床突旁動脈瘤頸內動脈近端阻斷策略數值模擬及其臨床應用

王明

摘? 要： 探討床突旁動脈瘤頸內動脈近端阻斷策略的血流動力學參數的變化和特征，為手術方式的選擇提供指導。方法： 利用一例床突旁動脈瘤患者的DICOM影像數據，通過MIMICS、3-matic、Geomagic Studio、Spaceclaim、DesignModeler、Meshing等軟件建立頸內動脈近端阻斷前后的動脈瘤及動脈瘤壁有限元模型，用Fluent、Transient Structural進行流固耦合計算求解。采用數值模擬與統計學分析頸內動脈阻斷前后的動脈瘤血流動力學參數及動脈瘤壁的應力應變。計算出頸內動脈阻斷前后模型的血流動力學參數及動脈瘤壁的應力應變參數，統計學結論顯示脈阻斷前后模型參數存在顯著性差異。用本項目所構建的床突旁動脈瘤的有限元模型可有效分析不同模式下的動脈瘤血流特征，為臨床治療中手術方方案的設計提供指導。

關鍵詞： 床突旁動脈瘤;雙向流固耦合;近端阻斷策略;數值模擬

【Abstract】： Purpose： The aim of this project are to investigate the changes and characteristics of hemodynamic parameters of proximal carotid artery occlusion strategy for cavernous sinus aneurysm， and to provide guidance for the selection of surgical methods. Methods： DICOM image data of a patient with cavernous sinus aneurysm were used to establish the finite element model of aneurysm and aneurysm wall before and after proximal occlusion of the internal carotid artery by using MIMICS， 3-matic， Geomagic Studio， Spaceclaim， DesignModeler， Meshing and other software. Fluid-solid coupling calculation was performed with Fluent and Transient Structural.The hemodynamic parameters of aneurysm and the stress and strain of aneurysm wall before and after internal carotid artery occlusion were analyzed by numerical simulation and statistics. Results： The hemodynamic parameters of the model and the stress-strain parameters of aneurysm wall before and after internal carotid artery occlusion were calculated. Statistical results showed that there were significant differences in the parameters of the models. Conclusion： The finite element model of cavernous sinus aneurysm constructed in this project can be used to effectively analyze the blood flow characteristics of aneurysms in different modes， and provide guidance for the design of surgical procedures in clinical treatment.

【Key words】： Cavernous sinus aneurysm; Bidirectional fluid-solid coupling; Proximal block strategy; The numerical simulation

0? 引言

腦動脈瘤是一種嚴重的腦血管疾病，其破裂概率為1%[1]，床突旁動脈瘤占顱內動脈瘤的3-5%，占頸內動脈瘤的14%[2-3]。床突旁動脈瘤的形成與床突旁內分支、血管硬化、自發性或外傷性血管夾層有關[4]。目前研究認為，壁面切應力、壓力、血流速度等血流動力學參數與動脈瘤形成、發展、破裂有著密切的關系。顱內常規動脈瘤的治療技術已經非常成熟，但對于海綿竇、床突旁及基底動脈動脈瘤等復雜動脈瘤，采用直接夾閉或栓塞都非常困難。因此通過改變動脈瘤局部血流動力學狀態包括血流速度大小、沖擊方向或通過減少瘤內的血流以促成血栓達到治療目的成為一種間接處理動脈瘤的策略。

近些年來，一些學者應用計算流體力學對顱內動脈瘤進行數值模擬分析，有的學者采用牛頓流體與非牛頓流體模式進行對比分析，也有的學者采用剛性壁的方法對動脈瘤進行數值分析[5-8]。動脈瘤是一種流體、固體相互耦合的物理場，而應用雙向流固耦合進行數值模擬分析更接近于動脈瘤的血流真實流動狀況。本文建立顱內床突旁動脈瘤頸內動脈近端阻斷前后的雙向流固耦合模型，利用Ansys有限元軟件對動脈瘤進行求解，獲得血流動力學參數、應力應變情況并對結果進行配對t檢驗統計學分析，進而為復雜動脈瘤的治療方案選擇提供理論指導。

參考文獻

[1]Paolo Di Achille， Jay D. Humphrey. Fluid-Solid-Growth TowardLarge-Scal Computational Intracranial Aneurysms[J]. Models of Yale J Biol Med. 2012， 85（2）： 217–228.

[2]Fuyu Wang， Bainan Xu， Zhenghui Sun， Chen Wu， Xiaojun Zhang. Wall shear stress and adjacent arteries intracranial aneurysms in[J]. Neural Regen Res. 2013， 15; 8（11）： 1007– 1015.

[3]J. D. Humphrey. Coupling hemodynamics with vascular wall mechanics and intracranial aneurysms mechanobiology to understand[J]. Int J Comut Fluid Dyn. 2009; 23（8）： 569–581.

[4]Benjamin Owen， Nicholas Bojdo， Andrey Jivkov， Bernard Keavney， Alistair Revell. Structural modelling of the cardiovascular system[J]. Biomech Model Mechanobiol. 2018; 17（5）： 1217–1242.

[5]Xu Bai-Nan， Wang Fu-Yu， Liu Lei， Zhang Xiao-Jun， Ju Hai-Yue. Hemodynamics aneurysms[J]. in internal carotid artery interaction model of fluid–solid Neurosurg Rev. 2011， 34（1）： 39–47.

[6]Fernando Mut， Rainald L?hner， Aichi Chien， Satoshi Tateshima， Fernando Vi?uela， Christopher Putman， Juan Cebral. Computational Hemodynamics Framework for the Aneurysms[J]. Analysis of Cerebral Int j numer method biomed eng. 2011， 27（6）： 822–839.

[7]Daniel M. Sforza， Christopher M. Putman， Juan R. Cebral. aneurysms Computational fluid dynamics in brain[J]. Int J Numer Method Biomed Eng. 2012， 28（0）： 801–808.

[8]Fatma Gulden Simsek， Young W. Kwon. Investigation of material modeling in fluid–structure analysis of an idealized three-layered abdominal interaction aneurysms[J]. initiation and fully developed aneurysm aorta： J Biol Phys. 2015， 41（2）： 173–201.

[9]Paris Perdikaris， Joseph A. Insley， Leopold Grinberg， Yue Yu， Michael E. Papka， George Em. Karniadakis. Visualizing multiphysics， intracranial aneurysms[J]. phenomena in interaction fluid-structure Parallel Comput. 2016， 55： 9–16.

[10]Tianlun Qiu， Guoliang Jin， Wuqiao Bao， Haitao Lu. Intercorrelations of in computational fluid intracranial aneurysms morphology with hemodynamics in dynamics[J]. Neurosciences. 2017， 22（3）： 205–212.

[11]Kristian Valen-Sendstad， Aslak W. Bergersen， Yuji Shimo gonya， et al. Real-World Wall Shear Stress： The Intracranial Aneurysm Variability in the Prediction of 2015 International CFD Challenge[J]. Aneurysm Cardiovasc Eng Technol. 2018; 9（4）： 544–564.

[12]Yunling Long， Jingru Zhong， Hongyu Yu， Huagang Yan， Zhizheng Zhuo， Qianqian Meng， Xinjian Yang， Haiyun Li. model-based approach to aneurysm A scaling rupture aneurysm assessing the role of flow pattern and energy loss in prediction[J]. J Transl Med. 2015; 13： 311.

[13]Gambaruto AM， Janela J， Moura A， et al. Sensitivity of hemodynamics in a patient specific cerebral aneurysm to vascular geometry and blood rheology[J]. Math Biosci Eng. 2011， 8（2）： 409-423.

[14]Cebral JR， Meng H. Counterpoint： realizing the clinical utility of computational fluid dynamics-closing the gap[J]. AJNR Am J Neuroradiol. 2012， 33（3）： 396–398.

[15]Xiang J， Natarajan SK， Tremmel M， Ma D， Mocco J， Hopkins LN， Siddiqui AH， Levy EI， Meng H. Hemodynamic morphologic discriminants for intracranial aneurysm rupture[J]. Stroke J Cereb Circ. 2011， 42（1）： 144–152.

[16]Lu G， Huang L， Zhang XL， Wang SZ， Hong Y， Hu Z， Geng DY. Influence of hemodynamic factors on rupture of intracranial aneurysms： patient-specific 3D mirror aneurysms model computational fluid dynamics simulation[J]. AJNR Am J Neuroradiol. 2011， 32（7）： 1255–1261.

[17]Jia Lu， Shouhua Hu， Madhavan L. Raghavan. A shell-based inverse approach of stress analysis intracranial aneurysms in[J]. Ann Biomed Eng. 2013， 41（7）： 1505–1515.

[18]Xu Bai-Nan， Wang Fu-Yu， Liu Lei， Zhang Xiao-Jun， Ju Hai-Yue. Hemodynamics model aneurysms[J]. in internal carotid artery interaction fluid–solid ofNeurosurg Rev. 2011 ， 34（1）： 39–47.

[19]Fatma Gulden Simsek， Young W. Kwon. Investigation analysis of an idealized interaction fluid structure of material modeling in initiation and fully aneurysm three-layered abdominal aorta： aneurysms developed[J]. J Biol Phys. 2015， 41（2）： 173–201.

[20]Yue Yu， Paris Perdikaris， George Em Karniadakis. Fractional modeling of viscoelasticity in aneurysms[J]. 3D cerebral arteries and J Comput Phys. 2016 ， 323： 219–242.

[21]J. D. Humphrey， G. A. Holzapfel. Mechanics， Aneurysms Mechanobiology， and Modeling of Human Abdominal Aorta and[J]. J Biomech. 2012， 45（5）： 805–814.

[22]Malebogo N. Ngoepe， Alejandro F. Frangi， James V. Byrne， Yiannis Ventikos. Thrombosis Review and the Computa tional Modeling Thereof： A Aneurysms in Cerebral Front Physiol[J]. 2018， 9： 306.

[23]Michael J Bonares， A Leonardo de Oliveira Manoel， R Loch Macdonald， Tom A Schweizer. Behavioral review intracr anial aneurysms： a systematic profile of unruptured[J]. Ann Clin Transl Neurol. 2014， 1（3）： 220–232.