ECR 2013 / C-2592
Characterisation of Neovascularization in Carotid plaque
Congress: ECR 2013
Poster No.: C-2592
Type: Educational Exhibit
Keywords: Haemorrhage, Blood, Biological effects, Imaging sequences, Contrast agent-intravenous, Ultrasound, MR, Vascular, Contrast agents, Arteries / Aorta
Authors: W. Abutaleb, M. J. Graves, J. H. Gillard; Cambridge/UK
DOI:10.1594/ecr2013/C-2592

Imaging findings OR Procedure details

In the background section, I have discussed the formation of neovascularisation within Carotid Plaques, its risk and the diagnostic management. In what follows, I present a novel study of combined non-invasive, non-ionizing radiation methods to detect the neovascularisation. These are dynamic contrast enhanced MRI (DCMR) and dynamic contrast enhanced ultrasound (DCUS) correlated with histopathology when applicable.

 

DCMRI method:

We are using a 1.5 tesla MRI machine.

Dedicated surface coil, used for better resolution.

Pre and post contrast multi phases Spoiled Gradient Echo sequences obtained

To analyse the data, Kinetic modelling of gadolinium uptake will be calculated. It's represented by the result of blood supply vessel surface area and permeability represented by transfer constant (Ktrans value) and the simpler value fractional plasma volume Vp – correlated with microvessel density (Fig. 6).

 

DCUS method:

B-mode and/or Doppler used to indicate the area of interest, where the highest level of stenosis preferring soft plaques if there are multiple plaques.

Contrast harmonic imaging was used to register the perfusion of bubble ultrasound for ~3 minutes. To analyse the data, for each case I'm measuring the intensity versus the time for the region of interest and a control region in the lumen (Fig. 7).

 

Recruitment challenges:

At this stage of the project, ultrasound modality proofed being more recruiting friendly than MRI. The ultrasound to MRI recruitment ratio is 10:7. However, the study is still under progress, and the challenges of analysing the ultrasound data seem higher than analysing the MRI.

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