0416 Imaging-informed computational modeling in medicine

  • Rafael Grytz, University of Alabama at Birmingham
  • Jessica Zhang, Carnegie Mellon University
  • Michael Girard, Singapore Eye Research Institute
  • Ian Sigal, University of Pittsburgh

Modern imaging technology and imaging-informed computational modeling approaches provide new understanding of biomedical mechanisms and unique opportunities for precision medicine. Advances in ex vivo imaging technologies provide new insight into (i) micro-structural mechanisms, while in vivo imaging techniques can provide (ii) large, cross-sectional data sets across populations (iii) rich, longitudinal data based on animal experiments, and (iv) precise, patient-specific data. Imaging-based computational models of tissues and organs are developed at multiple scales for mechanisms discovery, improved diagnostic based on data-rich modeling, and precision medicine based on patient-specific modeling. Imaging methods used in computational medicine include magnetic resonance imaging, computed tomography, ultrasound, optical coherence tomography, digital image correlation, multi-photon microscopy, and various other microscopy modalities. Imaging data thus provides the geometry critical for the generation of any realistic computational mechanics model. However, new imaging modalities enable the characterization of tissue properties and geometry changes over short and long time scales caused by acute loading and during tissue development, regeneration, aging, and disease progression. In combination with computational models, imaging data plays a fundamental role in the development of validated and predictive models for biological organs at the cell, tissue, and organ levels including the eye, brain, skin, and cardiovascular tissues.

In this minisymposium, we solicit novel contributions on imaging-based computational modeling in medicine. Computational models informed by or based on innovative use of imaging modalities for mechanism discovery, improved diagnostic, and precision medicine are welcome. The minisymposium aims to foster the interdisciplinary exchange between basic and clinical scientists, biophysicists, engineers, and mathematicians to jointly address the most important challenges and trends in imaging-informed computational medicine.

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