scholarly journals Fast semi-automated analysis of pulse wave velocity in the thoracic aorta using high temporal resolution 4D flow MRI

Author(s):  
Bruce Spottiswoode ◽  
Aurelien F Stalder ◽  
Mehmet A Gulsun ◽  
Karissa F Campione ◽  
Maria Carr ◽  
...  
2020 ◽  
pp. 0271678X2091030 ◽  
Author(s):  
Leonardo A Rivera-Rivera ◽  
Karly A Cody ◽  
Laura Eisenmenger ◽  
Paul Cary ◽  
Howard A Rowley ◽  
...  

Clinical evidence shows vascular factors may co-occur and complicate the expression of Alzheimer’s disease (AD); yet, the pathologic mechanisms and involvement of different compartments of the vascular network are not well understood. Diseases such as arteriosclerosis diminish vascular compliance and will lead to arterial stiffness, a well-established risk factor for cardiovascular morbidity. Arterial stiffness can be assessed using pulse wave velocity (PWV); however, this is usually done from carotid-to-femoral artery ratios. To probe the brain vasculature, intracranial PWV measures would be ideal. In this study, high temporal resolution 4D flow MRI was used to assess transcranial PWV in 160 subjects including AD, mild cognitive impairment (MCI), healthy controls, and healthy subjects with apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+). High temporal resolution imaging was achieved by high temporal binning of retrospectively gated data using a local-low rank approach. Significantly higher transcranial PWV in AD dementia and MCI subjects was found when compared to old-age-matched controls (AD vs. old-age-matched controls: P <0.001, AD vs. MCI: P = 0.029, MCI vs. old-age-matched controls P = 0.013). Furthermore, vascular changes were found in clinically healthy middle-age adults with APOE4+ and FH+ indicating significantly higher transcranial PWV compared to controls ( P <0.001).


2018 ◽  
Vol 9 (4) ◽  
pp. 674-687 ◽  
Author(s):  
Timothy Ruesink ◽  
Rafael Medero ◽  
David Rutkowski ◽  
Alejandro Roldán-Alzate

2021 ◽  
pp. 0271678X2110087
Author(s):  
Cecilia Björnfot ◽  
Anders Garpebring ◽  
Sara Qvarlander ◽  
Jan Malm ◽  
Anders Eklund ◽  
...  

Intracranial arterial stiffening is a potential early marker of emerging cerebrovascular dysfunction and could be mechanistically involved in disease processes detrimental to brain function via several pathways. A prominent consequence of arterial wall stiffening is the increased velocity at which the systolic pressure pulse wave propagates through the vasculature. Previous non-invasive measurements of the pulse wave propagation have been performed on the aorta or extracranial arteries with results linking increased pulse wave velocity to brain pathology. However, there is a lack of intracranial “target-organ” measurements. Here we present a 4D flow MRI method to estimate pulse wave velocity in the intracranial vascular tree. The method utilizes the full detectable branching structure of the cerebral vascular tree in an optimization framework that exploits small temporal shifts that exists between waveforms sampled at varying depths in the vasculature. The method is shown to be stable in an internal consistency test, and of sufficient sensitivity to robustly detect age-related increases in intracranial pulse wave velocity.


2022 ◽  
Vol 71 ◽  
pp. 103259
Author(s):  
Joaquín Mura ◽  
Julio Sotelo ◽  
Hernán Mella ◽  
James Wong ◽  
Tarique Hussain ◽  
...  

Author(s):  
Kelly Jarvis ◽  
Michael B. Scott ◽  
Gilles Soulat ◽  
Mohammed S. M. Elbaz ◽  
Alex J. Barker ◽  
...  

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Patrick Winter ◽  
Kristina Andelovic ◽  
Thomas Kampf ◽  
Jan Hansmann ◽  
Peter Michael Jakob ◽  
...  

Abstract Purpose Wall shear stress (WSS) and pulse wave velocity (PWV) are important parameters to characterize blood flow in the vessel wall. Their quantification with flow-sensitive phase-contrast (PC) cardiovascular magnetic resonance (CMR), however, is time-consuming. Furthermore, the measurement of WSS requires high spatial resolution, whereas high temporal resolution is necessary for PWV measurements. For these reasons, PWV and WSS are challenging to measure in one CMR session, making it difficult to directly compare these parameters. By using a retrospective approach with a flexible reconstruction framework, we here aimed to simultaneously assess both PWV and WSS in the murine aortic arch from the same 4D flow measurement. Methods Flow was measured in the aortic arch of 18-week-old wildtype (n = 5) and ApoE−/− mice (n = 5) with a self-navigated radial 4D-PC-CMR sequence. Retrospective data analysis was used to reconstruct the same dataset either at low spatial and high temporal resolution (PWV analysis) or high spatial and low temporal resolution (WSS analysis). To assess WSS, the aortic lumen was labeled by semi-automatically segmenting the reconstruction with high spatial resolution. WSS was determined from the spatial velocity gradients at the lumen surface. For calculation of the PWV, segmentation data was interpolated along the temporal dimension. Subsequently, PWV was quantified from the through-plane flow data using the multiple-points transit-time method. Reconstructions with varying frame rates and spatial resolutions were performed to investigate the influence of spatiotemporal resolution on the PWV and WSS quantification. Results 4D flow measurements were conducted in an acquisition time of only 35 min. Increased peak flow and peak WSS values and lower errors in PWV estimation were observed in the reconstructions with high temporal resolution. Aortic PWV was significantly increased in ApoE−/− mice compared to the control group (1.7 ± 0.2 versus 2.6 ± 0.2 m/s, p < 0.001). Mean WSS magnitude values averaged over the aortic arch were (1.17 ± 0.07) N/m2 in wildtype mice and (1.27 ± 0.10) N/m2 in ApoE−/− mice. Conclusion The post processing algorithm using the flexible reconstruction framework developed in this study permitted quantification of global PWV and 3D-WSS in a single acquisition. The possibility to assess both parameters in only 35 min will markedly improve the analyses and information content of in vivo measurements.


2020 ◽  
Vol 38 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Gilles Soulat ◽  
Umit Gencer ◽  
Nadjia Kachenoura ◽  
Olivier Villemain ◽  
Emmanuel Messas ◽  
...  

2013 ◽  
Vol 39 (4) ◽  
pp. 819-826 ◽  
Author(s):  
Benjamin R. Landgraf ◽  
Kevin M. Johnson ◽  
Alejandro Roldán-Alzate ◽  
Christopher J. Francois ◽  
Oliver Wieben ◽  
...  

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