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Digital pathology

At the Anatomical Pathology Department of the Jules Bordet Institute expert pathologists are increasingly turning to digital pathology, a truly essential "e-health" tool for analysing tumours and the tumour microenvironment.

It is the digitisation of microscopic slides on which samples (operative specimens, biopsies, cytological and blood samples, etc.) are placed. 

Synergy Study - breast cancer
Synergy clinical study : metastatic lymph node (breast carcinoma)

These slides are digitised using the latest generation scanners, at the cutting edge of technology. It is thanks to the combined efforts of pathologists and IT experts that it has been possible to develop and use these "modern microscopes". They are able to digitise, annotate and classify the slides on platforms that are easily accessible and totally secure.  Digital pathology facilitates the painstaking work of analysing cells and biological tissue that is the day-to-day work of pathologists. The Anatomical Pathology Department of the Jules Bordet Institute is committed to this development that marks a new stage in data management and computerisation.     

Digital pathology has a number of benefits :

  • It permits a morphological images storage that over time is more efficient and of a higher quality. The slides are digitised and no longer need to be conserved physically, thereby avoiding any loss of slide quality (over time). 
  • It represents the future of histopathology (the tissue analyse with a microscope) through a more precise diagnosis thanks to the various possibilities offered by artificial intelligence.
  • It permits an easy and secure data sharing with other experts to arrive at a medical opinion, including across the globe. 

Research

Publications, congress presentations, projects...
 

Virtual ESMO Annual 2020 congress

First findings from SYNERGY, a phase I/II trial testing the addition of the anti-CD73 oleclumab to the anti-PD-L1 durvalumab and chemotherapy as 1st line therapy for patients with metastatic triple-negative breast cancer
D. Eiger, C. Maurer, M. Brandão, P. Aftimos, K. Punie, D.Taylor, T. Van den Mooter, R.Poncin, JL. Canon, F. Duhoux, V. Casert, F. Clatot, C.Velghe, L. Craciun, M. Paesmans, E. de Azambuja, M. Ignatiadis, D. Larsimont, M. Piccart-Gebhart, L. Buisseret

Best oral presentation-Belgian Week of Pathology 2021

Implementation of automatic quantification of Ki-67 in well- differentiated gastro-entero-pancreatic neuroendocrine tumors: towards standardized evaluation into daily practice.
F. Lifrange, N. Gumus, L. Craciun, M. Gomez Galdon, P. Demetter, L. Verset.

Breast 2020 Dec; 54:179-186

Digital analysis of distant and cancer-associated mammary adipocytes.
E. Isnaldi, F. Richard, M. De Schepper, D. Vincent, S. Leduc, M. Maetens, T. Geukens, G. Floris, G. Rouas, F. Cardoso, C. Sotiriou, G. Zoppoli, D. Larsimont, E. Biganzoli, C. Desmedt.

J Clin Endocrinol Metab 2018

Distinctive Desmoplastic 3D Morphology Associated With BRAFV600E in Papillary Thyroid Cancers.
M. Tarabichi, A. Antoniou, S. Le Pennec, D. Gacquer, N. de Saint Aubain, L. Craciun, T. Cielen, I. Laios, D. Larsimont, G. Andry, JE. Dumont, C. Maenhaut, V. Detours.

San Antonio Breast Cancer Symposium 2021

Unravelling spatial tumor organization and heterogeneity in lobular breast cancer using spatial transcriptomics.
L. Collet, M. Serra, M. Rediti, F. Lifrange, D. Venet, X. Wang, D. Vincent, G. Rouas, D. Fimereli, D. Gacquer, AJ. Garcia, I. Veys, L. Craciun, D. Larsimont, M. Vikkula, F. Duhoux, F. Rothé, C. Sotiriou.

San Antonio Breast Cancer Symposium 2021

Integrating spatial transcriptomics and high-resolution morphological annotation to investigate tumor heterogeneity and PAM50 molecular subtyping in lobular breast cancer.
M. Serra, L. Collet, M. Rediti, F. Lifrange, D. Venet, X. Wang, D. Vincent, G. Rouas, D. Fimereli, D. Gacquer, AJ. Garcia, I. Veys, L. Craciun, D. Larsimont, M. Vikkula, F. Duhoux, F. Rothé, C. Sotiriou.

Molecular and Cellular Endocrinology 2022

Thyroid cancer under the scope of emerging technologies.
M. Tarabichi, P. Demetter, L. Craciun, C. Maenhaut, V. Detours.

NCI

Year 3: High-throughput truthing of microscope slides to validate artificial intelligence algorithms analyzing digital scans of pathology slides: data collection to create the medical device development tool (MDDT).
S.N Dudgeon, S. Wen, M. G Hanna, R. Gupta, M. Amgad, M. Sheth, H. Marble, R. Huang, M. D Herrmann, C. H Szu, D. Tong, B. Werness, E. Szu, D. Larsimont, A. Madabhushi, E. Hytopoulos, W. Chen, R. Singh, S. N Hart, A. Sharma, J. Saltz, R. Salgado, B. D Gallas.

J Pathol Inform 2021

A pathologist-annotated dataset for validating artificial intelligence: A project description and pilot study.
S. N Dudgeon, S. Wen, M. G Hanna, R. Gupta, M. Amgad, Ma. Sheth, H. Marble, R. Huang, M. D Herrmann, C. H Szu, D. Tong, B. Werness, E. Szu, D. Larsimont, A. Madabhushi, E. Hytopoulos, W. Chen, R. Singh, S. N Hart, A. Sharma, J. Saltz, R. Salgado, B. D Gallas.

BMC Cancer 2020

Retrospective analysis of the immunogenic effects of intra-arterial locoregional therapies in hepatocellular carcinoma: a rationale for combining selective internal radiation therapy (SIRT) and immunotherapy.
L. Craciun, R. de Wind, P. Demetter, V. Lucidi, A. Bohlok, S. Michiels, F. Bouazza, M. Vouche, I. Tancredi, G. Verset, S. Garaud, C. Naveaux, M. Gomez Galdon, K. Willard Gallo, A. Hendlisz, I. Duran Derijckere, P. Flamen, D. Larsimont, V. Donckier.