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VERDICT Prostate Parameter Estimation with AMICO

  • Elisenda Bonet-Carne
  • Alessandro Daducci
  • Edward Johnston
  • Joseph Jacobs
  • Alex Freeman
  • David Atkinson
  • David J. Hawkes
  • Shonit Punwani
  • Daniel C. Alexander
  • Eleftheria Panagiotaki
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

The VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours) technique estimates non-invasively cancer microstructure features. The clinical application of VERDICT for prostate cancer requires constraining some of the model’s parameter. This work uses the Accelerated Microstructure Imaging via Convex Optimization (AMICO) formulation for VERDICT (VERDICT-AMICO), to investigate parameter estimation for prostate tissue in an attempt to minimize the parameter constraints. We examine various dictionaries for VERDICT-AMICO enabling different levels of flexibility on the choice of parameter values. Depending on the stability of the fitting this procedure leads to the selection of a dictionary (or dictionaries) with the fewest number of model parameter constraints. Results show that with the current VERDICT imaging acquisition, the model can have an extra free parameter to fit, the extracellular diffusivity. In conclusion, the AMICO adaptation for VERDICT allowed testing of different values for the previously fixed model parameters, and helped relax assumptions of fixed extracellular diffusivity that the model currently uses for prostate cancer characterisation.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Elisenda Bonet-Carne
    • 1
    • 2
  • Alessandro Daducci
    • 3
    • 4
  • Edward Johnston
    • 2
  • Joseph Jacobs
    • 1
  • Alex Freeman
    • 5
  • David Atkinson
    • 2
  • David J. Hawkes
    • 6
  • Shonit Punwani
    • 2
  • Daniel C. Alexander
    • 1
  • Eleftheria Panagiotaki
    • 1
  1. 1.Department of Computer ScienceUCL Centre of Medical Imaging ComputingLondonUK
  2. 2.Division of MedicineUCL Centre for Medical ImagingLondonUK
  3. 3.Computer Science DepartmentUniversity of VeronaVeronaItaly
  4. 4.Radiology DepartmentCentre Hospitalier Universitaire Vaudois (CHUV)LausanneSwitzerland
  5. 5.University College London HospitalsLondonUK
  6. 6.Department of Medical PhysicsUCL Centre of Medical Imaging ComputingLondonUK

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