Carotid Plaque Phenotyping by Correlating Plaque Morphology from Computed Tomography Angiography with Transcriptional Profiling

Andrew Buckler,Ljubica P Matic,Eva Karlöf,Moritz L Liljeqvist,Lars Maegdefessel,Mawaddah A Toonsi,Malin Kronqvist,Mariette Lengquist,Ulf Hedin

doi:10.1016/j.ejvs.2021.07.011

Abstract

<h3>Objective</h3> Ischaemic strokes can be caused by unstable carotid atherosclerosis, but methods for identification of high risk lesions are lacking. Carotid plaque morphology imaging using software for visualisation of plaque components in computed tomography angiography (CTA) may improve assessment of plaque phenotype and stroke risk, but it is unknown if such analyses also reflect the biological processes related to lesion stability. Here, we investigated how carotid plaque morphology by image analysis of CTA is associated with biological processes assessed by transcriptomic analyses of corresponding carotid endarterectomies (CEAs). <h3>Methods</h3> Carotid plaque morphology was assessed in patients undergoing CEA for symptomatic or asymptomatic carotid stenosis consecutively enrolled between 2006 and 2015. Computer based analyses of pre-operative CTA was performed to define calcification, lipid rich necrotic core (LRNC), intraplaque haemorrhage (IPH), matrix (MATX), and plaque burden. Plaque morphology was correlated with molecular profiles obtained from microarrays of corresponding CEAs and models were built to assess the ability of plaque morphology to predict symptomatology. <h3>Results</h3> Carotid plaques (<i>n</i> = 93) from symptomatic patients (<i>n</i> = 61) had significantly higher plaque burden and LRNC compared with plaques from asymptomatic patients (<i>n</i> = 32). Lesions selected from the transcriptomic cohort (<i>n</i> = 40) with high LRNC, IPH, MATX, or plaque burden were characterised by molecular signatures coupled with inflammation and extracellular matrix degradation, typically linked with instability. In contrast, highly calcified plaques had a molecular signature signifying stability with enrichment of profibrotic pathways and repressed inflammation. In a cross validated prediction model for symptoms, plaque morphology by CTA alone was superior to the degree of stenosis. <h3>Conclusion</h3> The study demonstrates that CTA image analysis for evaluation of carotid plaque morphology, also reflects prevalent biological processes relevant for assessment of plaque phenotype. The results support the use of CTA image analysis of plaque morphology for risk stratification and management of patients with carotid stenosis.

Highlights

Unstable atherosclerotic plaques in the carotid bifurcation contribute to ischaemic strokes but methods to identify lesions at high risk are lacking.[1]
Comparison between computed tomography angiography (CTA) image analysis and histological analysis of corresponding carotid endarterectomy (CEA) specimens showed concordance between plaque morphology and histology, confirming previous validation of the software,[8,10,11] with accurate visualisation of plaque components obtained from software analysed CTA images (Fig. 1)
To investigate whether carotid plaque features by CTA represented relevant biological processes, plaque morphology was correlated with gene expression obtained from global genome microarrays

Summary

Introduction

Unstable atherosclerotic plaques in the carotid bifurcation contribute to ischaemic strokes but methods to identify lesions at high risk are lacking.[1]. Measurements of stenosis and stroke preventive treatment, carotid endarterectomy (CEA), restricted to patients with high degree stenosis,[2] resulting in moderate procedural efficacy.[3] Non-invasive imaging to characterise carotid plaque morphology holds promise for improved risk prediction based on plaque biology, rather than the degree of stenosis,[1,4] and the recent European Society for Vascular Surgery guidelines advocate the assessment of additional plaque parameters in high risk asymptomatic patients.[2] Establishing an association between plaque morphology and biological processes relevant for plaque instability would support implementation of carotid plaque imaging for improved patient management. These limitations can be mitigated with CTA post-processing using analytical software that improves characterisation of plaque morphology.8e13

Methods

Results

Conclusion