Abstract

Brief Description of the Purpose of the StudyTo compare the variability of vascularization flow index (VFI) related to serial acquisitions between spatio-temporal image correlation (STIC) and conventional static three-dimensional (3D) power Doppler (PD), using both an in vitro and an in vivo models. And to evaluate whether the curves from VFI values obtained in a STIC dataset are visually stable and resemble the spectral Doppler waveforms.MethodsTwo models were analyzed: a flow phantom (in vitro model) and a common carotid artery (in vivo model). VFI values were assessed from 0.38 cm3 spherical samples of main flow region of the static 3D datasets and from every ‘frame’ of STIC datasets. The variance of the minimum, mean, and maximum VFI values were compared between STIC and static 3D datasets.Main ResultsWe observed significant reduction in the variance of VFI values obtained in STIC compared to static datasets. The curves of VFI values obtained across the frames contained in the STIC are stable across different datasets and resemble the spectral Doppler waveforms.Importance of the Conclusions3DPD indices derived from STIC are more stable than those obtained from conventional static 3DPD datasets. Curves of VFI throughout a reconstituted cardiac cycle using STIC are repeatable and resemble those obtained from spectral Doppler analysis of the vessel. Brief Description of the Purpose of the StudyTo compare the variability of vascularization flow index (VFI) related to serial acquisitions between spatio-temporal image correlation (STIC) and conventional static three-dimensional (3D) power Doppler (PD), using both an in vitro and an in vivo models. And to evaluate whether the curves from VFI values obtained in a STIC dataset are visually stable and resemble the spectral Doppler waveforms. To compare the variability of vascularization flow index (VFI) related to serial acquisitions between spatio-temporal image correlation (STIC) and conventional static three-dimensional (3D) power Doppler (PD), using both an in vitro and an in vivo models. And to evaluate whether the curves from VFI values obtained in a STIC dataset are visually stable and resemble the spectral Doppler waveforms. MethodsTwo models were analyzed: a flow phantom (in vitro model) and a common carotid artery (in vivo model). VFI values were assessed from 0.38 cm3 spherical samples of main flow region of the static 3D datasets and from every ‘frame’ of STIC datasets. The variance of the minimum, mean, and maximum VFI values were compared between STIC and static 3D datasets. Two models were analyzed: a flow phantom (in vitro model) and a common carotid artery (in vivo model). VFI values were assessed from 0.38 cm3 spherical samples of main flow region of the static 3D datasets and from every ‘frame’ of STIC datasets. The variance of the minimum, mean, and maximum VFI values were compared between STIC and static 3D datasets. Main ResultsWe observed significant reduction in the variance of VFI values obtained in STIC compared to static datasets. The curves of VFI values obtained across the frames contained in the STIC are stable across different datasets and resemble the spectral Doppler waveforms. We observed significant reduction in the variance of VFI values obtained in STIC compared to static datasets. The curves of VFI values obtained across the frames contained in the STIC are stable across different datasets and resemble the spectral Doppler waveforms. Importance of the Conclusions3DPD indices derived from STIC are more stable than those obtained from conventional static 3DPD datasets. Curves of VFI throughout a reconstituted cardiac cycle using STIC are repeatable and resemble those obtained from spectral Doppler analysis of the vessel. 3DPD indices derived from STIC are more stable than those obtained from conventional static 3DPD datasets. Curves of VFI throughout a reconstituted cardiac cycle using STIC are repeatable and resemble those obtained from spectral Doppler analysis of the vessel.

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