MicroV Technology to Improve Transcranial Color Coded Doppler Examinations

Giovanni Malferrari, Giuseppe Pulito, Attilia Maria Pizzini, Nicola Carraro, Giorgio Meneghetti, Enzo Sanzaro, Patrizio Prati, Antonio Siniscalchi, Daniela Monaco

Research output: Contribution to journalArticle

Abstract

The purpose of this review is to provide an update on technology related to Transcranial Color Coded Doppler Examinations. Microvascularization (MicroV) is an emerging Power Doppler technology which can allow visualization of low and weak blood flows even at high depths, thus providing a suitable technique for transcranial ultrasound analysis. With MicroV, reconstruction of the vessel shape can be improved, without any overestimation. Furthermore, by analyzing the Doppler signal, MicroV allows a global image of the Circle of Willis. Transcranial Doppler was originally developed for the velocimetric analysis of intracranial vessels, in particular to detect stenoses and the assessment of collateral circulation. Doppler velocimetric analysis was then compared to other neuroimaging techniques, thus providing a cut-off threshold. Transcranial Color Coded Doppler sonography allowed the characterization of vessel morphology. In both Color Doppler and Power Doppler, the signal overestimated the shape of the intracranial vessels, mostly in the presence of thin vessels and high depths of study. In further neurosonology technology development efforts, attempts have been made to address morphology issues and overcome technical limitations. The use of contrast agents has helped in this regard by introducing harmonics and subtraction software, which allowed better morphological studies of vessels, due to their increased signal-to-noise ratio. Having no limitations in the learning curve, in time and contrast agent techniques, and due to its high signal-to-noise ratio, MicroV has shown great potential to obtain the best morphological definition.

Original languageEnglish
Pages (from-to)350-358
Number of pages9
JournalJournal of Neuroimaging
Volume28
Issue number4
DOIs
Publication statusPublished - Jul 1 2018

Fingerprint

Doppler Transcranial Ultrasonography
Signal-To-Noise Ratio
Contrast Media
Color
Circle of Willis
Technology
Doppler Color Ultrasonography
Collateral Circulation
Learning Curve
Neuroimaging
Pathologic Constriction
Software
Power (Psychology)
Industrial Development

Keywords

  • contrast enhancement
  • MicroV
  • morphological vessel resolution
  • transcranial color coded Doppler
  • transcranial power Doppler

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

Cite this

Malferrari, G., Pulito, G., Pizzini, A. M., Carraro, N., Meneghetti, G., Sanzaro, E., ... Monaco, D. (2018). MicroV Technology to Improve Transcranial Color Coded Doppler Examinations. Journal of Neuroimaging, 28(4), 350-358. https://doi.org/10.1111/jon.12517

MicroV Technology to Improve Transcranial Color Coded Doppler Examinations. / Malferrari, Giovanni; Pulito, Giuseppe; Pizzini, Attilia Maria; Carraro, Nicola; Meneghetti, Giorgio; Sanzaro, Enzo; Prati, Patrizio; Siniscalchi, Antonio; Monaco, Daniela.

In: Journal of Neuroimaging, Vol. 28, No. 4, 01.07.2018, p. 350-358.

Research output: Contribution to journalArticle

Malferrari, G, Pulito, G, Pizzini, AM, Carraro, N, Meneghetti, G, Sanzaro, E, Prati, P, Siniscalchi, A & Monaco, D 2018, 'MicroV Technology to Improve Transcranial Color Coded Doppler Examinations', Journal of Neuroimaging, vol. 28, no. 4, pp. 350-358. https://doi.org/10.1111/jon.12517
Malferrari G, Pulito G, Pizzini AM, Carraro N, Meneghetti G, Sanzaro E et al. MicroV Technology to Improve Transcranial Color Coded Doppler Examinations. Journal of Neuroimaging. 2018 Jul 1;28(4):350-358. https://doi.org/10.1111/jon.12517
Malferrari, Giovanni ; Pulito, Giuseppe ; Pizzini, Attilia Maria ; Carraro, Nicola ; Meneghetti, Giorgio ; Sanzaro, Enzo ; Prati, Patrizio ; Siniscalchi, Antonio ; Monaco, Daniela. / MicroV Technology to Improve Transcranial Color Coded Doppler Examinations. In: Journal of Neuroimaging. 2018 ; Vol. 28, No. 4. pp. 350-358.
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