Literature DB >> 24162859

Accuracy of computational cerebral aneurysm hemodynamics using patient-specific endovascular measurements.

Patrick M McGah1, Michael R Levitt, Michael C Barbour, Ryan P Morton, John D Nerva, Pierre D Mourad, Basavaraj V Ghodke, Danial K Hallam, Laligam N Sekhar, Louis J Kim, Alberto Aliseda.   

Abstract

Computational hemodynamic simulations of cerebral aneurysms have traditionally relied on stereotypical boundary conditions (such as blood flow velocity and blood pressure) derived from published values as patient-specific measurements are unavailable or difficult to collect. However, controversy persists over the necessity of incorporating such patient-specific conditions into computational analyses. We perform simulations using both endovascularly-derived patient-specific and typical literature-derived inflow and outflow boundary conditions. Detailed three-dimensional anatomical models of the cerebral vasculature are developed from rotational angiography data, and blood flow velocity and pressure are measured in situ by a dual-sensor pressure and velocity endovascular guidewire at multiple peri-aneurysmal locations in 10 unruptured cerebral aneurysms. These measurements are used to define inflow and outflow boundary conditions for computational hemodynamic models of the aneurysms. The additional in situ measurements which are not prescribed in the simulation are then used to assess the accuracy of the simulated flow velocity and pressure drop. Simulated velocities using patient-specific boundary conditions show good agreement with the guidewire measurements at measurement locations inside the domain, with no bias in the agreement and a random scatter of ≈25%. Simulated velocities using the simplified, literature-derived values show a systematic bias and over-predicted velocity by ≈30% with a random scatter of ≈40%. Computational hemodynamics using endovascularly measured patient-specific boundary conditions have the potential to improve treatment predictions as they provide more accurate and precise results of the aneurysmal hemodynamics than those based on commonly accepted reference values for boundary conditions.

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Year:  2013        PMID: 24162859      PMCID: PMC3941739          DOI: 10.1007/s10439-013-0930-3

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  33 in total

1.  Patient-specific computational hemodynamics of intracranial aneurysms from 3D rotational angiography and CT angiography: an in vivo reproducibility study.

Authors:  A J Geers; I Larrabide; A G Radaelli; H Bogunovic; M Kim; H A F Gratama van Andel; C B Majoie; E VanBavel; A F Frangi
Journal:  AJNR Am J Neuroradiol       Date:  2010-12-23       Impact factor: 3.825

2.  Computational hemodynamics in cerebral aneurysms: the effects of modeled versus measured boundary conditions.

Authors:  Alberto Marzo; Pankaj Singh; Ignacio Larrabide; Alessandro Radaelli; Stuart Coley; Matt Gwilliam; Iain D Wilkinson; Patricia Lawford; Philippe Reymond; Umang Patel; Alejandro Frangi; D Rod Hose
Journal:  Ann Biomed Eng       Date:  2010-10-23       Impact factor: 3.934

3.  Computational modeling and flow diverters: a teaching moment.

Authors:  D A Steinman
Journal:  AJNR Am J Neuroradiol       Date:  2011-05-26       Impact factor: 3.825

4.  Association of hemodynamic characteristics and cerebral aneurysm rupture.

Authors:  J R Cebral; F Mut; J Weir; C M Putman
Journal:  AJNR Am J Neuroradiol       Date:  2010-11-04       Impact factor: 3.825

5.  Temporal variations of wall shear stress parameters in intracranial aneurysms--importance of patient-specific inflow waveforms for CFD calculations.

Authors:  Christof Karmonik; Christopher Yen; Orlando Diaz; Richard Klucznik; Robert G Grossman; Goetz Benndorf
Journal:  Acta Neurochir (Wien)       Date:  2010-08       Impact factor: 2.216

6.  Validation of a patient-specific one-dimensional model of the systemic arterial tree.

Authors:  Philippe Reymond; Yvette Bohraus; Fabienne Perren; Francois Lazeyras; Nikos Stergiopulos
Journal:  Am J Physiol Heart Circ Physiol       Date:  2011-05-27       Impact factor: 4.733

7.  Hemodynamic-morphologic discriminants for intracranial aneurysm rupture.

Authors:  Jianping Xiang; Sabareesh K Natarajan; Markus Tremmel; Ding Ma; J Mocco; L Nelson Hopkins; Adnan H Siddiqui; Elad I Levy; Hui Meng
Journal:  Stroke       Date:  2010-11-24       Impact factor: 7.914

8.  Effect of velocity profile skewing on blood velocity and volume flow waveforms derived from maximum Doppler spectral velocity.

Authors:  Jonathan P Mynard; David A Steinman
Journal:  Ultrasound Med Biol       Date:  2013-02-27       Impact factor: 2.998

Review 9.  Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model--a report on the Virtual Intracranial Stenting Challenge 2007.

Authors:  A G Radaelli; L Augsburger; J R Cebral; M Ohta; D A Rüfenacht; R Balossino; G Benndorf; D R Hose; A Marzo; R Metcalfe; P Mortier; F Mut; P Reymond; L Socci; B Verhegghe; A F Frangi
Journal:  J Biomech       Date:  2008-06-25       Impact factor: 2.712

10.  Aneurysm growth occurs at region of low wall shear stress: patient-specific correlation of hemodynamics and growth in a longitudinal study.

Authors:  Loic Boussel; Vitaliy Rayz; Charles McCulloch; Alastair Martin; Gabriel Acevedo-Bolton; Michael Lawton; Randall Higashida; Wade S Smith; William L Young; David Saloner
Journal:  Stroke       Date:  2008-08-07       Impact factor: 7.914

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  8 in total

1.  Computational fluid dynamics of cerebral aneurysm coiling using high-resolution and high-energy synchrotron X-ray microtomography: comparison with the homogeneous porous medium approach.

Authors:  Michael R Levitt; Michael C Barbour; Sabine Rolland du Roscoat; Christian Geindreau; Venkat K Chivukula; Patrick M McGah; John D Nerva; Ryan P Morton; Louis J Kim; Alberto Aliseda
Journal:  J Neurointerv Surg       Date:  2016-07-12       Impact factor: 5.836

2.  Leveraging Patient-Specific Simulated Angiograms to Characterize Cerebral Aneurysm Hemodynamics using Computational Fluid Dynamics.

Authors:  V Chivukula; R White; A Shields; J Davies; M Mokin; D R Bednarek; S Rudin; C Ionita
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

3.  Efficient simulation of a low-profile visualized intraluminal support device: a novel fast virtual stenting technique.

Authors:  Shengzhang Wang; Xinjian Yang; Qianqian Zhang; Jian Liu; Yisen Zhang; Ying Zhang; Zhongbin Tian; Wenqiang Li; Junfan Chen; Xiao Mo; Yunhan Cai; Nikhil Paliwal; Hui Meng; Yang Wang
Journal:  Chin Neurosurg J       Date:  2018-03-22

4.  Computational Modeling of Venous Sinus Stenosis in Idiopathic Intracranial Hypertension.

Authors:  M R Levitt; P M McGah; K Moon; F C Albuquerque; C G McDougall; M Y S Kalani; L J Kim; A Aliseda
Journal:  AJNR Am J Neuroradiol       Date:  2016-05-19       Impact factor: 3.825

5.  In vitro validation of endovascular Doppler-derived flow rates in models of the cerebral circulation.

Authors:  P M McGah; J D Nerva; R P Morton; M C Barbour; M R Levitt; P D Mourad; L J Kim; A Aliseda
Journal:  Physiol Meas       Date:  2015-10-09       Impact factor: 2.833

Review 6.  Predictive modeling and in vivo assessment of cerebral blood flow in the management of complex cerebral aneurysms.

Authors:  Brian P Walcott; Clemens Reinshagen; Christopher J Stapleton; Omar Choudhri; Vitaliy Rayz; David Saloner; Michael T Lawton
Journal:  J Cereb Blood Flow Metab       Date:  2016-03-23       Impact factor: 6.200

7.  Phase-contrast MRI versus numerical simulation to quantify hemodynamical changes in cerebral aneurysms after flow diverter treatment.

Authors:  Sergey Sindeev; Philipp Georg Arnold; Sergey Frolov; Sascha Prothmann; Dieter Liepsch; Andrea Balasso; Philipp Berg; Stephan Kaczmarz; Jan Stefan Kirschke
Journal:  PLoS One       Date:  2018-01-05       Impact factor: 3.240

8.  A Highly Automated Computational Method for Modeling of Intracranial Aneurysm Hemodynamics.

Authors:  Jung-Hee Seo; Parastou Eslami; Justin Caplan; Rafael J Tamargo; Rajat Mittal
Journal:  Front Physiol       Date:  2018-06-12       Impact factor: 4.566

  8 in total

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