Publications by authors named "David Frakes"

55 Publications

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks.

Sci Rep 2020 06 11;10(1):9508. Epub 2020 Jun 11.

Department of Biomedical Engineering, Duke University, Durham, NC, USA.

Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient's hemodynamics and increase the severity of many cardiovascular diseases. Observing and quantifying associations between these factors and hemodynamics can be difficult due to the multitude of co-existing conditions and blood flow parameters in real patient data. Machine learning-driven, physics-based simulations provide a means to understand how potentially correlated conditions may affect a particular patient. Here, we use a combination of machine learning and massively parallel computing to predict the effects of physiological factors on hemodynamics in patients with coarctation of the aorta. We first validated blood flow simulations against in vitro measurements in 3D-printed phantoms representing the patient's vasculature. We then investigated the effects of varying the degree of stenosis, blood flow rate, and viscosity on two diagnostic metrics - pressure gradient across the stenosis (ΔP) and wall shear stress (WSS) - by performing the largest simulation study to date of coarctation of the aorta (over 70 million compute hours). Using machine learning models trained on data from the simulations and validated on two independent datasets, we developed a framework to identify the minimal training set required to build a predictive model on a per-patient basis. We then used this model to accurately predict ΔP (mean absolute error within 1.18 mmHg) and WSS (mean absolute error within 0.99 Pa) for patients with this disease.
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http://dx.doi.org/10.1038/s41598-020-66225-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289812PMC
June 2020

Hemodynamic and morphological characteristics of a growing cerebral aneurysm.

Neurosurg Focus 2019 07;47(1):E13

Departments of1Biomedical Engineering and.

The growth of cerebral aneurysms is linked to local hemodynamic conditions, but the driving mechanisms of the growth are poorly understood. The goal of this study was to examine the association between intraaneurysmal hemodynamic features and areas of aneurysm growth, to present the key hemodynamic parameters essential for an accurate prediction of the growth, and to gain a deeper understanding of the underlying mechanisms. Patient-specific images of a growing cerebral aneurysm in 3 different growth stages acquired over a period of 40 months were segmented and reconstructed. A unique aspect of this patient-specific case study was that while one side of the aneurysm stayed stable, the other side continued to grow. This unique case enabled the authors to examine their aims in the same patient with parent and daughter arteries under the same inlet flow conditions. Pulsatile flow in the aneurysm models was simulated using computational fluid dynamics and was validated with in vitro experiments using particle image velocimetry measurements. The authors' detailed analysis of intrasaccular hemodynamics linked the growing regions of aneurysms to flow instabilities and complex vortex structures. Extremely low velocities were observed at or around the center of the unstable vortex structure, which matched well with the growing regions of the studied cerebral aneurysm. Furthermore, the authors observed that the aneurysm wall regions with a growth greater than 0.5 mm coincided with wall regions of lower (< 0.5 Pa) time-averaged wall shear stress (TAWSS), lower instantaneous (< 0.5 Pa) wall shear stress (WSS), and high (> 0.1) oscillatory shear index (OSI). To determine which set of parameters can best identify growing and nongrowing aneurysms, the authors performed statistical analysis for consecutive stages of the growing CA. The results demonstrated that the combination of TAWSS and the distance from the center of the vortical structure has the highest sensitivity and positive predictive value, and relatively high specificity and negative predictive value. These findings suggest that an unstable, recirculating flow structure within the aneurysm sac created in the region adjacent to the aneurysm wall with low TAWSS may be introduced as an accurate criterion to explain the hemodynamic conditions predisposing the aneurysm to growth. The authors' findings are based on one patient's data set, but the study lays out the justification for future large-scale verification. The authors' findings can assist clinicians in differentiating stable and growing aneurysms during preinterventional planning.
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http://dx.doi.org/10.3171/2019.4.FOCUS19195DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605304PMC
July 2019

Improving the Accuracy of Two-Color Multiview (2CMV) Advanced Geospatial Information (AGI) Products Using Unsupervised Feature Learning and Optical Flow.

Sensors (Basel) 2019 Jun 8;19(11). Epub 2019 Jun 8.

School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA.

In two-color multiview (2CMV) advanced geospatial information (AGI) products, temporal changes in synthetic aperture radar (SAR) images acquired at different times are detected, colorized, and overlaid on an initial image such that new features are represented in cyan, and features that have disappeared are represented in red. Accurate detection of temporal changes in 2CMV AGI products can be challenging because of 'speckle noise' susceptibility and false positives that result from small orientation differences between objects imaged at different times. Accordingly, 2CMV products are often dominated by colored pixels when changes are detected via simple pixel-wise cross-correlation. The state-of-the-art in SAR image processing demonstrates that generating efficient 2CMV products, while accounting for the aforementioned problem cases, has not been well addressed. We propose a methodology to address the aforementioned two problem cases. Before detecting temporal changes, speckle and smoothing filters mitigate the effects of speckle noise. To detect temporal changes, we propose using unsupervised feature learning algorithms in conjunction with optical flow algorithms that track the motion of objects across time in small regions of interest. The proposed framework for distinguishing between actual motion and misregistration can lead to more accurate and meaningful change detection and improve object extraction from an SAR AGI product.
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http://dx.doi.org/10.3390/s19112605DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603653PMC
June 2019

Numerical study of hemodynamics in brain aneurysms treated with flow diverter stents using porous medium theory.

Comput Methods Biomech Biomed Engin 2019 Aug 2;22(11):961-971. Epub 2019 May 2.

b School of Biological and Health Systems Engineering , Arizona State University , Tempe , AZ , USA.

Conventional approaches of implementing computational fluid dynamics to study aneurysmal hemodynamics after treatment with a flow diverter stent are computationally expensive. Cumbersome meshing and lengthy simulation runtimes are common. To address these issues, we present a novel volume penalization method that considers flow diverters as heterogeneous porous media. The proposed model requires a considerably smaller number of mesh elements, leading to faster simulation runtimes. Three patient-specific aneurysms were virtually treated with flow diverters and aneurysmal hemodynamics were simulated. The results of the virtual deployments including aneurysmal hemodynamics were compared to corresponding results from conventional approaches. The comparisons showed that the proposed approach led to 9.12 times increase in the speed of simulations on average. Further, aneurysmal kinetic energy and inflow rate metrics for the proposed approach were consistent with those from conventional approaches, differing on average by 3.52% and 3.78%, respectively.
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http://dx.doi.org/10.1080/10255842.2019.1609457DOI Listing
August 2019

An Optical Flow-Based Approach for Minimally Divergent Velocimetry Data Interpolation.

Int J Biomed Imaging 2019 3;2019:9435163. Epub 2019 Feb 3.

School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, 85281, USA.

Three-dimensional (3D) biomedical image sets are often acquired with in-plane pixel spacings that are far less than the out-of-plane spacings between images. The resultant anisotropy, which can be detrimental in many applications, can be decreased using image interpolation. Optical flow and/or other registration-based interpolators have proven useful in such interpolation roles in the past. When acquired images are comprised of signals that describe the flow velocity of fluids, additional information is available to guide the interpolation process. In this paper, we present an optical-flow based framework for image interpolation that also minimizes resultant divergence in the interpolated data.
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http://dx.doi.org/10.1155/2019/9435163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6378004PMC
February 2019

Suitability of lattice Boltzmann inlet and outlet boundary conditions for simulating flow in image-derived vasculature.

Int J Numer Method Biomed Eng 2019 06 1;35(6):e3198. Epub 2019 Apr 1.

Department of Biomedical Engineering, Duke University, Durham, NC, USA.

The lattice Boltzmann method (LBM) is a popular alternative to solving the Navier-Stokes equations for modeling blood flow. When simulating flow using the LBM, several choices for inlet and outlet boundary conditions exist. While boundary conditions in the LBM have been evaluated in idealized geometries, there have been no extensive comparisons in image-derived vasculature, where the geometries are highly complex. In this study, the Zou-He (ZH) and finite difference (FD) boundary conditions were evaluated in image-derived vascular geometries by comparing their stability, accuracy, and run times. The boundary conditions were compared in four arteries: a coarctation of the aorta, dissected aorta, femoral artery, and left coronary artery. The FD boundary condition was more stable than ZH in all four geometries. In general, simulations using the ZH and FD method showed similar convergence rates within each geometry. However, the ZH method proved to be slightly more accurate compared with experimental flow using three-dimensional printed vasculature. The total run times necessary for simulations using the ZH boundary condition were significantly higher as the ZH method required a larger relaxation time, grid resolution, and number of time steps for a simulation representing the same physiological time. Finally, a new inlet velocity profile algorithm is presented for complex inlet geometries. Overall, results indicated that the FD method should generally be used for large-scale blood flow simulations in image-derived vasculature geometries. This study can serve as a guide to researchers interested in using the LBM to simulate blood flow.
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http://dx.doi.org/10.1002/cnm.3198DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605305PMC
June 2019

3D printing for congenital heart disease: a single site's initial three-yearexperience.

3D Print Med 2018 Nov 8;4(1):10. Epub 2018 Nov 8.

Arizona State University, Tempe, AZ, USA.

Background: 3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider impact of the novel planning augmentation tool. The work here presents the evolution of an institution's first 3 full years of 3D prints following consistent integration of the technology into clinical workflow (2012-2014) - a center which produced 79 models for surgical planning (within that time frame). Patient outcomes and technology acceptance following implementation of 3D printing were reviewed.

Methods: A retrospective analysis was designed to investigate the anatomical model's impact on time-based surgical metrics. A contemporaneous cohort of standard-of-care pre-procedural planning (no anatomical models) was identified for comparative analysis. A post-surgery technology acceptance assessment was also employed in a smaller subset to measure perceived efficacy of the anatomical models. The data was examined.

Results: Within the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. One hundred sixty four anatomical models had been generated for various purposes. An inclusion criterion based on lesion type limited those with anatomic models to 33; there were 113 cases matching the same criterion that received no anatomical model. Time-based metrics such as case length-of-time showed a mean reduction in overall time for anatomical models. These reductions were not statistically significant. The technology acceptance survey did demonstrate strong perceived efficacy. Anecdotal vignettes further support the technology acceptance.

Discussion & Conclusion: The anatomical models demonstrate trends for reduced operating room and case length of time when compared with similar surgeries in the same time-period; in turn, these reductions could have significant impact on patient outcomes and operating room economics. While analysis did not yield robust statistical powering, strong Cohen's d values suggest poor powering may be more related to sample size than non-ideal outcomes. The utility of planning with an anatomical model is further supported by the technology acceptance study which demonstrated that surgeons perceive the anatomical models to be an effective tool in surgical planning for a complex CHD repair. A prospective multi-center trial is currently in progress to further validate or reject these findings.
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http://dx.doi.org/10.1186/s41205-018-0033-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223396PMC
November 2018

Computing the ankle-brachial index with parallel computational fluid dynamics.

J Biomech 2019 01 19;82:28-37. Epub 2018 Oct 19.

Department of Biomedical Engineering, Duke University, Durham, NC, USA. Electronic address:

The ankle-brachial index (ABI), a ratio of arterial blood pressure in the ankles and upper arms, is used to diagnose and monitor circulatory conditions such as coarctation of the aorta and peripheral artery disease. Computational simulations of the ABI can potentially determine the parameters that produce an ABI indicative of ischemia or other abnormalities in blood flow. However, 0- and 1-D computational methods are limited in describing a 3-D patient-derived geometry. Thus, we present a massively parallel framework for computational fluid dynamics (CFD) simulations in the full arterial system. Using the lattice Boltzmann method to solve the Navier-Stokes equations, we employ highly parallelized and scalable methods to generate the simulation domain and efficiently distribute the computational load among processors. For the first time, we compute an ABI with 3-D CFD. In this proof-of-concept study, we investigate the dependence of ABI on the presence of stenoses, or narrowed regions of the arteries, by directly modifying the arterial geometry. As a result, our framework enables the computation a hemodynamic factor characterizing flow at the scale of the full arterial system, in a manner that is extensible to patient-specific imaging data and holds potential for treatment planning.
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http://dx.doi.org/10.1016/j.jbiomech.2018.10.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6666426PMC
January 2019

A New Method for Simulating Embolic Coils as Heterogeneous Porous Media.

Cardiovasc Eng Technol 2019 03 18;10(1):32-45. Epub 2018 Oct 18.

School of Biological and Health Systems Engineering, Arizona State University, 501 E Tyler Mall, BLDG ECG RM#334, Tempe, AZ, 85287, USA.

Purpose: To gain insight into the influence of coils on aneurysmal hemodynamics, computational fluid dynamics (CFD) can be used. Conventional methods of modeling coils consider the explicit geometry of the deployed devices within the aneurysm and discretize the fluid domain. However, the complex geometry of a coil mass leads to cumbersome domain discretization along with a significant number of mesh elements. These problems have motivated a homogeneous porous medium coil model, whereby the explicit geometry of the coils is greatly simplified, and relevant homogeneous porous medium parameters are approximated. Unfortunately, since the coils are not distributed uniformly in the aneurysm, the homogeneity assumption is no longer valid.

Methods: In this paper, a novel heterogeneous porous medium approach is introduced. To verify the model, we performed CFD simulations to calculate the pressure drop caused by actual deployed coils in a straight cylinder. Next, we considered three different anatomical aneurysm geometries virtually treated with coils and studied the hemodynamics using the presented heterogeneous porous medium model.

Results: We show that the blood kinetic energy predicted by the heterogeneous model is in strong agreement with the conventional approach. The homogeneity assumption, on the other hand, significantly over-predicts the blood kinetic energy within the aneurysmal sac.

Conclusions: These results indicate that the benefits of the porous medium assumption can be retained if a heterogeneous approach is applied. Implementation of the presented method led to a substantial reduction in the total number of mesh elements compared to the conventional method, and greater accuracy was enabled by considering heterogeneity compared to the homogenous approach.
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http://dx.doi.org/10.1007/s13239-018-00383-1DOI Listing
March 2019

Alternative methods for virtual heart transplant-Size matching for pediatric heart transplantation with and without donor medical images available.

Pediatr Transplant 2018 12 24;22(8):e13290. Epub 2018 Sep 24.

Division of Cardiology, Division of Cardiothoracic Surgery, Children's Heart Center, Phoenix Children's Hospital, Phoenix, Arizona.

Background: Listed pediatric heart transplant patients have the highest solid-organ waitlist mortality rate. The donor-recipient body weight (DRBW) ratio is the clinical standard for allograft size matching but may unnecessarily limit a patient's donor pool. To overcome DRBW ratio limitations, two methods of performing virtual heart transplant fit assessments were developed that account for patient-specific nuances. Method 1 uses an allograft total cardiac volume (TCV) prediction model informed by patient data wherein a matched allograft 3-D reconstruction is selected from a virtual library for assessment. Method 2 uses donor images for a direct virtual transplant assessment.

Methods: Assessments were performed in medical image reconstruction software. The allograft model was developed using allometric/isometric scaling assumptions and cross-validation.

Results: The final predictive model included gender, height, and weight. The 25th-, 50th-, and 75th-percentiles for TCV percentage errors were -13% (over-prediction), -1%, and 8% (under-prediction), respectively. Two examples illustrating the potential of virtual assessments are presented.

Conclusion: Transplant centers can apply these methods to perform their virtual assessments using existing technology. These techniques have potential to improve organ allocation. With additional experience and refinement, virtual transplants may become standard of care for determining suitability of donor organ size for an identified recipient.
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http://dx.doi.org/10.1111/petr.13290DOI Listing
December 2018

The Effect of Stents in Cerebral Aneurysms: A Review.

Asian J Neurosurg 2018 Apr-Jun;13(2):201-211

Division of Neurosurgery, Duke University, Durham, NC, USA.

The etiology of up to 95% of cerebral aneurysms may be accounted for by hemodynamically-induced factors that create vascular injury. The purpose of this review is to describe key physical properties that stents have and how they affect cerebral aneurysms. We performed a two-step screening process. First, a structured search was performed using the PubMed database. The following search terms and keywords were used: "Hemodynamics," "wall shear stress (WSS)," "velocity," "viscosity," "cerebral aneurysm," "intracranial aneurysm," "stent," "flow diverter," "stent porosity," "stent geometry," "stent configuration," and "stent design." Reports were considered if they included original data, discussed hemodynamic changes after stent-based treatment of cerebral aneurysms, examined the hemodynamic effects of stent deployment, and/or described the geometric characteristics of both stents and the aneurysms they were used to treat. The search strategy yielded a total of 122 articles, 61 were excluded after screening the titles and abstracts. Additional articles were then identified by cross-checking reference lists. The final collection of 97 articles demonstrates that the geometric characteristics and configurations of deployed stents influenced hemodynamic parameters such as aneurysmal WSS, inflow, and pressure. The geometric characteristics of the aneurysm and its position also had significant influences on intra-aneurysmal hemodynamics after treatment. In conclusion, changes in specific aneurysmal hemodynamic parameters that result from stenting relate to a number of factors including the geometric properties and configurations of deployed stents, the geometric properties of the aneurysm, and the pretreatment hemodynamics.
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http://dx.doi.org/10.4103/1793-5482.175639DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898080PMC
April 2018

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease.

Trends Biotechnol 2017 11 21;35(11):1049-1061. Epub 2017 Sep 21.

Brigham and Women's Hospital, Boston, MA, USA.

Noninvasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions.
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http://dx.doi.org/10.1016/j.tibtech.2017.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651201PMC
November 2017

Mathematical Analysis of Glioma Growth in a Murine Model.

Sci Rep 2017 05 31;7(1):2508. Epub 2017 May 31.

School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85287, USA.

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm to 62 mm, even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.
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http://dx.doi.org/10.1038/s41598-017-02462-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451439PMC
May 2017

Does the degree of coarctation of the aorta influence wall shear stress focal heterogeneity?

Annu Int Conf IEEE Eng Med Biol Soc 2016 Aug;2016:3429-3432

The development of atherosclerosis in the aorta is associated with low and oscillatory wall shear stress for normal patients. Moreover, localized differences in wall shear stress heterogeneity have been correlated with the presence of complex plaques in the descending aorta. While it is known that coarctation of the aorta can influence indices of wall shear stress, it is unclear how the degree of narrowing influences resulting patterns. We hypothesized that the degree of coarctation would have a strong influence on focal heterogeneity of wall shear stress. To test this hypothesis, we modeled the fluid dynamics in a patient-specific aorta with varied degrees of coarctation. We first validated a massively parallel computational model against experimental results for the patient geometry and then evaluated local shear stress patterns for a range of degrees of coarctation. Wall shear stress patterns at two cross sectional slices prone to develop atherosclerotic plaques were evaluated. Levels at different focal regions were compared to the conventional measure of average circumferential shear stress to enable localized quantification of coarctation-induced shear stress alteration. We find that the coarctation degree causes highly heterogeneous changes in wall shear stress.
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http://dx.doi.org/10.1109/EMBC.2016.7591465DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905411PMC
August 2016

Structural alterations of the brainstem in migraine.

Neuroimage Clin 2017 2;13:223-227. Epub 2016 Nov 2.

Mayo Clinic-Arizona, Department of Neurology, Phoenix, AZ, USA.

Atypical brainstem modulation of pain might contribute to changes in sensory processing typical of migraine. The study objective was to investigate whether migraine is associated with brainstem structural alterations that correlate with this altered pain processing. MRI T1-weighted images of 55 migraine patients and 58 healthy controls were used to: (1) create deformable mesh models of the brainstem that allow for shape analyses; (2) calculate volumes of the midbrain, pons, medulla and the superior cerebellar peduncles; (3) interrogate correlations between regional brainstem volumes, cutaneous heat pain thresholds, and allodynia symptoms. Migraineurs had smaller midbrain volumes (healthy controls = 61.28 mm, SD = 5.89; migraineurs = 58.80 mm, SD = 6.64;  = 0.038), and significant ( < 0.05) inward deformations in the ventral midbrain and pons, and outward deformations in the lateral medulla and dorsolateral pons relative to healthy controls. Migraineurs had a correlation between ASC-12 allodynia symptom severity with midbrain volume ( = - 0.32;  = 0.019) and a correlation between cutaneous heat pain thresholds with medulla ( = 0.337;  = 0.012) and cerebellar peduncle volumes ( = 0.435;  = 0.001). Migraineurs with greater symptoms of allodynia have smaller midbrain volumes and migraineurs with lower heat pain thresholds have smaller medulla and cerebellar peduncles. The brainstem likely plays a role in altered sensory processing in migraine and brainstem structure might reflect severity of allodynia and hypersensitivity to pain in migraine.
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http://dx.doi.org/10.1016/j.nicl.2016.10.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5157793PMC
November 2017

Three-dimensional printing: changing clinical care or just a passing fad?

Curr Opin Cardiol 2017 01;32(1):86-92

Phoenix Children's Hospital, Phoenix, Arizona, USA.

Purpose Of Review: Advances in medical imaging and three-dimensional (3D) reconstruction software have enabled a proliferation of 3D modeling and 3D printing for clinical applications. In particular, 3D printing has garnered an extraordinary media presence over the past few years. There is growing optimism that 3D printing can address patient specificity and complexity for improved interventional and surgical planning. Will this relatively untested technology bring about a paradigm shift in the clinical environment, or is it just a transient fad?

Recent Findings: Case studies and series centered around 3D printing are omnipresent in clinical and engineering journals. These primarily qualitative studies support the potential efficacy of the emerging technology. Few studies analyze the value of 3D printing, weighing its potential benefits against increasing costs (e.g., institutional overhead, labor, and materials).

Summary: Clinical integration of 3D printing is growing rapidly, and its adoption into clinical practice presents unique workflow challenges. There are numerous clinical trials on the horizon that will finally help to elucidate the measured impact of 3D printing on clinical outcomes through quantitative analyses of clinical and economic metrics. The contrived integration of 3D printing into clinical practice seems all but certain as the value of this technology becomes more and more evident.
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http://dx.doi.org/10.1097/HCO.0000000000000352DOI Listing
January 2017

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma.

Neuro Oncol 2017 01 8;19(1):128-137. Epub 2016 Aug 8.

Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.).

Background: Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments.

Methods: We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV).

Results: We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32).

Conclusion: MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.
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http://dx.doi.org/10.1093/neuonc/now135DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5193022PMC
January 2017

A High Performance Pulsatile Pump for Aortic Flow Experiments in 3-Dimensional Models.

Cardiovasc Eng Technol 2016 06 16;7(2):148-58. Epub 2016 Mar 16.

School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.

Aortic pathologies such as coarctation, dissection, and aneurysm represent a particularly emergent class of cardiovascular diseases. Computational simulations of aortic flows are growing increasingly important as tools for gaining understanding of these pathologies, as well as for planning their surgical repair. In vitro experiments are required to validate the simulations against real world data, and the experiments require a pulsatile flow pump system that can provide physiologic flow conditions characteristic of the aorta. We designed a newly capable piston-based pulsatile flow pump system that can generate high volume flow rates (850 mL/s), replicate physiologic waveforms, and pump high viscosity fluids against large impedances. The system is also compatible with a broad range of fluid types, and is operable in magnetic resonance imaging environments. Performance of the system was validated using image processing-based analysis of piston motion as well as particle image velocimetry. The new system represents a more capable pumping solution for aortic flow experiments than other available designs, and can be manufactured at a relatively low cost.
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http://dx.doi.org/10.1007/s13239-016-0260-3DOI Listing
June 2016

Cerebral Aneurysm Clipping Surgery Simulation Using Patient-Specific 3D Printing and Silicone Casting.

World Neurosurg 2016 Apr 22;88:175-181. Epub 2016 Jan 22.

School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, USA; Cardiac 3D Print Lab, Phoenix Children's Hospital, Phoenix, Arizona, USA; School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona, USA.

Background: Neurosurgery simulator development is growing as practitioners recognize the need for improved instructional and rehearsal platforms to improve procedural skills and patient care. In addition, changes in practice patterns have decreased the volume of specific cases, such as aneurysm clippings, which reduces the opportunity for operating room experience.

Objective: The authors developed a hands-on, dimensionally accurate model for aneurysm clipping using patient-derived anatomic data and three-dimensional (3D) printing. Design of the model focused on reproducibility as well as adaptability to new patient geometry.

Methods: A modular, reproducible, and patient-derived medical simulacrum was developed for medical learners to practice aneurysmal clipping procedures. Various forms of 3D printing were used to develop a geometrically accurate cranium and vascular tree featuring 9 patient-derived aneurysms. 3D printing in conjunction with elastomeric casting was leveraged to achieve a patient-derived brain model with tactile properties not yet available from commercial 3D printing technology. An educational pilot study was performed to gauge simulation efficacy.

Results: Through the novel manufacturing process, a patient-derived simulacrum was developed for neurovascular surgical simulation. A follow-up qualitative study suggests potential to enhance current educational programs; assessments support the efficacy of the simulacrum.

Conclusions: The proposed aneurysm clipping simulator has the potential to improve learning experiences in surgical environment. 3D printing and elastomeric casting can produce patient-derived models for a dynamic learning environment that add value to surgical training and preparation.
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http://dx.doi.org/10.1016/j.wneu.2015.12.102DOI Listing
April 2016

Matching Complexity and Educational Goals in Simulation-Based Education.

World Neurosurg 2016 Feb 24;86:10-2. Epub 2015 Dec 24.

Department of Neurological Surgery, Mayo Clinic, Scottsdale/Phoenix, Arizona, USA.

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http://dx.doi.org/10.1016/j.wneu.2015.12.016DOI Listing
February 2016

Hemodynamic characterization of geometric cerebral aneurysm templates.

J Biomech 2016 07 28;49(11):2118-2126. Epub 2015 Nov 28.

School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States; School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, United States.

Hemodynamics are currently considered to a lesser degree than geometry in clinical practices for evaluating cerebral aneurysm (CA) risk and planning CA treatment. This study establishes fundamental relationships between three clinically recognized CA geometric factors and four clinically relevant hemodynamic responses. The goal of the study is to develop a more combined geometric/hemodynamic basis for informing clinical decisions. Flows within eight idealized template geometries were simulated using computational fluid dynamics and measured using particle image velocimetry under both steady and pulsatile flow conditions. The geometric factor main effects were then analyzed to quantify contributions made by the geometric factors (aneurysmal dome size (DS), dome-to-neck ratio (DNR), and parent-vessel contact angle (PV-CA)) to effects on the hemodynamic responses (aneurysmal and neck-plane root-mean-square velocity magnitude (Vrms), aneurysmal wall shear stress (WSS), and cross-neck flow (CNF)). Two anatomical aneurysm models were also examined to investigate how well the idealized findings would translate to more realistic CA geometries. DNR made the greatest contributions to effects on hemodynamics including a 75.05% contribution to aneurysmal Vrms and greater than 35% contributions to all responses. DS made the next greatest contributions, including a 43.94% contribution to CNF and greater than 20% contributions to all responses. PV-CA and several factor interactions also made contributions of greater than 10%. The anatomical aneurysm models and the most similar idealized templates demonstrated consistent hemodynamic response patterns. This study demonstrates how individual geometric factors, and combinations thereof, influence CA hemodynamics. Bridging the gap between geometry and flow in this quantitative yet practical way may have potential to improve CA evaluation and treatment criteria. Agreement among results from idealized and anatomical models further supports the potential for a template-based approach to play a useful role in clinical practice.
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http://dx.doi.org/10.1016/j.jbiomech.2015.11.034DOI Listing
July 2016

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PLoS One 2015 24;10(11):e0141506. Epub 2015 Nov 24.

Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America.

Background: Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM.

Methods: We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set.

Results: We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients).

Conclusion: Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141506PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4658019PMC
June 2016

Hemodynamic Characterization of Geometric Cerebral Aneurysm Templates Treated With Embolic Coils.

J Biomech Eng 2016 Feb;138(2):021011

Embolic coiling is one of the most effective treatments for cerebral aneurysms (CAs), largely due to the hemodynamic modifications that the treatment effects in the aneurysmal environment. However, coiling can have very different hemodynamic outcomes in aneurysms with different geometries. Previous work in the field of biofluid mechanics has demonstrated on a general level that geometry is a driving factor behind aneurysmal hemodynamics. The goal of this study was to relate two specific geometric factors that describe CAs (i.e., dome size (DS) and parent-vessel contact-angle (PV-CA)) and one factor that describes treatment (i.e., coil packing density (PD)) to three clinically relevant hemodynamic responses (i.e., aneurysmal root-mean-square velocity (Vrms), aneurysmal wall shear stress (WSS), and cross-neck flow (CNF)). Idealized models of basilar tip aneurysms were created in both virtual and physical forms to satisfy two-level multifactorial experimental designs. Steady and pulsatile flow hemodynamics were then evaluated in the virtual models using computational fluid dynamics (CFD) (before and after virtual treatment with finite element (FE) embolic coil models), and hemodynamics were also evaluated in the physical models using particle image velocimetry (PIV) (before and after treatment with actual embolic coils). Results showed that among the factors considered, PD made the greatest contributions to effects on hemodynamic responses in and around the aneurysmal sac (i.e., Vrms and WSS), while DS made the greatest contributions to effects on hemodynamics at the neck (i.e., CNF). Results also showed that while a geometric factor (e.g., PV-CA) may play a relatively minor role in dictating hemodynamics in the untreated case, the same factor can play a much greater role after coiling. We consider the significance of these findings in the context of aneurysmal recurrence and rupture, and explore potential roles for the proposed methods in endovascular treatment planning.
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http://dx.doi.org/10.1115/1.4032046DOI Listing
February 2016

Ventriculostomy Simulation Using Patient-Specific Ventricular Anatomy, 3D Printing, and Hydrogel Casting.

World Neurosurg 2015 Nov 20;84(5):1333-9. Epub 2015 Jun 20.

Duke Neurosurgery, Duke University, Durham, North Carolina, USA.

Background: Educational simulators provide a means for students and experts to learn and refine surgical skills. Educators can leverage the strengths of medical simulators to effectively teach complex and high-risk surgical procedures, such as placement of an external ventricular drain.

Objective: Our objective was to develop a cost-effective, patient-derived medical simulacrum for cerebral lateral ventriculostomy.

Methods: A cost-effective, patient-derived medical simulacrum was developed for placement of an external lateral ventriculostomy. Elastomeric and gel casting techniques were used to achieve realistic brain geometry and material properties. 3D printing technology was leveraged to develop accurate cranial properties and dimensions. An economical, gravity-driven pump was developed to provide normal and abnormal ventricular pressures. A small pilot study was performed to gauge simulation efficacy using a technology acceptance model.

Results: An accurate geometric representation of the brain was developed with independent lateral cerebral ventricular chambers. A gravity-driven pump pressurized the ventricular cavities to physiologic values. A qualitative study illustrated that the simulation has potential as an educational tool to train medical professionals in the ventriculostomy procedure.

Conclusion: The ventricular simulacrum can improve learning in a medical education environment. Rapid prototyping and multi-material casting techniques can produce patient-derived models for cost-effective and realistic surgical training scenarios.
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http://dx.doi.org/10.1016/j.wneu.2015.06.016DOI Listing
November 2015

Computational Fluid Dynamics to Evaluate the Management of a Giant Internal Carotid Artery Aneurysm.

World Neurosurg 2015 Jun 22;83(6):1057-65. Epub 2014 Dec 22.

Department of Neurological Surgery, University of Southern California, Los Angeles, California, USA.

Background: Giant intracranial aneurysms are rare lesions that present uniquely complex therapeutic challenges. Computational fluid dynamics (CFD) has been used to simulate the hemodynamic environments of developing and ruptured cerebral aneurysms. In this study, we use CFD to examine retrospectively hemodynamic changes during the complicated clinical course of a giant carotid aneurysm.

Objective: To take an innovative, CFD-based approach to retrospective analysis of the surgical management and clinical course of a giant carotid aneurysm.

Methods: Pre- and posttreatment image data were first segmented to produce computational aneurysm models. Flow within the models was then simulated using CFD. Simulated flow and wall shear stress (WSS) profiles were analyzed and used to examine hemodynamic changes during the clinical course of the patient, after 2 independent treatments.

Results: Greater WSS magnitudes and a more localized flow impingement region were observed at the distal portion of the aneurysm after both clinical interventions. These relative, acute changes in hemodynamic features at the distal aneurysm wall were greatest after the second intervention and may have preceded rupture of the aneurysm in that region.

Conclusions: The application of CFD to the management of a giant intracranial aneurysm showed unexpected posttreatment changes in flow and WSS profiles. The simulation results offer a viable explanation for the observed clinical course. This study demonstrates potential for the use of CFD preoperatively for decision-making in the surgical and endovascular management of intracranial aneurysms.
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http://dx.doi.org/10.1016/j.wneu.2014.12.038DOI Listing
June 2015

Neuronavigation using three-dimensional proton magnetic resonance spectroscopy data.

Stereotact Funct Neurosurg 2014 18;92(5):306-14. Epub 2014 Sep 18.

School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Ariz., USA.

Background: Applications in clinical medicine can benefit from fusion of spectroscopy data with anatomical imagery. For example, new 3-dimensional (3D) spectroscopy techniques allow for improved correlation of metabolite profiles with specific regions of interest in anatomical tumor images, which can be useful in characterizing and treating heterogeneous tumors that appear structurally homogeneous.

Objectives: We sought to develop a clinical workflow and uniquely capable custom software tool to integrate advanced 3-tesla 3D proton magnetic resonance spectroscopic imaging ((1)H-MRSI) into industry standard image-guided neuronavigation systems, especially for use in brain tumor surgery.

Methods: (1)H-MRSI spectra from preoperative scanning on 15 patients with recurrent or newly diagnosed meningiomas were processed and analyzed, and specific voxels were selected based on their chemical contents. 3D neuronavigation overlays were then generated and applied to anatomical image data in the operating room. The proposed 3D methods fully account for scanner calibration and comprise tools that we have now made publicly available.

Results: The new methods were quantitatively validated through a phantom study and applied successfully to mitigate biopsy uncertainty in a clinical study of meningiomas.

Conclusions: The proposed methods improve upon the current state of the art in neuronavigation through the use of detailed 3D (1)H-MRSI data. Specifically, 3D MRSI-based overlays provide comprehensive, quantitative visual cues and location information during neurosurgery, enabling a progressive new form of online spectroscopy-guided neuronavigation.
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http://dx.doi.org/10.1159/000363751DOI Listing
June 2015

Comparison among different high porosity stent configurations: hemodynamic effects of treatment in a large cerebral aneurysm.

J Biomech Eng 2014 Feb;136(2):021013

Whether treated surgically or with endovascular techniques, large and giant cerebral aneurysms are particularly difficult to treat. Nevertheless, high porosity stents can be used to accomplish stent-assisted coiling and even standalone stent-based treatments that have been shown to improve the occlusion of such aneurysms. Further, stent assisted coiling can reduce the incidence of complications that sometimes result from embolic coiling (e.g., neck remnants and thromboembolism). However, in treating cerebral aneurysms at bifurcation termini, it remains unclear which configuration of high porosity stents will result in the most advantageous hemodynamic environment. The goal of this study was to compare how three different stent configurations affected fluid dynamics in a large patient-specific aneurysm model. Three common stent configurations were deployed into the model: a half-Y, a full-Y, and a crossbar configuration. Particle image velocimetry was used to examine post-treatment flow patterns and quantify root-mean-squared velocity magnitude (VRMS) within the aneurysmal sac. While each configuration did reduce VRMS within the aneurysm, the full-Y configuration resulted in the greatest reduction across all flow conditions (an average of 56% with respect to the untreated case). The experimental results agreed well with clinical follow up after treatment with the full-Y configuration; there was evidence of thrombosis within the sac from the stents alone before coil embolization was performed. A computational simulation of the full-Y configuration aligned well with the experimental and in vivo findings, indicating potential for clinically useful prediction of post-treatment hemodynamics. This study found that applying different stent configurations resulted in considerably different fluid dynamics in an anatomically accurate aneurysm model and that the full-Y configuration performed best. The study indicates that knowledge of how stent configurations will affect post-treatment hemodynamics could be important in interventional planning and demonstrates the capability for such planning based on novel computational tools.
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http://dx.doi.org/10.1115/1.4026257DOI Listing
February 2014

Finite element modeling of embolic coil deployment: multifactor characterization of treatment effects on cerebral aneurysm hemodynamics.

J Biomech 2013 Nov 18;46(16):2809-16. Epub 2013 Sep 18.

School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler, ECG 334, P.O. Box 879709, Tempe, AZ 85287-9709, United States. Electronic address:

Endovascular coiling is the most common treatment for cerebral aneurysms. During the treatment, a sequence of embolic coils with different stiffness, shapes, sizes, and lengths is deployed to fill the aneurysmal sac. Although coil packing density has been clinically correlated with treatment success, many studies have also reported success at low packing densities, as well as recurrence at high packing densities. Such reports indicate that other factors may influence treatment success. In this study, we used a novel finite element approach and computational fluid dynamics (CFD) to investigate the effects of packing density, coil shape, aneurysmal neck size, and parent vessel flow rate on aneurysmal hemodynamics. The study examines a testbed of 80 unique CFD simulations of post-treatment flows in idealized basilar tip aneurysm models. Simulated coil deployments were validated against in vitro and in vivo deployments. Among the investigated factors, packing density had the largest effect on intra-aneurysmal velocities. However, multifactor analysis of variance showed that coil shape can also have considerable effects, depending on packing density and neck size. Further, linear regression analysis showed an inverse relationship between mean void diameter in the aneurysm and mean intra-aneurysmal velocities, which underscores the importance of coil distribution and thus coil shape. Our study suggests that while packing density plays a key role in determining post-treatment hemodynamics, other factors such as coil shape, aneurysmal geometry, and parent vessel flow may also be very important.
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http://dx.doi.org/10.1016/j.jbiomech.2013.08.021DOI Listing
November 2013