Symptomatic vs. Asymptomatic Plaque Classification in Carotid Ultrasound | Journal of Medical Systems Skip to main content

Advertisement

Springer Nature Link
Log in

Symptomatic vs. Asymptomatic Plaque Classification in Carotid Ultrasound

  • ORIGINAL PAPER
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Quantitative characterization of carotid atherosclerosis and classification into symptomatic or asymptomatic type is crucial in both diagnosis and treatment planning. This paper describes a computer-aided diagnosis (CAD) system which analyzes ultrasound images and classifies them into symptomatic and asymptomatic based on the textural features. The proposed CAD system consists of three modules. The first module is preprocessing, which conditions the images for the subsequent feature extraction. The feature extraction stage uses image texture analysis to calculate Standard deviation, Entropy, Symmetry, and Run Percentage. Finally, classification is performed using AdaBoost and Support Vector Machine for automated decision making. For Adaboost, we compared the performance of five distinct configurations (Least Squares, Maximum- Likelihood, Normal Density Discriminant Function, Pocket, and Stumps) of this algorithm. For Support Vector Machine, we compared the performance using five different configurations (linear kernel, polynomial kernel configurations of different orders and radial basis function kernels). SVM with radial basis function kernel for support vector machine presented the best classification result: classification accuracy of 82.4%, sensitivity of 82.9%, and specificity of 82.1%. We feel that texture features coupled with the Support Vector Machine classifier can be used to identify the plaque tissue type. An Integrated Index, called symptomatic asymptomatic carotid index (SACI), is proposed using texture features to discriminate symptomatic and asymptomatic carotid ultrasound images using just one index or number. We hope this SACI can be used as an adjunct tool by the vascular surgeons for daily screening.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Sims, N. R., and Muyderman, H., Mitochondria, oxidative metabolism and cell death in stroke. Biochim. Biophys. Acta 1802:80–91, 2009.

    Google Scholar 

  2. Labarthe, D. R., Epidemiology and prevention of cardiovascular diseases: a global challenge. Aspen, Gaithersburg, 1998.

    Google Scholar 

  3. Maton, A., Hopkins, R. L. J., McLaughlin, C. W., Johnson, S., Warner, M. Q., LaHart, D., and Wright, J. D., Human biology and health. Prentice Hall, Englewood Cliffs, 1993.

    Google Scholar 

  4. Report on Atherosclerosis: http://en.wikipedia.org/wiki/Atherosclerosis, last accessed in Sept 2010.

  5. North American Symptomatic Carotid Endarterectomy Trial Collaborators, Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. N. Engl. J. Med. 325:445–453, 1991.

    Article  Google Scholar 

  6. European Carotid Surgery Trialists’ Collaborative Group, Randomised trial of endarterectomy for recently symptomatic carotid stenosis: Final results of the MRC European Carotid Surgery Trial (ECST). Lancet 351:1379–1387, 1998.

    Article  Google Scholar 

  7. Solberg, L. A., McGarry, P. A., Moossy, J., Strong, J. P., Tejada, C., and Loken, A. C., Severity of atherosclerosis in cerebral arteries, coronary arteries, and aortas. Ann. NY Acad. Sci. 149:956–973, 1968.

    Article  Google Scholar 

  8. Pancioli, A. M., Broderick, J., Kothari, R., Tuchfaber, A., Miller, R., Khoury, J., and Jauch, E., Public perceptions of stroke warning signs and knowledge of potential risk factors. JAMA 279:1288–1292, 1998.

    Article  Google Scholar 

  9. Craven, T., Ryu, J. E., Espeland, M. A., Kahl, F. R., McKinney, W. M., Toole, J. F., Mc Mahan, M. R., Thompson, C. J., Heiss, G., and Crouse, J. R., Evaluation of the associations between carotid artery atherosclerosis and coronary artery stenosis: a case-control study. Circulation 82:1288, 1990.

    Article  Google Scholar 

  10. Kallikazaros, I., Tsioufis, C., Sideris, S., Stefanadis, C., and Toutouzas, P., Carotid artery disease as a marker for presence of severe coronary artery disease in patients evaluated for chest pain. Stroke 30:1002–1007, 1999.

    Article  Google Scholar 

  11. Lerfeldt, B., Forsberg, M., Blomstrand, C., Mellström, D., and Volkmann, R., Cerebral Atherosclerosis as predictor of stroke and mortality in representative elderly population. Stroke 33:224–229, 2002.

    Article  Google Scholar 

  12. Joakimsen, O., Bønaa, K. H., Mathiesen, E. B., Strenland-Bugge, E., and Arnesen, E., Prediction of mortality by ultrasound screening of a general population for carotid stenosis. The Tromsø Study. Stroke 31:1871–1876, 2000.

    Article  Google Scholar 

  13. Chiesa, G., and Sirtori, C. R., Recombinant apolipoprotein A-I(Milano): A novel agent for the induction of regression of atherosclerotic plaques. Ann. Med. 35:267–273, 2003.

    Article  Google Scholar 

  14. Franceschini, G., Vecchio, G., Gianfranceschi, G., Magani, D., and Sirtori, C. R., Apolipoprotein AIMilano. Accelerated binding and dissociation from lipids of a human apolipoprotein variant. J. Biol. Chem. 260:16321–16325, 1985.

    Google Scholar 

  15. Gualandri, V., Franceschini, G., Sirtori, C. R., Gianfranceschi, G., Orsini, G. B., Cerrone, A., and Menotti, A., AIMilano apoprotein identification of the complete kindred and evidence of a dominant genetic transmission. Am. J. Hum. Genet. 37:1083–1097, 1985.

    Google Scholar 

  16. Nissen, S. E., Tsunoda, T., Tuzcu, E. M., Schoenhagen, P., Cooper, C. J., Yasin, M., Eaton, G. M., Lauer, M. A., Sheldon, W. S., Grines, C. L., Halpern, S., Crowe, T., Blankenship, J. C., and Kerensky, R., Effect of recombinant ApoA-I Milano on coronary atherosclerosis in patients with acute coronary syndromes: A randomized controlled trial. J. Am. Med. Assoc. 290:2292–2300, 2003.

    Article  Google Scholar 

  17. Nissen, S. E., Tuzcu, E. M., Schoenhagen, P., Brown, B. G., Ganz, P., Vogel, R. A., Crowe, T., Howard, G., Cooper, C. J., Brodie, B., Grines, C. L., and DeMaria, A. N., REVERSAL investigators. Effect of intensive compared with moderate lipid-lowering therapy on progression of coronary atherosclerosis: a randomized controlled trial. J. Am. Med. Assoc. 291:1071–1080, 2004.

    Article  Google Scholar 

  18. Gronholdt, M. L., Nordestgaard, B. G., Schroeder, T. V., Vorstrup, S., and Sillesen, H., Ultrasonic echolucent carotid plaques predict future strokes. Circulation 104:68–73, 2001.

    Article  Google Scholar 

  19. AbuRahma, A. F., Wulu, J. T., Jr., and Crotty, B., Carotid plaque ultrasonic heterogeneity and severity of stenosis. Stroke 33:1772–1775, 2002.

    Article  Google Scholar 

  20. Sabetai, M. M., Tegos, T. J., Nicolaides, A. N., El Atrozy, T. S., Dhanjil, S., Griffin, M., Belcaro, G., and Geroulakos, G., Hemispheric symptoms and carotid plaque echomorphology. J. Vasc. Surg. 31:39–49, 2000.

    Article  Google Scholar 

  21. Hatsukami, T. S., Ferguson, M. S., Beach, K. W., Gordon, D., Detmer, P. R., Burns, D. H., Alpers, C., and Strandness, D. E., Jr., Carotid plaque morphology and clinical events. Stroke 28:95–100, 1997.

    Article  Google Scholar 

  22. Droste, D. W., Karl, M., Bohle, R. M., and Kaps, M., Comparison of ultrasonic and histopathological features of carotid artery stenosis. Neurol. Res. 19:380–384, 1997.

    Google Scholar 

  23. Ringelstein, E. B., Sievers, C., Ecker, S., Schneider, P. A., and Otis, S. M., Noninvasive assessment of CO2-induced cerebral vasomotor response in normal individuals and patients with internal carotid artery occlusions. Stroke 19:963–969, 1988.

    Article  Google Scholar 

  24. Bogousslavsky, J., van der Melle, G., and Regli, F., The Lausanne stroke registry: Analysis of 1000 consecutive patients with first stroke. Stroke 19:1083–1092, 1998.

    Article  Google Scholar 

  25. Sitzer, M., Muller, W., Siebler, M., Hort, W., Kneimeyer, H. W., Janke, L., and Steinmtez, H., Plaque ulceration and lumen thrombus are the main sources of cerebral microemboli in high-grade internal carotid artery stenosis. Stroke 26:1231–1233, 1995.

    Article  Google Scholar 

  26. Golledge, J., Cuming, R., Beattie, D. K., Davies, A. H., and Greenhalgh, R. M., Clinical follow-up rather than duplex surveillance following carotid endarterectomy. J. Vasc. Surg. 25:55–63, 1997.

    Article  Google Scholar 

  27. Marcus, H. S., Thomson, N. D., and Brown, M. M., Asymptomatic cerebral embolic signals in symptomatic and asymptomatic carotid artery disease. Brain 118:1005–1011, 1995.

    Article  Google Scholar 

  28. Siebler, M., Nachtmann, A., Sitzer, M., Rose, G., Kleinscmidt, A., Rademacher, J., and Steinmetz, H., Cerebral microembolism and the risk of ischemia in asymptomatic high-grade internal carotid artery stenosis. Stroke 26:2184–2186, 1995.

    Article  Google Scholar 

  29. Schmidt, C., Fagerberg, B., Wirkstrand, J., Hulthe, J., and on behalf of the Ris study group, Multiple risk factor intervention reduces cardiovascular risk in hypertensive patients with echolucent plaques in the carotid artery. J. Intern. Med. 253:430–438, 2003.

    Article  Google Scholar 

  30. Gray-Weale, A. C., Graham, J. C., Burnett, J. R., Byrne, K., and Lusby, R. J., Carotid artery atheroma: comparison of preoperative B-mode ultrasound appearance with carotid endarterectomy specimen pathology. J. Cardiovasc. Surg. 29:676–681, 1988.

    Google Scholar 

  31. Joakimsen, O., Bøona, K. H., and Stensland-Bugge, E., Reproducibility of ultrasound assessment of carotid plaque occurrence, thickness, and morphology. The Tromsø study. Stroke 28:2201–2207, 1997.

    Article  Google Scholar 

  32. Kern, R., Szabo, K., Hennerici, M., and Meairs, S., Plaque characterization using compound ultrasound. Stroke 35:870–875, 2004.

    Article  Google Scholar 

  33. Fuster, V., Badimon, L., Badimon, J. J., and Chesebro, J. H., The pathogenesis of coronary artery disease and the acute coronary syndromes. N. Engl. J. Med. 326:310–8, 1992.

    Article  Google Scholar 

  34. Stoitsis, J., Tsiaparas, N., Golemati, S., Nikit, K. S. Characterization of carotid atherosclerotic plaques using frequency-based texture analysis and bootstrap. In: Proceedings of the 28th IEEE EMBS Annual International Conference New York City, USA, pp. 2392–2395, Aug 30–Sept 3, 2006.

  35. Stoitsis, J., Golemati, S., Tsiaparas, N., Nikita, K. S. Texture Characterization of Carotid Atherosclerotic Plaque from B-mode Ultrasound Using Gabor Filters, in: 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, pp. 455–458, September 2–6, 2009.

  36. Griffin, M. B., Kyriacou, E., Pattichis, C., Bond, D., Kakkos, S. K., Sabetai, M., Geroulakos, G., Georgiou, N., Doré, C. J., Nicolaides, A., Juxtaluminal gypoechoic area in ultrasonic images of carotid plaques and hemispheric symptoms. J. Vasc. Surg., 2010, in press.

  37. Tegos, T. J., Sohail, M., Sabetai, M. M., Robless, P., Akbar, N., Pare, G., Stansby, G., and Nicolaides, A. N., Echomorphologic and histopathologic characteristics of unstable carotid plaques. Am. J. Neuroradiol. 21:1937–1944, 2000.

    Google Scholar 

  38. Mirmehdi, M., Xie, X., and Suri, J. S., Hand book of texture analysis. Imperial College Press, UK, 2008.

    Book  Google Scholar 

  39. Gonzalez, R. C., and Woods, R. E., Digital image processing, 2nd edition. New Jersey, Prentice Hall, 2001.

    Google Scholar 

  40. Castellano, G., Bonilha, L., Li, L. M., and Cendes, F., Texture analysis of medical images. Clin. Radiol. 59:1061–1069, 2004.

    Article  Google Scholar 

  41. Tan, J. H., EYK, Ng, and Acharya, U. R., Study of normal ocular thermogram using textural parameters. Infrared Phys. Technol. 53:120–126, 2009.

    Article  Google Scholar 

  42. Galloway, M. M., Texture analysis using gray level run lengths. Comput. Graph. Image Process. 4:172–179, 1975.

    Article  Google Scholar 

  43. Aldrich, J., Doing least squares: Perspectives from Gauss and Yule. Int. Stat. Rev. 66:61–81, 1998.

    Article  MATH  Google Scholar 

  44. Bayes, T., and Price, R., An essay towards solving a problem in the doctrine of chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M. A. and F. R. S. Philos. Trans. R. Soc. Lond. 53:370–418, 1763.

    Article  Google Scholar 

  45. Krzanowski, W. J., Principles of multivariate analysis: a user's perspective. Oxford University Press, New York, 1988.

    MATH  Google Scholar 

  46. Stephen, I., Gallant Neural network learning and expert systems. MIT, Cambridge, 1993.

    Google Scholar 

  47. Iba, W., Langley, P. Induction of one-level decision trees. Proceedings of the Ninth International Conference on Machine Learning, 1992.

  48. DeLeo J. Receiver Operating Characteristic Laboratory (ROCLAB): Software for developing decision strategies that account for uncertainty management in artificial neural network decision-making. In: Proceedings of Second International Symposium on Uncertainty Modeling and Analysis, pp. 141–144, 1993.

  49. Downey, T. J., Meyer, D. J., Price, R. K., and Spitznagel, E. L., Using the receiver operating characteristic to assess the performance of neural classifiers. Neural Netw. 5:3642–3646, 1999.

    Google Scholar 

  50. Mougiakakou, S. G., Golemati, S., Gousias, I., Nicolaides, A. N., and Nikita, K. S., Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws’ texture and neural networks. Ultrasound Med. Biol. 33:26–36, 2007.

    Article  Google Scholar 

  51. Kyriacou, E., Pattichis, M. S., Christodoulou, C. I., Pattichis, C. S., Kakkos, S., Griffin, M., and Nicolaides, A., Ultrasound Imaging in the analysis of carotid plaque morphology for the assessment of stroke. Stud. Health Technol. Inform. 113:241–75, 2005.

    Google Scholar 

  52. Kyriacou, E., Pattichis, M. S., Pattichis, C. S., Mavrommatis, A., Christodoulou, C. I., Kakkos, S., and Nicolaides, S., Classification of atherosclerotic carotid plaques using morphological analysis on ultrasound images. Appl. Intell. 30:3–23, 2009.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of ECE, Ngee Ann Polytechnic, Singapore, 599489, Singapore

    Rajendra U. Acharya & A. P. C. Alvin

  2. Aberdeen University, Aberdeen, Scotland

    Oliver Faust

  3. School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50, Nanyang Avenue, Singapore, 639798, Singapore

    S. Vinitha Sree

  4. Biolab, Department of Electronics, Politecnico di Torino, Torino, Italy

    Filippo Molinari

  5. Department of Radiology, A.O.U Cagliari, Polo di Monserrato, Italy

    Luca Saba

  6. Vascular Screening Diagnostic Center Nicosia, Nicosia, Cyprus

    Andrew Nicolaides

  7. Biomedical Technologies Inc., Denver, CO, USA

    Jasjit S. Suri

  8. Idaho State University (Aff.), Pocatello, ID, USA

    Jasjit S. Suri

Authors
  1. Rajendra U. Acharya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oliver Faust
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. P. C. Alvin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. Vinitha Sree
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Filippo Molinari
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Luca Saba
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Andrew Nicolaides
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jasjit S. Suri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rajendra U. Acharya.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Acharya, R.U., Faust, O., Alvin, A.P.C. et al. Symptomatic vs. Asymptomatic Plaque Classification in Carotid Ultrasound. J Med Syst 36, 1861–1871 (2012). https://doi.org/10.1007/s10916-010-9645-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10916-010-9645-2

Keywords

Search

Navigation