Intracranial aneurysm wall displacement depicted by amplified Flow predicts growth.

Aneurysm MRI Magnetic Resonance Angiography Vessel Wall

Journal

Journal of neurointerventional surgery
ISSN: 1759-8486
Titre abrégé: J Neurointerv Surg
Pays: England
ID NLM: 101517079

Informations de publication

Date de publication:
06 Feb 2024
Historique:
received: 09 11 2023
accepted: 21 01 2024
medline: 7 2 2024
pubmed: 7 2 2024
entrez: 6 2 2024
Statut: aheadofprint

Résumé

Abnormal intracranial aneurysm (IA) wall motion has been associated with IA growth and rupture. Recently, a new image processing algorithm called amplified Flow (aFlow) has been used to successfully track IA wall motion by combining the amplification of cine and four-dimensional (4D) Flow MRI. We sought to apply aFlow to assess wall motion as a potential marker of IA growth in a paired-wise analysis of patients with growing versus stable aneurysms. In this retrospective case-control study, 10 patients with growing IAs and a matched cohort of 10 patients with stable IAs who had baseline 4D Flow MRI were included. The aFlow was used to amplify and extract IA wall displacements from 4D Flow MRI. The associations of aFlow parameters with commonly used risk factors and morphometric features were assessed using paired-wise univariate and multivariate analyses. aFlow quantitative results showed significantly (P=0.035) higher wall motion displacement depicted by mean±SD 90 aFlow-derived quantitative assessment of IA wall motion showed greater wall motion and higher variability of wall deformation in growing versus stable IAs.

Sections du résumé

BACKGROUND BACKGROUND
Abnormal intracranial aneurysm (IA) wall motion has been associated with IA growth and rupture. Recently, a new image processing algorithm called amplified Flow (aFlow) has been used to successfully track IA wall motion by combining the amplification of cine and four-dimensional (4D) Flow MRI. We sought to apply aFlow to assess wall motion as a potential marker of IA growth in a paired-wise analysis of patients with growing versus stable aneurysms.
METHODS METHODS
In this retrospective case-control study, 10 patients with growing IAs and a matched cohort of 10 patients with stable IAs who had baseline 4D Flow MRI were included. The aFlow was used to amplify and extract IA wall displacements from 4D Flow MRI. The associations of aFlow parameters with commonly used risk factors and morphometric features were assessed using paired-wise univariate and multivariate analyses.
RESULTS RESULTS
aFlow quantitative results showed significantly (P=0.035) higher wall motion displacement depicted by mean±SD 90
CONCLUSIONS CONCLUSIONS
aFlow-derived quantitative assessment of IA wall motion showed greater wall motion and higher variability of wall deformation in growing versus stable IAs.

Identifiants

pubmed: 38320850
pii: jnis-2023-021227
doi: 10.1136/jnis-2023-021227
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Aymeric Pionteck (A)

Mechanical Engineering, University of Washington, Seattle, Washington, USA.

Javid Abderezaei (J)

Mechanical Engineering, University of Washington, Seattle, Washington, USA.

Patrick Fillingham (P)

Neurological Surgery, University of Washington School of Medicine, Seattle, Washington, USA.

Ya-Chen Chuang (YC)

Mechanical Engineering, University of Washington, Seattle, Washington, USA.

Yu Sakai (Y)

Diagnostic, Molecular and Interventional Radiology, Mount Sinai Health System, New York, New York, USA.

Puneet Belani (P)

Diagnostic, Molecular and Interventional Radiology, Mount Sinai Health System, New York, New York, USA.

Brian Rigney (B)

Diagnostic, Molecular and Interventional Radiology, Mount Sinai Health System, New York, New York, USA.

Reade De Leacy (R)

Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Johanna T Fifi (JT)

Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Aichi Chien (A)

Radiological Sciences, University of California, Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

Geoffrey P Colby (GP)

Neurosurgery, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

Reza Jahan (R)

Radiological Sciences, University of California, Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

Gary Duckwiler (G)

Radiological Sciences, University of California, Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

James Sayre (J)

Radiological Sciences, University of California, Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

Samantha J Holdsworth (SJ)

Department of Anatomy, University of Auckland, Auckland, New Zealand.

Mahmud Mossa-Basha (M)

Radiology, University of Washington School of Medicine, Seattle, Washington, USA.

Michael R Levitt (MR)

Neurological Surgery, University of Washington School of Medicine, Seattle, Washington, USA.

J Mocco (J)

Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Mehmet Kurt (M)

Mechanical Engineering, University of Washington, Seattle, Washington, USA.

Kambiz Nael (K)

Diagnostic, Molecular and Interventional Radiology, Mount Sinai Health System, New York, New York, USA kambiznael@gmail.com.
Radiological Sciences, University of California, Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.

Classifications MeSH