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Research Papers

The Influence of Inaccuracies in Carotid MRI Segmentation on Atherosclerotic Plaque Stress Computations

[+] Author and Article Information
Harm A. Nieuwstadt

Department of Biomedical Engineering,
Erasmus MC,
Rotterdam, The Netherlands
e-mail: h.nieuwstadt@erasmusmc.nl

Lambert Speelman

Department of Biomedical Engineering,
Erasmus MC,
Rotterdam, The Netherlands

Marcel Breeuwer

Philips Healthcare,
Best, The Netherlands;
Department of Biomedical Engineering,
Eindhoven University of Technology,
Eindhoven 5612, The Netherlands

Aad van der Lugt

Department of Radiology,
Erasmus MC,
Rotterdam, The Netherlands

Anton F. W. van der Steen

Department of Biomedical Engineering,
Erasmus MC,
Rotterdam, The Netherlands;
Department of Imaging Science and Technology,
Delft University of Technology,
Delft 2628, The Netherlands

Jolanda J. Wentzel

Department of Biomedical Engineering,
Erasmus MC,
Rotterdam, The Netherlands

Frank J. H. Gijsen

Department of Biomedical Engineering,
Erasmus MC,
Rotterdam, The Netherlands

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the Journal of Biomechanical Engineering. Manuscript received August 16, 2013; final manuscript received November 21, 2013; accepted manuscript posted December 9, 2013; published online February 5, 2014. Editor: Victor H. Barocas.

J Biomech Eng 136(2), 021015 (Feb 05, 2014) (9 pages) Paper No: BIO-13-1369; doi: 10.1115/1.4026178 History: Received August 16, 2013; Revised November 21, 2013; Accepted December 09, 2013

Biomechanical finite element analysis (FEA) based on in vivo carotid magnetic resonance imaging (MRI) can be used to assess carotid plaque vulnerability noninvasively by computing peak cap stress. However, the accuracy of MRI plaque segmentation and the influence this has on FEA has remained unreported due to the lack of a reliable submillimeter ground truth. In this study, we quantify this influence using novel numerical simulations of carotid MRI. Histological sections from carotid plaques from 12 patients were used to create 33 ground truth plaque models. These models were subjected to numerical computer simulations of a currently used clinically applied 3.0 T T1-weighted black-blood carotid MRI protocol (in-plane acquisition voxel size of 0.62 × 0.62 mm2) to generate simulated in vivo MR images from a known underlying ground truth. The simulated images were manually segmented by three MRI readers. FEA models based on the MRI segmentations were compared with the FEA models based on the ground truth. MRI-based FEA model peak cap stress was consistently underestimated, but still correlated (R) moderately with the ground truth stress: R = 0.71, R = 0.47, and R = 0.76 for the three MRI readers respectively (p < 0.01). Peak plaque stretch was underestimated as well. The peak cap stress in thick-cap, low stress plaques was substantially more accurately and precisely predicted (error of −12 ± 44 kPa) than the peak cap stress in plaques with caps thinner than the acquisition voxel size (error of −177 ± 168 kPa). For reliable MRI-based FEA to compute the peak cap stress of carotid plaques with thin caps, the current clinically used in-plane acquisition voxel size (∼0.6 mm) is inadequate. FEA plaque stress computations would be considerably more reliable if they would be used to identify thick-cap carotid plaques with low stresses instead.

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References

Slager, C. J., Wentzel, J. J., Gijsen, F. J. H., Schuurbiers, J. C. H., van der Wal, A. C., van der Steen, A. F. W., and SerruysP. W., 2005, “The Role of Shear Stress in the Generation of Rupture-Prone Vulnerable Plaques,” Natl. Clin. Pract. Cardiovasc. Med., 2(8), pp. 401–407. [CrossRef]
Virmani, R., Burke, A. P., Farb, A., and Kolodgie, F. D., 2006, “Pathology of the Vulnerable Plaque,” J. Am. Coll. Cardiol., 47(8), pp. C13–C18. [CrossRef] [PubMed]
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S. Ford, E. S., Caroline S. Fox, C. S., Sheila Franco, S., Fullerton, H. Gillespie, C., Hailpern, S. M., Heit, J. A., Howard, V. J., Huffman, M. D., Kissela, B. M., Steven J. Kittner, S. J., Lackland, D. T., Lichtman, J. H., Lisabeth, L. D., Magid, D., Marcus, G. M., Marelli, A., Matchar, D. B., McGuire, D. K., Mohler, E. R., Moy, C. S., Michael E. Mussolino, M. E., Graham Nichol, nG., Nina P. Paynter, N. P., Schreiner, P. J., Sorlie, P. D., Stein, J., Turan, T. N., Virani, S. S., Wong, N. D., Woo, D., and Turner, M. B., 2013, “Heart Disease and Stroke Statistics–2013 Update: A Report From the American Heart Association,” Circulation, 127(1), pp. e6–e245. [CrossRef] [PubMed]
Rothwell, P. M., Eliasziw, M., Gutnikov, S. A., Fox, A. J., Taylor, D. W., Mayberg, M. R., Warlow, C. P., and Barnett, H. J. M., 2003, “Analysis of Pooled Data From the Randomised Controlled Trials of Endarterectomy For Symptomatic Carotid Stenosis,” Lancet, 361(9352), pp. 107–116. [CrossRef] [PubMed]
Rerkasem, K., and Rothwell, P. M., 2009, “Systematic Review of the Operative Risks of Carotid Endarterectomy for Recently Symptomatic Stenosis in Relation to the Timing of Surgery,” Stroke, 40(1), pp. e564–e572. [CrossRef] [PubMed]
Yadav, J. S., Wholey, M. H., Kuntz, R. E., Fayad, R., Katzen, B. T., Mishkel, G. J., Bajwa, T. K., Whitlow, P., Strickman, N. E., Jaff, M. R., Popma, J. J., Snead, D. B., Cutlip, D. E., Frith, B. G., and Ouriel, K., 2004, “Protected Carotid-Artery Stenting Versus Endarterectomy in High-Risk Patients,” New Engl. J. Med., 351(15), pp. 1493–1501. [CrossRef]
Barnett, H. J. M., Taylor, D. W., Eliasziw, M., Fox, A. J., Ferguson, G. G., Haynes, R. B., Rankin, R. N., Clagett, G. P., Hachinski, V. C., Sackett, D. L., Thorpe, K. E., Meldrum, H. E., and Spence, J. D., 1998, “Benefit of Carotid Endarterectomy in Patients With Symptomatic Moderate or Severe Stenosis,” New Engl. J. Med., 339(20), pp. 1415–1425. [CrossRef]
Richardson, P. D., Davies, M. J., and Born, G. V. R., 1989, “Influence of Plaque Configuration and Stress Distribution on Fissuring of Coronary Atherosclerotic Plaques,” Lancet, 2(8669), pp. 941–944. [CrossRef] [PubMed]
Loree, H. M., Kamm, R. D., Stringfellow, R. G., and Lee, R. T., 1992, “Effects of Fibrous Cap Thickness on Peak Circumferential Stress in Model Atherosclerotic Vessels,” Circ. Res., 71(4), pp. 850–858. [CrossRef] [PubMed]
Ohayon, J., Teppaz, P., Finet, G., and Rioufol, G., 2001, “In-Vivo Prediction of Human Coronary Plaque Rupture Location Using Intravascular Ultrasound and the Finite Element Method,” Coronary Artery Disease, 12(8), pp. 655–663. [CrossRef] [PubMed]
Sadat, U., Teng, Z., and Gillard, J. H., 2010, “Biomechanical Structural Stresses of Atherosclerotic Plaques,” Expert Rev. Cardiovasc. Ther., 8(10), pp. 1469–1481. [CrossRef] [PubMed]
Tang, D., Yang, C., Zheng, J., Woodard, P. K., Saffitz, J. E., Petruccelli, J. D., Sicard, G. A., and Yuan, C., 2005, “Local Maximal Stress Hypothesis and Computational Plaque Vulnerability Index for Atherosclerotic Plaque Assessment,” Ann. Biomed. Eng., 33(12), pp. 1789–1801. [CrossRef] [PubMed]
Gao, H., and Long, Q., 2008, “Effects of Varied Lipid Core Volume and Fibrous Cap Thickness on Stress Distribution in Carotid Arterial Plaques,” J. Biomech., 41(14), pp. 3053–3059. [CrossRef] [PubMed]
Akyildiz, A. C., Speelman, L., van Brummelen, H., Gutierrez, M. A., Virmani, R., van der Lugt, A., van der Steen, A. F. W., Wentzel, J. J., and Gijsen, F. J. H., 2011, “Effects of Intima Stiffness and Plaque Morphology on Peak Cap Stress,” Biomed. Eng. Online10(25), pp. 1–13. [CrossRef] [PubMed]
Teng, Z., Sadat, U., Wang, W., Bahaei, N. S., Chen, S., Young, V. E., Graves, Y., and Gillard, J. H., 2013, “Intraplaque Stretch in Carotid Atherosclerotic Plaque—An Effective Biomechanical Predictor for Subsequent Cerebrovascular Ischemic Events,” PlosOne, 8(4), p. e61522. [CrossRef]
Teng, Z., He, J., Degnan, A. J., Chen, S., Sadat, U., Bahaei, N. S., Rudd, J. H. F., and Gillard, J. H., 2012, “Critical Mechanical Conditions Around Neovessels in Carotid Atherosclerotic Plaque May Promote Intraplaque Hemorrhage,” Atherosclerosis, 223(2), pp. 321–326. [CrossRef] [PubMed]
Underhill, H. R., Hatsukami, T. S., Fayad, A. Z., Fuster, V., and Yuan, C., 2010, “MRI of Carotid Atherosclerosis: Clinical Implications and Future Directions,” Natl. Rev. Cardiol., 7(3), pp. 165–173. [CrossRef]
Li, F., Yarnykh, V. L., Hatsukami, T. S., Chu, B., Balu, N., Wang, J., Underhill, H. R., Zhao, X., Smith, R., and Yuan, C., 2010, “Scan-Rescan Reproducibility of Carotid Atherosclerotic Plaque Morphology and Tissue Composition Measurements Using Multicontrast MRI at 3 T,” J. Magn. Reson. Imag., 31(1), pp. 168–176. [CrossRef]
Gao, H., Long, Q., Graves, M., Gillard, J. H., and Li, Z., 2009, “Study of Reproducibility of Human Arterial Plaque Reconstruction and Its Effects on Stress Analysis Based on Multispectral In Vivo Magnetic Resonance Imaging,” J. Magn. Reson. Imag., 30(1), pp. 85–93. [CrossRef]
Li, Z.-Y., Howarth, S., Trivedi, R. A., U-King-Im, J. M., Graves, M. J., Brown, A., Wang, L., and Gillard, J. H., 2006, “Stress Analysis of Carotid Plaque Rupture Based on In Vivo High Resolution MRI,” J. Biomech., 39(14), pp. 2611–2622. [CrossRef] [PubMed]
Tang, D., Teng, Z., Canton, G., Yang, C., Ferguson, M., Huang, X., Zheng, J., Woodard, P. K., and Yuan, C., 2009, “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, 40(10), pp. 3258–3263. [CrossRef] [PubMed]
Sadat, U., Teng, Z., Young, V. E., Graves, M. J., Gaunt, M. E., and Gillard, J. H., 2011, “High-resolution Magnetic Resonance Imaging-Based Biomechanical Stress Analysis of Carotid Atheroma: A Comparison of Single Transient Ischaemic Attack, Recurrent Transient Ischaemic Attacks, Nondisabling Stroke and Asymptomatic Patient Groups,” Eur. J. Vasc. Endovasc. Surg., 41(1), pp. 83–90. [CrossRef] [PubMed]
Redgrave, J. N., Gallagher, P., Lovett, J. K., and Rothwell, P. M., 2008, “Critical Cap Thickness and Rupture in Symptomatic Carotid Plaques: The Oxford Plaque Study,” Stroke, 39(6), pp. 1722–1729. [CrossRef] [PubMed]
Nieuwstadt, H. A., Geraedts, T. R., Truijman, M. T. B., Kooi, M. E., van der Lugt, A., van der Steen, A. F. W., Wentzel, J. J., Breeuwer, M., and Gijsen, F. J. H., 2013, “Numerical Simulations of Carotid MRI Quantify the Accuracy in Measuring Atherosclerotic Plaque Components In Vivo,” Magn. Reson. Med. [CrossRef]
Finet, G., Ohayon, J., and Rioufol, G., 2004, “Biomechanical Interaction Between Cap Thickness, Lipid Core Composition and Blood Pressure in Vulnerable Coronary Plaque: Impact on Stability or Instability,” Coronary Artery Disease, 15(1), pp. 13–20. [CrossRef] [PubMed]
Nieuwstadt, H. A., Akyildiz, A. C., Speelman, L., Virmani, R., van der Lugt, A., van der Steen, A. F. W., Wentzel, J. J., and Gijsen, F. J. H., 2013, “The Influence of Axial Image Resolution on Atherosclerotic Plaque Stress Computations,” J. Biomech., 46(4), pp. 689–695. [CrossRef] [PubMed]
Groen, H. C., van Walsum, T., Rozie, S., Klein, S., van Gaalen, K., Gijsen, F. J. H., Wielopolski, P. A., van Beusekom, H. M. M., de Crom, R., Verhagen, H. J. M., van der Steen, A. W. F., van der Lugt, A., Wentzel, J. J., and Niessen, W. J., 2010, “Three-Dimensional Registration of Histology of Human Atherosclerotic Carotid Plaques to In-Vivo Imaging,” J. Biomech., 43(11), pp. 2087–2092. [CrossRef] [PubMed]
Speelman, L., Akyildiz, A. C., denAdel, B., Wentzel, J. J., van der Steen, A. F., Virmani, R., van der Weerd, L., Jukema, J. W., Poelmann, R. E., van Brummelen, E. H., and Gijsen, F. J. H., 2011, “Initial Stress in Biomechanical Models of Atherosclerotic Plaques,” J. Biomech., 44(13), pp. 2376–2382. [CrossRef] [PubMed]
Stöcker, T., Vahedipour, K., Pflugfelder, D., and Shah, N. J., 2010, “High-Performance Computing MRI Simulations,” Magn. Reson. Med., 64(1), pp. 186–193. [CrossRef] [PubMed]
Li, Z.-Y., Tang, T., U-King-Im, J., Graves, M., Sutcliffe, M., and Gillard, J. H., 2008, “Assessment of Carotid Plaque Vulnerability Using Structural and Geometrical Determinants,” Jpn. Circ. J., 72(7), pp. 1092–1099. [CrossRef]
Teng, Z., Sadat, U., Li, Z., Huang, X., Zhu, C., Young, V. E., Graves, M. J., and Gillard, J. H., 2010, “Arterial Luminal Curvature and Fibrous-Cap Thickness Affect Critical Stress Conditions Within Atherosclerotic Plaque: An In Vivo MRI-Based 2D Finite-Element Study,” Ann. Biomed. Eng., 38(10), pp. 3096–3101. [CrossRef] [PubMed]
Teng, Z., Sadat, U., Ji, G., Zhu, C., Young, V. E., Graves, M. J., and Gillard, J. H., 2011, “Lumen Irregularity Dominates the Relationship Between Mechanical Stress Condition, Fibrous-Cap Thickness, and Lumen Curvature in Carotid Atherosclerotic Plaque,” ASME J. Biomech. Eng., 133(3), p. 034501. [CrossRef]
Humprey, J. D., 2002, Cardiovascular Solid Mechanics: Cells, Tissues, and Organs, Springer, New York, 757 pp.
Adame, I. M., van der Geest, R. J., Wasserman, B. A., Mohamed, M. A., Reiber, J. H. C., and Lelieveldt, B. P. F., 2004, “Automatic Segmentation and Plaque Characterization in Atherosclerotic Carotid Artery MR Images,” MAGMA, 16(5), pp. 227–234. [CrossRef] [PubMed]
Ribbers, H., Lopata, R. G. P., Holewijn, S., Pasterkamp, G., Blankensteijn, J. D., and de Korte, C. L., 2007, “Noninvasive Two-dimensional Strain Imaging of Arteries: Validation in Phantoms and Preliminary Experience in Carotid Arteries In Vivo,” Ultrasound Med. Biol., 33(4), pp. 530–540. [CrossRef] [PubMed]
Jahnke, C., Dietrich, T., Paetsch, I., Koehler, U., Preetz, K., Schnackenburg, B., Fleck, E., Graf, K., and Nagel, E., 2007, “Experimental Evaluation of the Detectability of Submillimeter Atherosclerotic Lesions in Ex Vivo Human Iliac Arteries With Ultrahigh-field (7.0 T) Magnetic Resonance Imaging,” Int. J. Cardiovasc. Imaging, 23(4), pp. 519–527. [CrossRef] [PubMed]
Balu, N., Yarnykh, V. L., Chu, B., Wang, J., Hatsukami, T., and Yuan, C., 2011, “Carotid Plaque Assessment Using Fast 3D Isotropic Resolution Black-Blood MRI,” Magn. Reson. Med., 65(3), pp. 627–637. [CrossRef] [PubMed]
Rambhia, S. H., Liang, X., Xenos, M., Alemu, Y., Maldonado, N., Kelly, A., Chakraborti, S., Weinbaum, S., Cardoso, L., Einav, S., and Bluestein, D., 2012, “Microcalcifications Increase Coronary Vulnerable Plaque Rupture Potential: A Patient-Based Micro-CT Fluid–Structure Interaction Study,” Ann. Biomed. Eng., 40(7), pp. 1443–1454. [CrossRef] [PubMed]
Liu, W., Balu, N., Sun, J., Zhao, X., Chen, H., Yuan, C., Zhao, H., Xu, J., Wang, G., and Kerwin, W. S., 2012, “Segmentation of Carotid Plaque Using Multicontrast 3D Gradient Echo MRI,” J. Magn. Reson. Imaging, 35(4), pp. 812–8191. [CrossRef] [PubMed]
Farrell, B., Fraser, A., Sandercock, P., Slattery, J., and Warlow, C. P., 1998, “Randomised Trial of Endarterectomy for Recently Symptomatic Carotid Stenosis: Final Results of the MRC European Carotid Surgery Trial (ECST),” Lancet, 351(9113), pp. 1379–1387. [CrossRef] [PubMed]

Figures

Grahic Jump Location
Fig. 1

Methodology of the study. Each horizontally layered block represents an increasing arterial pressure of 0, 100, and 125 mmHg. Minimum FC thickness location and peak cap stress are indicated in ground truth and MRI models. In the simulated in vivo MR image, (+) indicates LRNC, (*) indicates lumen and the white arrow the FC location. In the stress maps, black arrows indicate location and magnitude (in kPa) of the peak cap stress.

Grahic Jump Location
Fig. 2

Example 1: Thin cap, high peak cap stress case. Ground truth model and stress map (first column), and the three MR reader segmentations and MRI model stress maps (columns 2 through 4). (*) indicates lumen, black arrows show the location of peak cap stress.

Grahic Jump Location
Fig. 3

Example 2: Thick cap, low peak cap stress case. Ground truth model and stress map (first column), and the three MR reader segmentations and MRI model stress maps (columns 2 through 4). (*) indicates lumen, black arrows show the location of peak cap stress.

Grahic Jump Location
Fig. 4

(a) Peak cap stress in MRI models as a function of peak cap stress in ground truth models for the three MR readers. Bin size is 200 kPa. (b) Difference in computed peak cap stress between MRI models and ground truth models as a function of ground truth minimum FC thickness. Bin size is 0.2 mm.

Grahic Jump Location
Fig. 5

Box plots showing grouped data for all plaque models: ground truth versus MRI models. GT = ground truth, R = reader. (+) indicates an outlier, (S) indicates significance with respect to the ground truth data distribution, p < 0.01, (NS) indicates no significance. Whiskers mark the extreme data points not considering outliers. (a)–(c) Geometrical parameters studied, (d) peak cap stress and (e) peak plaque stretch. For (c)–(e), data are split into two groups with a ground truth minimum FC thickness smaller (left) and larger (right) than 0.62 mm (MRI in-plane acquisition voxel size).

Grahic Jump Location
Fig. 6

Example of the modified MRI protocol. Ground truth model and stress map (first column). Segmentation and stress maps for original protocol (second column) and modified protocol (third column). (*) indicates lumen, black arrows show the location of peak cap stress.

Grahic Jump Location
Fig. 7

(a) Peak cap stress in MRI models as a function of peak cap stress in ground truth models for the original and the modified protocol. Bin size is 200 kPa. (b) Difference in computed peak cap stress between MRI models and ground truth models as a function of ground truth minimum FC thickness. Bin size is 0.2 mm. (c)–(f) Box plots showing grouped data of all parameters studied (c)–(f), for details see caption of Fig. 5.

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