Measuring global cerebrovascular pulsatility transmission using 4D flow MRI

Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to...

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Published inScientific reports Vol. 14; no. 1; pp. 12604 - 13
Main Authors Dempsey, Sergio, Safaei, Soroush, Holdsworth, Samantha J., Maso Talou, Gonzalo D.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 01.06.2024
Nature Publishing Group
Nature Portfolio
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ISSN2045-2322
2045-2322
DOI10.1038/s41598-024-63312-4

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Summary:Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to variability in pulsatility and spatial bias. Here, we propose a locus-independent pulsatility transmission coefficient computed by spatially tracking pulsatility along vessels to characterise the brain pulse dynamics at a whole-organ level. Our preliminary analyses in a cohort of 20 subjects indicate that this measurement agrees with clinical observations relating blood pulsatility with age, heart rate, and sex, making it a suitable candidate to study the risk of PWE. We identified transmission differences between vascular regions perfused by the basilar and internal carotid arteries attributed to the identified dependence on cerebral blood flow, and some participants presented differences between the internal carotid perfused regions that were not related to flow or pulsatility burden, suggesting underlying mechanical differences. Large populational studies would benefit from retrospective pulsatility transmission analyses, providing a new comprehensive arterial description of the hemodynamic state in the brain. We provide a publicly available implementation of our tools to derive this coefficient, built into pre-existing open-source software.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-63312-4