Estimation of aortic pulse wave transit time in MRI using complex wavelet cross-spectrum analysis

Ioannis Bargiotas, Elie Mousseaux, Wen Chung Yu, Bharath Ambale Venkatesh, Emilie Bollache, Alain De Cesare, Joao A.C. Lima, Alban Redheuil, Nadjia Kachenoura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Aortic pulse wave velocity (PWV) increases with arterial stiffness and aging and predicts cardiovascular mortality. It is commonly estimated using applanation tonometry at carotid and femoral arterial sites (cfPWV). Although cardiovascular MRI offers reliable segmental measurement of arterial length, accurate transit time (TT) determination between flow curves remains a challenge. We developed a wavelet-based method, which enables temporal localization of signal frequencies, to estimate TT by the weighted phase difference between ascending and descending aorta flow curves. We compared this approach in terms of linear correlations with age, cfPWV and effects of decreasing temporal resolution by factors of 2, 3 and 4, with previous methods which 1) restrict their analysis to systolic upslope (time domain upslopes-archPWVTU) and 2) decompose into harmonics flow curves from the whole cardiac cycle (Fourier-based-archPWVF-robust to low temporal resolution). We studied 71 healthy subjects (45±15 years, 29 females) who underwent MRI velocity acquisitions and cfPWV measurements. Wavelet method provided the highest linear correlations with age and cfPWV and was the most robust to low temporal resolutions. Wavelet method might help to overcome current limitations related to MRI low temporal resolution.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology Conference 2015, CinC 2015
EditorsAlan Murray
PublisherIEEE Computer Society
Pages725-728
Number of pages4
ISBN (Electronic)9781509006854
DOIs
StatePublished - Feb 16 2015
Event42nd Computing in Cardiology Conference, CinC 2015 - Nice, France
Duration: Sep 6 2015Sep 9 2015

Publication series

NameComputing in Cardiology
Volume42
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Other

Other42nd Computing in Cardiology Conference, CinC 2015
CountryFrance
CityNice
Period9/6/159/9/15

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

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