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A Two-Species Model for Abnormal Tau Dynamics in Alzheimer’s Disease

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops (MICCAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14394))

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Abstract

We construct image-driven, mechanism-based biomarkers for Alzheimer’s disease (AD). These markers are parameters and predictions of a biophysical model of misfolded tau propagation, which is calibrated using positron emission tomography (PET) data. An example of such a model is the widely used single-species Fisher-Kolmogorov model (FK). In this article, we reveal a qualitative inconsistency between tau observations and the FK model predictions: FK has a bias towards maintaining the maximum misfolded tau to region of the initial misfolding, which most clinicians and modelers consider it to be the entorhinal cortex (EC). To partially address this EC bias, we introduce a simplified Heterodimer Fisher-Kolmogorov model (HFK) that tracks the dynamics of both abnormal and normal tau. To construct both FK and HFK models, we use a coarse, graph-based representation where nodes represent brain regions and edges represent inter-region connectivity computed using white matter tractography. The model parameters comprise migration, proliferation and clearance rates, which are estimated using a derivative-based optimization algorithm. We compare tau progression predictions between the FK and HFK models and conduct experiments using PET from 45 AD subjects. The HFK model achieved an average of 3.94% less relative fitting error compared to the FK model. Qualitatively, FK model overestimates misfolded tau in EC while HFK does not.

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Author information

Authors and Affiliations

  1. Oden Institute, University of Texas at Austin, 201 E. 24th Street, Austin, TX, USA

    Zheyu Wen, Ali Ghafouri & George Biros

Authors
  1. Zheyu Wen
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  2. Ali Ghafouri
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  3. George Biros
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Corresponding author

Correspondence to Zheyu Wen .

Editor information

Editors and Affiliations

  1. Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Jonghye Woo

  2. Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands

    Alessa Hering

  3. The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Wilson Silva

  4. Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Xiang Li

  5. A*STAR, Institute of High Performance Computing, Singapore, Singapore

    Huazhu Fu

  6. Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Xiaofeng Liu

  7. Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Fangxu Xing

  8. University of Maryland Baltimore County, Baltimore, MD, USA

    Sanjay Purushotham

  9. National Institutes of Health, Bethesda, MD, USA

    Tejas S. Mathai

  10. National Institutes of Health, Bethesda, MD, USA

    Pritam Mukherjee

  11. Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands

    Max De Grauw

  12. The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Regina Beets Tan

  13. The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Valentina Corbetta

  14. University Hospital Freiburg, Freiburg, Germany

    Elmar Kotter

  15. University of Bern, Bern, Switzerland

    Mauricio Reyes

  16. University of Tübingen, Tübingen, Germany

    Christian F. Baumgartner

  17. Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Quanzheng Li

  18. University of Southern California, Los Angeles, CA, USA

    Richard Leahy

  19. Peking University, Beijing, China

    Bin Dong

  20. Hong Kong University of Science and Technology, Kowloon, Hong Kong

    Hao Chen

  21. Vanderbilt University, Nashville, TN, USA

    Yuankai Huo

  22. University of Sydney, Camperdown, NSW, Australia

    Jinglei Lv

  23. Institute of High Performance Computing, Singapore, Singapore

    Xinxing Xu

  24. Hong Kong University of Science and Technology, Hong Kong, China

    Xiaomeng Li

  25. Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

    Dwarikanath Mahapatra

  26. University of Alberta, Edmonton, AB, Canada

    Li Cheng

  27. LITIS, University of Rouen, Rouen, France

    Caroline Petitjean

  28. ImViA Laboratory, University of Burgundy, Dijon, France

    Benoît Presles

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Wen, Z., Ghafouri, A., Biros, G. (2023). A Two-Species Model for Abnormal Tau Dynamics in Alzheimer’s Disease. In: Woo, J., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops. MICCAI 2023. Lecture Notes in Computer Science, vol 14394. Springer, Cham. https://doi.org/10.1007/978-3-031-47425-5_7

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  • DOI: https://doi.org/10.1007/978-3-031-47425-5_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47424-8

  • Online ISBN: 978-3-031-47425-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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