title: In vitro model test and preliminary clinical application of a new method of ultrasonographic imaging: Vascular enhancement technology.
abstract: Vascular enhancement technology (VET) is a new form of ultrasonographic technology that can optimize images by enhancing the B-mode display with information derived from power Doppler. We designed an in vitro model to evaluate the accuracy and application method of VET and to apply this technology preliminarily in vivo in the vascular periphery. An in vitro model was designed with a flow pump system to simulate blood flow in soft tissue and the intracranial vasculature. Modeling vessels were imaged by traditional B mode, color Doppler flow imaging and VET. The diameter of the various silicon tubes was measured to verify the accuracy of VET. For in vivo application, 15 normal subjects and 26 patients suspected of having carotid artery plaques and cerebrovascular disease were examined using these three image modes. The imaging effects were observed and compared. VET imaging could clarify the lumens of the modeling vessels and reduce artifacts. The caliber of three sizes of silicon tubing was also measured accurately by VET. Of 15 normal subjects, sound artifacts in large vessels were inhibited and the intermedia membrane was clearly displayed by VET. The boundaries of carotid plaques were manifested by VET with well-defined edges. Three cases of hypoechoic soft plaque on the anterior wall missed in B-mode imaging were detected by VET. Intracranial scanning with VET identified cerebral vascular disease, including cerebral stenosis, arteriovenous malformations and aneurysms. The size and shape of the focus displayed by VET coincided with that observed using digital subtraction arteriography. VET is helpful in improving detection of the boundary of vessels and visualization of the microvasculature.
authors.affiliation: Department of Ultrasound Diagnostics, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
authors.forename: Xi
authors.initials: X
authors.lastname: Liu
authors.forename: Yun You
authors.initials: YY
authors.lastname: Duan
authors.forename: Jia
authors.initials: J
authors.lastname: Wang
authors.forename: Si Guo
authors.initials: SG
authors.lastname: Sun
authors.forename: Juan
authors.initials: J
authors.lastname: Li
authors.forename: Wei Hua
authors.initials: WH
authors.lastname: Hou
authors.forename: Tie Sheng
authors.initials: TS
authors.lastname: Cao
mesh_terms: D000328:Adult; D015901:Angiography, Digital Subtraction; D016477:Artifacts; D001808:Blood Vessels / Q000000981:diagnostic imaging*; D016893:Carotid Stenosis / Q000000981:diagnostic imaging*; D002539:Cerebral Arterial Diseases / Q000000981:diagnostic imaging; D004453:Echoencephalography / Q000379:methods; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging; D008955:Models, Cardiovascular; D018615:Ultrasonography, Doppler, Color / Q000379:methods; D055815:Young Adult