Estimation of aortic pulse wave transit time in cardiovascular magnetic resonance using complex wavelet cross-spectrum analysis

• Published in: Journal of cardiovascular magnetic resonance Vol. 17; no. 1; p. 65
• Main Authors: Bargiotas, Ioannis, Mousseaux, Elie, Yu, Wen-Chung, Venkatesh, Bharath Ambale, Bollache, Emilie, de Cesare, Alain, Lima, Joao A.C., Redheuil, Alban, Kachenoura, Nadjia
• Format: Journal Article
• Language: English
• Published: London BioMed Central 30.07.2015; BioMed Central Ltd
• Subjects: Adult; Age Factors; Angiology; Aorta - physiology; Baltimore; Bioengineering; Cardiology; Cardiology and cardiovascular system; Female; Fourier Analysis; Health aspects; Healthy Volunteers; Heart beat; Human health and pathology; Humans; Imaging; Life Sciences; Linear Models; Magnetic Resonance Imaging - methods; Male; Medicine; Medicine & Public Health; Methods; Middle Aged; Models, Cardiovascular; Mortality; Paris; Predictive Value of Tests; Pulse Wave Analysis - methods; Radiology; Time Factors; Vascular Stiffness; Wavelet Analysis; Paris; Baltimore; Flow Curve; Applanation Tonometry; Cardiovascular Magnetic Resonance; Pulse Wave Velocity; Short Time Fourier Transform
• ISSN: 1097-6647; 1532-429X
• DOI: 10.1186/s12968-015-0164-7

Background Aortic pulse wave velocity (PWV), which substantially increases with arterial stiffness and aging, is a major predictor of cardiovascular mortality. It is commonly estimated using applanation tonometry at carotid and femoral arterial sites (cfPWV). More recently, several cardiovascular magnetic resonance (CMR) studies have focused on the measurement of aortic arch PWV (archPWV). Although the excellent anatomical coverage of CMR offers reliable segmental measurement of arterial length, accurate transit time (TT) determination remains a challenge. Recently, it has been demonstrated that Fourier-based methods were more robust to low temporal resolution than time-based approaches. Methods We developed a wavelet-based method, which enables temporal localization of signal frequencies, to estimate TT from ascending and descending aortic CMR flow curves. This method (archPWV WU ) combines the robustness of Fourier-based methods to low temporal resolution with the possibility to restrict the analysis to the reflectionless systolic upslope. We compared this method with Fourier-based (archPWV F ) and time domain upslope (archPWV TU ) methods in relation to linear correlations with age, cfPWV and effects of decreasing temporal resolution by factors of 2, 3 and 4. We studied 71 healthy subjects (45 ± 15 years, 29 females) who underwent CMR velocity acquisitions and cfPWV measurements. Results Comparison with age resulted in the highest correlation for the wavelet-based method (archPWV WU :r = 0.84, p  < 0.001; archPWV TU :r = 0.74, p  < 0.001; archPWV F :r = 0.63, p  < 0.001). Associations with cfPWV resulted in the highest correlations for upslope techniques whether based on wavelet (archPWV WU :r = 0.58, p  < 0.001) or time (archPWV TU :r = 0.58, p  < 0.001) approach. Furthermore, while decreasing temporal resolution by 4-fold induced only a minor decrease in correlation of both archPWV WU (r decreased from 0.84 to 0.80) and archPWV F (r decreased from 0.63 to 0.51) with age, it induced a major decrease for the archPWV TU age relationship (r decreased from 0.74 to 0.38). Conclusions By CMR, measurement of aortic arch flow TT using systolic upslopes resulted in a better correlation with age and cfPWV, as compared to the Fourier-based approach applied on the entire cardiac cycle. Furthermore, methods based on harmonic decomposition were less affected by low temporal resolution. Since the proposed wavelet approach combines these two advantages, it might help to overcome current technical limitations related to CMR temporal resolution and evaluation of patients with highly stiff arteries.