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Quantification of blood flow patterns in the cerebral arterial circulation of individual (human) subjects
Author(s) -
Park Chang S.,
Hartung Grant,
Alaraj Ali,
Du Xinjian,
Charbel Fady T.,
Linninger Andreas A.
Publication year - 2020
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.3288
Subject(s) - cerebral blood flow , blood flow , cerebral circulation , flow (mathematics) , hemodynamics , set (abstract data type) , computer science , medicine , cardiology , mathematics , geometry , programming language
There is a growing research interest in quantifying blood flow distribution for the entire cerebral circulation to sharpen diagnosis and improve treatment options for cerebrovascular disease of individual patients. We present a methodology to reconstruct subject‐specific cerebral blood flow patterns in accordance with physiological and fluid mechanical principles and optimally informed by in vivo neuroimage data of cerebrovascular anatomy and arterial blood flow rates. We propose an inverse problem to infer blood flow distribution across the visible portion of the arterial network that best matches subject‐specific anatomy and a given set of volumetric flow measurements. The optimization technique also mitigates the effect of uncertainties by reconciling incomplete flow data and by dissipating unavoidable acquisition errors associated with medical imaging data.