How might Flow Vortex Analysis Help in Characterization of ICA Aneurismal Flow: A Case Study Using Siemens CFD Prototype

Software and VTK

Jingfneg Jiang1, Kevin Sunderland1, Gouthami Chintalapani2, Kevin Royalty2 and Charles M Strother3

1Michigan Technological University2Siemens Medical Solutions (USA), Inc.

3University of Wisconsin-Madison

ASNR 2015

1. J. Jiang and K. Sunderland are supported by a research contract from Siemens Medical Solution (USA), Inc.

2. G. Chintalapani and K. Royalty are employed by Siemens Medical Solution (USA), Inc.

Disclosure

Hemodynamics plays a vital role in the origin, growth and rupture of aneurysms

A growing body of literature indicates computational fluid dynamics (CFD) simulations could potentially provide insight into clinical management of cerebral aneurysms1,2

Introduction

CFD produces results of mathematical models (i.e. Navier-Stokes equations) that researchers postulate capture the basic laws governing the physics of fluid flows. Widely used and valued for industrial

applications such as airplane design

Image-based CFD simulations3 are under a rapid development “Patient-specific” vessel geometry is

currently used Patient-specific physiological data could

potentially further enhance the predictions

What is CFD?

Clinical Utility of CFD? Clinical Utility of CFD? Significant anatomical and

hemodynamic variations make interpretation of aneurismal dynamics difficulty

Viewing time-resolved 3D hemodynamic (hundreds of) images may become a time-consuming and difficult task for physicians

Jiang and Strother, ICS, 2009

Objective:Objective: To improve potential clinical utility of CFD, automated flow analysis may be useful

Vortex core may provide relevant information related to flow physics The usefulness of vortex core analysis was demonstrated through a pilot study using 5

sets of ICA tandem (closely-space) aneurysms

Study DesignStudy Design:• 10 lateral ICA aneurysms in 5 patients; two closely spaced aneurysms in each patients • CFD simulations of those six aneurysms were performed using Siemens CFD prototype software • Automated vortex core analysis was performed using in-house software derived from Visualization ToolKit (VTK, Kitware Inc., NY)

Purpose

Workflow

Step 1: CFD Simulations

CFD Simulation Conditions Typical waveforms (transient flow rates) were selected based

on averaged Phase-contrast MR measurements6,7 For instance, averaged flow rate at the ICA was 280 ml/min

Transient CFD simulations were performed for 2 cardiac cycles A voxel-based method8 (i.e. Siemens CFD prototype solver)

was used to solve the Navier-Stokes equations Time steps were sufficiently fine and were adaptively chosen

by the Siemens CFD solver 18 phases/steps of the second cardiac cycles were analyzed

Step2: Isolate Aneurismal Flow

This algorithm was based on an published aneurysm extraction algorithm10 and implemented in the VTK

Vortex Analysis The well-known Lambda2 method by Jeong

and Hussain99 was used to define the vortex core areas Two negative eigenvalues from a matrix derived from

local velocity gradients

A simple Marching-cube algorithm was used to segment out the vortex core volumes Implemented in the VMTK5

Temporal Flow Stability Flow stability was assessed by tracking changes of

the vortex core(s) over time Calculate a temporally –averaged velocity field Calculate the time-averaged vortex core(s) from the time-

average velocity field (purple colored vortex core below) Compare the (volume) overlap between the time-averaged

vortex core(s) and the instantaneous vortex core(s) The (temporal) flow stability assessment is between 0 and 1

and there, is easy to interpret Low overlap means low (temporal) flow stability

The extracted vortex cores were visually consistent with velocity Vector plot

Vortex Cores Velocity Plot

Results

Purple and green colors represent two vortex cores of the proximal and distal aneurysms, respectively

The calculate overlap value was consistent with visual assessments of temporal flow stability

Results

Overlap = 0.57 Overlap = 0.87

Mean Overlap of Vortex Cores

Proximal Aneurysms 0.90 ± 0.06

Distal Aneurysms 0.78 ± 0.08

Summary Results

• Temporal flow stability in proximal aneurysms were greater as compared to that in distal aneurysms (p = 0.03 [rank-sum test]) in data investigated

• Flow instability in the distal aneurysm might be induced by disturbed flow coming out from the proximal aneurysm

Vortex analysis results are yet to be verified with imaging measurements (e.g. Phase-contrast MR angiography)

Only 10 aneurysms were studied

Study Limitations

Conclusion and Future WorkPreliminary results demonstrate that vortex-

core analysis can potentially provide relevant information to characterize aneurismal hemodynamics Assessment of temporal flow stability through

vortex core analysis might be an independent variable

Future work is to verify results and explore its use in a clinical setting

[1]J. R. Cebral, F. Mut, M. Raschi, E. Scrivano, R. Ceratto, P. Lylyk, and C. M. Putman, "Aneurysm rupture following treatment with flow-diverting stents: computational hemodynamics analysis of treatment," AJNR Am J Neuroradiol, vol. 32, pp. 27-33, Jan 2010.

[2]J. Xiang, V. M. Tutino, K. V. Snyder, and H. Meng, "CFD: computational fluid dynamics or confounding factor dissemination? The role of hemodynamics in intracranial aneurysm rupture risk assessment," AJNR Am J Neuroradiol, vol. 35, pp. 1849-57, Oct 2014.

[3]D. A. Steinman, J. S. Milner, C. J. Norley, S. P. Lownie, and D. W. Holdsworth, "Image-based computational simulation of flow dynamics in a giant intracranial aneurysm," AJNR Am J Neuroradiol, vol. 24, pp. 559-66, Apr 2003.

[4]N. M. Kakalis, A. P. Mitsos, J. V. Byrne, and Y. Ventikos, "The haemodynamics of endovascular aneurysm treatment: a computational modelling approach for estimating the influence of multiple coil deployment," IEEE Trans Med Imaging, vol. 27, pp. 814-24, Jun 2008.

[5]L. Antiga and D. A. Steinman, "Robust and objective decomposition and mapping of bifurcating vessels," IEEE Trans Med Imaging, vol. 23, pp. 704-13, Jun 2004.

[6]M. D. Ford, N. Alperin, S. H. Lee, D. W. Holdsworth, and D. A. Steinman, "Characterization of volumetric flow rate waveforms in the normal internal carotid and vertebral arteries," Physiol Meas, vol. 26, pp. 477-88, Aug 2005.

References

[7]M. Zhao, S. Amin-Hanjani, S. Ruland, A. P. Curcio, L. Ostergren, and F. T. Charbel, "Regional cerebral blood flow using quantitative MR angiography," AJNR Am J Neuroradiol, vol. 28, pp. 1470-3, Sep 2007.

[8] V. Mihalef, P. Sharma, A. Kamen, and T. Redel, “An immersed porous boundary method for computational fluid dynamics of blood flow in aneurysms with flow diverters,” in Proceedings of the ASME Summer Bioengineering Conference, 2012.

[9] J. Jeong and E. Hussain, “On the identification of a vortex”, J. of Fluid Mechanics, vol. 285, pp. 69-95, 1995.

[10] J. Jiang and C. M. Strother, "Interactive decomposition and mapping of saccular cerebral aneurysms using harmonic functions: its first application with "patient-specific" computational fluid dynamics (CFD) simulations," IEEE Trans Med Imaging, vol. 32, pp. 153-64, Feb 2013.

References