Introduction

The incidence of liver diseases, including hepatobiliary cancers, acute liver failure (ALF), and acute-on-chronic liver failure (ACLF), is steadily increasing. Liver transplantation (LT) remains a highly effective treatment for advanced liver disease and liver cancer, but its impact is constrained by graft scarcity and a six-month post-transplant mortality of approximately 10%. Graft allocation relies on statistical models designed to ensure fairness among candidates, yet evolving clinical profiles increasingly challenge their accuracy.

ACLF patients now account for a growing proportion of transplant candidates and are frequently prioritized on waiting lists. However, this population is highly heterogeneous: some patients experience prohibitive short-term mortality despite transplantation, whereas others may recover without LT. These uncertainties raise critical questions regarding transplantation futility and emphasize the need for improved predictive tools to better evaluate individual benefit–risk balance. This challenge is further amplified by expanding LT indications, including the demonstrated survival benefit in patients with colorectal cancer liver metastases reported in the first international randomized trial (Adam, Lancet 2024).

In liver oncology, surgical resection remains the reference treatment, while advances in interventional radiology and medical oncology increasingly promote minimally invasive strategies that aim to improve both survival and quality of life. Across transplantation and cancer care, personalized medicine is essential to identify patients with rapid disease progression, refine surveillance strategies, and optimize treatment timing.

Importantly, liver disease is a systemic condition that frequently affects other organs, particularly the heart and lungs. Liver dysfunction can induce or worsen cardiac and pulmonary impairment, thereby influencing eligibility, peri-procedural risk, and long-term outcomes of liver-directed therapies. Cardiac function is a critical determinant in surgical, radiological, and transplant decision-making, yet predicting cardiac complications related to liver disease or its treatments remains challenging. Conversely, patients with primary cardiac disorders, including congenital heart disease, often develop secondary liver pathology.

These complex liver–heart–lung interactions highlight the need for a holistic, multi-organ approach to personalized liver medicine. Within this framework, temporal regulation also plays a role: disruptions of circadian rhythms have been associated with poorer outcomes in large cancer cohorts, supporting the integration of circadian biomarkers through monitoring. Together, multi-organ integration and time-aware assessment offer a more comprehensive strategy to improve outcomes and reduce complications, particularly in the context of liver transplantation.

Project Objectives

To efficiently develop and transfer digital twins, imaging, circardian rythms study and other innovations into clinical practice, we aimed to create a multidisciplinary team. This team will include medical experts in surgery, interventional radiology, hepatology, and intensive care medicine, along with scientists with expertise in computational mechanics, bioengineering, machine learning, light spectroscopy, imaging, circardian rythms and physiology. The goal is to integrate the expertise of scientists and clinicians, foster a collaborative environment that bridges their respective fields, and create new pathways for personalized clinical practice.

The overall objective of this joint INRIA-INSERM team is to enhance and refine surveillance and therapeutic strategies through an innovative approach that integrates multimodal data (clinical, biological, immunological, pathological, and imaging at various scales) with digital twins for liver diseases and related organs. These digital twins will be designed for personalized treatment, supporting planning, adjustments during therapy, and prognosis post-treatment, potentially leading to new treatment strategies. The development of these digital twins will be complemented by research into innovative imaging technologies, particularly the light imaging of excised tissues.

  • European Projects : ERC MoDeLLiver (PI : I. Vignon-Clementel), ARTEMIS EU project (Scientific coordinator : I. Vignon-Clementel ; N. Golse and other colleagues from AP-HP are involved)
  • National Initiatives: BPI MediTwin project (PI : I. Vignon-Clementel), France 2030 BOP’TECH program (PI : E.Vibert), PEPR TREASURE (Co-PI : E. Vibert), ITMO Cancer CIRCADIAN (Co-PI : S. Dulong), PHRC RAPID (PI: N. Golse), PRHC Immunotime (PI : D. Duchemann)

Digital twins and biomarkers for personalized treatment supporting diagnosis, treatment planning, adjustments during therapy, and prognosis are based on 3 main pillars

Integration of hepatology-driven cohorts: : studies on acute-on-chronic liver failure (ACLF), metabolic liver disease, transplant immunology, for development and clinical validation of predictive models

Innovative imaging technologies: : spectral imaging of excised tissues, a hybrid operating room : ultrasound & cone-beam CT, novel tomography imaging

Mathematical models, digital components and clinical application :

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Publications majeures

Les membres de l’équipe (28 HEPA_TEAM_MEMBER_COUNT)

Permanent members (12 HEPA_TEAM_MEMBER_COUNT)

Irene-Vignon-Clementel
Irene-Vignon-Clementel
INRIA (DR)
ICHAI Philippe
ICHAI Philippe
PH (APHP)
VIBERT Eric
VIBERT Eric
PUPH (UPS)
AZOULAY Daniel
AZOULAY Daniel
PUPH (UPS)
SALLOUM Chady
SALLOUM Chady
PH (APHP)
GOLSE Nicolas
GOLSE Nicolas
MCU-PH (UPS)
COILLY Audrey
COILLY Audrey
PUPH (UPS)
FERAY Cyrille
FERAY Cyrille
PUPH (UPS)
KOUNIS Illias
KOUNIS Illias
PH (APHP)
SEBAGH Mylene
SEBAGH Mylene
PH (APHP)
KASCAKOVA Slavka
KASCAKOVA Slavka
MCU (UPS)
DULONG Sandrine
DULONG Sandrine
MCU (UPS)

Etudiants en thèse (6 HEPA_TEAM_MEMBER_COUNT)

Kounis Ilias
Kounis Ilias
PH (APHP)
Rodrigue DOAMBA
Rodrigue DOAMBA
Doctorant
Belkacem ACIDI
Belkacem ACIDI
IGR
Kevin Kakkarian
Kevin Kakkarian
Sophie-Guiti Malekzadeh-Milani
Sophie-Guiti Malekzadeh-Milani
PH (APHP)
Garance Martin
Garance Martin
CCA-AHU (APHP)

Chercheur Inria (10 HEPA_TEAM_MEMBER_COUNT)

Friederike Schäfer
Friederike Schäfer
Postdoctorant (INRIA)
Peter Kottman
Peter Kottman
Doctorant (INRIA)
Pavlos Varsos
Pavlos Varsos
Doctorant (INRIA)
Francesco Songia
Francesco Songia
Doctorant (INRIA)
Sylvain Freud
Sylvain Freud
Ingénieur (INRIA)
Ramdane Bessaid
Ramdane Bessaid
Ingénieur (INRIA)
Morgane Garreau
Morgane Garreau
SRP
Aseem Milind Pradhan
Aseem Milind Pradhan
Postdoctorant (INRIA)
Jérôme Kowalski
Jérôme Kowalski
Doctorant (INRIA)
Mahdi Rezaei Adariani
Mahdi Rezaei Adariani