Advertisement

Simultaneous extraction of carotid artery intima-media interfaces in ultrasound images: assessment of wall thickness temporal variation during the cardiac cycle

  • Guillaume ZahndEmail author
  • Maciej Orkisz
  • André Sérusclat
  • Philippe Moulin
  • Didier Vray
Original Article

Abstract

Objectives

   The aim of this work is to present and evaluate a novel segmentation method for localizing the contours of the intima-media complex in the carotid artery wall through longitudinal ultrasound B-mode imaging. The method is used to investigate the association between atherosclerosis risk factors and the cyclic variation of the intima-media thickness during the heart beat.

Methods

   The framework introduced is based on two main features. The first is a simultaneous extraction of both the lumen-intima and the media-adventitia interfaces, using the combination of an original shape-adapted filter bank and a specific dynamic programming scheme. The second is an innovative spatial transformation that eases the extraction of skewed and curved contours, and exploits the result from the previous image as a priori information, when processing the current image. The intima-media thickness is automatically derived from the estimated contours for each time step during the cardiac cycle. Our method was evaluated in vivo on 57 healthy volunteers and 25 patients at high cardiovascular risk. Reference contours were generated for each subject by averaging the tracings performed by three experienced observers.

Results

   Segmentation errors were \(29 \pm 27\,\upmu \hbox {m}\) for the lumen-intima interface, \(42 \pm 38\,\upmu \hbox {m}\) for the media-adventitia interface, and \(22 \pm 16\,\upmu \hbox {m}\) for the intima-media thickness. This uncertainty was similar to inter- and intra-observer variability. Furthermore, the amplitude of the temporal variation in thickness of the intima-media layers during the cardiac cycle was significantly higher in at-risk patients compared to healthy volunteers \((79 \pm 36\) vs. \(64 \pm 26\,\upmu \hbox {m},\, p=0.032)\).

Conclusion

   The method proposed may provide a relevant diagnostic aid for atherosclerosis screening in clinical studies.

Keywords

Atherosclerosis Carotid artery Contour segmentation Dynamic programming Intima-media thickness  Shape-adapted filter 

Notes

Acknowledgments

This work was done within the French ANR Labex PRIMES and CeLyA. The authors would like to thank Dr. ir. Theo van Walsum, Dr. ir. Stefan Klein, and Dr. Aad van der Lugt for their valuable suggestions when proofreading the manuscript.

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Acharya UR, Vinitha Sree S, Muthu Rama Krishnan M, Molinari F, Saba L, Ho SYS, Ahuja AT, Ho SC, Nicolaides A, Suri JS (2012) Atherosclerotic risk stratification strategy for carotid arteries using texture-based features. Ultrasound Med Biol 38(6):899–915PubMedCrossRefGoogle Scholar
  2. 2.
    Baldassarre D, Amato M, Bondioli A, Sirtori CR, Tremoli E (2000) Carotid artery intima-media thickness measured by ultrasonography in normal clinical practice correlates well with atherosclerosis risk factors. Stroke 31(10):2426–2430PubMedCrossRefGoogle Scholar
  3. 3.
    Bellman R (1966) Dynamic programming. Science 153(3731): 34–37Google Scholar
  4. 4.
    Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327(8476):307–310CrossRefGoogle Scholar
  5. 5.
    Bots ML, Hoes AW, Koudstaal PJ, Hofman A, Grobbee DE (1997) Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam study. Circulation 96(5):1432–1437PubMedCrossRefGoogle Scholar
  6. 6.
    Boutouyrie P, Germain DP, Tropeano AI, Laloux B, Carenzi F, Zidi M, Jeunemaitre X, Laurent S (2001) Compressibility of the carotid artery in patients with pseudoxanthoma elasticum. Hypertension 38(5):1181–1184PubMedCrossRefGoogle Scholar
  7. 7.
    Burke GL, Evans G, Riley WA, Sharrett AR, Howard G, Barnes RW, Rosamond W, Crow RS, Rautaharju PM, Heiss G (1995) Arterial wall thickness is associated with prevalent cardiovascular disease in middle-aged adults: the Atherosclerosis Risk in Communities (ARIC) study. Stroke 26(3):386–391PubMedCrossRefGoogle Scholar
  8. 8.
    Celermajer DS, Sorensen KE, Gooch VM, Sullivan ID, Lloyd JK, Deanfield JE, Spiegelhalter DJ (1992) Non-invasive detection of endothelial dysfunction in children and adults at risk of atherosclerosis. Lancet 340(8828):1111–1115PubMedCrossRefGoogle Scholar
  9. 9.
    Cheng DC, Jiang X (2008) Detections of arterial wall in sonographic artery images using dual dynamic programming. IEEE Trans Inf Technol Biomed 12(6):792–799PubMedCrossRefGoogle Scholar
  10. 10.
    Cheng DC, Schmidt-Trucksäss A, Cheng K, Burkhardt H (2002) Using snakes to detect the intimal and adventitial layers of the common carotid artery wall in sonographic images. Comput Methods Program Biomed 67(1):27–37CrossRefGoogle Scholar
  11. 11.
    Cinthio M, Jansson T, Ahlgren ÅR, Lindström K, Persson HW (2010) A method for arterial diameter change measurements using ultrasonic B-mode data. Ultrasound Med Biol 36(9):1504–1512PubMedCrossRefGoogle Scholar
  12. 12.
    Cinthio M, Jansson T, Persson HW, Lindstrom K, Ahlgren ÅR (2005) New non-invasive method for intima-media thickness and intima-media compression measurements. In: IEEE international ultrasonics symposium, vol 1, Rotterdam, Netherlands, pp 385–388Google Scholar
  13. 13.
    Cohen L (2006) Minimal paths and fast marching methods for image analysis. In: Paragios N, Chen Y, Faugeras O (eds) Handbook of mathematical models in computer vision. Springer, US, pp 97–111Google Scholar
  14. 14.
    Delsanto S, Molinari F, Giustetto P, Liboni W, Badalamenti S, Suri JS (2007) Characterization of a completely user-independent algorithm for carotid artery segmentation in 2-D ultrasound images. IEEE Trans Instrum Meas 56(4):1265–1274CrossRefGoogle Scholar
  15. 15.
    Destrempes F, Meunier J, Giroux MF, Soulez G, Cloutier G (2009) Segmentation in ultrasonic B-mode images of healthy carotid arteries using mixtures of Nakagami distributions and stochastic optimization. IEEE Trans Med Imaging 28(2):215–229PubMedCrossRefGoogle Scholar
  16. 16.
    Faita F, Gemignani V, Bianchini E, Giannarelli C, Ghiadoni L, Demi M (2008) Real-time measurement system for evaluation of the carotid intima-media thickness with a robust edge operator. J Ultrasound Med 27(9):1353–1361PubMedGoogle Scholar
  17. 17.
    Ford ES (2005) Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence. Diabetes Care 28(7):1769–1778PubMedCrossRefGoogle Scholar
  18. 18.
    Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S (2007) Explaining the decrease in US deaths from coronary disease, 1980–2000. N Engl J Med 356(23):2388–2398PubMedCrossRefGoogle Scholar
  19. 19.
    Gemignani V, Faita F, Ghiadoni L, Poggianti E, Demi M (2007) A system for real-time measurement of the brachial artery diameter in B-mode ultrasound images. IEEE Trans Med Imaging 26(3):393–404PubMedCrossRefGoogle Scholar
  20. 20.
    Golemati S, Gastounioti A, Nikita KS (2013) Toward novel noninvasive and low-cost markers for predicting strokes in asymptomatic carotid atherosclerosis: the role of ultrasound image analysis. IEEE Trans Biomed Eng 60(3):653CrossRefGoogle Scholar
  21. 21.
    Golemati S, Stoitsis J, Sifakis EG, Balkizas T, Nikita KS (2007) Using the Hough transform to segment ultrasound images of longitudinal and transverse sections of the carotid artery. Ultrasound Med Biol 33(12):1918–1932PubMedCrossRefGoogle Scholar
  22. 22.
    Haller C, Schulz J, Schmidt-Trucksäss A, Burkardt H, Schmitz D, Dickhuth HH, Sandrock M (2007) Sequential based analysis of intima-media thickness (IMT) in common carotid artery studies. Atherosclerosis 195(2):e203–e209PubMedCrossRefGoogle Scholar
  23. 23.
    Ilea DE, Duffy C, Kavanagh L, Stanton A, Whelan PF (2013) Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery. IEEE Trans Ultrason Ferroelectr Freq Control 60(1):158–177PubMedCrossRefGoogle Scholar
  24. 24.
    Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L, Ducimetiere P, Benetos A (2001) Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension 37(5):1236–1241PubMedCrossRefGoogle Scholar
  25. 25.
    Lee YB, Choi YJ, Kim MH (2010) Boundary detection in carotid ultrasound images using dynamic programming and a directional Haar-like filter. Comput Biol Med 40(8):687–697PubMedCrossRefGoogle Scholar
  26. 26.
    Liang Q, Wendelhag I, Wikstrand J, Gustavsson T (2000) A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images. IEEE Trans Med Imaging 19(2):127–142PubMedCrossRefGoogle Scholar
  27. 27.
    Loizou CP, Pattichis CS, Pantziaris M, Tyllis T, Nicolaides A (2007) Snakes based segmentation of the common carotid artery intima media. Med Biol Eng Comput 45(1):35–49PubMedCrossRefGoogle Scholar
  28. 28.
    Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M (2007) Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation 115(4):459–467PubMedCrossRefGoogle Scholar
  29. 29.
    Meinders JM, Kornet L, Hoeks APG (2003) Assessment of spatial inhomogeneities in intima media thickness along an arterial segment using its dynamic behavior. Am J Physiol-Heart Circ Physiol 285(1):H384–H391PubMedGoogle Scholar
  30. 30.
    Metz CT, Klein S, Schaap M, van Walsum T, Niessen WJ (2011) Nonrigid registration of dynamic medical imaging data using nD+t B-splines and a groupwise optimization approach. Med Image Anal 15(2):238–249PubMedCrossRefGoogle Scholar
  31. 31.
    Molinari F, Liboni W, Giustetto P, Badalamenti S, Suri JS (2009) Automatic computer-based tracings (ACT) in longitudinal 2-D ultrasound images using different scanners. J Mech Med Biol 9(04):481–505CrossRefGoogle Scholar
  32. 32.
    Molinari F, Zeng G, Suri JS (2010) A state of the art review on intima-media thickness (IMT) measurement and wall segmentation techniques for carotid ultrasound. Comput Methods Program Biomed 100(3):201–221CrossRefGoogle Scholar
  33. 33.
    Molinari F, Zeng G, Suri JS (2011) Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images. Med Biol Eng Comput 49(8):177–192CrossRefGoogle Scholar
  34. 34.
    Nilsson T, Ahlgren ÅR, Jansson T, Persson HW, Lindström K, Nilsson J, Cinthio M (2011) A method for measuring the variation of intima-media thickness during the entire cardiac cycle using B-mode images. In: IEEE international ultrasonics symposium, Orlando, FL, pp 2126–2129Google Scholar
  35. 35.
    O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson SKJ (1999) Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. N Engl J Med 340(1):14–22PubMedCrossRefGoogle Scholar
  36. 36.
    Pannier B, Guerin AP, Marchais SJ, Metivier F, Safar ME, London GM (2000) Postischemic vasodilation, endothelial activation, and cardiovascular remodeling in end-stage renal disease. Kidney Int 57(3):1091–1099PubMedCrossRefGoogle Scholar
  37. 37.
    Polak JF, Johnson C, Harrington A, Wong Q, O’Leary DH, Burke G, Yanez ND: Changes in carotid intima-media thickness during the cardiac cycle: the multi-ethnic study of atherosclerosis. J Am Heart Assoc 1(4) (2012). doi: 10.1161/JAHA.112.001420
  38. 38.
    Polak JF, Meisner A, Pencina MJ, Wolf PA, D’Agostino RB (2012) Variations in common carotid artery intima-media thickness during the cardiac cycle: implications for cardiovascular risk assessment. J Am Soc Echocardiogr 25(9):1023–1028PubMedCentralPubMedCrossRefGoogle Scholar
  39. 39.
    Rocha R, Campilho A, Silva J, Azevedo E, Santos R (2010) Segmentation of the carotid intima-media region in B-mode ultrasound images. Image Vis Comput 28(4):614–625CrossRefGoogle Scholar
  40. 40.
    Rossi AC, Brands PJ, Hoeks APG (2010) Automatic localization of intimal and adventitial carotid artery layers with noninvasive ultrasound: a novel algorithm providing scan quality control. Ultrasound Med Biol 36(3):467–479PubMedCrossRefGoogle Scholar
  41. 41.
    Sandrock M, Hansel J, Schulze J, Schmitz D, Niess A, Burkhardt H, Schmidt-Trucksäss A (2008) Sequentially based analysis versus image based analysis of intima media thickness in common carotid arteries studies—do major IMT studies underestimate the true relations for cardio-and cerebrovascular risk? Cardiovasc Ultrasound 6(32):1–8Google Scholar
  42. 42.
    Schaar JA, Muller JE, Falk E, Virmani R, Fuster V, Serruys PW, Colombo A, Stefanadis C, Ward CS, Moreno PR, Maseri A, van der Steen AFW (2003) Terminology for high-risk and vulnerable coronary artery plaques. Report of a meeting on the vulnerable plaque, June 17 and 18, (2003) Santorini, Greece. Eur Heart J 25(12):1077–1082 CrossRefGoogle Scholar
  43. 43.
    Selzer RH, Hodis HN, Kwong-Fu H, Mack WJ, Lee PL, Liu CR, Liu CH (1994) Evaluation of computerized edge tracking for quantifying intima-media thickness of the common carotid artery from B-mode ultrasound images. Atherosclerosis 111(1):1–11PubMedCrossRefGoogle Scholar
  44. 44.
    Selzer RH, Mack WJ, Lee PL, Kwong-Fu H, Hodis HN (2001) Improved common carotid elasticity and intima-media thickness measurements from computer analysis of sequential ultrasound frames. Atherosclerosis 154(1):185–193PubMedCrossRefGoogle Scholar
  45. 45.
    Sethian JA (1996) A fast marching level set method for monotonically advancing fronts. Proc Natl Acad Sci 93(4):1591–1595PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Teynor A, Caviezel S, Dratva J, Künzli N, Schmidt-Trucksäss A (2012) An automated, interactive analysis system for ultrasound sequences of the common carotid artery. Ultrasound Med Biol 38(8):1440–1450PubMedCrossRefGoogle Scholar
  47. 47.
    Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N, Csiba L, Desvarieux M, Ebrahim S, Jaff M, Kownator S, Naqvi T, Prati P, Rundek T, Sitzer M, Schminke U, Tardif JC, Taylor A, Vicaut E, Woo KS (2012) Mannheim carotid intima-media thickness and plaque consensus (2004–2006–2011). Cerebrovasc Dis 34:290–296PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Trawiński Z (2008) Ultrasonic method for relative changes of intima-media thickness measurements in common carotid artery. Hydroacoustics 11:411–418Google Scholar
  49. 49.
    Trawiński Z, Powałowski T (2006) Modeling and ultrasonic examination of common carotid artery wall thickness changes. Arch Acoust 31:29–34Google Scholar
  50. 50.
    Wijeysundera HC, Machado M, Farahati F, Wang X, Witteman W, van der Velde G, Tu JV, Lee DS, Goodman SG, Petrella R, O’Flaherty M, Krahn M, Capewell S (2010) Association of temporal trends in risk factors and treatment uptake with coronary heart disease mortality, 1994–2005. JAMA J Am Med Assoc 303(18):1841–1847CrossRefGoogle Scholar
  51. 51.
    Wikstrand J (2007) Methodological considerations of ultrasound measurement of carotid artery intima-media thickness and lumen diameter. Clin Physiol Funct Imaging 27(6):341–345PubMedCrossRefGoogle Scholar
  52. 52.
    Woodman RJ, Playford DA, Watts GF, Cheetham C, Reed C, Taylor RR, Puddey IB, Beilin LJ, Burke V, Mori TA, Green D (2001) Improved analysis of brachial artery ultrasound using a novel edge-detection software system. J Appl Physiol 91(2):929–937PubMedGoogle Scholar
  53. 53.
    Zahnd G, Vray D, Sérusclat A, Alibay D, Bartold M, Brown A, Durand M, Jamieson LM, Kapellas K, Maple-Brown LJ, O’Dea K, Moulin P, Celermajer DS, Skilton MR (2012) Longitudinal displacement of the carotid wall and cardiovascular risk factors: associations with aging, adiposity, blood pressure and periodontal disease independent of cross-sectional distensibility and intima-media thickness. Ultrasound Med Biol 38(10):1705–1715PubMedCrossRefGoogle Scholar

Copyright information

© CARS 2013

Authors and Affiliations

  • Guillaume Zahnd
    • 1
    • 2
    Email author
  • Maciej Orkisz
    • 1
  • André Sérusclat
    • 3
  • Philippe Moulin
    • 4
    • 5
  • Didier Vray
    • 1
  1. 1.CREATIS, CNRS UMR 5220, INSERM U1044, INSA-Lyon, Université Lyon 1Université de LyonLyonFrance
  2. 2.Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical InformaticsErasmus MCRotterdamThe Netherlands
  3. 3.Department of RadiologyLouis Pradel HospitalLyonFrance
  4. 4.Department of EndocrinologyLouis Pradel Hospital, Hospices Civils de Lyon, Université LyonLyonFrance
  5. 5.INSERM UMR 1060LyonFrance

Personalised recommendations