title: An improved spectral width Doppler method for estimating Doppler angles in flows with existence of velocity gradients.
abstract: Doppler angle (i.e., beam-to-flow angle) is an important parameter for quantitative flow measurements. With known Doppler angles, volumetric flows can be obtained by the mean flow velocity times the cross-section area of the vessel. The differences or changes between prestenotic and poststenotic volumetric flows have been quantified as an indicator for assessing the clinical severity of the stenosis. Therefore, several research groups have dedicated themselves to developing user-independent methods to determine automatically the Doppler angle. Nevertheless, most of these methods were developed for narrow ultrasound beam measurements. For small vessels, where the beam width is a significant fraction of the diameter of the vessel, the effect of velocity gradients plays an important role and should not be ignored in the Doppler angle estimations. Accordingly, this paper is concerned with a method for improving the estimation of Doppler angles from spectral width Doppler (SWD) method, but correcting for velocity-gradient broadening that may arise when the beam has a nonzero width. In our method, Doppler angles were firstly calculated by SWD and then were corrected by an artificial neural network (ANN) method to neutralize the contribution of velocity gradient broadening (VGB). This SWD and ANN conjoint method has been successfully applied to estimate Doppler angles from 50 degrees to 80 degrees for constant flows in 10 mm, 4 mm and 1 mm diameter tubes, whose mean flow velocities were 15.3, 19.9 and 25.5 cm/s, respectively, and the achieved mean absolute errors of the estimated Doppler angles were 1.46 degrees , 1.01 degrees and 1.3 degrees.
authors.affiliation: Institute of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan.
authors.forename: Po-Lei
authors.initials: PL
authors.lastname: Lee
authors.forename: Yi-Hong
authors.initials: YH
authors.lastname: Chou
authors.forename: Jen-Chuen
authors.initials: JC
authors.lastname: Hsieh
authors.forename: Huihua Kenny
authors.initials: HK
authors.lastname: Chiang
mesh_terms: D001783:Blood Flow Velocity; D006801:Humans; D016571:Neural Networks, Computer; D016491:Peripheral Vascular Diseases / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D011673:Pulsatile Flow; D012815:Signal Processing, Computer-Assisted; D018615:Ultrasonography, Doppler, Color / Q000379:methods*