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Multiscale mechanobiology modeling for surgery assessment

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Abstract

This paper discusses some of the concept of modeling surgery outcome. It is also an attempt to offer a road map for progress. This paper may serve as a common ground of discussion for both communities i.e surgeons and computational scientist in its broadest sense. Predicting surgery outcome is a very difficult task. All patients are different, and multiple factors such as genetic, or environment conditions plays a role. The difficulty is to construct models that are complex enough to address some of these significant multiscale elements and simple enough to be used in clinical conditions and calibrated on patient data. We will provide a multilevel progressive approach inspired by two applications in surgery that we have been working on. One is about vein graft adaptation after a transplantation, the other is the recovery of cosmesis outcome after a breast lumpectomy. This work, that is still very much in progress, may teach us some lessons. We are convinced that the digital revolution that is transforming the working environment of the surgeon makes closer collaboration between surgeons and computational scientist unavoidable. We believe that “computational surgery” will allow the community to develop predictive model of the surgery outcome and greatprogresses in surgery procedures that goes far beyond the operating room procedural aspect.

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Authors and Affiliations

  1. Dept. of Computer Science, University of Houston, Houston, USA

    M. Garbey

  2. The Methodist Institute for Technology, Innovation and Education Houston, Houston, TX, USA

    M. Garbey & B. L. Bass

  3. Dept. of Surgery, The Methodist Hospital, Houston, TX, USA

    B. L. Bass

  4. Dept. of Surgery, University of Florida, Gainesville, USA

    S. Berceli

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  1. M. Garbey
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  2. B. L. Bass
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  3. S. Berceli
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Garbey, M., Bass, B.L. & Berceli, S. Multiscale mechanobiology modeling for surgery assessment. Acta Mech Sin 28, 1186–1202 (2012). https://doi.org/10.1007/s10409-012-0133-4

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  • DOI: https://doi.org/10.1007/s10409-012-0133-4

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