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Deuter D, Haj A, Brawanski A, Krenkel L, Schmidt NO, Doenitz C. Fast simulation of hemodynamics in intracranial aneurysms for clinical use. Acta Neurochir (Wien) 2025; 167:56. [PMID: 40029490 PMCID: PMC11876267 DOI: 10.1007/s00701-025-06469-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 02/14/2025] [Indexed: 03/05/2025]
Abstract
BACKGROUND A widely accepted tool to assess hemodynamics, one of the most important factors in aneurysm pathophysiology, is Computational Fluid Dynamics (CFD). As current workflows are still time consuming and difficult to operate, CFD is not yet a standard tool in the clinical setting. There it could provide valuable information on aneurysm treatment, especially regarding local risks of rupture, which might help to optimize the individualized strategy of neurosurgical dissection during microsurgical aneurysm clipping. METHOD We established and validated a semi-automated workflow using 3D rotational angiographies of 24 intracranial aneurysms from patients having received aneurysm treatment at our centre. Reconstruction of vessel geometry and generation of volume meshes was performed using AMIRA 6.2.0 and ICEM 17.1. For solving ANSYS CFX was used. For validational checks, tests regarding the volumetric impact of smoothing operations, the impact of mesh sizes on the results (grid convergence), geometric mesh quality and time tests for the time needed to perform the workflow were conducted in subgroups. RESULTS Most of the steps of the workflow were performed directly on the 3D images requiring no programming experience. The workflow led to final CFD results in a mean time of 22 min 51.4 s (95%-CI 20 min 51.562 s-24 min 51.238 s, n = 5). Volume of the geometries after pre-processing was in mean 4.46% higher than before in the analysed subgroup (95%-CI 3.43-5.50%). Regarding mesh sizes, mean relative aberrations of 2.30% (95%-CI 1.51-3.09%) were found for surface meshes and between 1.40% (95%-CI 1.07-1.72%) and 2.61% (95%-CI 1.93-3.29%) for volume meshes. Acceptable geometric mesh quality of volume meshes was found. CONCLUSIONS We developed a semi-automated workflow for aneurysm CFD to benefit from hemodynamic data in the clinical setting. The ease of handling opens the workflow to clinicians untrained in programming. As previous studies have found that the distribution of hemodynamic parameters correlates with thin-walled aneurysm areas susceptible to rupture, these data might be beneficial for the operating neurosurgeon during aneurysm surgery, even in acute cases.
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Affiliation(s)
- Daniel Deuter
- Klinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | - Amer Haj
- Klinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Alexander Brawanski
- Klinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Lars Krenkel
- Regensburg Center of Biomedical Engineering (RCBE), OTH Regensburg and University of Regensburg, 93053, Regensburg, Germany
| | - Nils-Ole Schmidt
- Klinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Christian Doenitz
- Klinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
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Song M, Wang S, Qian Q, Zhou Y, Luo Y, Gong X. Intracranial aneurysm CTA images and 3D models dataset with clinical morphological and hemodynamic data. Sci Data 2024; 11:1213. [PMID: 39532900 PMCID: PMC11557944 DOI: 10.1038/s41597-024-04056-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 10/31/2024] [Indexed: 11/16/2024] Open
Abstract
Intracranial aneurysm is a cerebrovascular disease associated with a high rupture risk, often resulting in death or severe disability. Recent advances in AI enable the prediction of intracranial aneurysm initiation, progression, and rupture through medical image analysis. Despite growing research interest, there is a shortage of publicly available datasets for training and validating AI models. This paper presents a comprehensive dataset comprising high-resolution CTA images of 99 patients with 105 MCA aneurysms and 44 normal healthy controls, along with their respective clinical data and 3D models of aneurysms and the parent arteries derived from the CTA images. Furthermore, recognizing the significance of blood hemodynamics on aneurysm development, this dataset also included the morphological and hemodynamic parameters obtained by computational fluid dynamics (CFD) for each patient and healthy control, which can be utilized by researchers without prior CFD experience. This dataset will facilitate hypothesis-driven or data-driven research on intracranial aneurysms, and has the potential to deepen our understanding of this disease.
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Affiliation(s)
- Miao Song
- College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China
| | - Simin Wang
- College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China
| | - Qian Qian
- Yunnan Key Laboratory of Computer Technology Applications, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650504, China
| | - Yuan Zhou
- Logistics Engineering College, Shanghai Maritime University, Shanghai, 201306, China
| | - Yi Luo
- Department of Radiology, the First Affiliated Hospital of University of Science and Technology of China, Hefei, Anhui, 230036, China
| | - Xijun Gong
- Department of Radiology, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China.
- Medical Imaging Center, Anhui Medical University, Hefei, Anhui, 230032, China.
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Tang Y, Wei H, Zhang Z, Fu M, Feng J, Li Z, Liu X, Wu Y, Zhang J, You W, Xue R, Zhuo Y, Jiang Y, Li Y, Li R, Liu P. Transition of intracranial aneurysmal wall enhancement from high to low wall shear stress mediation with size increase: A hemodynamic study based on 7T magnetic resonance imaging. Heliyon 2024; 10:e30006. [PMID: 38694075 PMCID: PMC11061692 DOI: 10.1016/j.heliyon.2024.e30006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 04/11/2024] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
Background Wall shear stress (WSS) has been proved to be related to the formation, development and rupture of intracranial aneurysms. Aneurysm wall enhancement (AWE) on magnetic resonance imaging (MRI) can be caused by inflammation and have confirmed its relationship with low WSS. High WSS can also result in inflammation but the research of its correlation with AWE is lack because of the focus on large aneurysms limited by 3T MRI in most previous studies.This study aimed to assess the potential association between high or low WSS and AWE in different aneuryms. Especially the relationship between high WSS and AWE in small aneurysm. Methods Forty-three unruptured intracranial aneurysms in 42 patients were prospectively included for analysis. 7.0 T MRI was used for imaging. Aneurysm size was measured on three-dimensional time-of-flight (TOF) images. Aneurysm-to-pituitary stalk contrast ratio (CRstalk) was calculated on post-contrast black-blood T1-weighted fast spin echo sequence images. Hemodynamics were assessed by four-dimensional flow MRI. Results The small aneurysms group had more positive WSS-CRstalk correlation coefficient distribution (dome: 78.6 %, p = 0.009; body: 50.0 %, p = 0.025), and large group had more negative coefficient distribution (dome: 44.8 %, p = 0.001; body: 69.0 %, p = 0.002). Aneurysm size was positively correlated with the significant OSI-CRstalk correlation coefficient at the dome (p = 0.012) and body (p = 0.010) but negatively correlated with the significant WSS-CRstalk correlation coefficient at the dome (p < 0.001) and body (p = 0.017). Conclusion AWE can be mediated by both high and low WSS, and translate from high WSS- to low WSS-mediated pathways as size increase. Additionally, AWE may serve as an indicator of the stage of aneurysm development via different correlations with hemodynamic factors.
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Affiliation(s)
- Yudi Tang
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Haining Wei
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Medical School, Tsinghua University, Beijing, China
| | - Zihao Zhang
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
| | - Mingzhu Fu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Medical School, Tsinghua University, Beijing, China
| | - Junqiang Feng
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhixin Li
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xinke Liu
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center, Beijing, China
| | - Yue Wu
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jinyuan Zhang
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wei You
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Rong Xue
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yan Zhuo
- State Key Laboratory of Brain and Cognitive Science, Beijing MR Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yuhua Jiang
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center, Beijing, China
| | - Youxiang Li
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center, Beijing, China
| | - Rui Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Medical School, Tsinghua University, Beijing, China
| | - Peng Liu
- Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center, Beijing, China
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Shields A, Williams K, Bhurwani MMS, Nagesh SVS, Chivukula VK, Bednarek DR, Rudin S, Davies J, Siddiqui AH, Ionita CN. Enhancing cerebral vasculature analysis with pathlength-corrected 2D angiographic parametric imaging: A feasibility study. Med Phys 2024; 51:2633-2647. [PMID: 37864843 PMCID: PMC10994741 DOI: 10.1002/mp.16808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/09/2023] [Accepted: 09/27/2023] [Indexed: 10/23/2023] Open
Abstract
BACKGROUND 2D angiographic parametric imaging (API) quantitatively extracts imaging biomarkers related to contrast flow and is conventionally applied to 2D digitally subtracted angiograms (DSA's). In the interventional suite, API is typically performed using 1-2 projection views and is limited by vessel overlap, foreshortening, and depth-integration of contrast motion. PURPOSE This work explores the use of a pathlength-correction metric to overcome the limitations of 2D-API: the primary objective was to study the effect of converting 3D contrast flow to projected contrast flow using a simulated angiographic framework created with computational fluid dynamics (CFD) simulations, thereby removing acquisition variability. METHODS The pathlength-correction framework was applied to in-silico angiograms, generating a reference (i.e., ground-truth) volumetric contrast distribution in four patient-specific intracranial aneurysm geometries. Biplane projections of contrast flow were created from the reference volumetric contrast distributions, assuming a cone-beam geometry. A Parker-weighted reconstruction was performed to obtain a binary representation of the vessel structure in 3D. Standard ray tracing techniques were then used to track the intersection of a ray from the focal spot with each voxel of the reconstructed vessel wall to a pixel in the detector plane. The lengths of each ray through the 3D vessel lumen were then projected along each ray-path to create a pathlength-correction map, where the pixel intensity in the detector plane corresponds to the vessel width along each source-detector ray. By dividing the projection sequences with this correction map, 2D pathlength-corrected in-silico angiograms were obtained. We then performed voxel-wise (3D) API on the ground-truth contrast distribution and compared it to pixel-wise (2D) API, both with and without pathlength correction for each biplane view. The percentage difference (PD) between the resultant API biomarkers in each dataset were calculated within the aneurysm region of interest (ROI). RESULTS Intensity-based API parameters, such as the area under the curve (AUC) and peak height (PH), exhibited notable changes in magnitude and spatial distribution following pathlength correction: these now accurately represent conservation of mass of injected contrast media within each arterial geometry and accurately reflect regions of stagnation and recirculation in each aneurysm ROI. Improved agreement was observed between these biomarkers in the pathlength-corrected biplane maps: the maximum PD within the aneurysm ROI is 3.3% with pathlength correction and 47.7% without pathlength correction. As expected, improved agreement with ROI-averaged ground-truth 3D counterparts was observed for all aneurysm geometries, particularly large aneurysms: the maximum PD for both AUC and PH was 5.8%. Temporal parameters (mean transit time, MTT, time-to-peak, TTP, time-to-arrival, TTA) remained unaffected after pathlength correction. CONCLUSIONS This study indicates that the values of intensity-based API parameters obtained with conventional 2D-API, without pathlength correction, are highly dependent on the projection orientation, and uncorrected API should be avoided for hemodynamic analysis. The proposed metric can standardize 2D API-derived biomarkers independent of projection orientation, potentially improving the diagnostic value of all acquired 2D-DSA's. Integration of a pathlength correction map into the imaging process can allow for improved interpretation of biomarkers in 2D space, which may lead to improved diagnostic accuracy during procedures involving the cerebral vasculature.
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Affiliation(s)
- Allison Shields
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
| | - Kyle Williams
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
| | | | - Swetadri Vasan Setlur Nagesh
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
| | - Venkat Keshav Chivukula
- Department of Biomedical Engineering, Florida Institute of Technology, Melbourne, Florida, USA 32901
| | - Daniel R. Bednarek
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
| | - Stephen Rudin
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
| | - Jason Davies
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
- Department of Neurosurgery, University at Buffalo, Buffalo, New York, USA 14203
| | - Adnan H Siddiqui
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
- Department of Neurosurgery, University at Buffalo, Buffalo, New York, USA 14203
| | - Ciprian N. Ionita
- Medical Physics Program, University at Buffalo, Buffalo, New York, USA 14203
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA 14203
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Hemodynamic Analysis Shows High Wall Shear Stress Is Associated with Intraoperatively Observed Thin Wall Regions of Intracranial Aneurysms. J Cardiovasc Dev Dis 2022; 9:jcdd9120424. [PMID: 36547421 PMCID: PMC9780790 DOI: 10.3390/jcdd9120424] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/23/2022] [Accepted: 11/26/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Studying the relationship between hemodynamics and local intracranial aneurysm (IA) pathobiology can help us understand the natural history of IA. We characterized the relationship between the IA wall appearance, using intraoperative imaging, and the hemodynamics from CFD simulations. METHODS Three-dimensional geometries of 15 IAs were constructed and used for CFD. Two-dimensional intraoperative images were subjected to wall classification using a machine learning approach, after which the wall type was mapped onto the 3D surface. IA wall regions included thick (white), normal (purple-crimson), and thin/translucent (red) regions. IA-wide and local statistical analyses were performed to assess the relationship between hemodynamics and wall type. RESULTS Thin regions of the IA sac had significantly higher WSS, Normalized WSS, WSS Divergence and Transverse WSS, compared to both normal and thick regions. Thicker regions tended to co-locate with significantly higher RRT than thin regions. These trends were observed on a local scale as well. Regression analysis showed a significant positive correlation between WSS and thin regions and a significant negative correlation between WSSD and thick regions. CONCLUSION Hemodynamic simulation results were associated with the intraoperatively observed IA wall type. We consistently found that elevated WSS and WSSNorm were associated with thin regions of the IA wall rather than thick and normal regions.
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Chivukula V, White R, Shields A, Davies J, Mokin M, Bednarek DR, Rudin S, Ionita C. Leveraging Patient-Specific Simulated Angiograms to Characterize Cerebral Aneurysm Hemodynamics using Computational Fluid Dynamics. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2022; 12036:120360S. [PMID: 35983495 PMCID: PMC9385184 DOI: 10.1117/12.2611473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Cerebral aneurysms (CA) affect nearly 6% of the US population and its rupture is one of the major causes of hemorrhagic stroke. Neurointerventionalists performing endovascular therapy (ET) to treat CA rely on qualitative image sequences obtained under fluoroscopy guidance alone, and do not have access to crucial quantitative information regarding blood flow before, during and after treatment - partially contributing to a failure rate of up to 30%. Computational fluid dynamics (CFD) is a powerful tool that can provide a wealth of quantitative data; however, CFD has found limited utility in the clinic due to the challenges in obtaining hemodynamic boundary conditions for each patient. In this work, we present a novel CFD-based simulated angiogram approach (SAA) that resolves the blood flow physics and interaction between blood and injected contrast agent to extract quantitative hemodynamic parameters which can be used to design real-time parametric imaging analysis. The SAA enables correlating contrast agent transport to the underlying hemodynamic conditions via time-density curves (TDC) obtained at several points in the region of interest. The ability of the TDC and the SAA to provide critical hemodynamic parameters in and around CA anatomies, such as washout and local flow changes is explored and presented. This provides invaluable quantitative data to the clinician at the time of intervention, since it incorporates the physics of blood flow and correlates the contrast transport to hemodynamic parameters quantitatively - thereby enabling the clinician to take informed decisions that improve treatment outcomes.
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Affiliation(s)
- V Chivukula
- Biomedical Engineering, Florida Institute of Technology
| | - R White
- Biomedical Engineering, Florida Institute of Technology
| | - A Shields
- Medical Physics, State University of New York at Buffalo
- Canon Stroke and Vascular Research Center, State University of New York at Buffalo
| | - J Davies
- Department of Neurosurgery, State University of New York at Buffalo
| | - M Mokin
- Department of Neurology and Neurosurgery, University of South Florida
| | - D R Bednarek
- Medical Physics, State University of New York at Buffalo
- Canon Stroke and Vascular Research Center, State University of New York at Buffalo
| | - S Rudin
- Medical Physics, State University of New York at Buffalo
- Canon Stroke and Vascular Research Center, State University of New York at Buffalo
- Department of Neurosurgery, State University of New York at Buffalo
| | - C Ionita
- Medical Physics, State University of New York at Buffalo
- Canon Stroke and Vascular Research Center, State University of New York at Buffalo
- Department of Neurosurgery, State University of New York at Buffalo
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Liu Q, Yang Y, Yang J, Li M, Yang S, Wang N, Wu J, Jiang P, Wang S. Rebleeding of Ruptured Intracranial Aneurysm After Admission: A Multidimensional Nomogram Model to Risk Assessment. Front Aging Neurosci 2021; 13:692615. [PMID: 34539377 PMCID: PMC8440913 DOI: 10.3389/fnagi.2021.692615] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/28/2021] [Indexed: 12/23/2022] Open
Abstract
Objective Rebleeding is recognized as the main cause of mortality after intracranial aneurysm rupture. Though timely intervention can prevent poor prognosis, there is no agreement on the surgical priority and choosing medical treatment for a short period after rupture. The aim of this study was to investigate the risk factors related to the rebleeding after admission and establish predicting models for better clinical decision-making. Methods The patients with ruptured intracranial aneurysms (RIAs) between January 2018 and September 2020 were reviewed. All patients fell to the primary and the validation cohort by January 2020. The hemodynamic parameters were determined through the computational fluid dynamics simulation. Cox regression analysis was conducted to identify the risk factors of rebleeding. Based on the independent risk factors, nomogram models were built, and their predicting accuracy was assessed by using the area under the curves (AUCs). Result A total of 577 patients with RIAs were enrolled in this present study, 86 patients of them were identified as undergoing rebleeding after admission. Thirteen parameters were identified as significantly different between stable and rebleeding aneurysms in the primary cohort. Cox regression analysis demonstrated that six parameters, including hypertension [hazard ratio (HR), 2.54; P = 0.044], bifurcation site (HR, 1.95; P = 0.013), irregular shape (HR, 4.22; P = 0.002), aspect ratio (HR, 12.91; P < 0.001), normalized wall shear stress average (HR, 0.16; P = 0.002), and oscillatory stress index (HR, 1.14; P < 0.001) were independent risk factors related to the rebleeding after admission. Two nomograms were established, the nomogram including clinical, morphological, and hemodynamic features (CMH nomogram) had the highest predicting accuracy (AUC, 0.92), followed by the nomogram including clinical and morphological features (CM nomogram; AUC, 0.83), ELAPSS score (AUC, 0.61), and PHASES score (AUC, 0.54). The calibration curve for the probability of rebleeding showed good agreement between prediction by nomograms and actual observation. In the validation cohort, the discrimination of the CMH nomogram was superior to the other models (AUC, 0.93 vs. 0.86, 0.71 and 0.48). Conclusion We presented two nomogram models, named CMH nomogram and CM nomogram, which could assist in identifying the RIAs with high risk of rebleeding.
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Affiliation(s)
- Qingyuan Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Junhua Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Maogui Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shuzhe Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Nuochuan Wang
- Department of Blood Transfusion, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jun Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Pengjun Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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Wiśniewski K, Tyfa Z, Tomasik B, Reorowicz P, Bobeff EJ, Posmyk BJ, Hupało M, Stefańczyk L, Jóźwik K, Jaskólski DJ. Risk Factors for Recanalization after Coil Embolization. J Pers Med 2021; 11:jpm11080793. [PMID: 34442437 PMCID: PMC8398571 DOI: 10.3390/jpm11080793] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 08/11/2021] [Indexed: 11/19/2022] Open
Abstract
The aim of our study was to identify risk factors for recanalization 6 months after coil embolization using clinical data followed by computational fluid dynamics (CFD) analysis. Methods: Firstly, clinical data of 184 patients treated with coil embolization were analyzed retrospectively. Secondly, aneurysm models for high/low recanalization risk were generated based on ROC curves and their cut-off points. Afterward, CFD was utilized to validate the results. Results: In multivariable analysis, aneurysm filling during the first embolization was an independent risk factor whilst packing density was a protective factor of recanalization after 6 months in patients with aSAH. For patients with unruptured aneurysms, packing density was found to be a protective factor whilst the aneurysm neck size was an independent risk factor. Complex flow pattern and multiple vortices were associated with aneurysm shape and were characteristic of the high recanalization risk group. Conclusions: Statistical analysis suggested that there are various factors influencing recanalization risk. Once certain values of morphometric parameters are exceeded, a complex flow with numerous vortices occurs. This phenomenon was revealed due to CFD investigations that validated our statistical research. Thus, the complex flow pattern itself can be treated as a relevant recanalization predictor.
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Affiliation(s)
- Karol Wiśniewski
- Department of Neurosurgery and Neurooncology, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland; (E.J.B.); (B.J.P.); (M.H.); (D.J.J.)
- Correspondence: ; Tel.: +48-042-6776770
| | - Zbigniew Tyfa
- Institute of Turbomachinery, Medical Apparatus Division, Lodz University of Technology, Wolczanska 219/223, 90-924 Lodz, Poland; (Z.T.); (P.R.); (K.J.)
| | - Bartłomiej Tomasik
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, 15 Mazowiecka St., 92-215 Lodz, Poland;
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Piotr Reorowicz
- Institute of Turbomachinery, Medical Apparatus Division, Lodz University of Technology, Wolczanska 219/223, 90-924 Lodz, Poland; (Z.T.); (P.R.); (K.J.)
| | - Ernest J. Bobeff
- Department of Neurosurgery and Neurooncology, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland; (E.J.B.); (B.J.P.); (M.H.); (D.J.J.)
| | - Bartłomiej J. Posmyk
- Department of Neurosurgery and Neurooncology, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland; (E.J.B.); (B.J.P.); (M.H.); (D.J.J.)
| | - Marlena Hupało
- Department of Neurosurgery and Neurooncology, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland; (E.J.B.); (B.J.P.); (M.H.); (D.J.J.)
| | - Ludomir Stefańczyk
- Department of Radiology-Diagnostic Imaging, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland;
| | - Krzysztof Jóźwik
- Institute of Turbomachinery, Medical Apparatus Division, Lodz University of Technology, Wolczanska 219/223, 90-924 Lodz, Poland; (Z.T.); (P.R.); (K.J.)
| | - Dariusz J. Jaskólski
- Department of Neurosurgery and Neurooncology, Medical University of Lodz, Kopcińskiego 22, 90-153 Lodz, Poland; (E.J.B.); (B.J.P.); (M.H.); (D.J.J.)
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9
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The association between hemodynamics and wall characteristics in human intracranial aneurysms: a review. Neurosurg Rev 2021; 45:49-61. [PMID: 33913050 DOI: 10.1007/s10143-021-01554-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/02/2021] [Accepted: 04/20/2021] [Indexed: 12/28/2022]
Abstract
Hemodynamics plays a key role in the natural history of intracranial aneurysms (IAs). However, studies exploring the association between aneurysmal hemodynamics and the biological and mechanical characteristics of the IA wall in humans are sparse. In this review, we survey the current body of literature, summarize the studies' methodologies and findings, and assess the degree of consensus among them. We used PubMed to perform a systematic review of studies that explored the association between hemodynamics and human IA wall features using different sources. We identified 28 publications characterizing aneurysmal flow and the IA wall: 4 using resected tissues, 17 using intraoperative images, and 7 using vessel wall magnetic resonance imaging (MRI). Based on correlation to IA tissue, higher flow conditions, such as high wall shear stress (WSS) with complex pattern and elevated pressure, were associated with degenerated walls and collagens with unphysiological orientation and faster synthesis. MRI studies strongly supported that low flow, characterized by low WSS and high blood residence time, was associated with thicker walls and post-contrast enhancement. While significant discrepancies were found among those utilized intraoperative images, they generally supported that thicker walls coexist at regions with prolonged residence time and that thinner regions are mainly exposed to higher pressure with complex WSS patterns. The current body of literature supports a theory of two general hemodynamic-biologic mechanisms for IA development. One, where low flow conditions are associated with thickening and atherosclerotic-like remodeling, and the other where high and impinging flow conditions are related to wall degeneration, thinning, and collagen remodeling.
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Ou C, Qian Y, Zhang X, Liu J, Liu W, Su H, Zhang N, Zhang J, He X, Duan CZ. Elevated Lipid Infiltration Is Associated With Cerebral Aneurysm Rupture. Front Neurol 2020; 11:154. [PMID: 32373039 PMCID: PMC7179664 DOI: 10.3389/fneur.2020.00154] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 02/18/2020] [Indexed: 12/24/2022] Open
Abstract
Background: Intracranial aneurysm wall degradation can be associated with lipid infiltration. However, the relationship between lipid infiltration and aneurysm rupture has not been explored quantitatively. To investigate the correlation between lipid infiltration and aneurysm rupture, we utilized patient-specific simulation of low-density lipoprotein (LDL) transport to analyze lipid infiltration in the cerebral aneurysm wall. Methods: Sixty-two aneurysms were analyzed. Patient blood pressure, plasma LDL concentration, and three-dimensional angiographic images were obtained to simulate LDL transport in aneurysms. Morphological, hemodynamic, and lipid accumulation parameters were compared between ruptures and unruptured groups. Multivariate logistic regression was also performed to determine parameters that are independently associated with rupture. Results: Size ratio, wall shear stress, low shear area, relative residence time, area-averaged LDL infiltration rate, and maximum LDL infiltration rate were significant parameters in univariate analysis (P < 0.05). Multivariate analysis revealed that only average LDL infiltration remained as a significant variable (P < 0.05). The prediction model derived showed good performance for rupture prediction (AUC, 0.885; 95% CI, 0.794–0.976). Conclusions: Ruptured aneurysms showed significantly higher LDL infiltration compared to unruptured ones. Our results suggested that lipid infiltration may promote aneurysm rupture. Lipid infiltration characteristics should be considered when assessing aneurysm rupture risk.
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Affiliation(s)
- Chubin Ou
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yi Qian
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Xin Zhang
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jiahui Liu
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Wenchao Liu
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Hengxian Su
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Nan Zhang
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jianbo Zhang
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Xuying He
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Chuan-Zhi Duan
- Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, National Key Clinical Specialty, Engineering Technology Research Center of Education Ministry of China, Neurosurgery Institute, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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Cancelliere NM, Najafi M, Brina O, Bouillot P, Vargas MI, Lovblad KO, Krings T, Pereira VM, Steinman DA. 4D-CT angiography versus 3D-rotational angiography as the imaging modality for computational fluid dynamics of cerebral aneurysms. J Neurointerv Surg 2019; 12:626-630. [DOI: 10.1136/neurintsurg-2019-015389] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 11/06/2019] [Accepted: 11/07/2019] [Indexed: 11/03/2022]
Abstract
Background and purposeComputational fluid dynamics (CFD) can provide valuable information regarding intracranial hemodynamics. Patient-specific models can be segmented from various imaging modalities, which may influence the geometric output and thus hemodynamic results. This study aims to compare CFD results from aneurysm models segmented from three-dimensional rotational angiography (3D-RA) versus novel four-dimensional CT angiography (4D-CTA).MethodsFourteen patients with 16 cerebral aneurysms underwent novel 4D-CTA followed by 3D-RA. Endoluminal geometries were segmented from each modality using an identical workflow, blinded to the other modality, to produce 28 'original' models. Each was then minimally edited a second time to match length of branches, producing 28 additional 'matched' models. CFD simulations were performed using estimated flow rates for 'original' models (representing real-world experience) and patient-specific flow rates from 4D-CTA for 'matched' models (to control for influence of modality alone).ResultsOverall, geometric and hemodynamic results were consistent between models segmented from 3D-RA and 4D-CTA, with correlations improving after matching to control for operator-introduced variability. Despite smaller 4D-CTA parent artery diameters (3.49±0.97 mm vs 3.78±0.92 mm for 3D-RA; p=0.005) and sac volumes (157 (37–750 mm3) vs 173 (53–770 mm3) for 3D-RA; p=0.0002), sac averages of time-averaged wall shear stress (TAWSS), oscillatory shear (OSI), and high frequency fluctuations (measured by spectral power index, SPI) were well correlated between 3D-RA and 4D-CTA 'matched' control models (TAWSS, R2=0.91; OSI, R2=0.79; SPI, R2=0.90).ConclusionsOur study shows that CFD performed using 4D-CTA models produces reliable geometric and hemodynamic information in the intracranial circulation. 4D-CTA may be considered as a follow-up imaging tool for hemodynamic assessment of cerebral aneurysms.
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Jiang P, Liu Q, Wu J, Chen X, Li M, Li Z, Yang S, Guo R, Gao B, Cao Y, Wang R, Wang S. Hemodynamic characteristics associated with thinner regions of intracranial aneurysm wall. J Clin Neurosci 2019; 67:185-190. [PMID: 31253387 DOI: 10.1016/j.jocn.2019.06.024] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Revised: 04/20/2019] [Accepted: 06/09/2019] [Indexed: 11/30/2022]
Abstract
Aneurysm wall thickness is an important determinant of aneurysm progression and intra-procedural rupture. Several previous studies have evaluated the association between hemodynamic stress and aneurysm wall thickness, but conflicting results were obtained and no consensus has been achieved. According to the intraoperative findings, twenty-eight unruptured middle cerebral artery (MCA) aneurysms presented with thin-walled regions were enrolled in our study. Patient-specific 3D aneurysm models were constructed from preoperative computed tomography angiography (CTA) data and computational fluid dynamics (CFD) analyses were performed under pulsatile-flow conditions. Thin-walled regions of aneurysm dome were recognized by two experienced reviewers based on the intraoperative microscopy findings. Hemodynamic parameters derived from CFD analysis, including normalized wall shear stress (NWSS), normalized pressure (NP), the oscillatory shear index (OSI) and relative residence time (RRT), were compared between thin-walled regions and surrounding normal-thickness areas. Of the included aneurysms, twenty-eight pairs of thin-walled and normal surrounding regions were determined. Compared with surrounding tissues, thin-walled regions of aneurysm wall tended to present with higher pressure (1.232 vs 1.043, p < 0.05) and lower wall shear stress (0.693 vs 0.868, p < 0.05). Multivariate analysis revealed that elevated NP was significantly associated with thinning of the local aneurysm wall. Higher pressure and lower WSS were characteristic hemodynamic features associated with thinner regions of the aneurysm wall, elevated NP was an independent risk factor for local aneurysm wall thinning. CFD seems to be a useful method to estimate the location of thin-walled region, which will be helpful in reducing the risk of intraoperative rupture.
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Affiliation(s)
- Pengjun Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Qingyuan Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Jun Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Xin Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Maogui Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Zhengsong Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Shuzhe Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Rui Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Bin Gao
- School of Life Science and BioEngineering, Beijing University of Technology, Beijing, People's Republic of China
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Rong Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People's Republic of China; Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, People's Republic of China.
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