sinusoidal endothelial cells, the lumen of ABCC2+ bile canaliculi, HepPar-1+-TMPRSS2+ hepatocytes, cholangiocytes, and CD34+ capillary vessels. ACE2 steeply increased between 30 and 50 years of age; was related to liver fat area, inflammation, high immune reactivity, and fibrogenesis; and was upregulated in steatohepatitis. Although ACE2 mRNA was unmodified in alcoholic or viral hepatitis, it was upregulated in fibroinflammatory livers from overweight patients. In vitro, treatment of primary human hepatocytes with inflammatory cytokines alone downregulated but long chain fatty acids upregulated ACE2 mRNA expression. Conclusions:Lipid overload in fatty liver disease leads to an increased availability of ACE2 receptors. Impact and implications:COVID-19 can be a deadly disease in vulnerable individuals. Patients with fatty liver disease are at a higher risk of experiencing severe COVID-19 and liver injury. Recent studies have indicated that one of the reasons for this vulnerability is the presence of a key cell surface protein called ACE2, which serves as the main SARS-CoV-2 virus receptor. We describe the cellular sources of ACE2 in the liver. In patients with fatty liver disease, ACE2 levels increase with age, liver fat content, fibroinflammatory changes, enhanced positive immune checkpoint levels, and innate immune reactivity. Moreover, we show that long chain fatty acids can induce ACE2 expression in primary human hepatocytes. Understanding the cellular sources of ACE2 in the liver and the factors that influence its availability is crucial. This knowledge will guide further research and help protect potentially vulnerable patients through timely vaccination boosters, dietary adjustments, and improved hygiene practices.

Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), KRAS, and BRAF mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to predict tumor status. In this systematic review, we evaluated the role of AI in predicting MSI status, KRAS, and BRAF mutations in colorectal cancer. Studies published in PubMed up to June 2023 were included (n = 17), and we reported the risk of bias and the performance for each study. Some studies were impacted by the reduced number of slides included in the data set and the lack of external validation cohorts. Deep learning models for the d-MMR/MSI status showed a good performance in training cohorts (mean AUC = 0.89, [0.74–0.97]) but slightly less than expected in the validation cohort when available (mean AUC = 0.82, [0.63–0.98]). Contrary to the MSI status, the prediction of KRAS and BRAF mutations was less explored with a less robust methodology. The performance was lower, with a maximum of 0.77 in the training cohort, 0.58 in the validation cohort for KRAS, and 0.82 AUC in the training cohort for BRAF.

Background: Artificial Intelligence (AI)-based Deep Neural Networks (DNNs) can handle a wide range of applications in image analysis, ranging from automated segmentation to diagnostic and prediction. As such, they have revolutionized healthcare, including in the liver pathology field. Objective: The present study aims to provide a systematic review of applications and performances provided by DNN algorithms in liver pathology throughout the Pubmed and Embase databases up to December 2022, for tumoral, metabolic and inflammatory fields. Results: 42 articles were selected and fully reviewed. Each article was evaluated through the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, highlighting their risks of bias. Conclusions: DNN-based models are well represented in the field of liver pathology, and their applications are diverse. Most studies, however, presented at least one domain with a high risk of bias according to the QUADAS-2 tool. Hence, DNN models in liver pathology present future opportunities and persistent limitations. To our knowledge, this review is the first one solely focused on DNN-based applications in liver pathology, and to evaluate their bias through the lens of the QUADAS2 tool.