Hamid BEHNAM, Zahra ALIZADEH SANI, Samrand SHARIFI

A new technique for the measurement and assessment of carotid artery wall vibrations using ultrasound RF echoes

Atherosclerosis is known as the leading cause of heart attacks and brain strokes. One of the symptoms ofthis disease is the reduction of artery wall motion caused by age. This study presents a novel method to extract highfrequency components of wall motion, wall vibrations, based on discrete wavelet transform. The fractal dimension, largestLyapunov exponent, and spectral entropy are then analyzed to indicate the chaotic behavior in wall vibrations. Phaseinformation from demodulated radiofrequency signals is extracted and the entropy of phase-difference is computed as astatistical measure for better characterization of the artery wall tissue. The results show that these features correlatewith age (P < 0.001) and also increase with age. The phase-difference entropy also shows significant correlation withage (r = 0.34, P < 0.001). The measurement results indicate that while age increases, vibrations of the artery wallare irregular and represent chaotic behavior. Our results raise hopes that the proposed approach may be effective indiagnosing atherosclerosis.

PDF

___

[1] Lee RT, Libby P. The unstable atheroma. Arterioscl Thromb Vas 1997; 17: 1859–1867.
[2] Kondo K, Nemoto M, Harada N, Fukushima D, Masuda H, Sugo N. Comparison between quantitative stiffness measurements and ultrasonographic findings of fresh carotid plaques. Ultrasound Med Biol 2017; 43: 138-144.
[3] Kiechl S, Willeit J. The natural course of atherosclerosis. Part I: Incidence and progression. Arterioscl Thromb Vas 1999; 19: 1484–1490.
[4] Ciccone MM, Scicchitano P, Zito A, Agati L, Gesualdo M, Mandolesi S, Carbonara R, Ciciarello F, Fedele F. Correlation between coronary artery disease severity, left ventricular mass index and carotid intima media thickness, assessed by radio-frequency. Cardiovasc Ultrasoun 2011; 9: 32.
[5] Smedby O. Do plaques grow upstream or downstream? An angiographic study in the femoral artery. Arterioscl Throm Vas 1997; 17: 912–918.
[6] Jaffer FA, O’Donnel CJ, Larson MG, Chan SK, Kissinger KV, Kupka MJ, Salton C, Botnar RM, Levy D, Manning WJ. Age and sex distribution of subclinical aortic atherosclerosis: a magnetic resonance imaging examination of the Framingham heart study. Arterioscl Throm Vas 2002; 22: 849–854.
[7] Wendelhag I, Wiklund O, Wikstrand J. On quantifying plaque size and intima-media thickness in carotid and femoral arteries: comments on results from a prospective ultrasound study in patients with familial hypercholesterolemia. Arterioscl Throm Vas 1996; 16: 843–850.
[8] Larsson M, Heyde B, Kremer F, Brodin LA, D’Hooge J. Ultrasound speckle tracking for radial, longitudinal and circumferential strain estimation of the carotid artery – An in vitro validation via sonomicrometry using clinical and high-frequency ultrasound. Ultrasonics 2015; 56: 399-408.
[9] Khan A, Sikdar S, Hatsukami T, Cebral J, Jones M, Huston J, Howard G, Lal BK. Noninvasive characterization of carotid plaque strain. Vascular Surg 2017; 65: 1653-63.
[10] Czernuszewicz JT, Homeister WJ, Caughey CM, Farber AM, Fulton JJ, Ford P, Marston AW, Vallabhaneni R, Nichols CT, Gallippi MC. Non-invasive in vivo characterization of human carotid plaques with acoustic radiation force impulse ultrasound: comparison with histology after endarterectomy. Ultrasound Med Biol 2015; 41: 685-697.
[11] Huang C, He Q, Huang M, Huang L, Zhao X, Yuan C, Luo J. Non-invasive identification of vulnerable atherosclerotic plaques using texture analysis in ultrasound carotid elastography: an in vivo feasibility study validated by magnetic resonance imaging. Ultrasound Med Biol 2017; 43: 817-830.
[12] Hallock P. Arterial elasticity in man in relation to age as evaluated by the pulse wave velocity method. Arch Intern Med 1934; 54: 770–798.
[13] Giannattasio C, Failla M, Emanuelli G, Grappiolo A, Boffi L, Corsi D, Mancia G. Local effects of atherosclerotic plaque on arterial distensibility. Hypertension 2001; 38: 1177-1180.
[14] Kanber B, Hartshorne TC, Horsfield MA, Naylor AR, Robinson TG, Ramnarine KV. Wall motion in the stenotic carotid artery: association with greyscale plaque characteristics, the degree of stenosis and cerebrovascular symptoms. Cardiovasc Ultrasoun 2013; 11: 37.
[15] Cecelja M, Chowienczyk P. Role of arterial stiffness in cardiovascular disease. JRSM Cardiovascular Disease. 2012; 1: 11.
[16] Hasegawa H, Kanai H, Hoshimiya N, Chubachi N, Koiwa Y. Accuracy evaluation in the measurement of a small change in the thickness of arterial walls and the measurement of elasticity of the human carotid artery. Jpn J Appl Phys 1998; 37: 3101-3105.
[17] Kanai H, Sato M, Koiwa Y, Chubachi N. Transcutaneous measurement and spectrum analysis of heart wall vibrations. IEEE T Ultrason Ferr 1996; 43: 791-810.
[18] Kanai H, Koiwa Y. Real-time velocimetry for evaluation of change in thickness of arterial wall. Ultrasonics 2000; 38: 381-386.
[19] Hasegawa H, Kanai H, Koiwa Y. Modified phased tracking method for measurement of change in thickness of arterial wall. Jpn J Appl Phys 2002; 41: 3563-3571.
[20] Kanai H, Haseqawa H, Ichiki M, Tezuka F, Koiwa Y. Elasticity imaging of atheroma with transcutaneous ultrasound: preliminary study. Circulation 2003; 107: 3018-3021.
[21] Smedby R. Do plaques grow upstream or downstream? An angiographic study in the femoral artery. Arterioscl Throm Vas 1997; 17: 912–918.
[22] Jaffer FA, O’Donnel CJ, Larson MG, Chan SK, Kissinger KV, Kupka MJ, Salton C, Botnar RM, Levy D, Manning WJ. Age and sex distribution of subclinical aortic atherosclerosis: a magnetic resonance imaging examination of the Framingham heart study. Arterioscl Throm Vas 2002; 22: 849–854.
[23] Wendelhag I, Wiklund O, Wikstrand J. On quantifying plaque size and intima-media thickness in carotid and femoral arteries: comments on results from a prospective ultrasound study in patients with familial hypercholesterolemia. Arterioscl Throm Vas 1996; 16: 843–850.
[24] Moradi M, Abolmaesumi P, Isotalo P, Siemens D, Sauerbrei E, Mousavi P. Detection of prostate cancer from RF ultrasound echo signals using fractal analysis. In: Proceedings of the 2006 IEEE EMBC. New York, NY, USA: IEEE, 2006. pp. 2400-2403.
[25] D’Hooge J. Interaction of ultrasonic waves and tissues: modeling, simulations and applications. PhD, Louven University, Louven, Belgium, 1999.
[26] Wagner RF, Insana MF, Brown DG. Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound. J Opt Soc Am A 1987; 4: 910-922.
[27] Dydenko I, Friboulet D, Gorce JM, D’Hooge J, Bijnens B, Magnin I. Towards ultrasound cardiac image segmentation based on the radiofrequancy signal. Journal of Medical Image Analysis 2003; 7: 353-367.
[28] Laurent S, Marais L, Boutouyrie P. The noninvasive assessment of vascular aging. Can J Cardiol 2016; 32: 669-679.
[29] Sunagawa K, Kanai H, Koiwa Y, Nitta K, Tanaka M. Simultaneous measurement of vibrations on the arterial wall downstream and upstream from an atherosclerotic lesions. In: Proceedings of the 1999 IEEE Ultrasonics Symposium; Tahoe, NV, USA. New York, NY, USA: IEEE, 1999. pp. 1507–1510.
[30] Zavar M, Rahati S, Akbarzadeh TM, Ghasemifard H. Evolutionary model selection in a wavelet-based support vector machine for automated seizure detection. Expert Syst Appl 2011; 38: 10751–10758.
[31] Garnett PW. Chaos Theory Tamed. 1st ed. Washington, DC, USA: Joseph Henry Press, 1997.