This study used computational fluid dynamics to model the effects of a Pipeline Embolization Device on blood flow in a growing cerebral aneurysm at three stages. The model was created from a patient's CT scan. Simulations were run before and after virtual device placement. After treatment, there were reductions in velocity, pressure, and wall shear stress within the aneurysm at all stages. Treating earlier was found to be more effective at reducing harmful hemodynamics, suggesting optimal treatment timing is during earlier aneurysm growth.

1. ACKNOWLEDGEMENTS
55%
60%
65%
70%
75%
80%
STAGE 1 STAGE 2 STAGE 3
ANEURYSM GROWTH STAGE
REDUCTIONINRMS
VELOCITYMAGNITUDE
2 mL/s 3 mL/s 4 mL/s
REFERENCES
COMPUTATIONAL EXAMINATION OF HEMODYNAMIC EFFECTS IN A PATIENT-SPECIFIC GROWING
CEREBRAL ANEURYSM BEFORE AND AFTER VIRTUAL TREATMENT WITH A PIPELINE
EMBOLIZATION DEVICE
Chad Hyslop1, Priya Nair1, Matthew Mortensen1,2, Jonathan Placencia1, David Frakes1,2,3
1SBHSE, Arizona State University, Tempe, AZ 85287; 2EndoVantage, LLC, Scottsdale, AZ 85257; 3ECEE, Arizona State University, Tempe, AZ 85287
Cerebral aneurysms (CAs) are pathological dilatations of a weakened region in the arterial blood vessel wall in the
brain.[1] On average, there is a CA rupturing every 18 minutes in the United States, leading to fatalities in
approximately 40% of cases. Out of the other 60%, 4 out of 7 of these people will have disabilities.[2] Even though CA
treatment by endovascular coiling is considered to be the gold standard by many clinicians, certain complications,
such as coil herniation into the parent vessel, are more likely to occur when treating wide-necked CAs (aneurysms
with a dome-to-neck ratio of < 2). Consequently, flow diversion devices have been developed to avoid these
complications by placing a low porosity mesh-like stent along the parent vessel covering the aneurysm neck. The
function of these devices is to divert flow from entering into the aneurysm, creating blood stasis to allow for intra-
aneurysmal thrombosis. In conventional clinical practice, the impact of hemodynamics on CA progression and
treatment timing are considered only to a limited degree during CA evaluation due to lack of patient-specific flow
information and treatment modeling. Fortunately, emerging applications of novel finite element modeling (FEM) of
endovascular devices coupled with computational fluid dynamics (CFD) now have the potential to predict treatment
effects in the clinical setting. This study investigates the effects of hemodynamics in a patient-specific, wide-necked,
growing CA model before and after virtual treatment with a Pipeline Embolization Device (PED), and compares the
changes in post-treatment blood flow between three stages of aneurysmal growth.
STEP 1: Computational Model Creation
[1] Lasheras, JC., 2007.
[2] Brain Aneurysm Foundation.
http://www.bafound.org/Statistics_and_Facts
Justin Ryan, Ph.D., Research Scientist, Phoenix
Children’s Hospital, Phoenix, AZ
Michael Caplan, Ph.D., Associate Professor, SBHSE,
Arizona State University, Tempe, AZ
Brian W. Chong, M.D., Consultant, Departments of
Radiology and Neurosurgery, Mayo Clinic Hospital,
Phoenix, AZ
EndoVantage, LLC, Scottsdale, AZ
Image Processing Applications Laboratory, SBHSE,
Arizona State University, Tempe, AZ
STEP 2: Virtual Device Deployment
STEP 3: CFD Simulations
Fluid and device domains were discretized into
tetrahedral mesh elements using Ansys ICEM
(ANSYS, Inc., Canonsburg, Pennsylvania USA).
Simulations were performed in Ansys FLUENT
where blood was assumed to be incompressible and
Newtonian, and the model and the device were
assumed to be rigid with no-slip condition imposed at
the walls.
Steady-state inflow rates of 2, 3, and 4 mL/s were
explored, before and after virtual treatment.
STEP 4: Analysis
Simulation results were analyzed using Tecplot 360.
Root-mean-squared (RMS) velocity magnitude,
average pressure, and average wall shear stress (WSS)
were calculated over the aneurysmal domain.
RESULTSINTRODUCTION
Figure 1 - Computational model construction process for a
patient-specific CA: (a) CT image data set, (b) segmentation
and reconstruction, (c) extrusion of inlet and outlet vessels,
and smoothing of 3D computational model.
METHODS
CONCLUSIONS
After PED deployment, the CFD results showed lower RMS velocity magnitude, average pressure, and average
WSS in stage 1 as compared to stages 2 and 3 at steady inflow rates of 3 and 4 mL/s.
The impinging flow jet was noticeably disbursed after PED deployment and velocity magnitudes were visually
reduced within the aneurysm (Figure 5).
The observations made here with respect to PED treatment suggest that treating the aneurysm earlier is more
effective in terms of aneurysmal hemodynamic reductions.
In the clinical setting, this information may be useful during CA evaluation and in determining when the optimal
time is to treat the CA.
Figure 5 - Streamtraces, color-coded by velocity
magnitude, at 3 mL/s steady-state inflow rate for (top)
untreated and (bottom) treated cases.
Figure 3 – Pressure distributions at 3 mL/s steady state-
inflow rate for (top) untreated and (bottom) treated cases.
Treated cases result in 39%, 23%, & 22% reduction in
aneurysmal pressureavg at stages 1, 2, & 3, respectively.
STAGE 1 STAGE 2 STAGE 3
UNTREATEDTREATED
STAGE 1 STAGE 2 STAGE 3
UNTREATEDTREATED
Figure 2 – Computational aneurysm models virtually
treated with PED using device specific FEM models
available in EVIS software (EndoVantage, LLC).
STAGE 1 STAGE 2 STAGE 3
DNR = 1.174DNR = 1.060 DNR = 1.065
ICA Inlet
Outlet PCA Outlet
Aneurysm
PED Figure 6 - Percentage reductions in aneurysmal RMS
velocity magnitude with respect to the untreated models
for each growth stage under conditions of 2, 3, and 4
mL/s steady-state inflow rate.
STAGE 3STAGE 1 STAGE 2
UNTREATEDTREATED
Velocity
Magnitude
(m/s)
Figure 4 - WSS distributions at 3 mL/s steady-state inflow
rate for (top) untreated and (bottom) treated cases.
Treated cases result in 86%, 83%, & 82% reduction in
aneurysmal WSSavg at stages 1, 2, & 3, respectively.
The ICA Inlet has been omitted from all views in Figures 3 and 4 for clarity purposes, however, a small portion of
the ICA inlet is shown in Figure 5 so as to reveal the stream traces.
Stage 1 is at 49 years of age, stage 2 is 445 days post stage 1, and stage 3 is 759 days post stage 2.
(a) (b) (c)