Etiological diagnosis of dementia using federated AI

I was awarded the Erasmus MC fellowship 2022, check out the project video here!

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Research projects

Dr. Esther Bron is PI in several multicenter projects (CVON Heart Brain Connection, ImProVas, Parelsnoer), and coordinator of the Image & Data Science Platform. She won the Young eScientist Award 2018 by the Netherlands eScience Center and was finalist for the Young Outstanding Researcher Award 2020 by Alzheimer Nederland. Recent research outcomes of Esther Brons team include development of DEBM – a novel disease progression model, which is currently being evaluated in several neurodegenerative diseases (i.e. Alzheimer’s disease, frontotemporal dementia, Creutzfeldt-Jacob’s disease, multiple sclerosis). In addition, the team developed neural network approaches for cross-sectional and longitudinal white matter tract segmentation. Esther (co-)organized two international grand challenges for the objective comparison of algorithms for AD diagnosis (CADDementia challenge) and prediction (TADPOLE challenge).

International collaborations

Dr. Esther Bron collaborates with clinicians, companies, and several national and international research groups. A major partner is the Progression Of Neurodegenerative Disease (POND) group at University College London, with whom she organized the TADPOLE challenge which evaluates which data, processing pipelines, and predictive models provide the best estimates of future AD progression. In 2018, Esther won the Young eScientist Award which led to a collaboration with the Netherlands eScience Center and several international research teams (e.g. National University of Singapore, Tecnologico de Monterrey) on the TADPOLE-SHARE project.

Health-RI

Esther also works for Health-RI as the Imaging Data Coordinator, part of the Architecture team. The mission of Health-RI data is to achieve better health for citizens and patients by reusing health data with an integrated health data infrastructure for research and innovation. Esther is setting up the Imaging Data working group to integrate the infrastructure for finding, getting and using Imaging Data with the eight Health-RI nodes in the Netherlands.

PhD degree

Esther obtained her PhD degree on March 9 2016 with her thesis entitled Advanced MRI Analysis for Computer-Aided Diagnosis of Dementia. In her PhD research under supervision of Prof. W.J. Niessen, dr. S. Klein and dr. M. Smits, she developed and improved multiple methods for computer-aided diagnosis of dementia. As part of this, she organized the CADDementia challenge which compared image-based diagnosis algorithms. In the CADDementia workshop at the MICCAI 2014 conference, she presented the results of this challenge. With this project, Esther was nominated for the Dutch Data Prize 2014 and won a Best Scientific Paper Presentation Award at the European Congress of Radiology in 2015.

Contact

Erasmus MC - University Medical Center Rotterdam

Department of Radiology & Nuclear Medicine
Office Na2506
P.O. Box 2040
3000 CA Rotterdam, NL

Publications

1. Journal Papers

  • J.M. Poos, L.D.M. Grandpierre, E.L. van der Ende, J.L. Panman, J.M. Papma, H. Seelaar, E. van den Berg, R. van ’t Klooster, E.E. Bron, R.M.E. Steketee, M.W.e Vernooij, Y.A.L. Pijnenburg, S.A.R.B. Rombouts, J.C. van Swieten, L.C. Jiskoot, Longitudinal brain atrophy rates in patients with presymptomatic genetic frontotemporal dementia, Neurology, 2022
  • E.E. Bron, S. Klein, A. Reinke, J.M. Papma, L. Maier-Hein, D.C. Alexander, N.P. Oxtoby, Ten years of image analysis and machine learning competitions in dementia, NeuroImage, 2022
  • C.A. de Planque, L. Gaillard, H.A. Vrooman, B. Li, E.E. Bron, M.L.C. van Veelen, I.M.J. Mathijssen, M.H.G. Dremmen, A diffusion tensor imaging analysis of frontal lobe white matter microstructure in trigonocephaly patients, Pediatric Neurology, 2021
  • R.V. Marinescu, N.P. Oxtoby, A.L. Young, E.E. Bron, A.W. Toga, M.W. Weiner, F. Barkhof, N.C. Fox, A. Eshaghi, T. Toni, M. Salaterski, V. Lunina, M. Ansart, S. Durrleman, P. Lu, S. Iddi, D. Li, W.K. Thompson, M.C. Donohue, A. Nahon, Y. Levy, D. Halbersberg, M. Cohen, H. Liao, T. Li, K. Yu, H. Zhu, J.G. Tamez-Pena, A. Ismail, T. Wood, H. Corrada Bravo, M. Nguyen, N. Sun, J. Feng, B.T.T. Yeo, G. Chen, K. Qi, S. Chen, D. Qiu, I. Buciuman, A. Kelner, R. Pop, D. Rimocea, M.M. Ghazi, M. Nielsen, S. Ourselin, L. Sorensen, V. Venkatraghavan, K. Liu, C. Rabe, P. Manser, S.M. Hill, J. Howlett, Z. Huang, S. Kiddle, S. Mukherjee, A. Rouanet, B. Taschler, B.D.M. Tom, S.R. White, N. Faux, S. Sedai, J. de Velasco Oriol, E.E V. Clemente, K. Estrada, L. Aksman, A. Altmann, C.M. Stonnington, Y. Wang, J. Wu, V. Devadas, C. Fourrier, L.L. Raket, A. Sotiras, G. Erus, J. Doshi, C. Davatzikos, J. Vogel, A. Doyle, A. Tam, A. Diaz-Papkovich, E. Jammeh, I. Koval, P. Moore, T.J. Lyons, J. Gallacher, J. Tohka, R. Ciszek, B. Jedynak, K. Pandya, M. Bilgel, W. Engels, J. Cole, P. Golland, S. Klein, D.C. Alexander, The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up, Machine Learning for Biomedical Imaging (MELBA), 2021
  • S. Kuipers, L.M. Overmars, B. van Es, J. de Bresser, E.E. Bron, I.E. Hoefer, L.J. Kappelle, C.E. Teunissen, G.J. Biessels, S. Haitjema, A cluster of blood-based protein biomarkers reflecting coagulation relates to the burden of cerebral small vessel disease, Journal of Cerebral Blood Flow and Metabolism, 2021

2. Conference Papers

3. Book Chapters

4. Conference Proceedings

5. Conference Abstracts

  • J.M. Poos, L.D.M. Grandpierre, E.L. van der Ende, J.L. Panman, J.M. Papma, H. Seelaar, E. van den Berg, R. van ’t Klooster, E.E. Bron, R.M.E. Steketee, M.W.e Vernooij, Y.A.L. Pijnenburg, S.A.R.B. Rombouts, J.C. van Swieten, L.C. Jiskoot, Longitudinal brain atrophy rates in presymptomatic genetic frontotemporal dementia, Alzheimer’s Association International Conference (AAIC), 2022
  • B. Li, X. Liu, W.J. Niessen, E. Wolvius, M.W. Vernooij, M.A. Ikram, G.V. Roshchupkin*, E.E. Bron*, A high-resolution autoencoder for construction of interpretable brain MRI endophenotypes, Organization for Human Brain Mapping Annual Meeting (oral presentation), 2022
  • B. Li, J. de Bresser, W.J. Niessen, M.J.P. van Osch, W.M. van der Flier, G.J. Biessels, M.W. Vernooij, E.E. Bron, Prior-knowledge-informed deep learning for lacune detection andquantification using multi-site MRI, Organization for Human Brain Mapping Annual Meeting, 2022
  • N.L.P. Starmans, F.J. Wolters, A.E. Leeuwis, E.E. Bron, H.-P. Brunner la Rocca, J. Staals, G.J. Biessels, L.J. Kappelle, for the Heart-Brain Connection Consortium, Twenty-four hour blood pressure variability and the volume and progression of cerebral white matter hyperintensities, 8th European Stroke Organisation Conference , 2022
  • V. Venkatraghavan, S. Klein, L. Fani, L.S. Ham, H. Vrooman, M.K. Ikram, W.J. Niessen, E.E. Bron, Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations, ApoE Symposium, 2021

6. Invited Lectures

  • E.E. Bron, Image analysis and machine learning competitions in dementia , POND2022, Center for Medical Image Computing, University College London, 06-07-2022
  • E.E. Bron, Clinical validation of commercial automated volumetric MRI tools in the memory clinic, Symposium on Opportunities and Barriers to Neuroimaging-based AI in Memory Clinics for Age-related Dementias, Annual Meeting of the Organization for Human Brain Mapping, 21-06-2022
  • E.E. Bron, M. Birhanu, Federated learning in population imaging: the Netherlands Consortium of Dementia Cohorts, Health-RI Imaging Community, 12-05-2022
  • E.E. Bron, Machine learning in dementia: imaging, benchmarks and federated learning, Demon Network Seminar, Demon Dementia Network, 06-05-2022
  • E.E. Bron, Can AI aid diagnosis in real patients?, Young Medical Delta Symposium “Designing with Diversity”, 13-04-2022

Team

  • Esther Bron posing for a picture
    Esther Bron, PhD

    Assistant Professor

  • Bo Li
    Bo Li

    Postdoctoral researcher / PhD candidate

  • Wenjie Kang

    PhD Candidate

  • Myrthe van Haaften

    PhD Candidate

  • Jing Yu

    Affiliated PhD Candidate

  • Alexander Harms

    Research Software Engineer

  • Claudia Chinea Hammecher

    MSc Biomedical Engineering, TU Delft

  • Interested in joining?

    See MSc projects here!

Former team members

  • Myrthe van Haaften

    MSc Technical Medicine, EMC/TU Delft/LUMC (2022)

  • Mahlet Birhanu

    Research Software Engineer (2022)

  • Karina Hoefnagel

    BSc Psychobiology, Universiteit van Amsterdam (2022)

  • Dalia Aljawaheri

    MSc Nanobiology, TU Delft (2021)

  • Vikram Venkatraghavan

    Postdoctoral researcher / PhD candidate (2021)

  • Diede Wijnbergen

    MSc Technical Medicine, EMC/TU Delft/LUMC (2021)

  • Lotte Mulder

    MSc Biomedical Engineering, TU Delft (2021)

  • Liselot Goris

    MSc Biomedical Engineering, U Twente (2021)

  • Niels de Bruin

    MSc Computer Science, TU Delft (2020)

  • Thomas Michelotti

    MSc Econometrics, EUR (2020)

  • Savine Martens

    MSc Biomedical Engineering, TU Delft (2020)

  • Theodoros Theodoridis

    MSc Medical Natural Sciences, VU (2019)

  • Marloes Adank

    MSc Biomedical Engineering, TU Delft (2019)

  • Jara Linders

    MSc Brain & Cognitive Sciences, UvA (2019)

  • Leontine Ham

    MSc Medical Natural Sciences, VU (2018)

  • Thomas Michaud

    MSc, ENSEEIHT Toulouse (2018)

  • Sara Laros

    BSc Medical Natural Sciences, VU (2018)

  • Jim Smit

    BSc Clinical Technology, EMC/TU Delft/LUMC (2017)

  • Sandrine Lacomme

    MSc, ENSEEIHT Toulouse (2013)

  • Ines Merida

    MSc, Polytech Marseille (2012)