Advertisement

Evaluation of semi-automatic arterial stenosis quantification

  • Marcela Hernández Hoyos
  • Jean-Michel Serfaty
  • Albinka Maghiar
  • Catherine Mansard
  • Maciej Orkisz
  • Isabelle E. Magnin
  • Philippe C. Douek
Original article

Abstract

Object: To assess the accuracy and reproducibility of semi-automatic vessel axis extraction and stenosis quantification in 3D contrast-enhanced Magnetic Resonance Angiography (CE-MRA) of the carotid arteries (CA).

Materials and methods: A total of 25 MRA datasets was used: 5 phantoms with known stenoses, and 20 patients (40 CAs) drawn from a multicenter trial database. Maracas software extracted vessel centerlines and quantified the stenoses, based on boundary detection in planes perpendicular to the centerline. Centerline accuracy was visually scored. Semi-automatic measurements were compared with: (1) theoretical phantom morphometric values, and (2) stenosis degrees evaluated by two independent radiologists.

Results: Exploitable centerlines were obtained in 97% of CA and in all phantoms. In phantoms, the software achieved a better agreement with theoretic stenosis degrees (weighted kappa κ w =  0.91) than the radiologists (κ w   =   0.69). In patients, agreement between software and radiologists varied from κ w =0.67 to 0.90. In both, Maracas was substantially more reproducible than the readers. Mean operating time was within 1 min/ CA.

Conclusion: Maracas software generates accurate 3D centerlines of vascular segments with minimum user intervention. Semi-automatic quantification of CA stenosis is also accurate, except in very severe stenoses that cannot be segmented. It substantially reduces the inter-observer variability.

Keywords

Vascular diseases Carotid artery stenosis Magnetic resonance angiography Three-dimensional image Computer assisted image processing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lee VS, Doug JM, Krinsky GA, Rofsky NM (2000) Gadolinium-enhanced MR angiography: artifacts and pitfalls. Am J Roentgenol 175:197–205Google Scholar
  2. 2.
    Barbier C, Lefevre F, Bui P, Denny P, Aiouaz C, Becker S (2001) Contrast-enhanced MRA of the carotid arteries using 0.5 Tesla: comparison with selective digital angiography. J Radiol 82:245–249PubMedGoogle Scholar
  3. 3.
    Vanninen RL, Manninen HI, Partanen PK, Tulla H, Vainio PA (1996) How should we estimate carotid stenosis using magnetic resonance angiography? Neuroradiol 38:299–305Google Scholar
  4. 4.
    Serfaty JM, Chirossel P, Chevallier JM, Ecochard R, Froment JC, Douek PC (2000) Accuracy of three-dimensional gadolinium-enhanced MR Angiography in the assessment of extracranial carotid artery disease. Am J Roentgenol 175: 455–463Google Scholar
  5. 5.
    van Bemmel CM, Elgersma OEH, Vonken EPA, Fiorelli M, Leeuven MS, Niessen WJ (2004) Evaluation of semiautomated internal carotid artery stenosis quantification from 3-dimensional contrast-enhanced MRA. Invest Radiol 39:418–426PubMedCrossRefGoogle Scholar
  6. 6.
    van Bemmel CM, Viergever MA, Niessen WJ (2004) Semiautomatic segmentation and stenosis quantification of 3D contrast-enhanced MR Angiograms of the internal carotid artery. Magn Reson Med 51:753–760PubMedCrossRefGoogle Scholar
  7. 7.
    Wong KS, Lam WW, Liang E, Huang YN, Chan YL, Kay R (1996) Variability of magnetic resonance angiography and computed tomography angiography in grading middle cerebral artery stenosis. Stroke 6:1084–1087Google Scholar
  8. 8.
    NASCET Partners (1991) Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. N Engl J Med 325:445–453CrossRefGoogle Scholar
  9. 9.
    ECAAS Partners (1995) Endarterectomy for asymptomatic carotid artery stenosis. JAMA 273:1421–1428CrossRefGoogle Scholar
  10. 10.
    Elgersma OE, Wust AF, Buijs PC, van Der Graaf Y, Eikelboom BC, Mali WP (2000) Multidirectional depiction of internal carotid arterial stenosis: three-dimensional time-of-flight MR angiography versus rotational and conventional digital subtraction angiography. Radiol 216:511–516Google Scholar
  11. 11.
    Hernández Hoyos M, Orkisz M, Puech P, Mansard-Desbleds C, Douek P, Magnin IE (2002) Computer assisted analysis of 3D MRA images. Radiographics 22:421–436PubMedGoogle Scholar
  12. 12.
    Hernández Hoyos M, Orkisz M, Douek PC, Magnin IE (2005) Assessment of carotid artery stenoses in 3D contrast-enhanced magnetic resonance angiography, based on improved generation of the centerline. Mach Graph Vis 14:349–378Google Scholar
  13. 13.
    Hernández Hoyos M, Orlowski P, Piatkowska-Janko E, Bogorodzki P, Orkisz M (2006) Vascular centerline extraction in 3D MR angiograms for phase contrast MRI blood flow measurement. J Comput Assist Radiol Surg 1:51–61CrossRefGoogle Scholar
  14. 14.
    Mukundan R, Ramakrishnan KR (1998) Moment functions in image analysis, theory and applications. World Scientific Publishing Co. Pte. Ltd., Singapore 150 pGoogle Scholar
  15. 15.
    Hofman M, Visser F, van Rossum A, Vink Q, Sprenger M, Westerhof N (1995) In vivo validation of magnetic resonance blood volume flow measurements with limited spatial resolution in small vessels. Magn Reson Med 33:778–784PubMedGoogle Scholar
  16. 16.
    Hoogeveen R, Bakker C, Mali W, Viergever M (1997) diameter measurements in TOF and PC angiography: a need for standardization? In: 5th annual meeting International Society of Magnetic Resonance Medicine, Vancouver, p 1847Google Scholar
  17. 17.
    Hoogeveen RM, Bakker C, Viergever MA (1998) Limits to the accuracy of vessel diameter measurement in MR Angiography. J Magn Reson Imaging 8:1228–1235PubMedGoogle Scholar
  18. 18.
    Frangi AF, Niessen WJ, Hoogeveen RM, Walsum T, Viergever MA (1999) Model-based quantitation of 3-D magnetic resonance angiographic images. IEEE Trans Med Imaging 18:946–956PubMedCrossRefGoogle Scholar
  19. 19.
    Renaudin CP, Barbier B, Roriz R, Revel D, Amiel M (1994) Coronary arteries: new design for three-dimensional arterial phantom. Radiol 190:579–582Google Scholar
  20. 20.
    Nonent M, Serfaty J-M, Nigoghossian N, Rouhart F, Derex L, Rotaru C, et al. (2004) Concordance rate differences of 3 noninvasive imaging techniques to measure carotid stenosis in clinical routine practice: results of the CARMEDAS multicenter study. Stroke 2235:682–686CrossRefGoogle Scholar
  21. 21.
    Douek P, Revel D, Chazel S, Falise B, Villard J, Amiel M (1995) Fast MR angiography of the aortoiliac arteries and arteries of the lower extremity: value of bolus-enhanced, whole-volume subtraction technique. Am J Roentgenol 165:431–437Google Scholar
  22. 22.
    Bland J, Altman D (1986) Statistical method for assessing agreement between two methods of clinical measurement. Lancet I:307–310Google Scholar

Copyright information

© CARS 2006

Authors and Affiliations

  • Marcela Hernández Hoyos
    • 1
    • 3
  • Jean-Michel Serfaty
    • 1
    • 2
  • Albinka Maghiar
    • 2
  • Catherine Mansard
    • 1
  • Maciej Orkisz
    • 1
  • Isabelle E. Magnin
    • 1
  • Philippe C. Douek
    • 1
    • 2
  1. 1.CREATIS Research Unit, CNRS (UMR 5515), INSERM (U630)INSA de Lyon and Université Claude Bernard Lyon 1, INSA – Blaise PascalVilleurbanne CedexFrance
  2. 2.Département de RadiologieHôpital Cardiovasculaire et Pneumologique L. PradelBronFrance
  3. 3.Grupo de Ingeniería Biomédica, Grupo ImagíneUniversidad de los AndesBogotaColombia

Personalised recommendations