狭窄
放射科
大脑中动脉
经颅多普勒
超声波
医学
血流动力学
心脏病学
缺血
作者
Giovanni Malferrari,Nicola Merli,Vincenzo Inchingolo,Antonio Siniscalchi,Domenico Laterza,Daniela Monaco,Giorgia Arnone,Andrea Zini,Francesco Prada,Cristiano Azzini,Maura Pugliatti
标识
DOI:10.1016/j.ultrasmedbio.2023.07.004
摘要
The aim of the work described here was to determine the possible impact of the new technique advanced hemodynamic ultrasound evaluation (AHUSE) in identification of severe intracranial stenosis. Transcranial Doppler (TCD) and transcranial color-coded Doppler (TCCD) provide reliable velocimetric data, the indirect analysis of which allows us to obtain information on the patency of vessels and assumed stenosis range. However, very tight stenoses (>95%) cannot be detected with velocimetric criteria because of spectrum drops and the absence of high velocities, so that the right curve of the Spencer equation cannot be solved. Likewise, high velocities are not detected when analyzing morphologically long stenosis. Furthermore, the current classifications based on velocimetric criteria do not provide any categorization on stenoses with multiple acceleration points (MAPs).With this Technical Note we aim to introduce, in addition to velocimetric criteria, more morphological criteria based on TCCD with the algorithm of AHUSE to optimize the characterization of intracranial stenosis (IS). TCCD-AHUSE relies on intensity-based next-generation techniques and can be used to identify IS with MAPs and simultaneously perform a morphological assessment of the stenosis length.We introduce a new technical ultrasound (U) approach that we tested in a sample of four different types of stenoses combining velocimetric data and AHUSE using Esaote Microvascularization (MicroV) technique to the M1 tract of the middle cerebral artery (MCA).The authors believe that a multiparametric evaluation is more sensitive and supports the clinician by introducing the morphological concept, not just the velocimetric concept, to differentiate the IS pattern of MCA. The potential for developing a diagnostic/prognostic algorithm is discussed.
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