OpenLiverLab - Open source library for the liver, from images to clinicians

Leveren er kroppens største indre organ og en kraftstasjon som lagrer essensielle vitaminer og mineraler, utfører over 500 metabolske funksjoner og renser blodet vårt. Å forstå dens komplekse struktur er avgjørende, spesielt når det gjelder å diagnostisere og behandle leverkreft, en av de vanligste krefttypene i verden. I nesten to tiår har leger brukt datamaskinassisterte systemer (CAS) for å hjelpe til med å planlegge og veilede leverkreftbehandlinger som kirurgi og tumorablasjon. Disse systemene forbedrer nøyaktigheten av tumorlokalisering og øker legens selvtillit under prosedyrer. Imidlertid er det utfordrende å lage pasientspesifikke modeller for disse systemene på grunn av leverens intrikate nettverk av blodårer og gallekanaler. OpenLiverLab-prosjektet er et banebrytende samarbeid mellom to ekspertteam fra University Clermont Auvergne og Oslo universitetssykehus. Dette prosjektet har som mål å utvikle avansert programvare som kan lage detaljerte, personlige levermodeller. Disse modellene vil hjelpe leger med å planlegge og utføre leverkreftbehandlinger mer effektivt. Ved å kombinere ekspertise innen biologi, informatikk og medisinsk avbildning, håper OpenLiverLab-prosjektet å overvinne de nåværende utfordringene med å modellere leverens vaskulære nettverk og forbedre resultatene for leverkreftpasienter.

The OpenLiverLab project has contributed the consolidation of the combined Slicer-Liver and R-VesselX plugins in 3D Slicer, providing clinicians with a powerful software toolkit for (1) segmentation of liver anatomy, (2) advanced analytics of liver anatomy, including functional separation of the liver and (3) planning of liver therapies. One important result of this project is the verification of cross-compatibility of the software tools in Slicer-Liver and R-VesselX. Currently, the two teams are working on the generation of a dataset resulting from the integration of Slicer-Liver and R-VesselX. Slicer-Liver and R-VesselX are the most comprehensive software extensions for 3D Slicer and the possibility to join them together enables a solid ecosystem for managment of liver cancer therapies research

For nearly two decades, surgeons and interventional radiologists have employed computer-assisted systems (CAS). These systems have the ability to support the decision-making process for planning and guiding liver cancer therapies like surgical resection, tumor ablation or trans-arterial chemo-embolization (TACE). CAS have shown not only to improve the tumor localization, but also to increase the orientation and the confidence of the physician during the therapy. However, CAS heavily rely on the use of patient specific models that are difficult to obtain and analyze. In the liver, particularly, the complexity lies in its complicated network of vessels and bile ducts. Investigating human vascular networks has been a source of various multidisciplinary research implying biology, physiology, mathematics, computer science, among others. The increasing evolution of computer science in this research has raised the interest in numerically modeling vessels. Despite numerous developments in this field, computer extraction and modeling of vascular networks from images is still an open challenge. The goal of the OpenLiverLab project is to consolidate a workflow comprising the analysis and generation of patient-specific liver models (segmentation, geometric modeling and perfusion modeling) to support planning and guidance of liver cancer therapies (resection and ablation). This is a new cooperation between two complementary teams (UCA and OUS) that will enable the development of novel softwares dedicated to clinicians. Two major clinical applications are targeted, and comply with current research topics for the liver: hepatic surgery and TACE. This project benefits from the results obtained by 2 national fundings: the R-Vessel-X project - Robust vascular network extraction and understanding within hepatic biomedical images and the ALive project - Analytics for computation and visualization of liver resections.