Information Theoretic Measurement of Blood Flow Complexity in Vessels and Aneurysms: Interlacing Complexity Index

  • Jose M. PozoEmail author
  • Arjan J. Geers
  • Alejandro F. Frangi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10434)


Haemodynamics is believed to be a crucial factor in the aneurysm formation, evolution and eventual rupture. The 3D blood flow is typically derived by computational fluid dynamics (CFD) from patient-specific models obtained from angiographic images. Typical quantitative haemodynamic indices are local. Some qualitative classifications of global haemodynamic features have been proposed. However these classifications are subjective, depending on the operator visual inspection.

In this work we introduce an information theoretic measurement of the blood flow complexity, based on Shannon’s Mutual Information, named Interlacing Complexity Index (ICI). ICI is an objective quantification of the flow complexity from aneurysm inlet to aneurysm outlets. It measures how unpredictable is the location of the streamlines at the outlets from knowing the location at the inlet, relative to the scale of observation.

We selected from the @neurIST database a set of 49 cerebral vasculatures with aneurysms in the middle cerebral artery. Surface models of patient-specific vascular geometries were obtained by geodesic active region segmentation and manual correction, and unsteady flow simulations were performed imposing physiological flow boundary conditions. The obtained ICI has been compared to several qualitative classifications performed by an expert, revealing high correlations.


Aneurysms CFD Haemodynamics Flow complexity Mutual information 



The work has been partially supported by the project OCEAN (EP/M006328/1) funded by the Engineering and Physical Sciences Research Council.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jose M. Pozo
    • 1
    Email author
  • Arjan J. Geers
    • 2
  • Alejandro F. Frangi
    • 1
  1. 1.Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Department of Electronic and Electrical EngineeringThe University of SheffieldSheffieldUK
  2. 2.CISTIB, Department of Information and Communication TechnologiesUniversitat Pompeu FabraBarcelonaSpain

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