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      動(dòng)脈瘤栓塞手術(shù)液固兩相流數(shù)值模擬分析

      2020-12-24 08:01:42張洋樊俊杰陳盈盈陳廣新王汝良任春娜
      軟件 2020年7期
      關(guān)鍵詞:渦流壁面栓塞

      張洋 樊俊杰 陳盈盈 陳廣新 王汝良 任春娜

      摘? 要: 不同程度動(dòng)脈瘤栓塞的紅細(xì)胞顆粒運(yùn)動(dòng)狀況數(shù)值模擬,應(yīng)用液固兩相流計(jì)算流體力學(xué)仿真,血液流動(dòng)采用瞬態(tài),血管壁采用剛性壁模擬。通過仿真計(jì)算,最終獲取動(dòng)脈瘤栓塞程度不同的兩相流的血流狀況:動(dòng)脈瘤栓塞程度不同,導(dǎo)致動(dòng)脈瘤內(nèi)紅細(xì)胞體積分?jǐn)?shù)分布不同,血流速度分布、壁面切應(yīng)力分布不同,栓塞也導(dǎo)致紅細(xì)胞聚集現(xiàn)象不同。

      關(guān)鍵詞: 動(dòng)脈瘤栓塞;多相流;紅細(xì)胞聚集

      中圖分類號(hào): TP391.4 ???文獻(xiàn)標(biāo)識(shí)碼: A??? DOI:10.3969/j.issn.1003-6970.2020.07.029

      本文著錄格式:張洋,樊俊杰,陳盈盈,等. 動(dòng)脈瘤栓塞手術(shù)液固兩相流數(shù)值模擬分析[J]. 軟件,2020,41(07):143-147+169

      Numerical Simulation of Liquid-solid Two-phase Flow in Aneurysm Embolization

      ZHANG Yang1, FAN Jun-jie2, CHEN Ying-ying3, CHEN Guang-xin3, WANG Ru-liang4, REN Chun-na3

      (1. Department of Laboratory Medicine, Second Affiliated Hospital, Mudanjiang Medical College, Heilongjiang, Mudanjiang 157011;2. School of Health Management, Mudanjiang College of Medicine, Heilongjiang, Mudanjiang 157011;3. College of Medical Imaging, Mudanjiang Medical College, Heilongjiang, Mudanjiang 157011;4. Department of Radiology, Red Flag Hospital, Mudanjiang Medical College, Heilongjiang, Mudanjiang 157011)

      【Abstract】: The Movement of Red Blood cell particles in different degrees of aneurysm embolization was simulated by liquid-solid flow simulation, transient blood flow simulation and rigid wall simulation, respectively. Finally, the blood flow of two-phase flow with different degrees of aneurysm embolization was obtained by simulation calculation. The different degrees of aneurysm embolization resulted in different distributions of red blood cell volume fraction, blood flow velocity and wall shear stress, embolization also causes different aggregations of red blood cells.

      【Key words】: Aneurysm; Embolization; Multiphase flow; Erythrocyte aggregation

      0? 引言

      顱內(nèi)動(dòng)脈瘤(Intracranial aneurysm,IA)是多種因素導(dǎo)致的動(dòng)脈壁的異常瘤樣擴(kuò)張,常發(fā)生于顱內(nèi)大動(dòng)脈的分叉及彎曲處,破裂會(huì)導(dǎo)致蛛網(wǎng)膜下腔出血,具有極高的致死率及致殘率。影響動(dòng)脈瘤生長(zhǎng)和破裂的因素主要包括先天生理性、病理性及血流動(dòng)力學(xué)因素。對(duì)于IA的治療主要包括開顱夾閉術(shù)及血管內(nèi)介入栓塞兩種方法[1-3]。無論是哪種方法,由于動(dòng)脈瘤自身的復(fù)雜性及不完全閉塞的發(fā)生,即使是有經(jīng)驗(yàn)的臨床醫(yī)生,術(shù)后的復(fù)發(fā)率依舊很高[4-7]。栓塞手術(shù)由于創(chuàng)傷小,操作相對(duì)簡(jiǎn)單等優(yōu)勢(shì)和栓塞材料及技術(shù)的不斷發(fā)展進(jìn)步逐漸被廣泛應(yīng)用于臨床。但同時(shí)由于彈簧圈具有可壓縮性使得動(dòng)脈瘤復(fù)發(fā)的可能性大大增加,有研究表明栓塞程度是動(dòng)脈瘤復(fù)發(fā)的重要影響因素,Brzegowy等人回顧性分析破裂與未破裂前交通動(dòng)脈瘤的栓塞治療,同樣得出影響顱內(nèi)動(dòng)脈瘤復(fù)發(fā)的最大因素就是栓塞密度,初始栓塞的不完全極易引起動(dòng)脈瘤的復(fù)發(fā)[8-9]。栓塞程度低,彈簧圈會(huì)隨著血流的沖擊逐漸壓縮,進(jìn)而向遠(yuǎn)側(cè)移位、復(fù)發(fā)。趙慶平等提出瘤腔內(nèi)的血流速度與瘤腔大小呈負(fù)相關(guān),即栓塞程度越低,腔內(nèi)血流速度加快時(shí),血液對(duì)壁面產(chǎn)生的力就可能導(dǎo)致動(dòng)脈瘤的復(fù)發(fā)[10]。但這些研究并未明確指明血流動(dòng)力學(xué)因素在不同栓塞程度下的變化。近年來隨著計(jì)算機(jī)的發(fā)展及有限元軟件的開發(fā),尤其是計(jì)算流體動(dòng)力學(xué)數(shù)值模擬方法的應(yīng)用,使得血流建模能更好解釋血流動(dòng)力學(xué)在IA發(fā)病機(jī)制中的作用[11-16]。因此為了探究不同栓塞密度下血流動(dòng)力學(xué)的具體變化,建立了不同栓塞程度的模型,來為臨床醫(yī)生制定更好的栓塞策略提供指導(dǎo)。

      1? 材料與方法

      1.1 ?個(gè)體化模型構(gòu)建

      本文研究采用牡丹江醫(yī)學(xué)院附屬紅旗醫(yī)院影像科提供的一例真實(shí)基底動(dòng)脈頂端動(dòng)脈瘤患者的DICOM格式的頭部CTA影像資料。動(dòng)脈瘤CTA影像顯示位置如圖1所示。

      在MIMICS軟件(Materialise公司,比利時(shí))中,對(duì)DICOM格式數(shù)據(jù)進(jìn)行閾值分割、三維重建,然后利用3-matic(Materialise公司,比利時(shí))軟件對(duì)獲取的初步模型去除細(xì)小分支血管、保留載瘤動(dòng)脈血管,截取出、入口平面,最后對(duì)三角面片進(jìn)行光滑,獲取動(dòng)脈瘤的理想模型[17-18](圖2)。

      為了比較不完全栓塞、完全栓塞、栓塞手術(shù)前的動(dòng)脈瘤血流動(dòng)力學(xué)參數(shù)的差異,本文在栓塞數(shù)千的動(dòng)脈瘤模型基礎(chǔ)上構(gòu)建了中度栓塞和完全栓塞的模型(圖3)。

      1.2 ?網(wǎng)格劃分

      利用ANSYS FLUNET MESHING軟件對(duì)術(shù)前動(dòng)脈瘤模型、不完全栓塞動(dòng)脈瘤模型、完全栓塞動(dòng)脈瘤模型進(jìn)行四面體網(wǎng)格劃分,為保證計(jì)算精度,邊界層6層加密。

      1.3 ?血液兩相流控制方程

      血液為有形成分與血漿組成。血漿占血液總體積的55%,而懸浮在血漿中的有形成分主要是紅細(xì)胞、白細(xì)胞、血小板三類,其中紅細(xì)胞占95%[19-20]。在液固兩相流模型中,考慮到血細(xì)胞中絕大部分是紅細(xì)胞而在計(jì)算中忽略其它有形成分的影響,假設(shè)血液是由紅細(xì)胞懸浮于血漿構(gòu)成的兩相流系統(tǒng)。液相(連續(xù)相):血漿設(shè)為不可壓縮的牛頓流體。固相(離散相):紅細(xì)胞設(shè)定為球形剛性顆粒,顆粒液固兩相流的控制方程為[21-25]

      1.4 ?邊界條件與參數(shù)設(shè)定

      利用ANSYS FLUENT計(jì)算流體力學(xué)分析軟件進(jìn)行瞬態(tài)仿真計(jì)算。邊界條件設(shè)定為:入口為速度入口,液相與固相采用相同的速度波形。速度入口曲線如圖4所示。

      2 ?計(jì)算結(jié)果

      2.1 ?紅細(xì)胞體積分?jǐn)?shù)

      圖5為動(dòng)脈瘤入口紅細(xì)胞速度達(dá)到峰值時(shí)刻圖,選取紅細(xì)胞速度達(dá)到峰值時(shí)刻的動(dòng)脈瘤0度栓塞、50%栓塞、100%栓塞的動(dòng)脈瘤紅細(xì)胞體積分?jǐn)?shù)圖進(jìn)行分析(圖6、圖7、圖8)。由圖可見,在動(dòng)脈瘤栓塞0度時(shí),動(dòng)脈瘤的紅細(xì)胞在瘤頸處出現(xiàn)局部、少量的聚集現(xiàn)象,這一點(diǎn)符合真實(shí)臨床診斷,動(dòng)脈瘤50%栓塞在瘤壁頂端形成較明顯的聚集情況,而動(dòng)脈瘤100%栓塞在瘤壁頂端形成更為明顯的聚集情況。動(dòng)脈瘤的紅細(xì)胞聚集則形成血栓。

      2.2 ?血液速度場(chǎng)

      本文通過計(jì)算,比較了三種不同程度栓塞的動(dòng)脈瘤流場(chǎng)分布,如圖9、10、11所示,動(dòng)脈瘤0度栓塞、動(dòng)脈瘤50%栓塞、動(dòng)脈瘤100%栓塞均出現(xiàn)不同程度的渦流,流體從載瘤管方向沖向瘤頸遠(yuǎn)端,然后順著瘤壁形成渦流,渦流的中心偏向瘤頸的遠(yuǎn)端,載流管內(nèi)的有形顆粒進(jìn)入流體內(nèi)部并在渦流中心停留堆積,最終形成血栓。50%程度栓塞時(shí),瘤內(nèi)的速度相較于0程度栓塞較快,說明栓塞起到了提高瘤內(nèi)的血液流動(dòng)能力,而相較于100%栓塞程度的動(dòng)脈瘤,50%不完全栓塞的動(dòng)脈瘤的流線存在不穩(wěn)定現(xiàn)象。

      2.3 ?壁面剪切應(yīng)力分布

      為便于觀察,在瘤頸處選擇一點(diǎn)為觀察點(diǎn)。圖12、圖13、圖14為動(dòng)脈瘤0度栓塞、動(dòng)脈瘤50%栓塞、動(dòng)脈瘤100%栓塞的觀察點(diǎn)壁面切應(yīng)力隨時(shí)間變化曲線。由三個(gè)圖可見,動(dòng)脈瘤瘤壁的壁面壓力隨時(shí)間變化,但隨著動(dòng)脈瘤的栓塞程度變化為栓塞程度越大,壁面壓力越大,說明栓塞有助于改變壁面壓力程度。瘤頂附近的剪切應(yīng)力不足 , 將導(dǎo)致了血管內(nèi)皮 細(xì)胞出現(xiàn)變形和功能退化, 所以瘤頂區(qū)域?yàn)楦呶R灼屏训膮^(qū)域,栓塞手術(shù)可降低破裂風(fēng)險(xiǎn)。

      3 ?結(jié)論與展望

      本文通過對(duì)動(dòng)脈瘤0度栓塞、50%栓塞、100%栓塞進(jìn)行了多項(xiàng)流顆粒物數(shù)值模擬,得出以下結(jié)論:

      (1)動(dòng)脈瘤栓塞程度越高越有利于紅細(xì)胞在動(dòng)脈瘤中的濃度極化,形成血栓。

      (2)動(dòng)脈瘤栓塞程度越高,越降低流場(chǎng)的渦流程度。

      (3)動(dòng)脈瘤的栓塞程度越高,可提高瘤壁的壁面剪切應(yīng)力,降低動(dòng)脈瘤破裂風(fēng)險(xiǎn)。

      本文的創(chuàng)新之處在于在動(dòng)脈瘤數(shù)值模擬中考慮了紅細(xì)胞顆粒運(yùn)動(dòng)的影響,分析了紅細(xì)胞運(yùn)動(dòng)在動(dòng)脈瘤栓塞手術(shù)中的濃度極化現(xiàn)象。本文不足之處在于樣本量不足,因此,在下一步研究中應(yīng)增加臨床樣本量;此外,考慮到實(shí)驗(yàn)技術(shù)條件所限,本文計(jì)算采用的時(shí)血管剛性壁,血管壁實(shí)際為彈性壁,在下一步研究中,將拓展到超彈性結(jié)構(gòu)的血管壁與血液雙向流固耦合分析。

      參考文獻(xiàn)

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      2. Phan Kevin, Huo Ya R, Jia Fangzhi et al. Meta-analysis of stent-assisted coiling versus coiling-only for the treatment of intracranial aneurysms[J]. J Clin Neurosci, 2016, 31: 15-22.

      3. Gawlitza Matthias, Soize Sebastien, Januel Anne-Christine et al. Treatment of recurrent aneurysms using the Woven EndoBridge(WEB): anatomical and clinical results[J]. J Neurointerv Surg, 2018, 10: 629-633.

      4. Huang De-Zhang, Jiang Bin, He Wei et al. Risk factors for the recurrence of an intracranial saccular aneurysm following endovascular treatment[J]. Oncotarget, 2017, 8: 33676- 33682.

      5. Yu Le-Bao, Fang Zhi-Jun, Yang Xin-Jian et al. Management of Residual and Recurrent Aneurysms After Clipping or Coiling: Clinical Characteristics, Treatments, and Follow-Up Outcomes[J]. World Neurosurg, 2019, 122: e838-e846.

      6. Zhang Donghuan, Wang Honglei, Liu Tianyi et al. Re-Recurrence of Intracranial Aneurysm with Proximal Vascular Stenosis After Primary Clipping and Secondary Endovascular Embolization: A Case Report and Literature Review[J]. World Neurosurg, 2019, 121: 28-32.

      7. Kim S-T, Baek J W, Jin S-C et al. Coil Embolization in Patients with Recurrent Cerebral Aneurysms Who Previously Underwent Surgical Clipping[J]. AJNR Am J Neuroradiol, 2019, 40: 116-121.

      8. Brzegowy Pawe?, Kucyba?a Iwona, Krupa Kamil et al. Angiographic and clinical results of anterior communicating artery aneurysm endovascular treatment[J]. Wideochir Inne Tech Maloinwazyjne, 2019, 14: 451-460.

      9. Chueh Ju-Yu, Vedantham Srinivasan, Wakhloo Ajay K et al. Aneurysm permeability following coil embolization: packing density and coil distribution[J]. J Neurointerv Surg, 2015, 7: 676-81.

      10. Zhao Qingping, Chen Guangzhong, Li Tielin, Zhao Wei, Yuan Yuan, Feng Yanqiu. Hemodynamic analysis of embolization density and recurrence of intracranial aneurysm[J]. Chinese Journal of neuropsychiatric diseases, 2013, 39(06): 339-343

      11. Liang Li, Steinman David A, Brina Olivier et al. Towards the Clinical utility of CFD for assessment of intracranial aneurysm rupture-a systematic review and novel parameter- ranking tool[J]. J Neurointerv Surg, 2019, 11: 153-158.

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

      13. Roloff Christoph, Stucht Daniel, Beuing Oliver et al. Comparison of intracranial aneurysm flow quantification techniques: standard PIV vs stereoscopic PIV vs tomographic PIV vs phase-contrast MRI vs CFD[J]. J Neurointerv Surg, 2019, 11: 275-282.

      14. Frolov S V, Sindeev S V, Liepsch D et al. Experimental and CFD flow studies in an intracranial aneurysm model with Newtonian and non-Newtonian fluids[J]. Technol Health Care, 2016, 24: 317-33.

      15. Botti Lorenzo, Paliwal Nikhil, Conti Pierangelo et al. Modeling hemodynamics in intracranial aneurysms: Comparing accuracy of CFD solvers based on finite element and finite volume schemes[J]. Int J Numer Method Biomed Eng, 2018, 34: e3111.

      16. Xiang J, Tutino V M, Snyder K V et al. CFD: computational fluid dynamics or confounding factor dissemination? The role of hemodynamics in intracranial aneurysm rupture risk assessment[J]. AJNR Am J Neuroradiol, 2014, 35: 1849-57.

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      dynamic and morphological characteristics of a growing cerebral aneurysm[J]. Neurosurg Focus, 2019, 47: E13.

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