A patient-specific cerebral blood flow model

• Published in: Journal of biomechanics Vol. 98; p. 109445
• Main Authors: Helthuis, Jasper H.G., van Doormaal, Tristan P.C., Amin-Hanjani, Sepideh, Du, XinJian, Charbel, Fady T., Hillen, Berend, van der Zwan, Albert
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 02.01.2020; Elsevier Limited
• Subjects: Aneurysms; Arteries; Asymmetry; Blood flow; Blood pressure; Blood vessels; Boundary conditions; Cerebral blood flow; Cerebrovascular diseases; Hemodynamics; Magnetic resonance imaging; Mathematical models; Mathematical morphology; Model accuracy; Modelling; Morphology; Patient-specific; Patients; Regression analysis; Software; Structured tree; Vascular diseases; Veins & arteries; United States > US; Structured tree; Modelling; Hemodynamics; Patient-specific; Cerebral blood flow
• ISSN: 0021-9290; 1873-2380; 1873-2380
• DOI: 10.1016/j.jbiomech.2019.109445

In clinical practice, many complex choices in treatment of complex cerebrovascular diseases have to be made. A patient-specific mathematical blood flow could aid these decisions. For certain cases, less accuracy is required and more simplistic models might be feasible. The current study is aiming to validate a patient-specific simplistic blood flow model in 20 healthy subjects. All subjects underwent MRI and Noninvasive Optimal Vessel Analysis (NOVA) to obtain patient-specific vascular morphology and flow measurements of all major cerebral arteries for validation. The mathematical model used was based on the Hagen-Poiseuille equations. Proximal boundary conditions were patient-specific blood pressure cuff measurements. For distal boundary conditions, a structured tree and a simple autoregulatory model were applied. Autoregulatory parameters were optimized based on the data of 10 additional healthy subjects. A median percentual flow difference of −3% (interquartile range −36% to 17%) was found. Regression analysis to an identity line resulted in R2 values of 0.71 for absolute flow values. Bland-Altman plots showed a bias (levels of agreement) of 5% (-70 to 80%) for absolute flow. Based on these results the model proved to be accurate within a range that might be feasible for use in clinic. Major limitations to the model arise from the simplifications made compared to the actual physiological situation and limitations in the validation method. As the model is validated in healthy subjects only, further validation in actual patients is needed.