Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
JCR Impact Factor (IF) – 2.1
5-Year Impact Factor – 2.2
Scopus CiteScore – 3.4 (CiteScore Tracker 3.7)
Index Copernicus  – 161.11; MNiSW – 70 pts

ISSN 1899–5276 (print)
ISSN 2451-2680 (online)
Periodicity – monthly

Download original text (EN)

Advances in Clinical and Experimental Medicine

2017, vol. 26, nr 1, January-February, p. 123–128

doi: 10.17219/acem/66365

Publication type: original article

Language: English

Download citation:

  • BIBTEX (JabRef, Mendeley)
  • RIS (Papers, Reference Manager, RefWorks, Zotero)

An evaluation of dual source computed tomography used with the de Weert classification to detect vulnerable plaque, using IVUS virtual histology as a standard of reference

Bartosz Dołęga-Kozierowski1,2,A,B,C,E,F, Piotr Klimeczek2,3,A,B,C,E,F, Michał Lis2,4,B,C,E, Róża Krycińska2,3,C,D, Anna Chrapusta4,E, Urszula Zaleska-Dorobisz5,F, Jerzy Garcarek5,F, Wojciech Witkiewicz6,F

1 Radiology Department, Regional Specialized Hospital, Wrocław, Poland

2 WroVasc Integrated Cardiovascular Centre, Wrocław, Poland

3 Radiology Department, Rydygier Hospital, Kraków, Poland

4 Burn and Plastic Surgery Department, Rydygier Hospital, Kraków, Poland

5 Department of Radiology, Wroclaw Medical University, Poland

6 Vascular Surgery Department, Regional Specialized Hospital, Wrocław, Poland

Abstract

Background. One of the main risk factors for cerebral ischemic events is atherosclerotic disease of the internal carotid artery (ICA). Nowadays, increasing attention is being paid to the relationship between the morphological features of atherosclerotic plaque and the occurrence of stroke. Several studies have demonstrated that the presence of specific vulnerable plaque types, with a large lipid core and thin fibrous cap, can be used as an independent risk predictor of cerebral ischemic events.
Objectives. The present study is an attempt to develop the method of plaque surface morphology assessment presented by de Weert et al. by correlating the results of Dual Source Computed Tomography (DSCT) with those from intravascular ultrasound virtual histology (IVUS-VH).
Material and Methods. A group of 30 symptomatic patients (13 men and 17 women; 72 ± 9 years) with ICA stenosis suspected on the basis of ultrasound imaging (US) and confirmed to be above 70% in DSCT underwent intravascular ultrasound (IVUS) imaging.
Results. The results of DSCT were categorized according to the de Weert classification. There were 13 cases (43%) with smooth wall surfaces, 10 cases (33%) with discreet wall irregularities, and seven cases (23%) with incursions of contrast, indicating the presence of ulceration. In the IVUS-VH examinations, 4 out of 30 cases (13%) were identified as having adaptive intimal thickening (AIT), 4 (13%) as showing pathological intimal thickening (PIT), 6 (20%) with fibroatheromas (FA), six (20%) with fibrocalcific plaque (FCa), and 10 (33%) as having thin-cap fibroatheroma (TCFA), which is high-risk plaque. Comparing the above results showed that all the patients with confirmed wall ulceration in DSCT were characterized as having high-risk plaque in IVUS-VH.
Conclusion. Using DSCT with the de Weert classification of plaque surface morphology makes reliable detection of ulcerations possible; therefore, this could become a significant new technique to improve current imaging protocols for patients with a high risk of ischemic cerebrovascular events.

Key words

atherosclerosis, ischemic stroke, IVUS, DSCT, ICA stenosis

References (31)

  1. Mozaffarian D, et al. Executive summary: Heart disease and stroke statistics-2016 update: A report from the American Heart Associa-tion. Circulation. 2016;133: 447–454.
  2. Rothwell PM, Eliasziw M, Gutnikov SA, et al. Analysis of pooled data from the randomized controlled trials of endarterectomy for symptomatic carotid stenosis. Lancet. 2003;11:107–116.
  3. North American Symptomatic Carotid Endarterectomy Trial Collaborators. Beneficial effect of carotid endarterectomy in sympto-matic patients high with grade stenosis: N Engl J Med. 1991; 15:445–453.
  4. European Carotid Surgery Trialists’ Collaborative Group MRC European Carotid Surgery Trial: Interim results for symptomatic patients with severe (70%–99%) or with mild (0%–29%) carotid stenosis. Lancet. 1991;25:1235–1243.
  5. Narula J, Nakano M, Virmani R, et al. Histopathologic characteristics of atherosclerotic coronary disease and implications of the find-ings for the invasive and noninvasive detection of vulnerable plaques. J Am Coll Cardiol. 2013;12:1041–1051.
  6. Naghavi M, Libby P, Falk E, et al. From vulnerable plaque to vulnerable patient: A call for new definitions and risk assessment strat-egies: Part I. Circulation. 2003;14:1772–1778.
  7. Gupta A, Baradaran H, Schweitzer AD, et al. Carotid plaque MRI and stroke risk: A systematic review and meta-analysis. Stroke. 2013;44:3071–3077.
  8. Howard DP, van Lammeren GW, Rothwell PM, et al. Symptomatic carotid atherosclerotic disease: Correlations between plaque com-position and ipsilateral stroke risk. Stroke 2015;46(1):182–189.
  9. Huibers A, de Borst GJ, Wan S, et al. Non-invasive carotid artery imaging to identify the vulnerable plaque: Current status and future goals. Eur J Vasc Endovasc Surg. 2015;50:563–572.
  10. Brinjikji W, Huston J, Rabinstein AA, Kim GM, Lerman A, Lanzino G. Contemporary carotid imaging: from degree of stenosis to plaque vulnerability. J Neurosurg. 2016;124(1):27–42.
  11. Truijman MT, Kooi ME, van Dijk AC, et al. Plaque at RISK (PARISK): Prospective multicenter study to improve diagnosis of high-risk carotid plaques. Int J Stroke. 2014; 9:747–754.
  12. de Weert TT, Cretier S, Groen HC, et al. Atherosclerotic plaque surface morphology in the carotid bifurcation assessed with multi-detector computed tomography angiography. Stroke. 2009;40(4): 1334–1340.
  13. Konig A, Margolis MP, Virmani R, Holmes D, Klauss V. Technology insight: In vivo coronary plaque classification by intravascular ul-trasonography radiofrequency analysis. Nat Clin Pract Cardiovasc Med. 2008;5(4):219–229.
  14. Anders Persson, Protocol Dual Energy Head and Neck CTA, Dual Source CT community http://www.dsct.com/index.php/protocol-dual-energy-head-and-neck-cta/ Published April 8, 2008, Accesed January 2, 2011.
  15. Lanzer P, Mastering endovascular techniques: A guide to excellence, Philadelphia 2006, 1st ed. Lippincott Williams & Wilkins, 85–86.
  16. Stary HC, Chandler AB, Dinsmore RE, et al. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Associa-tion. Circulation. 1995;1;92(5):1355–1374.
  17. Mintz GS, Painter JA, Pichard AD, et al. Atherosclerosis in angiographically “normal” coronary artery reference segments: an intrav-ascular ultrasound study with clinical correlations. J Am Coll Cardiol. 1995;25(7):1479–1485.
  18. Coutinho JM, Derkatch S, Potvin AR, et al. Nonstenotic carotid plaque on CT angiography in patients with cryptogenic stroke. Neu-rology. 2016;16:665–672.
  19. Rothwell PM, Gibson R, Warlow CP. Interrelation between plaque surface morphology and degree of stenosis on carotid angio-grams and the risk of ischemic stroke in patients with symptomatic carotid stenosis. On behalf of the European Carotid Surgery Trialists’ Collaborative Group. Stroke. Stroke. 2000;31(3):615–621.
  20. Park AE, McCarthy WJ, Pearce WH, Matsumura JS, Yao JS. Carotid plaque morphology correlates with presenting symptomatology. J Vasc Surg. 1998;27(5):872–878.
  21. Lovett JK, Gallagher PJ, Hands LJ, Walton J, Rothwell PM. Histological correlates of carotid plaque surface morphology on lumen contrast imaging. Circulation. 2004;12:2190–2197.
  22. Saba L, Caddeoc G, Sanfilippob R, Montiscib R, Mallarinia G. CT and ultrasound in the study of ulcerated carotid plaque compared with surgical results: Potentialities and advantages of multidetector row CT angiography. AJNR Am J Neuroradiol. 2007;28(6):1061–1066.
  23. Nasu K, Tsuchikane E, Katoh O, et al. Accuracy of in vivo coronary plaque morphology assessment: A validation study of in vivo virtual histology compared with in vitro histopathology. J Am Coll Cardiol. 2006;20:2405–2412.
  24. Nair A, Kuban BD, Tuzcu EM, Schoenhagen P, Nissen SE, Vince DG. Coronary plaque classification with intravascular ultrasound radio-frequency data analysis. Circulation. 2002;22:2200–2206.
  25. Springer I, Dewey M. Comparison of multislice computed tomography with intravascular ultrasound for detection and characteri-zation of coronary artery plaques: A systematic review. Eur J Radiol. 2009;71:275–282.
  26. Das M, Braunschweig T, Mühlenbruch G, et al. Carotid plaque analysis: Comparison of dualsource computed tomography (CT) fin-dings and histopathological correlation. Eur J Vasc Endovasc Surg. 2009;38(1):14–19.
  27. Flohr TG, McCollough CH, Bruder H et al. First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol. 2006;16(2):256–268.
  28. Kristanto W, van Ooijen PM, Jansenvan der Weide MC, Vliegenthart R, Oudkerk M. A meta analysis and hierarchical classification of HU-based atherosclerotic plaque characterization criteria. PLoS One. 2013;3:e73460.
  29. Wintermark M, Jawadi SS, Rapp JH, et al. High-resolution CT imaging of carotid artery atherosclerotic plaques. AJNR Am J Neuroradiol. 2008;29(5):875–882.
  30. Obaid DR, Calvert PA, Gopalan D, et al. Dual-energy computed tomography imaging to determine atherosclerotic plaque composi-tion: A prospective study with tissue validation. J Cardiovasc Comput Tomogr. 2014;8(3):230–237.
  31. Hetterich H, Webber N, Willner M, et al. AHA classification of coronary and carotid atherosclerotic plaques by grating-based pha-se-contrast computed tomography. Eur Radiol. 2016;26(9):3223–3233.