Color‑coded duplex sonography vs. 3.0 Tesla magnetic resonance angiography for detection of intracranial stenosis of the internal carotid artery: A prospective cohort study

Xiao,Lu; Chu,Wen; Wang,Hua

doi:10.3892/etm.2019.8255

Color‑coded duplex sonography vs. 3.0 Tesla magnetic resonance angiography for detection of intracranial stenosis of the internal carotid artery: A prospective cohort study

Authors:
- Lu Xiao
- Wen Chu
- Hua Wang
View Affiliations

Affiliations: Department of Ultrasound, Luoyang Central Hospital Affiliated to Zhengzhou University, Luoyang, Henan 471000, P.R. China
Published online on: November 29, 2019 https://doi.org/10.3892/etm.2019.8255
Pages: 473-480
Copyright: © Xiao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Hemodynamic changes may provide important information for clinical decision‑making in internal carotid artery (ICA) stenosis. The degree of stenosis is responsible for the hemodynamic changes. For detection of intracranial stenosis, each diagnostic method has its own advantages and disadvantages. The goal of the present study was to compare the sensitivity and accuracy of color‑coded duplex sonography with that of magnetic resonance angiography (MRA) for the detection of intracranial stenosis. Patients with 3 vessels and/or left stem coronary artery disease were subjected to transcranial and extracranial color‑coded duplex sonography (n=998), MRA (n=998) and invasive catheter angiography (n=939). The degree of stenosis was defined according to the Warfarin‑Aspirin Symptomatic Intracranial Disease methodology. A ≥50% reduction in artery diameter was considered as a positive obstructive lesion. The benefits of each imaging method were assessed by clinical decision‑making analysis. Color‑coded duplex sonography and MRA, had sensitivities of 0.935 and 0.957 and accuracies of 0.92 and 0.974, respectively, when using invasive catheter angiography as a gold standard. The number of false‑positive obstructive lesions detected by MRA was significantly higher than that for color‑coded duplex sonography (53 vs. 13, P<0.0001). Color‑coded duplex sonography was able to detect an obstructive lesion in one single image for ICAs with ≥57% stenosis, while MRA was only capable of detecting an obstructive lesion in one single image for ICAs with ≥80% stenosis. In conclusion, color‑coded duplex sonography is a reliable method for the detection of intracranial stenosis in patients with coronary artery disease.

View Figures

View References

1	Valaikiene J, Ryliskyte L, Valaika A, Puronaite R, Dementaviciene J, Vaitkevicius A, Badariene J, Butkuviene I, Kalinauskas G and Laucevicius A: A high prevalence of intracranial stenosis in patients with coronary artery disease and the diagnostic value of transcranial duplex sonography. J Stroke Cerebrovasc Dis. 28:1015–1021. 2019. View Article : Google Scholar : PubMed/NCBI
2	Bos D, van der Rijk MJ, Geeraedts TE, Hofman A, Krestin GP, Witteman JC, van der Lugt A, Ikram MA and Vernooij MW: Intracranial carotid artery atherosclerosis: Prevalence and risk factors in the general population. Stroke. 43:1878–1884. 2012. View Article : Google Scholar : PubMed/NCBI
3	Jin H, Peng Q, Nan D, Lv P, Liu R, Sun W, Teng Y, Liu Y, Fan C, Xing H, et al: Prevalence and risk factors of intracranial and extracranial artery stenosis in asymptomatic rural residents of 13 villages in China. BMC Neurol. 17:1362017. View Article : Google Scholar : PubMed/NCBI
4	Mazighi M, Labreuche J, Gongora-Rivera F, Duyckaerts C, Hauw JJ and Amarenco P: Autopsy prevalence of intracranial atherosclerosis in patients with fatal stroke. Stroke. 39:1142–1147. 2008. View Article : Google Scholar : PubMed/NCBI
5	Valaikiene J, Schuierer G, Ziemus B, Dietrich J, Bogdahn U and Schlachetzki F: Transcranial color-coded duplex sonography for detection of distal internal carotid artery stenosis. Am J Neuroradiol. 29:347–353. 2008. View Article : Google Scholar : PubMed/NCBI
6	Baradaran H, Patel P, Gialdini G, Al-Dasuqi K, Giambrone A, Kamel H and Gupta A: Quantifying intracranial internal carotid artery stenosis on MR Angiography. Am J Neuroradiol. 38:986–990. 2017. View Article : Google Scholar : PubMed/NCBI
7	Chen J, Zhao B, Bu C and Xie G: Relationship between the hemodynamic changes on multi-Td pulsed arterial spin labeling images and the degrees of cerebral artery stenosis. Magn Reson Imaging. 32:1277–1283. 2014. View Article : Google Scholar : PubMed/NCBI
8	Pu Y, Liu L and Wang Y, Zou X, Pan Y, Soo Y, Leung T, Zhao X, Wong KS and Wang Y; Chinese IntraCranial AtheroSclerosis (CICAS) Study Group, : Geographic and sex difference in the distribution of intracranial atherosclerosis in China. Stroke. 44:2109–2114. 2013. View Article : Google Scholar : PubMed/NCBI
9	Liebeskind DS, Kosinski AS, Saver JL and Feldmann E; SONIA Investigators, : Computed tomography angiography in the stroke outcomes and neuroimaging of intracranial atherosclerosis (SONIA) study. Interv Neurol. 2:153–159. 2014. View Article : Google Scholar : PubMed/NCBI
10	Duffis EJ, Jethwa P, Gupta G, Bonello K, Gandhi CD and Prestigiacomo CJ: Accuracy of computed tomographic angiography compared to digital subtraction angiography in the diagnosis of intracranial stenosis and its impact on clinical decision-making. J Stroke Cerebrovasc Dis. 22:1013–1017. 2013. View Article : Google Scholar : PubMed/NCBI
11	Ryoo S, Lee MJ, Cha J, Jeon P and Bang OY: Differential vascular pathophysiologic types of intracranial atherosclerotic stroke: A high-resolution wall magnetic resonance imaging study. Stroke. 46:2815–2821. 2015. View Article : Google Scholar : PubMed/NCBI
12	Liu Q, Huang J, Degnan AJ, Chen S, Gillard JH, Teng Z and Lu J: Comparison of high-resolution MRI with CT angiography and digital subtraction angiography for the evaluation of middle cerebral artery atherosclerotic steno-occlusive disease. Int J Cardiovasc Imaging. 29:1491–1498. 2013. View Article : Google Scholar : PubMed/NCBI
13	Kochar M and Min JK: Physiologic assessment of coronary artery disease by cardiac computed tomography. Korean Circ J. 43:435–442. 2013. View Article : Google Scholar : PubMed/NCBI
14	Fitzgerald M, Saville BR and Lewis RJ: Decision curve analysis. JAMA. 13:409–410. 2015. View Article : Google Scholar
15	Bash S, Villablanca JP, Jahan R, Duckwiler G, Tillis M, Kidwell C, Saver J and Sayre J: Intracranial vascular stenosis and occlusive disease: Evaluation with CT angiography, MR angiography, and digital subtraction angiography. Am J Neuroradiol. 26:1012–1021. 2005.PubMed/NCBI
16	Ahn SH, Lee J, Kim YJ, Kwon SU, Lee D, Jung SC, Kang DW and Kim JS: Isolated MCA disease in patients without significant atherosclerotic risk factors: A high-resolution magnetic resonance imaging study. Stroke. 46:697–703. 2015. View Article : Google Scholar : PubMed/NCBI
17	Hirooka R, Ogasawara K, Inoue T, Fujiwara S, Sasaki M, Chida K, Ishigaki D, Kobayashi M, Nishimoto H, Otawara Y, et al: Simple assessment of cerebral hemodynamics using single-slab 3D time-of-flight MR angiography in patients with cervical internal carotid artery steno-occlusive diseases: Comparison with quantitative perfusion single-photon emission CT. AJNR Am J Neuroradiol. 30:559–563. 2009. View Article : Google Scholar : PubMed/NCBI
18	Cho YD, Lee JY, Kwon BJ, Kang HS and Han MH: False-positive diagnosis of cerebral aneurysms using MR angiography: Location, anatomic cause, and added value of source image data. Clin Radiol. 66:726–731. 2011. View Article : Google Scholar : PubMed/NCBI
19	Park S, Lee DH, Ryu C-W, Pyun HW, Choi CG, Kim SJ and Suh DC: Incidental saccular aneurysms on head MR angiography: 5 years' experience at a single large-volume center. J Stroke. 16:189–194. 2014. View Article : Google Scholar : PubMed/NCBI
20	Lee JD, Ryu SJ, Chang YJ, Hsu KC, Chen YC, Huang YC, Lee M, Hsiao MC and Lee TH: Carotid ultrasound criteria for detecting intracranial carotid stenosis. Eur Neurol. 57:156–160. 2007. View Article : Google Scholar : PubMed/NCBI