OBJECTIVES: To compare the variability in vascularization flow index (VFI) seen in serial acquisitions obtained using spatiotemporal image correlation (STIC) and using conventional static three-dimensional (3D) power Doppler (PD), for both in-vitro and in-vivo models, and to evaluate whether the curves formed by VFI values obtained from successive 'frames' in a STIC dataset are consistent and resemble the waveforms obtained by spectral Doppler analysis. METHODS: The study was divided into two parts: in the first part (the in-vitro model) we scanned a flow phantom, while in the second part (the in-vivo model) we scanned a common carotid artery. Conventional static 3D and STIC-PD datasets were alternately acquired from these two models. VFI values were assessed from 0.38-cm(3) spherical samples of the main flow region in the static 3D datasets and in every frame of the STIC datasets. The variance of the minimum, mean and maximum VFI values from each STIC dataset was compared with the variance of VFI values from the static 3D datasets. RESULTS: Ten static 3D and 10 STIC datasets were acquired from each model. Analysis of the in-vitro and in-vivo models showed a significant reduction in the variance of VFI values obtained using STIC as compared to static datasets. Additionally, we observed that the curves formed by VFI values obtained from successive frames in each STIC dataset were consistent across different datasets and that they resembled the waveforms obtained by spectral Doppler in both models. CONCLUSIONS: 3D-PD indices derived from STIC are more stable than those obtained from conventional static 3D-PD datasets. The curves of VFI throughout a reconstructed cardiac cycle using STIC are repeatable and resemble those obtained by spectral Doppler analysis of the vessel.
OBJECTIVES: To compare the variability in vascularization flow index (VFI) seen in serial acquisitions obtained using spatiotemporal image correlation (STIC) and using conventional static three-dimensional (3D) power Doppler (PD), for both in-vitro and in-vivo models, and to evaluate whether the curves formed by VFI values obtained from successive 'frames' in a STIC dataset are consistent and resemble the waveforms obtained by spectral Doppler analysis. METHODS: The study was divided into two parts: in the first part (the in-vitro model) we scanned a flow phantom, while in the second part (the in-vivo model) we scanned a common carotid artery. Conventional static 3D and STIC-PD datasets were alternately acquired from these two models. VFI values were assessed from 0.38-cm(3) spherical samples of the main flow region in the static 3D datasets and in every frame of the STIC datasets. The variance of the minimum, mean and maximum VFI values from each STIC dataset was compared with the variance of VFI values from the static 3D datasets. RESULTS: Ten static 3D and 10 STIC datasets were acquired from each model. Analysis of the in-vitro and in-vivo models showed a significant reduction in the variance of VFI values obtained using STIC as compared to static datasets. Additionally, we observed that the curves formed by VFI values obtained from successive frames in each STIC dataset were consistent across different datasets and that they resembled the waveforms obtained by spectral Doppler in both models. CONCLUSIONS: 3D-PD indices derived from STIC are more stable than those obtained from conventional static 3D-PD datasets. The curves of VFI throughout a reconstructed cardiac cycle using STIC are repeatable and resemble those obtained by spectral Doppler analysis of the vessel.
Authors: Linda Wu; Ana Ferreira; Gordon N Stevenson; Jennifer Sanderson; Aditi Mahajan; Neama Meriki; Alec W Welsh Journal: Australas J Ultrasound Med Date: 2017-07-11