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Safdar S, Zwick BF, Yu Y, Bourantas GC, Joldes GR, Warfield SK, Hyde DE, Frisken S, Kapur T, Kikinis R, Golby A, Nabavi A, Wittek A, Miller K. SlicerCBM: automatic framework for biomechanical analysis of the brain. Int J Comput Assist Radiol Surg 2023; 18:1925-1940. [PMID: 37004646 PMCID: PMC10497672 DOI: 10.1007/s11548-023-02881-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/17/2023] [Indexed: 04/04/2023]
Abstract
PURPOSE Brain shift that occurs during neurosurgery disturbs the brain's anatomy. Prediction of the brain shift is essential for accurate localisation of the surgical target. Biomechanical models have been envisaged as a possible tool for such predictions. In this study, we created a framework to automate the workflow for predicting intra-operative brain deformations. METHODS We created our framework by uniquely combining our meshless total Lagrangian explicit dynamics (MTLED) algorithm for computing soft tissue deformations, open-source software libraries and built-in functions within 3D Slicer, an open-source software package widely used for medical research. Our framework generates the biomechanical brain model from the pre-operative MRI, computes brain deformation using MTLED and outputs results in the form of predicted warped intra-operative MRI. RESULTS Our framework is used to solve three different neurosurgical brain shift scenarios: craniotomy, tumour resection and electrode placement. We evaluated our framework using nine patients. The average time to construct a patient-specific brain biomechanical model was 3 min, and that to compute deformations ranged from 13 to 23 min. We performed a qualitative evaluation by comparing our predicted intra-operative MRI with the actual intra-operative MRI. For quantitative evaluation, we computed Hausdorff distances between predicted and actual intra-operative ventricle surfaces. For patients with craniotomy and tumour resection, approximately 95% of the nodes on the ventricle surfaces are within two times the original in-plane resolution of the actual surface determined from the intra-operative MRI. CONCLUSION Our framework provides a broader application of existing solution methods not only in research but also in clinics. We successfully demonstrated the application of our framework by predicting intra-operative deformations in nine patients undergoing neurosurgical procedures.
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Affiliation(s)
- Saima Safdar
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia.
| | - Benjamin F Zwick
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Yue Yu
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - George C Bourantas
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
- Department of Agriculture, University of Patras Nea Ktiria, 30200, Campus Mesologhi, Greece
| | - Grand R Joldes
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Simon K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Damon E Hyde
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sarah Frisken
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Tina Kapur
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Ron Kikinis
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Alexandra Golby
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Arya Nabavi
- Department of Neurosurgery, KRH Klinikum Nordstadt, Hannover, Germany
| | - Adam Wittek
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Karol Miller
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
- Harvard Medical School, Boston, MA, USA
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Alkhatib F, Wittek A, Zwick BF, Bourantas GC, Miller K. Computation for biomechanical analysis of aortic aneurysms: the importance of computational grid. Comput Methods Biomech Biomed Engin 2023:1-17. [PMID: 37264784 DOI: 10.1080/10255842.2023.2218521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Aortic wall stress is the most common variable of interest in abdominal aortic aneurysm (AAA) rupture risk assessment. Computation of such stress has been dominated by finite element analysis. However, the effects of finite element (FE) formulation, element quality, and methods of FE mesh construction on the efficiency, robustness, and accuracy of such computation have attracted little attention. In this study, we fill this knowledge gap by comparing the results of the calculated aortic wall stress for ten AAA patients using tetrahedral and hexahedral meshes when varying the FE formulation (displacement-based and hybrid), FE shape functions, spatial integration scheme, and number of elements through the wall thickness.
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Affiliation(s)
- Farah Alkhatib
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
| | - Adam Wittek
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
| | - Benjamin F Zwick
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
| | - George C Bourantas
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
- Department of Agriculture, University of Patras, Rio, Greece
| | - Karol Miller
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
- Harvard Medical School, Boston, MA, USA
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Zwick BF, Safdar S, Bourantas GC, Joldes GR, Hyde DE, Warfield SK, Wittek A, Miller K. Image data and computational grids for computing brain shift and solving the electrocorticography forward problem. Data Brief 2023; 48:109122. [PMID: 37128587 PMCID: PMC10147975 DOI: 10.1016/j.dib.2023.109122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 05/03/2023] Open
Abstract
This article describes the dataset applied in the research reported in NeuroImage article "Patient-specific solution of the electrocorticography forward problem in deforming brain" [1] that is available for download from the Zenodo data repository (https://zenodo.org/record/7687631) [2]. Preoperative structural and diffusion-weighted magnetic resonance (MR) and postoperative computed tomography (CT) images of a 12-year-old female epilepsy patient under evaluation for surgical intervention were obtained retrospectively from Boston Children's Hospital. We used these images to conduct the analysis at The University of Western Australia's Intelligent Systems for Medicine Laboratory using SlicerCBM [3], our open-source software extension for the 3D Slicer medical imaging platform. As part of the analysis, we processed the images to extract the patient-specific brain geometry; created computational grids, including a tetrahedral grid for the meshless solution of the biomechanical model and a regular hexahedral grid for the finite element solution of the electrocorticography forward problem; predicted the postoperative MRI and DTI that correspond to the brain configuration deformed by the placement of subdural electrodes using biomechanics-based image warping; and solved the patient-specific electrocorticography forward problem to compute the electric potential distribution within the patient's head using the original preoperative and predicted postoperative image data. The well-established and open-source file formats used in this dataset, including Nearly Raw Raster Data (NRRD) files for images, STL files for surface geometry, and Visualization Toolkit (VTK) files for computational grids, allow other research groups to easily reuse the data presented herein to solve the electrocorticography forward problem accounting for the brain shift caused by implantation of subdural grid electrodes.
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Affiliation(s)
- Benjamin F. Zwick
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
- Corresponding author.
| | - Saima Safdar
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - George C. Bourantas
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Grand R. Joldes
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Damon E. Hyde
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Simon K. Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Adam Wittek
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
| | - Karol Miller
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia
- Harvard Medical School, Boston, MA, USA
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Lampropoulos DS, Boutopoulos ID, Bourantas GC, Miller K, Zampakis PE, Loukopoulos VC. Hemodynamics of anterior circulation intracranial aneurysms with daughter blebs: investigating the multidirectionality of blood flow fields. Comput Methods Biomech Biomed Engin 2023; 26:113-125. [PMID: 35297711 DOI: 10.1080/10255842.2022.2048374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Recent advances in diagnostic neuroradiological imaging, allowed the detection of unruptured intracranial aneurysms (IAs). The shape - irregular or multilobular - of the aneurysmal dome, is considered as a possible rupture risk factor, independently of the size, the location and patient medical background. Disturbed blood flow fields in particular is thought to play a key role in IAs progression. However, there is an absence of widely-used hemodynamic indices to quantify the extent of a multi-directional disturbed flow. We simulated blood flow in twelve patient-specific anterior circulation unruptured intracranial aneurysms with daughter blebs utilizing the spectral/hp element framework Nektar++. We simulated three cardiac cycles using a volumetric flow rate waveform while we considered blood as a Newtonian fluid. To investigate the multidirectionality of the blood flow fields, besides the time-averaged wall shear stress (TAWSS), we calculated the oscillatory shear index (OSI), the relative residence time (RRT) and the time-averaged cross flow index (TACFI). Our CFD simulations suggest that in the majority of our vascular models there is a formation of complex intrasaccular flow patterns, resulting to low and highly oscillating WSS, especially in the area of the daughter blebs. The existence of disturbed multi-directional blood flow fields is also evident by the distributions of the RRT and the TACFI. These findings further support the theory that IAs with daughter blebs are linked to a potentially increased rupture risk.
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Affiliation(s)
| | | | - George C Bourantas
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia
| | - Karol Miller
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.,Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Petros E Zampakis
- Department of Diagnostic and Interventional Neuroradiology, University of Patras, Patras, Greece
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Lampropoulos DS, Bourantas GC, Zwick BF, Kagadis GC, Wittek A, Miller K, Loukopoulos VC. Simulation of intracranial hemodynamics by an efficient and accurate immersed boundary scheme. Int J Numer Method Biomed Eng 2021; 37:e3524. [PMID: 34448366 DOI: 10.1002/cnm.3524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
We use computational fluid dynamics (CFD) to simulate blood flow in intracranial aneurysms (IAs). Despite ongoing improvements in the accuracy and efficiency of body-fitted CFD solvers, generation of a high quality mesh appears as the bottleneck of the flow simulation and strongly affects the accuracy of the numerical solution. To overcome this drawback, we use an immersed boundary method. The proposed approach solves the incompressible Navier-Stokes equations on a rectangular (box) domain discretized using uniform Cartesian grid using the finite element method. The immersed object is represented by a set of points (Lagrangian points) located on the surface of the object. Grid local refinement is applied using an automated algorithm. We verify and validate the proposed method by comparing our numerical findings with published experimental results and analytical solutions. We demonstrate the applicability of the proposed scheme on patient-specific blood flow simulations in IAs.
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Affiliation(s)
| | - George C Bourantas
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia
| | - Benjamin F Zwick
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia
| | - George C Kagadis
- Department of Medical Physics, School of Medicine, University of Patras, Rion, Greece
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Adam Wittek
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia
| | - Karol Miller
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA
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Bourantas GC, Loukopoulos VC, Burganos VN, Nikiforidis GC. A meshless point collocation treatment of transient bioheat problems. Int J Numer Method Biomed Eng 2014; 30:587-601. [PMID: 24574248 DOI: 10.1002/cnm.2626] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Revised: 10/01/2013] [Accepted: 12/19/2013] [Indexed: 06/03/2023]
Abstract
A meshless numerical method is proposed for the solution of the transient bioheat equation in two and three dimensions. The Pennes bioheat equation is extended in order to incorporate water evaporation, tissue damage, and temperature-dependent tissue properties during tumor ablation. The conductivity of the tissue is not assumed constant but is treated as a local function to simulate local variability due to the existence of usually unclear interfacing of healthy and pathological segments. In this way, one avoids the need for accurate identification of the boundaries between pathological and healthy regions, which is a typical problem in medical practice, and sidesteps, evidently, the corresponding mathematical treatment of such boundaries, which is usually a tedious procedure with some inevitable degree of approximation. The numerical results of the new method for test applications of the bioheat transfer equation are validated against analytical predictions and predictions of other numerical methods. 3D simulations are presented that involve the modeling of tumor ablation and account for metabolic heat generation, blood perfusion, and heat ablation using realistic values for the various parameters. An evaluation of the effective medium approximation to homogenize conductivity fields for use with the bioheat equation is also provided.
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Affiliation(s)
- G C Bourantas
- Institute of Chemical Engineering Sciences, Foundation for Research and Technology, PO Box 1414, GR-26504, Patras, Greece
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Bourantas GC, Ghommem M, Kagadis GC, Katsanos K, Loukopoulos VC, Burganos VN, Nikiforidis GC. Real-time tumor ablation simulation based on the dynamic mode decomposition method. Med Phys 2014; 41:053301. [DOI: 10.1118/1.4870976] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Kagadis GC, Skouras ED, Bourantas GC, Paraskeva CA, Katsanos K, Karnabatidis D, Nikiforidis GC. Computational representation and hemodynamic characterization of in vivo acquired severe stenotic renal artery geometries using turbulence modeling. Med Eng Phys 2008; 30:647-60. [PMID: 17714975 DOI: 10.1016/j.medengphy.2007.07.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2006] [Revised: 04/02/2007] [Accepted: 07/11/2007] [Indexed: 11/22/2022]
Abstract
The present study reports on computational fluid dynamics in the case of severe renal artery stenosis (RAS). An anatomically realistic model of a renal artery was reconstructed from CT scans, and used to conduct CFD simulations of blood flow across RAS. The recently developed shear stress transport (SST) turbulence model was pivotally applied in the simulation of blood flow in the region of interest. Blood flow was studied in vivo under the presence of RAS and subsequently in simulated cases before the development of RAS, and after endovascular stent implantation. The pressure gradients in the RAS case were many orders of magnitude larger than in the healthy case. The presence of RAS increased flow resistance, which led to considerably lower blood flow rates. A simulated stent in place of the RAS decreased the flow resistance at levels proportional to, and even lower than, the simulated healthy case without the RAS. The wall shear stresses, differential pressure profiles, and net forces exerted on the surface of the atherosclerotic plaque at peak pulse were shown to be of relevant high distinctiveness, so as to be considered potential indicators of hemodynamically significant RAS.
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Affiliation(s)
- George C Kagadis
- Department of Medical Physics, School of Medicine, University of Patras, GR 26500 Rion, Greece.
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