Patient-individualized boundary conditions for CFD simulations using time-resolved 3D angiography

  • Marco Boegel
  • Sonja Gehrisch
  • Thomas Redel
  • Christopher Rohkohl
  • Philip Hoelter
  • Arnd Doerfler
  • Andreas Maier
  • Markus Kowarschik
Original Article



Hemodynamic simulations are of increasing interest for the assessment of aneurysmal rupture risk and treatment planning. Achievement of accurate simulation results requires the usage of several patient-individual boundary conditions, such as a geometric model of the vasculature but also individualized inflow conditions.


We propose the automatic estimation of various parameters for boundary conditions for computational fluid dynamics (CFD) based on a single 3D rotational angiography scan, also showing contrast agent inflow. First the data are reconstructed, and a patient-specific vessel model can be generated in the usual way. For this work, we optimize the inflow waveform based on two parameters, the mean velocity and pulsatility. We use statistical analysis of the measurable velocity distribution in the vessel segment to estimate the mean velocity. An iterative optimization scheme based on CFD and virtual angiography is utilized to estimate the inflow pulsatility. Furthermore, we present methods to automatically determine the heart rate and synchronize the inflow waveform to the patient’s heart beat, based on time–intensity curves extracted from the rotational angiogram. This will result in a patient-individualized inflow velocity curve.


The proposed methods were evaluated on two clinical datasets. Based on the vascular geometries, synthetic rotational angiography data was generated to allow a quantitative validation of our approach against ground truth data. We observed an average error of approximately \(5.7\,\%\) for the mean velocity, \(7.1\,\%\) for the pulsatility. The heart rate was estimated very precisely with an average error of about \(0.8\,\%\), which corresponds to about 6 ms error for the duration of one cardiac cycle. Furthermore, a qualitative comparison of measured time–intensity curves from the real data and patient-specific simulated ones shows an excellent match.


The presented methods have the potential to accurately estimate patient-specific boundary conditions from a single dedicated rotational scan.


Angiography Computational fluid dynamics Hemodynamics Cone beam CT Flow quantification 



The authors gratefully acknowledge funding of the Erlangen Graduate School in Advanced Optical Technologies (SAOT) by the German Research Foundation (DFG) in the framework of the German excellence initiative.

Compliance with ethical standards

Conflict of interest

S. Gehrisch, T. Redel and M. Kowarschik are employees of Siemens Healthcare GmbH.

Ethical approval

This study has been performed retrospectively. Formal consent is not required.

Informed consent

For this type of study, formal consent is not required.


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Copyright information

© CARS 2016

Authors and Affiliations

  1. 1.Pattern Recognition Lab, Department of Computer ScienceFriedrich-Alexander Universität Erlangen-NürnbergErlangenGermany
  2. 2.Siemens Healthcare GmbHForchheimGermany
  3. 3.Department of NeuroradiologyUniversitätsklinikum ErlangenErlangenGermany

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