Literature DB >> 19859863

In-vivo quantification of wall motion in cerebral aneurysms from 2D cine phase contrast magnetic resonance images.

C Karmonik1, O Diaz, R Grossman, R Klucznik.   

Abstract

PURPOSE: The quantification of wall motion in cerebral aneurysms is of interest for the assessment of aneurysmal rupture risk, for providing boundary conditions for computational simulations and as a validation tool for theoretical models.
MATERIALS AND METHODS: 2D cine phase contrast magnetic resonance imaging (2D pcMRI) in combination with quantitative magnetic resonance angiography (QMRA) was evaluated for measuring wall motion in 7 intracranial aneurysms. In each aneurysm, 2 (in one case 3) cross sections, oriented approximately perpendicular to each other, were measured.
RESULTS: The maximum aneurysmal wall distention ranged from 0.16 mm to 1.6 mm (mean 0.67 mm), the maximum aneurysmal wall contraction was -1.91 mm to -0.34 mm (mean 0.94 mm), and the average wall displacement ranged from 0.04 mm to 0.31 mm (mean 0.15 mm). Statistically significant correlations between average wall displacement and the shape of inflow curves (p-value < 0.05) were found in 7 of 15 cross sections; statistically significant correlations between the displacement of the luminal boundary center point and the shape of inflow curves (p-value < 0.05) were found in 6 of 15 cross sections.
CONCLUSION: 2D pcMRI in combination with QMRA is capable of visualizing and quantifying wall motion in cerebral aneurysms. However, application of this technique is currently restricted by its limited spatial resolution.

Entities:  

Mesh:

Year:  2009        PMID: 19859863     DOI: 10.1055/s-0028-1109670

Source DB:  PubMed          Journal:  Rofo        ISSN: 1438-9010


  7 in total

1.  Intracranial aneurysmal pulsatility as a new individual criterion for rupture risk evaluation: biomechanical and numeric approach (IRRAs Project).

Authors:  M Sanchez; O Ecker; D Ambard; F Jourdan; F Nicoud; S Mendez; J-P Lejeune; L Thines; H Dufour; H Brunel; P Machi; K Lobotesis; A Bonafe; V Costalat
Journal:  AJNR Am J Neuroradiol       Date:  2014-05-22       Impact factor: 3.825

2.  Magnetic resonance imaging as a tool to assess reliability in simulating hemodynamics in cerebral aneurysms with a dedicated computational fluid dynamics prototype: preliminary results.

Authors:  Christof Karmonik; Y Jonathan Zhang; Orlando Diaz; Richard Klucznik; Sasan Partovi; Robert G Grossman; Gavin W Britz
Journal:  Cardiovasc Diagn Ther       Date:  2014-04

Review 3.  Intracranial Aneurysms: Wall Motion Analysis for Prediction of Rupture.

Authors:  A E Vanrossomme; O F Eker; J-P Thiran; G P Courbebaisse; K Zouaoui Boudjeltia
Journal:  AJNR Am J Neuroradiol       Date:  2015-04-30       Impact factor: 3.825

Review 4.  Physical factors effecting cerebral aneurysm pathophysiology.

Authors:  Chander Sadasivan; David J Fiorella; Henry H Woo; Baruch B Lieber
Journal:  Ann Biomed Eng       Date:  2013-04-03       Impact factor: 3.934

5.  A review on imaging techniques and quantitative measurements for dynamic imaging of cerebral aneurysm pulsations.

Authors:  L B Stam; R Aquarius; G A de Jong; C H Slump; F J A Meijer; H D Boogaarts
Journal:  Sci Rep       Date:  2021-01-26       Impact factor: 4.379

6.  A new cerebral vessel benchmark dataset (CAPUT) for validation of image-based aneurysm deformation estimation algorithms.

Authors:  Daniel Schetelig; Andreas Frölich; Tobias Knopp; René Werner
Journal:  Sci Rep       Date:  2018-10-30       Impact factor: 4.379

7.  Analysis of the influence of imaging-related uncertainties on cerebral aneurysm deformation quantification using a no-deformation physical flow phantom.

Authors:  Daniel Schetelig; Jan Sedlacik; Jens Fiehler; Andreas Frölich; Tobias Knopp; Thilo Sothmann; Jonathan Waschkewitz; René Werner
Journal:  Sci Rep       Date:  2018-07-20       Impact factor: 4.379

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.