Real-Time Contrast-Free Ultrasonic Blood Flow Velocity Profile Measurement G.G. Koutsouridis, N. Bijnens, P.J. Brands, F.N. van de Vosse and M.C.M. Rutten Problem Description 1. Ultrasonic Perpendicular Velocimetry Wall Doppler Ultrasound UPV Figure 1 Current ultrasound research system with real-time GPU module design for the UPV method 1. Ultrasonic Perpendicular Velocimetry (UPV) to RF-data for accurate velocity and flow assessment is time consuming due to data size and post processing [1,2]. Wall Ultrasound beam Ultrasound beam Centerline 2. Fast Fourier Transform (FFT) on Butterworth Band Pass Filters (BPF) for vessel’s wall removal requires contrast agents dispersion in the fluid for the application of Cross- correlation. Aim In-vitro (aortic-like polyurethane vessel) with Blood Mimicking Fluid (BMF), resembling the Methods Real-time UPV on Graphics Processing Unit (GPU) [3]. rheological (shear thinning) & acoustical (backscattering) Blood’s properties, as contrast agent. Ex-vivo (porcine carotid arteries) with BMF & contrast-free real Blood, implementing Wavelet Transform (WT) filtering. Results Methods • In-vitro and Ex-vivo constant and physiological pulsating flows of 1Hz and peak flow velocity 0.8m/sec. • Ultrasound RF-data acquired at 33MHz (Fast B-mode) 6 seconds of images, at 730frames/sec. Results Acceleration offered by the UPV method for the real-time (Figure 3.[#]) perpendicular assessment of the velocity profiles. 6 seconds of images, at 730frames/sec. For the UPV technique, the process consisted, among others (Figure 1), of the following steps: Wall removal and contrast-free fluid scattering enhancement via WT Daubechies8 filtering (localization 3.[1] 3.[2] in time & frequency) for functions with discontinuities and sharp peaks (Figure 2). High Pass Filtering (HPF) of the sequential frames in the time direction. (i) (ii) (iii) (i) (ii) (iii) In-vitro constant flow BMF In-vitro pulsating flow BMF Application of improved Cross-correlation for the assessment of velocity profiles. 3.[3] 0.7 0.6 0.7 0.6 (i) (ii) (iii) Ex-vivo pulsating flow Blood 0.4 0.5 0.6 0 0.2 0.4 v ax (m/s) 0.4 0.5 0.6 0 0.2 0.4 0.6 v ax (m/s) Figure 3.[#] Real-time GPU velocity profile (▪) assessment with: (i) No filtering, (ii) WT and (iii) WT & HPF 0.2 0.3 v(m/s) -5 0 5 x 10 -3 r(m) 0.04 0.06 0.2 0.3 v(m/s) -5 0 5 x 10 -3 r(m) 0.04 0.06 m/s) Conclusion The WT filtering technique allows measurement of Blood flow without contrast agents, while the GPU allows a real-time -5 0 5 -0.1 0 0.1 -5 0 5 0 0.02 0.04 Δ v (m/s) -5 0 5 -3 -0.1 0 0.1 r(m) -5 0 5 -3 0 0.02 0.04 Δ v (m without contrast agents, while the GPU allows a real-time assessment of axial velocity distribution. With a real-time implementation of the local ultrasound pressure estimation, real-time characteristic vascular impedance assessment, as a diagnostic tool, will be feasible even In-vivo. Figure 2 The effect of WT Daub8 (right) vs BPF (left) on the quality of the velocity profiles assessed by UPV. Left panels show estimates from individual frames, while top and bottom indicate mean values and standard deviations x 10 -3 r(m) x 10 -3 r(m) x 10 -3 r(m) x 10 -3 r(m) diagnostic tool, will be feasible even In-vivo. References [1] Beulen, B.W.A.M.M. et al. (2010), “Perpendicular ultrasound velocity measurement by 2D cross correlation of RF data. Part A: validation in a straight tube”, Exp Fluids, 49, pp. 1177-1186. [2] Beulen, B.W.A.M.M. et al. (2011), “Toward noninvasive blood pressure assessment in arteries by using ultrasound”, Ultrasound in Med. & Biol., 37:5, pp. 788-797. [3] Owens, J.D. et al. (2008), “GPU Computing: Graphics Processing Units–powerful, programmable and highly parallel–are increasingly targeting general-purpose computing applications”, Proceeding of the IEEE, 96:5, pp. 879-899. / Department of Biomedical Engineering