title: Functional assessment of cerebral artery stenosis: A pilot study based on computational fluid dynamics.
abstract: The fractional pressure ratio is introduced to quantitatively assess the hemodynamic significance of severe intracranial stenosis. A computational fluid dynamics-based method is proposed to non-invasively compute the FPRCFDand compared against fractional pressure ratio measured by an invasive technique. Eleven patients with severe intracranial stenosis considered for endovascular intervention were recruited and an invasive procedure was performed to measure the distal and the aortic pressure ( Pdand Pa). The fractional pressure ratio was calculated as [Formula: see text]. The computed tomography angiography was used to reconstruct three-dimensional (3D) arteries for each patient. Cerebral hemodynamics was then computed for the arteries using a mathematical model governed by Navier-Stokes equations and with the outflow conditions imposed by a model of distal resistance and compliance. The non-invasive [Formula: see text], [Formula: see text], and FPRCFDwere then obtained from the computational fluid dynamics calculation using a 16-core parallel computer. The invasive and non-invasive parameters were tested by statistical analysis. For this group of patients, the computational fluid dynamics method achieved comparable results with the invasive measurements. The fractional pressure ratio and FPRCFDare very close and highly correlated, but not linearly proportional, with the percentage of stenosis. The proposed computational fluid dynamics method can potentially be useful in assessing the functional alteration of cerebral stenosis.
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
authors.forename: Jia
authors.initials: J
authors.lastname: Liu
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
authors.forename: Zhengzheng
authors.initials: Z
authors.lastname: Yan
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Yuehua
authors.initials: Y
authors.lastname: Pu
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
authors.forename: Wen-Shin
authors.initials: WS
authors.lastname: Shiu
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
authors.forename: Jianhuang
authors.initials: J
authors.lastname: Wu
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
authors.forename: Rongliang
authors.initials: R
authors.lastname: Chen
authors.affiliation: 3 Faculty of Medicine, Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.
authors.forename: Xinyi
authors.initials: X
authors.lastname: Leng
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Haiqiang
authors.initials: H
authors.lastname: Qin
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Liu
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Baixue
authors.initials: B
authors.lastname: Jia
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Ligang
authors.initials: L
authors.lastname: Song
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Yilong
authors.initials: Y
authors.lastname: Wang
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Zhongrong
authors.initials: Z
authors.lastname: Miao
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Wang
authors.affiliation: 2 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Liping
authors.initials: L
authors.lastname: Liu
authors.affiliation: 1 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|4 Department of Computer Science, University of Colorado, Boulder, USA.
authors.forename: Xiao-Chuan
authors.initials: XC
authors.lastname: Cai
mesh_terms: D001011:Aorta / Q000503:physiopathology; D001794:Blood Pressure / Q000502:physiology*; D002536:Cerebral Arteries / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology; D002560:Cerebrovascular Circulation / Q000502:physiology; D019295:Computational Biology; D000072226:Computed Tomography Angiography; D003251:Constriction, Pathologic; D005260:Female; D006801:Humans; D002537:Intracranial Arteriosclerosis / Q000150:complications / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010865:Pilot Projects; D020521:Stroke / Q000000981:diagnostic imaging* / Q000209:etiology / Q000473:pathology / Q000503:physiopathology
keywords: Stroke; and brain ischemia; cerebral blood flow; cerebral hemodynamics; mathematical modelling