Top

Neuroradiology

Published in:

01-10-2021 | CT Angiography | Diagnostic Neuroradiology

Semiautomated carotid artery plaque composition: are intraplaque CT imaging features associated with cardiovascular risk factors?

Authors: John C. Benson, Giuseppe Lanzino, Valentina Nardi, Luis Savastano, Amir Lerman, Waleed Brinjikji

Published in: Neuroradiology | Issue 10/2021

Abstract

Background

Little remains known about the connection between cardiovascular (CV) risk factors and carotid plaque morphologies. This study set out to assess for any such associations.

Materials and methods

A retrospective review was completed of consecutive patients that had CTA neck imaging prior to CEA. Body mass index (BMI), tobacco and/or alcohol use, and history of diabetes and/or hypertension were collected from patients’ medical records. Lab values were dichotomized based on values: total cholesterol < 200 or ≥ 200; low-density lipoprotein (LDL) < 130 or ≥ 130, high-density lipoprotein < 35 or ≥ 35, and triglycerides < 200 or ≥ 200. A semiautomated analysis of CTA images computed maximum stenosis, intraplaque volumes of intraplaque hemorrhage, lipid-rich necrotic core (LRNC), and matrix, and intraplaque volume and proportional plaque makeup of calcifications of each carotid plaque.

Results

Of 87 included patients, 54 (62.1%) were male. Mean age was 70.1 years old. Both diabetes and hypertension were associated with greater intraplaque calcification volume (p = 0.0009 and p = 0.01, respectively), and greater proportion of calcification within a plaque (p = 0.004 and p = 0.01, respectively). Higher BMI was associated with greater intraplaque volume of LRNC (p=0.02) and matrix (0.0007). Elevated total cholesterol was associated with both larger intraplaque calcification volume (p = 0.04) and greater proportion of calcification within a plaque (p = 0.01); elevated LDL was associated with greater intraplaque calcification volume (p = 0.005).

Conclusion

Multiple CV risk factors are associated with morphological differences in carotid artery plaques. Dysregulation of both total cholesterol and LDL and higher BMI are associated with higher volumes of intraplaque LRNC, a marker of plaque vulnerability.

Brinjikji W, Huston J, Rabinstein AA, Kim G-M, Lerman A, Lanzino G (2016) Contemporary carotid imaging: from degree of stenosis to plaque vulnerability. J Neurosurg 124(1):27–42. https://doi.org/10.3171/2015.1.JNS142452CrossRefPubMed

Trelles M, Eberhardt KM, Buchholz M, Schindler A, Bayer-Karpinska A, Dichgans M, Reiser MF, Nikolaou K, Saam T (2013) CTA for screening of complicated atherosclerotic carotid plaque--American Heart Association type VI lesions as defined by MRI. AJNR Am J Neuroradiol 34(12):2331–2337. https://doi.org/10.3174/ajnr.A3607CrossRefPubMedPubMedCentral

Rafailidis V, Chryssogonidis I, Tegos T, Kouskouras K, Charitanti-Kouridou A (2017) Imaging of the ulcerated carotid atherosclerotic plaque: a review of the literature. Insights Imaging 8(2):213–225. https://doi.org/10.1007/s13244-017-0543-8CrossRefPubMedPubMedCentral

Gupta A, Baradaran H, Mtui EE, Kamel H, Pandya A, Giambrone A, Iadecola C, Sanelli PC (2015) Detection of Symptomatic Carotid Plaque Using Source Data from MR and CT Angiography: A Correlative Study. Cerebrovasc Dis Basel Switz 39(3-4):151–161. https://doi.org/10.1159/000373918CrossRef

Wagenknecht L, Wasserman B, Chambless L, Coresh J, Folsom A, Mosley T, Ballantyne C, Sharrett R, Boerwinkle E (2009) Correlates of carotid plaque presence and composition as measured by MRI: the Atherosclerosis Risk in Communities Study. Circ Cardiovasc Imaging 2(4):314–322. https://doi.org/10.1161/CIRCIMAGING.108.823922CrossRefPubMedPubMedCentral

Wasserman BA, Sharrett AR, Lai S, Gomes AS, Cushman M, Folsom AR, Bild DE, Kronmal RA, Sinha S, Bluemke DA (2008) Risk factor associations with the presence of a lipid core in carotid plaque of asymptomatic individuals using high-resolution MRI: the multi-ethnic study of atherosclerosis (MESA). Stroke. 39(2):329–335. https://doi.org/10.1161/STROKEAHA.107.498634CrossRefPubMed

Saba L, Micheletti G, Brinjikji W, Garofalo P, Montisci R, Balestrieri A, Suri JS, DeMarco JK, Lanzino G, Sanfilippo R (2019) Carotid Intraplaque-Hemorrhage Volume and Its Association with Cerebrovascular Events. AJNR Am J Neuroradiol 40(10):1731–1737. https://doi.org/10.3174/ajnr.A6189CrossRefPubMedPubMedCentral

Yahagi K, Kolodgie FD, Lutter C, Mori H, Romero ME, Finn AV, Virmani R (2017) Pathology of human coronary and carotid artery atherosclerosis and vascular calcification in diabetes mellitus. Arterioscler Thromb Vasc Biol 37(2):191–204. https://doi.org/10.1161/ATVBAHA.116.306256CrossRefPubMed

Wong KK, Thavornpattanapong P, Cheung SC, Sun Z, Tu J (2012) Effect of calcification on the mechanical stability of plaque based on a three-dimensional carotid bifurcation model. BMC Cardiovasc Disord 12(1):7. https://doi.org/10.1186/1471-2261-12-7CrossRefPubMedPubMedCentral

10.

Shaalan WE, Cheng H, Gewertz B, McKinsey JF, Schwartz LB, Katz D, Cao D, Desai T, Glagov S, Bassiouny HS (2004) Degree of carotid plaque calcification in relation to symptomatic outcome and plaque inflammation. J Vasc Surg 40(2):262–269. https://doi.org/10.1016/j.jvs.2004.04.025CrossRefPubMed

11.

Uwatoko T, Toyoda K, Inoue T, Yasumori K, Hirai Y, Makihara N, Fujimoto S, Ibayashi S, Iida M, Okada Y (2007) Carotid artery calcification on multislice detector-row computed tomography. Cerebrovasc Dis Basel Switz 24(1):20–26. https://doi.org/10.1159/000103112CrossRef

12.

Hill MD (2014) Stroke and diabetes mellitus. Handb Clin Neurol 126:167–174. https://doi.org/10.1016/B978-0-444-53480-4.00012-6CrossRefPubMed

13.

van den Bouwhuijsen QJA, Vernooij MW, Hofman A, Krestin GP, van der Lugt A, Witteman JCM (2012) Determinants of magnetic resonance imaging detected carotid plaque components: the Rotterdam Study. Eur Heart J 33(2):221–229. https://doi.org/10.1093/eurheartj/ehr227CrossRefPubMed

14.

Rozie S, de Weert TT, de Monyé C, Homburg PJ, Tanghe HLJ, Dippel DWJ, van der Lugt A (2009) Atherosclerotic plaque volume and composition in symptomatic carotid arteries assessed with multidetector CT angiography; relationship with severity of stenosis and cardiovascular risk factors. Eur Radiol 19(9):2294–2301. https://doi.org/10.1007/s00330-009-1394-6CrossRefPubMedPubMedCentral

15.

Vukadinovic D, Rozie S, van Gils M, van Walsum T, Manniesing R, van der Lugt A, Niessen WJ (2012) Automated versus manual segmentation of atherosclerotic carotid plaque volume and components in CTA: associations with cardiovascular risk factors. Int J Card Imaging 28(4):877–887. https://doi.org/10.1007/s10554-011-9890-6CrossRef

16.

Adraktas DD, Tong E, Furtado AD, Cheng S-C, Wintermark M (2014) Evolution of CT imaging features of carotid atherosclerotic plaques in a 1-year prospective cohort study. J Neuroimaging Off J Am Soc Neuroimaging 24(1):1–6. https://doi.org/10.1111/j.1552-6569.2012.00705.xCrossRef

17.

Zhu G, Li Y, Ding V, Jiang B, Ball RL, Rodriguez F, Fleischmann D, Desai M, Saloner D, Gupta A, Saba L, Hom J, Wintermark M Semiautomated Characterization of Carotid Artery Plaque Features From Computed Tomography Angiography to Predict Atherosclerotic Cardiovascular Disease Risk Score. J Comput Assist Tomogr. Published online May 6, 2019. https://doi.org/10.1097/RCT.0000000000000862

18.

Ajay G, Hediyeh B, Hooman K et al (2014) Evaluation of computed tomography angiography plaque thickness measurements in high-grade carotid artery stenosis. Stroke. 45(3):740–745. https://doi.org/10.1161/STROKEAHA.113.003882CrossRef

19.

Baradaran H, Al-Dasuqi K, Knight-Greenfield A et al Association between carotid plaque features on CTA and cerebrovascular ischemia: a systematic review and meta-analysis. Am J Neuroradiol. Published online October 26, 2017. https://doi.org/10.3174/ajnr.A5436

20.

Wintermark M, Jawadi SS, Rapp JH, Tihan T, Tong E, Glidden DV, Abedin S, Schaeffer S, Acevedo-Bolton G, Boudignon B, Orwoll B, Pan X, Saloner D (2008) High-resolution CT imaging of carotid artery atherosclerotic plaques. Am J Neuroradiol 29(5):875–882. https://doi.org/10.3174/ajnr.A0950CrossRefPubMedPubMedCentral

21.

de Weert TT, Ouhlous M, Meijering E, Zondervan PE, Hendriks JM, van Sambeek MRHM, Dippel DWJ, van der Lugt A (2006) In vivo characterization and quantification of atherosclerotic carotid plaque components with multidetector computed tomography and histopathological correlation. Arterioscler Thromb Vasc Biol 26(10):2366–2372. https://doi.org/10.1161/01.ATV.0000240518.90124.57CrossRefPubMed

22.

Chrencik MT, Khan AA, Luther L, Anthony L, Yokemick J, Patel J, Sorkin JD, Sikdar S, Lal BK (2019) Quantitative assessment of carotid plaque morphology (geometry and tissue composition) using computed tomography angiography. J Vasc Surg 70(3):858–868. https://doi.org/10.1016/j.jvs.2018.11.050CrossRefPubMedPubMedCentral

23.

Sheahan M, Ma X, Paik D, Obuchowski NA, St. Pierre S, Newman WP III, Rae G, Perlman ES, Rosol M, Keith JC Jr, Buckler AJ (2018) Atherosclerotic plaque tissue: noninvasive quantitative assessment of characteristics with software-aided measurements from conventional CT angiography. Radiology. 286(2):622–631. https://doi.org/10.1148/radiol.2017170127CrossRefPubMed

Title: Semiautomated carotid artery plaque composition: are intraplaque CT imaging features associated with cardiovascular risk factors?
Authors: John C. Benson
Giuseppe Lanzino
Valentina Nardi
Luis Savastano
Amir Lerman
Waleed Brinjikji
Publication date: 01-10-2021
Publisher: Springer Berlin Heidelberg
Keyword: CT Angiography
Published in: Neuroradiology / Issue 10/2021
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-021-02662-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Semiautomated carotid artery plaque composition: are intraplaque CT imaging features associated with cardiovascular risk factors?

Abstract

Background

Materials and methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Materials and methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 10/2021

A 10-year longitudinal study of deep white matter lesions on magnetic resonance imaging

Distinct pattern of microsusceptibility changes on brain magnetic resonance imaging (MRI) in critically ill patients on mechanical ventilation/oxygenation

The topology of ventricle surfaces and its application in the analysis of hydrocephalic ventricles: a proof-of-concept study

MR vessel wall imaging in tubercular meningitis

The diagnostic contribution of intracranial vessel wall imaging in the differentiation of primary angiitis of the central nervous system from other intracranial vasculopathies

Impaired intrinsic functional connectivity among medial temporal lobe and sub-regions related to memory deficits in intracranial dural arteriovenous fistula