Skip to main content
Log in

Diagnostic performance of MRI for detecting intraplaque hemorrhage in the carotid arteries: a meta-analysis

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To investigate the diagnostic performance of MRI in diagnosing carotid atherosclerotic intraplaque hemorrhage (IPH) and to provide a clinical guide for MRI application.

Methods

We searched MEDLINE, Embase, and Cochrane library from the earliest available date of indexing through November 30, 2017. All investigators screened and selected studies comparing the use of MRI with histology. The accuracy to diagnose pathological IPH was expressed by sensitivity, specificity, negative likelihood ratios (LRs), positive LRs, and the area under summary receiver-operating characteristic (SROC) curve. We calculated the post-test probability to assess the clinical utility of MRI.

Results

We analyzed 696 patients from 20 articles. The sensitivity and specificity were 87% (95% CI, 81–91%) and 92% (95% CI, 87–95%), respectively. The positive and negative LRs were 10.27 (95% CI, 6.76–15.59) and 0.15 (95% CI, 0.10–0.21), respectively. The area under SROC curve was 0.95 (95% CI, 0.93–0.97). MRI was accurate in confirming or in ruling out disease over a wide range of pre-test probabilities of IPH: MRI could increase the post-test probability to > 80% in patients with a pre-test probability > 27% and could decrease the post-test probability to < 20% in patients with a pre-test probability < 64%.

Conclusion

Non-invasive MRI has excellent specificity and good sensitivity for diagnosing IPH. MRI is a tool for confirming or ruling out carotid atherosclerotic IPH.

Key Points

• Non-invasive MRI has excellent performance for diagnosing IPH, which is a component of vulnerable plaque.

• The high accuracy of MRI for IPH helps clinicians analyze the prognosis of clinical events and plan personalized treatment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

AUROC:

Area under receiver of operating characteristic

CE:

Contrast enhanced

CI:

Confidence interval

DTI:

Direct thrombus imaging

FFE:

Fast field echo

FSE:

Fast-spin echo

GRE:

Gradient recalled echo

IPH:

Intraplaque hemorrhage

LR:

Likelihood ratio

MRA:

MR angiography

MRI:

Magnetic resonance imaging

PDWI:

Proton density weighted imaging

QUADAS:

Quality Assessment of Diagnostic Accuracy Studies

RAGE:

Rapid acquisition gradient echo

SE:

Spin echo

SROC:

Summary receiver-operating characteristic

T1WI:

T1-weighted imaging

T2WI:

T2-weighted imaging

TFE:

Turbo field echo

TOF:

Time of flight

TSE:

Turbo spin echo

References

  1. Howard DP, van Lammeren GW, Rothwell PM et al (2015) Symptomatic carotid atherosclerotic disease: correlations between plaque composition and ipsilateral stroke risk. Stroke 46:182–189

    Article  PubMed  Google Scholar 

  2. Park JS, Kwak HS, Lee JM, Koh EJ, Chung GH, Hwang SB (2015) Association of carotid intraplaque hemorrhage and territorial acute infarction in patients with acute neurological symptoms using carotid magnetization-prepared rapid acquisition with gradient-echo. J Korean Neurosurg Soc 57:94–99

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Halliday A, Harrison M, Hayter E et al (2010) 10-year stroke prevention after successful carotid endarterectomy for asymptomatic stenosis (ACST-1): a multicentre randomised trial. Lancet 376:1074–1084

    Article  PubMed  PubMed Central  Google Scholar 

  4. Barnett HJM, Taylor DW, Haynes RB et al (1991) Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. N Engl J Med 325:445–453

    Article  CAS  PubMed  Google Scholar 

  5. Brinjikji W, Huston J 3rd, Rabinstein AA, Kim GM, Lerman A, Lanzino G (2016) Contemporary carotid imaging: from degree of stenosis to plaque vulnerability. J Neurosurg 124:27–42

    Article  CAS  PubMed  Google Scholar 

  6. Freilinger TM, Schindler A, Schmidt C et al (2012) Prevalence of nonstenosing, complicated atherosclerotic plaques in cryptogenic stroke. JACC Cardiovasc Imaging 5:397–405

    Article  PubMed  Google Scholar 

  7. Kolodgie FD, Yahagi K, Mori H et al (2017) High-risk carotid plaque: lessons learned from histopathology. Semin Vasc Surg 30:31–43

    Article  PubMed  Google Scholar 

  8. Zhao Q, Zhao X, Cai Z, Li F, Yuan C, Cai J (2011) Correlation of coronary plaque phenotype and carotid atherosclerotic plaque composition. Am J Med Sci 342:480–485

    Article  PubMed  Google Scholar 

  9. McNally JS, McLaughlin MS, Hinckley PJ et al (2015) Intraluminal thrombus, intraplaque hemorrhage, plaque thickness, and current smoking optimally predict carotid stroke. Stroke 46:84–90

    Article  PubMed  Google Scholar 

  10. Fisher M, Paganini-Hill A, Martin A et al (2005) Carotid plaque pathology: thrombosis, ulceration, and stroke pathogenesis. Stroke 36:253–257

    Article  PubMed  Google Scholar 

  11. Stary HC (2000) Natural history and histological classification of atherosclerotic lesions: an update. Arterioscler Thromb Vasc Biol 20:1177–1178

    Article  CAS  PubMed  Google Scholar 

  12. Ramnarine KV, Garrard JW, Kanber B, Nduwayo S, Hartshorne TC, Robinson TG (2014) Shear wave elastography imaging of carotid plaques: feasible, reproducible and of clinical potential. Cardiovasc Ultrasound 12:49

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kanber B, Hartshorne TC, Horsfield MA, Naylor AR, Robinson TG, Ramnarine KV (2015) A novel ultrasound-based carotid plaque risk index associated with the presence of cerebrovascular symptoms. Ultraschall Med 36:480–486

    CAS  PubMed  Google Scholar 

  14. Kwee RM, van Oostenbrugge RJ, Hofstra L et al (2008) Identifying vulnerable carotid plaques by noninvasive imaging. Neurology 70:2401–2409

    Article  CAS  PubMed  Google Scholar 

  15. Arai D, Yamaguchi S, Murakami M et al (2011) Characteristics of carotid plaque findings on ultrasonography and black blood magnetic resonance imaging in comparison with pathological findings. Acta Neurochir Suppl 112:15–19

    Article  PubMed  Google Scholar 

  16. Shimada Y, Oikawa K, Fujiwara S et al (2017) Comparison of three-dimensional T1-weighted magnetic resonance and contrast-enhanced ultrasound plaque images for severe stenosis of the cervical carotid artery. J Stroke Cerebrovasc Dis 26:1916–1922

    Article  PubMed  Google Scholar 

  17. Rafailidis V, Chryssogonidis I, Xerras C et al (2018) A comparative study of color Doppler imaging and contrast-enhanced ultrasound for the detection of ulceration in patients with carotid atherosclerotic disease. Eur Radiol. https://doi.org/10.1007/s00330-018-5773-8

  18. Yao B, Yang L, Wang G et al (2016) Diffusion measurement of intraplaque hemorrhage and intramural hematoma using diffusion weighted MRI at 3T in cervical artery. Eur Radiol 26:3737–3743

    Article  PubMed  Google Scholar 

  19. Chai JT, Biasiolli L, Li L et al (2016) Quantification of lipid-rich core in carotid atherosclerosis using magnetic resonance T2 mapping: relation to clinical presentation. JACC Cardiovasc Imaging 10:747–756

    Article  PubMed  Google Scholar 

  20. Narumi S, Sasaki M, Natori T et al (2015) Carotid plaque characterization using 3D T1-weighted MR imaging with histopathologic validation: a comparison with 2D technique. AJNR Am J Neuroradiol 36:751–756

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J (2003) The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 3:25

    Article  PubMed  PubMed Central  Google Scholar 

  22. Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58:882–893

    Article  PubMed  Google Scholar 

  23. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH (2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 58:982–990

    Article  PubMed  Google Scholar 

  24. Chu H, Cole SR (2006) Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach. J Clin Epidemiol 59:1331–1332 author reply 1332-1333

    Article  PubMed  Google Scholar 

  25. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327:557–560

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jaeschke R, Guyatt GH, Sackett DL (1994) Users’ guides to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? The Evidence-Based Medicine Working Group. JAMA 271:703–707

    Article  CAS  PubMed  Google Scholar 

  27. Lukanova DV, Nikolov NK, Genova KZ, Stankev MD, Georgieva EV (2015) The accuracy of noninvasive imaging techniques in diagnosis of carotid plaque morphology. Open Access Maced J Med Sci 3:224–230

    Article  PubMed  PubMed Central  Google Scholar 

  28. Millon A, Mathevet JL, Boussel L et al (2013) High-resolution magnetic resonance imaging of carotid atherosclerosis identifies vulnerable carotid plaques. J Vasc Surg 57:1046–1051.e2

    Article  PubMed  Google Scholar 

  29. Narumi S, Sasaki M, Ohba H et al (2013) Prediction of carotid plaque characteristics using non-gated MR imaging: correlation with endarterectomy specimens. AJNR Am J Neuroradiol 34:191–197

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Qiao Y, Etesami M, Malhotra S et al (2011) Identification of intraplaque hemorrhage on MR angiography images: a comparison of contrast-enhanced mask and time-of-flight techniques. AJNR Am J Neuroradiol 32:454–459

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Ota H, Yarnykh VL, Ferguson MS et al (2010) Carotid intraplaque hemorrhage imaging at 3.0-T MR imaging: comparison of the diagnostic performance of three T1-weighted sequences. Radiology 254:551–563

    Article  PubMed  PubMed Central  Google Scholar 

  32. Yim YJ, Choe YH, Ko Y et al (2008) High signal intensity halo around the carotid artery on maximum intensity projection images of time-of-flight MR angiography: a new sign for intraplaque hemorrhage. J Magn Reson Imaging 27:1341–1346

    Article  PubMed  Google Scholar 

  33. Watanabe Y, Nagayama M, Suga T et al (2008) Characterization of atherosclerotic plaque of carotid arteries with histopathological correlation: vascular wall MR imaging vs. color Doppler ultrasonography (US). J Magn Reson Imaging 28:478–485

    Article  PubMed  Google Scholar 

  34. Bitar R, Moody AR, Leung G et al (2008) In vivo 3D high-spatial-resolution MR imaging of intraplaque hemorrhage. Radiology 249:259–267

    Article  PubMed  Google Scholar 

  35. Esposito L, Sievers M, Sander D et al (2007) Detection of unstable carotid artery stenosis using MRI. J Neurol 254:1714–1722

    Article  CAS  PubMed  Google Scholar 

  36. Puppini G, Furlan F, Cirota N et al (2006) Characterisation of carotid atherosclerotic plaque: comparison between magnetic resonance imaging and histology. Radiol Med 111:921–930

    Article  CAS  PubMed  Google Scholar 

  37. Honda M, Kitagawa N, Tsutsumi K, Nagata I, Morikawa M, Hayashi T (2006) High-resolution magnetic resonance imaging for detection of carotid plaques. Neurosurgery 58:338–346 discussion 338-346

    Article  PubMed  Google Scholar 

  38. Clarke SE, Beletsky V, Hammond RR, Hegele RA, Rutt BK (2006) Validation of automatically classified magnetic resonance images for carotid plaque compositional analysis. Stroke 37:93–97

    Article  PubMed  Google Scholar 

  39. Saam T, Ferguson MS, Yarnykh VL et al (2005) Quantitative evaluation of carotid plaque composition by in vivo MRI. Arterioscler Thromb Vasc Biol 25:234–239

    Article  CAS  PubMed  Google Scholar 

  40. Kampschulte A, Ferguson MS, Kerwin WS et al (2004) Differentiation of intraplaque versus juxtaluminal hemorrhage/thrombus in advanced human carotid atherosclerotic lesions by in vivo magnetic resonance imaging. Circulation 110:3239–3244

    Article  CAS  PubMed  Google Scholar 

  41. Chu B, Kampschulte A, Ferguson MS et al (2004) Hemorrhage in the atherosclerotic carotid plaque: a high-resolution MRI study. Stroke 35:1079–1084

    Article  PubMed  Google Scholar 

  42. Cappendijk VC, Cleutjens KB, Heeneman S et al (2004) In vivo detection of hemorrhage in human atherosclerotic plaques with magnetic resonance imaging. J Magn Reson Imaging 20:105–110

    Article  PubMed  Google Scholar 

  43. Moody AR, Murphy RE, Morgan PS et al (2003) Characterization of complicated carotid plaque with magnetic resonance direct thrombus imaging in patients with cerebral ischemia. Circulation 107:3047–3052

    Article  PubMed  Google Scholar 

  44. Cai JM, Hatsukami TS, Ferguson MS, Small R, Polissar NL, Yuan C (2002) Classification of human carotid atherosclerotic lesions with in vivo multicontrast magnetic resonance imaging. Circulation 106:1368–1373

    Article  PubMed  Google Scholar 

  45. Wang X, Sun J, Zhao X et al (2017) Ipsilateral plaques display higher T1 signals than contralateral plaques in recently symptomatic patients with bilateral carotid intraplaque hemorrhage. Atherosclerosis 257:78–85

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sun J, Underhill HR, Hippe DS, Xue Y, Yuan C, Hatsukami TS (2012) Sustained acceleration in carotid atherosclerotic plaque progression with intraplaque hemorrhage: a long-term time course study. JACC Cardiovasc Imaging 5:798–804

    Article  PubMed  PubMed Central  Google Scholar 

  47. Raman SV, Winner MW 3rd, Tran T et al (2008) In vivo atherosclerotic plaque characterization using magnetic susceptibility distinguishes symptom-producing plaques. JACC Cardiovasc Imaging 1:49–57

    Article  PubMed  PubMed Central  Google Scholar 

  48. Saam T, Hetterich H, Hoffmann V et al (2013) Meta-analysis and systematic review of the predictive value of carotid plaque hemorrhage on cerebrovascular events by magnetic resonance imaging. J Am Coll Cardiol 62:1081–1091

    Article  PubMed  Google Scholar 

  49. Li D, Zhao H, Chen X et al (2018) Identification of intraplaque haemorrhage in carotid artery by simultaneous non-contrast angiography and intraPlaque haemorrhage (SNAP) imaging: a magnetic resonance vessel wall imaging study. Eur Radiol 28:1681–1686

    Article  PubMed  Google Scholar 

  50. Oei ML, Ozgun M, Seifarth H et al (2010) T1-weighted MRI for the detection of coronary artery plaque haemorrhage. Eur Radiol 20:2817–2823

    Article  PubMed  Google Scholar 

  51. Boyko EJ (1994) Ruling out or ruling in disease with the most sensitive or specific diagnostic test: short cut or wrong turn? Med Decis Making 14:175–179

    Article  CAS  PubMed  Google Scholar 

  52. Yamada N, Higashi M, Otsubo R et al (2007) Association between signal hyperintensity on T1-weighted MR imaging of carotid plaques and ipsilateral ischemic events. AJNR Am J Neuroradiol 28:287–292

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Yuan C, Mitsumori LM, Ferguson MS et al (2001) In vivo accuracy of multispectral magnetic resonance imaging for identifying lipid-rich necrotic cores and intraplaque hemorrhage in advanced human carotid plaques. Circulation 104:2051–2056

    Article  CAS  PubMed  Google Scholar 

  54. Sun J, Zhao XQ, Balu N et al (2017) Carotid plaque lipid content and fibrous cap status predict systemic CV outcomes: the MRI substudy in AIM-HIGH. JACC Cardiovasc Imaging 10:241–249

    Article  PubMed  PubMed Central  Google Scholar 

  55. Gupta A, Baradaran H, Schweitzer AD et al (2013) Carotid plaque MRI and stroke risk: a systematic review and meta-analysis. Stroke 44:3071–3077

    Article  PubMed  Google Scholar 

Download references

Funding

This study has received funding by grants from the National Key R&D Program of China (2016YFC1300300).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Min Li or Gang Sun.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Gang Sun.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

The author Min Li has significant statistical expertise.

Informed consent

Written informed consent was not required for this study because all analyses were based on previously published studies; thus, no patient consent is required.

Ethical approval

Institutional Review Board approval was not required because all analyses were based on previously published studies; thus, no ethical approval is required.

Methodology

• prospective

• diagnostic study

• multicenter study

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 421 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, T., Jia, S., Wang, X. et al. Diagnostic performance of MRI for detecting intraplaque hemorrhage in the carotid arteries: a meta-analysis. Eur Radiol 29, 5129–5138 (2019). https://doi.org/10.1007/s00330-019-06053-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-019-06053-7

Keywords

Navigation