ULB research| Personal data | Research themes | Ongoing teaching | Publications |
DECAESTECKER Christine
Units
The main research themes of the laboratory focus on the identification and validation of new biomarkers in human cancers with diagnostic, prognostic and theragnostic purposes. The research activities combine fundamental and clinical aspects. For more than 15 years, our investigations have been focused on protein biomarkers in human tissue samples, animals and in vitro models. Immunohistochemistry (IHC) plays an essential role in the validation of these biomarkers because, as opposed to other biochemical approaches, this technology enables morphological control and thus protein localization at histological and cellular levels. A close collaboration with the Laboratory of Image Synthesis and Analysis (LISA, Ecole polytechnique, U.L.B., www.lisa.ulb.ac.be) allows us to develop standardized tools for characterizing protein expression by using the multiple abilities provided by digital image analysis. From this collaboration was created the interfaculty unit, DIAPath (Digital Image Analysis in Pathology, www.ulb.ac.be/rech/inventaire/unites/ULB723.html), which is included in the Center for Microscopy and Molecular Imaging (CMMI, Biopark of Gosselies, www.cmmi.be).Our know-how in biomarkers is often requested by other university and biotech research teams. These collaborations lead us to analyse human tumours from many origins as well as pathologic tissues from other diseases, such as inflammatory diseases, graft-versus-host or diabetes.
Person in charge of the Unit : Oui
LISA (Laboratory of Image Synthesis and Analysis) brings together expertise in image processing and analysis, pattern recognition, image synthesis and virtual reality. Its LISA-IA unit focuses on the fields of image analysis and pattern recognition and develops new methods for 2D and 3D object segmentation, recognition or tracking, multi-modal image registration, as well as machine and deep learning methods for signal and image processing. In the latter context, research is being carried out on the ability to deal with imperfect (weak or noisy) annotations and on methods of evaluating algorithms in such situations where the ground truth is not available. Developed algorithms are related to biomedical and industrial applications. Following a problem-centered approach, the unit tackles all hardware and software aspects of the chain in multidisciplinary teams (MDs, biologists, engineers, computer scientists, mathematicians, as well as art historians and archaeologists) over multi-institutional collaborations to deliver functional applications. The research is funded both by institutional/public funds and industry collaborations. LISA's achievements include one patent, several highly cited biomedical papers, implementation of acquisition and thermoregulation devices for live cell imaging, multi-media event organization and international cultural heritage projects.
Digital Image Analysis in Pathology
Person in charge of the Unit : Oui
DIAPath is a transdisciplinary and interfaculty research unit (Faculties of Medicine and École polytechnique de Bruxelles) integrated into the "Center for Microscopy and Molecular Imaging" (CMMI, Biopark of Gosselies). This unit is the result of a long-standing collaboration between the Pathology Department of the Erasme Hospital and the Laboratory of Image Synthesis and Analysis (LISA, Ecole polytechnique, ULB). Thanks to this collaboration, DIAPath is developing an integrated computational pathology approach for the characterisation, validation and monitoring of histopathological biomarkers in animal and human tissues. The approach developed by DIAPath uses histological, immunohistochemistry (IHC) and chromogenic in situ hybridisation (CISH) techniques. In addition, the unit has developed Whole Slide Imaging for the objective and quantitative characterisation of biomarkers using image analysis aided by artificial intelligence. These biomarkers can be morphological in nature or concern the expression, colocalisation or co-expression of antigens (or other labelled molecules), as well as their distribution in histological samples. Data analysis skills complete the set-up. The overall objective is to extract information useful for understanding disease processes and responses to treatment, as well as to identify and validate new biomarkers useful for diagnostic, prognostic and therapeutic purposes. DIAPath is continuing to develop its skills to extend its tissue labelling, imaging and analysis techniques to fluorescence.
Projetcs
PROTHER-WAL : Proton Therapy Research in Wallonia
Image acquisition and processing for planning and monitoring proton therapy treatment (WP4) From macro (in vivo) to micro (histology) for preclinical animal model, involving image co-registration and quantitative analysis of tissue-based biomarkers Aims: analysis of treatment effects on tumor (microenvironment, healthy tissue, ...), validation of PET/IRM tracers
Whole slide imaging and analysis in digital pathology
Tissue-based biomarker characterization from whole slide image analysis using machine and deep learning and image registration. This also includes the development of methods able to deal with imperfect (weak or noisy) annotations and methods of evaluating algorithms in such situations where the ground truth is not available This research is carried out in close collaboration with the Pathology Department of the Erasme hospital and the DIAPath pole (https://www.cmmi.be/?page_id=12) of the Center for Microscopy and Molecular Imaging (CMMI, Biopark of Gosselies, ULB).
ARIAC (Applications et Recherche pour une Intelligence Artificielle de Confiance)
As part of the dynamics of the Walloon AI programme of Digital Wallonia, its objective is to create IT tools based on trusted artificial intelligence that can offer a competitive advantage to the Walloon industrial sector.
Preclinical Imaging Management System (PIMS)
In strong collaboration with Telemis, this project aims to develop a prototypical system for image gathering, visualisation, communication and archiving, which is adapted to manage the different image modalities included in the CMMI, including non-DICOM modalities and particularly histological and cellular microscopy.
Development of a digital pathology platform within the CMMI (DIAPath department: Digital Image Analysis in Pathology) Provide state-of-the-art expertise in the field of histopathology and related imaging technologies. Meet the specific needs of scientific and industrial partners.
In vitro cell motility analysis
Partners: Unibioscreen S.A. Development of new image analysis method for in-vitro high throughput drug screening using phase-contrast video microscopy.
Setup of computer based tools and 3D biological models (in-vitro and ex-vivo) for a realistic study of cancerous cell migration and an efficient identification of potentially active anti-motility molecules.
Development of a digital pathology platform within the CMMI
Characterization of tissue-based biomarkers using image analysis
Development of image analysis tools, notably involving Artificial Intelligence (machine learning and deep learning), for the characterization of histopathological biomarkers via the extraction of new morphological, protein or genomic descriptors (based on IHC or CISH). In addition to morphological aspects, these descriptors allow to describe staining heterogeneity (on whole slides) via topological aspects (organization, spatial distribution, hot-spots) as well as the colocalization of biomarkers on whole slides and TMA.
Development of computer-based tools for the automatic tracking and the behavior analysis of cancerous cells evolving in in-vitro 2D- or 3D-environment.
Application of assemblies of weakened classifiers to remote sensed image segmentation, in particular using exogeneous data. Partner : IGEAT (ULB).
PROTHER-WAL : Proton Therapy Research in Wallonia
Image acquisition and processing for planning and monitoring proton therapy treatment (WP4) From macro (in vivo) to micro (histology) for preclinical animal model, involving image co-registration and quantitative analysis of tissue-based biomarkers Aims: analysis of treatment effects on tumor (microenvironment, healthy tissue, ...), validation of PET/IRM tracers
