MRI-based biomechanical parameters for carotid artery plaque vulnerability assessment

Summary

Carotid atherosclerotic plaques are a major cause of ischaemic stroke. The biomechanical environment to which the arterial wall and plaque is subjected to plays an important role in the initiation, progression and rupture of carotid plaques. MRI is frequently used to characterize the morphology of a carotid plaque, but new developments in MRI enable more functional assessment of carotid plaques. In this review, MRI based biomechanical parameters are evaluated on their current status, clinical applicability, and future developments. Blood flow related biomechanical parameters, including endothelial wall shear stress and oscillatory shear index, have been shown to be related to plaque formation. Deriving these parameters directly from MRI flow measurements is feasible and has great potential for future carotid plaque development prediction. Blood pressure induced stresses in a plaque may exceed the tissue strength, potentially leading to plaque rupture. Multi-contrast MRI based stress calculations in combination with tissue strength assessment based on MRI inflammation imaging may provide a plaque stress-strength balance that can be used to assess the plaque rupture risk potential. Direct plaque strain analysis based on dynamic MRI is already able to identify local plaque displacement during the cardiac cycle. However, clinical evidence linking MRI strain to plaque vulnerability is still lacking. MRI based biomechanical parameters may lead to improved assessment of carotid plaque development and rupture risk. However, better MRI systems and faster sequences are required to improve the spatial and temporal resolution, as well as increase the image contrast and signal-to-noise ratio.

Keywords

Atherosclerosis - inflammation - MRI - biomechanics

• References

• 1 Underhill HR. et al. MRI of carotid atherosclerosis: clinical implications and future directions. Nat Rev Cardiol 2010; 7: 165-173.
• 2 Simpson RJ. et al. MR imaging-detected carotid plaque hemorrhage is stable for 2 years and a marker for stenosis progression. Am J Neuroradiol 2015; 36: 1171-1175.
• 3 Prabhakaran S. et al. Carotid plaque surface irregularity predicts ischaemic stroke: the northern Manhattan study. Stroke 2006; 37: 2696-2701.
• 4 Singh N. et al. Moderate carotid artery stenosis: MR imaging-depicted intra-plaque hemorrhage predicts risk of cerebrovascular ischaemic events in asymptomatic men. Radiology 2009; 252: 502-508.
• 5 den Hartog AG. et al. Current status of clinical magnetic resonance imaging for plaque characterisation in patients with carotid artery stenosis. Eur J Vasc En-dovasc Surg 2013; 45: 7-21.
• 6 Li F. et al. Scan-rescan reproducibility of carotid atherosclerotic plaque morphology and tissue composition measurements using multicontrast MRI at 3T. J Magn Reson Imaging 2010; 31: 168-176.
• 7 Chen H. et al. Scan-rescan reproducibility of quantitative assessment of inflammatory carotid atherosclerotic plaque using dynamic contrast-enhanced 3T CMR in a multi-center study. J Cardiovasc Magn Reson 2014; 16: 51.
• 8 Saam T. et al. Quantitative evaluation of carotid plaque composition by in vivo MRI. Arterioscler Thromb Vasc Biol 2005; 25: 234-239.
• 9 Bitar R. et al. In vivo 3D high-spatial-resolution MR imaging of intraplaque hemorrhage. Radiology 2008; 249: 259-267.
• 10 Du J. et al. Direct imaging and quantification of carotid plaque calcification. Magn Reson Med 2011; 65: 1013-1020.
• 11 Hatsukami TS. et al. Visualization of fibrous cap thickness and rupture in human atherosclerotic carotid plaque in vivo with high-resolution magnetic resonance imaging. Circulation 2000; 102: 959-964.
• 12 Cai J-M. et al. Classification of human carotid atherosclerotic lesions with in vivo multicontrast magnetic resonance imaging. Circulation 2002; 106: 1368-1373.
• 13 Cibis M. et al. Wall shear stress calculations based on 3D cine phase contrast MRI and computational fluid dynamics: a comparison study in healthy carotid arteries. NMR Biomed 2014; 27: 826-834.
• 14 Papathanasopoulou P. et al. MRI measurement of time-resolved wall shear stress vectors in a carotid bifurcation model, and comparison with CFD predictions. J Magn Reson Imaging 2003; 17: 153-162.
• 15 Nederveen AJ. et al. MRI strain imaging of the carotid artery: Present limitations and future challenges. J Biomech 2014; 47: 824-833.
• 16 Te Boekhorst BC. et al. Molecular MRI of Inflammation in Atherosclerosis. Curr Cardiovasc Imaging Rep 2012; 5: 60-68.
• 17 Malek AM. Hemodynamic Shear Stress and Its Role in Atherosclerosis. J Am Med Assoc 1999; 282: 2035.
• 18 Cheng C. et al. Shear stress-induced changes in atherosclerotic plaque composition are modulated by chemokines. J Clin Invest 2007; 117: 616-626.
• 19 Matlung HL. et al. Transglutaminase activity regulates atherosclerotic plaque composition at locations exposed to oscillatory shear stress. Atherosclerosis 2012; 224: 355-362.
• 20 Tang D. et al. Sites of rupture in human atherosclerotic carotid plaques are associated with high structural stresses: an in vivo MRI-based 3D fluid-structure interaction study. Stroke 2009; 40: 3258-3263.
• 21 Ku DN. et al. Pulsatile flow and atherosclerosis in the human carotid bifurcation. Positive correlation between plaque location and low oscillating shear stress. Arteriosclerosis 1985; 5: 293-302.
• 22 LaDisa JF. et al. Time-efficient patient-specific quantification of regional carotid artery fluid dynamics and spatial correlation with plaque burden. Med Phys 2010; 37: 784-792.
• 23 Lee S-W. et al. Correlations among indicators of disturbed flow at the normal carotid bifurcation. J Biomech Eng 2009; 131: 061013.
• 24 Antiga L. et al. An image-based modeling framework for patient-specific computational hemodynamics. Med Biol Eng Comput 2008; 46: 1097-1112.
• 25 Stalder AF. et al. Quantitative 2D and 3D phase contrast MRI: optimized analysis of blood flow and vessel wall parameters. Magn Reson Med 2008; 60: 1218-1231.
• 26 Petersson S. et al. Assessment of the accuracy of MRI wall shear stress estimation using numerical simulations. J Magn Reson Imaging 2012; 36: 128-138.
• 27 Potters WV. et al. Volumetric arterial wall shear stress calculation based on cine phase contrast MRI. J Magn Reson Imaging 2015; 41: 505-516.
• 28 Oshinski JN. et al. Mean-average wall shear stress measurements in the common carotid artery. J Cardiovasc Magn Reson 2006; 8: 717-722.
• 29 Wu SP. et al. Wall shear rates differ between the normal carotid, femoral, and brachial arteries: an in vivo MRI study. J Magn Reson Imaging 2004; 19: 188-193.
• 30 Steinman DA. Image-based computational fluid dynamics modeling in realistic arterial geometries. Ann Biomed Eng 2002; 30: 483-497.
• 31 Oshinski JN. et al. Determination of wall shear stress in the aorta with the use of MR phase velocity mapping. J Magn Reson Imaging 1995; 5: 640-647.
• 32 Masaryk AM. et al. In vitro and in vivo comparison of three MR measurement methods for calculating vascular shear stress in the internal carotid artery. AJNR Am J Neuroradiol 1999; 20: 237-245.
• 33 Oyre S. et al. Accurate noninvasive quantitation of blood flow, cross-sectional lumen vessel area and wall shear stress by three-dimensional paraboloid modeling of magnetic resonance imaging velocity data. J Am Coll Cardiol 1998; 32: 128-134.
• 34 Cheng CP. et al. Quantification of wall shear stress in large blood vessels using Lagrangian interpolation functions with cine phase-contrast magnetic resonance imaging. Ann Biomed Eng 2002; 30: 1020-1032.
• 35 Gelfand BD. et al. Spatial and spectral heterogeneity of time-varying shear stress profiles in the carotid bifurcation by phase-contrast MRI. J Magn Reson Imaging 2006; 24: 1386-1392.
• 36 Box FMA. et al. Reproducibility of wall shear stress assessment with the paraboloid method in the internal carotid artery with velocity encoded MRI in healthy young individuals. J Magn Reson Imaging 2007; 26: 598-605.
• 37 Jiang J. et al. Quantifying errors in flow measurement using phase contrast magnetic resonance imaging: comparison of several boundary detection methods. Magn Reson Imaging 2015; 33: 185-193.
• 38 Herment A. et al. Automated segmentation of the aorta from phase contrast MR images: validation against expert tracing in healthy volunteers and in patients with a dilated aorta. J Magn Reson Imaging 2010; 31: 881-888.
• 39 Markl M. et al. In vivo wall shear stress distribution in the carotid artery: effect of bifurcation geometry, internal carotid artery stenosis, and recanalization therapy. Circ Cardiovasc Imaging 2010; 3: 647-655.
• 40 van Ooij P. et al. A methodology to detect abnormal relative wall shear stress on the full surface of the thoracic aorta using four-dimensional flow MRI. Magn Reson Med 2015; 73: 1216-1227.
• 41 Lorenz R. et al. Influence of eddy current, Maxwell and gradient field corrections on 3D flow visualization of 3D CINE PC-MRI data. Magn Reson Med 2014; 72: 33-40.
• 42 O’Brien KR. et al. MRI phase contrast velocity and flow errors in turbulent stenotic jets. J Magn Reson Imaging 2008; 28: 210-218.
• 43 Cheng C. et al. Atherosclerotic lesion size and vulnerability are determined by patterns of fluid shear stress. Circulation 2006; 113: 2744-2753.
• 44 van Bochove GS. et al. MRI-determined carotid artery flow velocities and wall shear stress in a mouse model of vulnerable and stable atherosclerotic plaque. MAGMA 2010; 23: 77-84.
• 45 Peiffer V. et al. Computation in the rabbit aorta of a new metric - the transverse wall shear stress - to quantify the multidirectional character of disturbed blood flow. J Biomech 2013; 46: 2651-2658.
• 46 He X, Ku DN. Pulsatile flow in the human left coronary artery bifurcation: average conditions. J Biomech Eng 1996; 118: 74-82.
• 47 Harloff A. et al. Wall shear stress distribution at the carotid bifurcation: influence of eversion carotid endarterectomy. Eur Radiol 2013; 23: 3361-3369.
• 48 Gallo D. et al. Helical flow in carotid bifurcation as surrogate marker of exposure to disturbed shear. J Biomech 2012; 45: 2398-2404.
• 49 Giese D. et al. Towards highly accelerated Cartesian time-resolved 3D flow cardiovascular magnetic resonance in the clinical setting. J Cardiovasc Magn Reson 2014; 16: 42.
• 50 Knobloch V. et al. Sparsity transform k-t principal component analysis for accelerating cine three-dimensional flow measurements. Magn Reson Med 2013; 70: 53-63.
• 51 Schnell S. et al. k-t GRAPPA accelerated four-dimensional flow MRI in the aorta: effect on scan time, image quality, and quantification of flow and wall shear stress. Magn Reson Med 2014; 72: 522-533.
• 52 Barnett HJ. et al. Benefit of carotid endarterectomy in patients with symptomatic moderate or severe stenosis. North American Symptomatic Carotid End-arterectomy Trial Collaborators. N Engl J Med 1998; 339: 1415-1425.
• 53 Yuan C. et al. Identification of fibrous cap rupture with magnetic resonance imaging is highly associated with recent transient ischaemic attack or stroke. Circulation 2002; 105: 181-185.
• 54 Chu B. et al. Hemorrhage in the atherosclerotic carotid plaque: a high-resolution MRI study. Stroke 2004; 35: 1079-1084.
• 55 Sadat U. et al. Utility of high resolution MR imaging to assess carotid plaque morphology: a comparison of acute symptomatic, recently symptomatic and asymptomatic patients with carotid artery disease. Atherosclerosis 2009; 207: 434-439.
• 56 Altaf N. et al. Detection of intraplaque hemorrhage by magnetic resonance imaging in symptomatic patients with mild to moderate carotid stenosis predicts recurrent neurological events. J Vasc Surg 2008; 47: 337-342.
• 57 Takaya N. et al. Association between carotid plaque characteristics and subsequent ischaemic cerebrovascular events: a prospective assessment with MRI-initial results. Stroke 2006; 37: 818-823.
• 58 Richardson PD. et al. Influence of plaque configuration and stress distribution on fissuring of coronary atherosclerotic plaques. Lancet 1989; 2: 941-944.
• 59 Sadat U. et al. High-resolution magnetic resonance imaging-based biomechan-ical stress analysis of carotid atheroma: a comparison of single transient is-chaemic attack, recurrent transient ischaemic attacks, non-disabling stroke and asymptomatic patient groups. Eur J Vasc Endovasc Surg 2011; 41: 83-90.
• 60 Zhu C. et al. Normalized wall index specific and MRI-based stress analysis of atherosclerotic carotid plaques: a study comparing acutely symptomatic and asymptomatic patients. Circ J 2010; 74: 2360-2364.
• 61 Sadat U. et al. Association between biomechanical structural stresses of atherosclerotic carotid plaques and subsequent ischaemic cerebrovascular events-- a longitudinal in vivo magnetic resonance imaging-based finite element study. Eur J Vasc Endovasc Surg 2010; 40: 485-491.
• 62 Li Z-Y. et al. Stress analysis of carotid plaque rupture based on in vivo high resolution MRI. J Biomech 2006; 39: 2611-2622.
• 63 Holzapfel GA. et al. Computational approaches for analyzing the mechanics of atherosclerotic plaques: a review. J Biomech 2014; 47: 859-869.
• 64 Huang Y. et al. The influence of computational strategy on prediction of mechanical stress in carotid atherosclerotic plaques: comparison of 2D structure-only, 3D structure-only, one-way and fully coupled fluid-structure interaction analyses. J Biomech 2014; 47: 1465-1471.
• 65 Nieuwstadt HA. et al. The influence of axial image resolution on atherosclerotic plaque stress computations. J Biomech 2013; 46: 689-695.
• 66 Gao H. et al. Study of carotid arterial plaque stress for symptomatic and asymptomatic patients. J Biomech 2011; 44: 2551-2557.
• 67 Nieuwstadt HA. et al. Atherosclerotic plaque fibrous cap assessment under an oblique scan plane orientation in carotid MRI. Quant Imaging Med Surg 2014; 4: 216-224.
• 68 Zhu C. et al. 3D high-resolution contrast enhanced MRI of carotid atheroma-- a technical update. Magn Reson Imaging 2014; 32: 594-597.
• 69 Fan Z. et al. Carotid arterial wall MRI at 3T using 3D variable-flip-angle turbo spin-echo (TSE) with flow-sensitive dephasing (FSD). J Magn Reson Imaging 2010; 31: 645-654.
• 70 Liu W. et al. Segmentation of carotid plaque using multicontrast 3D gradient echo MRI. J Magn Reson Imaging 2012; 35: 812-819.
• 71 Redgrave JN. et al. Critical cap thickness and rupture in symptomatic carotid plaques: the oxford plaque study. Stroke. 2008; 39: 1722-1729.
• 72 Coolen BF. et al. Three-dimensional quantitative T1 and T2 mapping of the carotid artery: Sequence design and in vivo feasibility. Magn Reson Med. 2015 Epub ahead of print.
• 73 de Rotte AAJ. et al. Seven-tesla magnetic resonance imaging of atherosclerotic plaque in the significantly stenosed carotid artery: a feasibility study. Invest Radiol 2014; 49: 749-757.
• 74 Xie Y. et al. Improved black-blood imaging using DANTE-SPACE for simultaneous carotid and intracranial vessel wall evaluation. Magn Reson Med. 2015 Epub ahead of print.
• 75 Fan Z. et al. Multi-contrast atherosclerosis characterization (MATCH) of carotid plaque with a single 5-min scan: technical development and clinical feasibility. J Cardiovasc Magn Reson 2014; 16: 53.
• 76 Makhijani MK. et al. Accelerated 3D MERGE carotid imaging using compressed sensing with a hidden Markov tree model. J Magn Reson Imaging 2012; 36: 1194-1202.
• 77 Ebenstein DM. et al. Nanomechanical properties of calcification, fibrous tissue, and hematoma from atherosclerotic plaques. J Biomed Mater Res A 2009; 91: 1028-1037.
• 78 Teng Z. et al. Material properties of components in human carotid atherosclerotic plaques: a uniaxial extension study. Acta Biomater 2014; 10: 5055-5063.
• 79 Chai C-K. et al. Compressive mechanical properties of atherosclerotic plaques-indentation test to characterise the local anisotropic behaviour. J Biomech 2014; 47: 784-792.
• 80 Chai C-K. et al. Local anisotropic mechanical properties of human carotid atherosclerotic plaques - characterisation by micro-indentation and inverse finite element analysis. J Mech Behav Biomed Mater 2015; 43: 59-68.
• 81 Akyildiz AC. et al. Effects of intima stiffness and plaque morphology on peak cap stress. Biomed Eng Online 2011; 10: 25.
• 82 Yuan J. et al. Influence of material property variability on the mechanical behaviour of carotid atherosclerotic plaques: A 3D fluid-structure interaction analysis. Int J Numer Method Biomed Eng. 2015 Epub ahead of print.
• 83 Franquet A. et al. A new method for the in vivo identification of mechanical properties in arteries from cine MRI images: theoretical framework and validation. IEEE Trans Med Imaging 2012; 6: 1-16.
• 84 Nieuwstadt HA. et al. Carotid plaque elasticity estimation using ultrasound elas-tography, MRI, and inverse FEA - A numerical feasibility study. Med Eng Phys 2015; 37: 801-807.
• 85 Liu H. et al. Using in vivo Cine and 3D multi-contrast MRI to determine human atherosclerotic carotid artery material properties and circumferential shrinkage rate and their impact on stress/strain predictions. J Biomech Eng 2012; 134: 11008.
• 86 Taviani V. et al. Estimation of aortic pulse pressure using fourier velocity encoded M-mode MR. J Magn Reson Imaging 2014; 39: 85-93.
• 87 Lendon CL. et al. Atherosclerotic plaque caps are locally weakened when mac-rophages density is increased. Atherosclerosis 1991; 87: 87-90.
• 88 Walsh MT. et al. Uniaxial tensile testing approaches for characterisation of atherosclerotic plaques. J Biomech 2014; 47: 793-804.
• 89 Alie N. et al. Inflammation, Atherosclerosis, and Coronary Artery Disease: PET/ CT for the Evaluation of Atherosclerosis and Inflammation. Clin Med Insights Cardiol 2014; 8: 13-21.
• 90 Chan JMS. et al. Imaging of the vulnerable carotid plaque: biological targeting of inflammation in atherosclerosis using iron oxide particles and MRI. Eur J Vasc Endovasc Surg 2014; 47: 462-469.
• 91 Millon A. et al. Clinical and histological significance of gadolinium enhancement in carotid atherosclerotic plaque. Stroke 2012; 43: 3023-3028.
• 92 Schaar JA. et al. Intravascular palpography for vulnerable plaque assessment. J Am Coll Cardiol 2006; 47: C86-91.
• 93 Naim C. et al. Characterisation of carotid plaques with ultrasound elastography: feasibility and correlation with high-resolution magnetic resonance imaging. Eur Radiol 2013; 23: 2030-2041.
• 94 Avril S. et al. In vivo time-resolved sub-pixel measurements of wall deformation in the common carotid artery. 7th Eur Symp Vasc Biomater ESVB 2011 2011; 1-35.
• 95 Lin AP. et al. Circumferential strain in the wall of the common carotid artery: comparing displacement-encoded and cine MRI in volunteers. Magn Reson Med 2008; 60: 8-13.
• 96 Osman NF. Detecting stiff masses using strain-encoded (SENC) imaging. Magn Reson Med 2003; 49: 605-608.
• 97 Hamdan A. et al. Strain-encoded MRI to evaluate normal left ventricular function and timing of contraction at 3.0 Tesla. J Magn Reson Imaging 2009; 29: 799-808.
• 98 Yang C. et al. Advanced human carotid plaque progression correlates positively with flow shear stress using follow-up scan data: an in vivo MRI multi-patient 3D FSI study. J Biomech 2010; 43: 2530-2538.