Modeling arterial pulse waves in healthy aging: a database for in silico evaluation of hemodynamics and pulse wave indexes

The arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health. It is widely measured by both consumer and clinical devices. However, the physical determinants of the PW are not yet fully understood, and the development of PW analysis algorithms is limited by a lack of PW...

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Bibliographic Details
Published in:American journal of physiology. Heart and circulatory physiology 2019-11, Vol.317 (5), p.H1062-H1085
Main Authors: Charlton, Peter H, Mariscal Harana, Jorge, Vennin, Samuel, Li, Ye, Chowienczyk, Phil, Alastruey, Jordi
Format: Article
Language:English
Subjects:
Adult
Age Factors
Aged
Aging
Algorithms
Arteries - physiology
Computer applications
Computer Simulation
Databases, Factual
Female
Flow velocity
Healthy Aging
Hemodynamics
Humans
Literature reviews
Male
Middle Aged
Models, Cardiovascular
Morphology
Numerical Analysis, Computer-Assisted
Pulse Wave Analysis
Vascular Stiffness
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Summary:The arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health. It is widely measured by both consumer and clinical devices. However, the physical determinants of the PW are not yet fully understood, and the development of PW analysis algorithms is limited by a lack of PW data sets containing reference CV measurements. Our aim was to create a database of PWs simulated by a computer to span a range of CV conditions, representative of a sample of healthy adults. The typical CV properties of 25-75 yr olds were identified through a literature review. These were used as inputs to a computational model to simulate PWs for subjects of each age decade. Pressure, flow velocity, luminal area, and photoplethysmographic PWs were simulated at common measurement sites, and PW indexes were extracted. The database, containing PWs from 4,374 virtual subjects, was verified by comparing the simulated PWs and derived indexes with corresponding in vivo data. Good agreement was observed, with well-reproduced age-related changes in hemodynamic parameters and PW morphology. The utility of the database was demonstrated through case studies providing novel hemodynamic insights, in silico assessment of PW algorithms, and pilot data to inform the design of clinical PW algorithm assessments. In conclusion, the publicly available PW database is a valuable resource for understanding CV determinants of PWs and for the development and preclinical assessment of PW analysis algorithms. It is particularly useful because the exact CV properties that generated each PW are known. First, a comprehensive literature review of changes in cardiovascular properties with age was performed. Second, an approach for simulating pulse waves (PWs) at different ages was designed and verified against in vivo data. Third, a PW database was created, and its utility was illustrated through three case studies investigating the determinants of PW indexes. Fourth, the database and tools for creating the database, analyzing PWs, and replicating the case studies are freely available.
ISSN:0363-6135
1522-1539
DOI:10.1152/AJPHEART.00218.2019