Vessel Wall Quantification

Automated quantification of vessel wall MR imaging studies

NWO (Dutch Organization for Scientific Research) in the form of a Casimir grant
Rob J. van der Geest, PhD


Black-blood vessel wall MRI can be used for visualization of the luminal and outer wall boundaries of the carotid arteries and the aorta. Measurement of the thickness of the vessel wall is relevant for assessment of progression or regression of disease. In this project, automated methods are developed for quantification of parameters describing the status of the vessel wall from MR imaging studies.


The goal of this project is to develop tools for accurate and reproducible measurement of the vessel wall status from MR vessel wall studies.


The developed contour detection is highly automated. The user has to identify the approximate center of the vessel wall in a cross-sectional image. The outer contour is detected based on ellipse fitting, followed by dynamic programming. The lumen contour is detected inside the region defined by the detected outer contour. As the lumen contour can have a more irregular shape, less constraint can be imposed on the contour shape. An automated optimization system has been implemented allowing obtaining optimal settings of the contour detection algorithm for image data from various anatomical regions, MR systems and particular pulse sequences. Plaque components in the vessel wall can be identified manually.


A software package, VesselMASS, has been developed providing semi-automated contour detection of the lumen and outer wall boundaries. VesselMASS is being used in various large scale clinical trials.

Figure 1
Figure 1
Screen shot of the VesselMASS software package showing automatically detected lumen and outer wall contours of the carotid artery. The graph shows the average vessel wall thickness for each slice level.


  1. Adame, IM, van der Geest RJ, Mohamed M, Wasserman BA, Reiber JHC, Lelieveldt BPF. Automatic Plaque Characterization and Vessel Wall Segmentation in Magnetic Resonance Images of Atherosclerotic Carotid Arteries, SPIE. Medical Imaging 2004; 5370,:265-273, 2004.
  2. Adame IM, van der Geest RJ, Wasserman BA, Mohamed M, Reiber JHC, Lelieveldt BPF. Automatic segmentation and plaque characterization in atherosclerotic carotid artery MR images MAGMA (Magnetic Resonance Materials in Physics, Biology and Medicine) 2004;16 (5): 227-234.
  3. Adame IM, de Koning PJH, Lelieveldt BPF, Wasserman BA, Reiber JHC, van der Geest RJ. An integrated automated analysis method for quantifying vessel stenosis and plaque burden from carotid MRI images: Combined postprocessing of MRA and vessel wall MR. Stroke 2006;37(8):2162-2164.
  4. Adame IM, van der Geest RJ, Bluemke DA, Lima JA, Reiber JHC, Lelieveldt RBF. Automatic vessel wall contour detection and quantification of wall thickness in in-vivo MR images of the human aorta. J Magn Reson Imaging. 2006;24:595-602.
  5. Alizahed Dehnavi RA, Doornbos J, Tamsma JT, Stuber M, Putter H, van der Geest RJ, Lamb HJ, de Roos A. Assessment of the carotid artery by MRI at 3T: A study on reproducibility. J. Magn. Reson. Imaging 2007;25:1035-1043.
  6. Roes SD, Westenberg JJ, Doornbos J, van der Geest RJ, Angelié E, de Roos A, Stuber M. Aortic vessel wall magnetic resonance imaging at 3.0 tesla: A reproducibility study of respiratory navigator gated free-breathing 3D black blood magnetic resonance imaging. Magn Reson Med 2009; 61:35-44.
  7. El Aidi H, Mani V, Weinshelbaum KB, Aguiar SH, Taniguchi H, Postley JE, Samber DD, Cohen EI, Stern J, van der Geest RJ, Reiber JH, Woodward M, Fuster V, Gidding SS, Fayad ZA. Cross-sectional, prospective study of MRI reproducibility in the assessment of plaque burden of the carotid arteries and aorta. Nat Clin Pract Cardiovasc Med 2009;6(3)219-228.
  8. Mani V, Muntner P, Gidding SS, Aguiar SH, El Aidi H, Weinshelbaum KB, Taniguchi H, van der Geest RJ, Reiber JH, Bansilal S, Farkouh M, Fuster V, Postley JE, Woodward M, Fayad ZA. Cardiovascular magnetic resonance parameters of atherosclerotic plaque burden improve discrimination of prior major adverse cardiovascular events. J Cardiovasc Magn Reson. 2009;11(1):10.
  9. Kornaat PR, Sharma R, van der Geest RJ, Lamb HJ, Kloppenburg M, Hellio le Graverand MP, Bloem JL, Watt I. Positive association between increased popliteal artery vessel wall thickness and generalized osteoarthritis: is OA also part of the metabolic syndrome? Skeletal Radiol. 2009.
  10. Duivenvoorden R, de Groot E, Elsen BM, Lameris JS, van der Geest RJ, Stroes ES, Kastelein JJP, Nederveen AJ. In Vivo Quantification of Carotid Artery Wall Dimensions 3.0-Tesla MRI Versus B-Mode Ultrasound Imaging. Circ Cardiovasc Imaging 2009;2(3):235-242.
  11. Kwee RM, Teule GJJ, van Oostenbrugge RJ, Mess WH, Prins MH, van der Geest RJ, ter Berg JWM, Franke CL, Korten AGGC, Meems BJ, Hofman PAM, van Engelshoven JMA, Wildberger JE, Kooi EM. Multimodality Imaging of Carotid Artery Plaques 18F-Fluoro-2-Deoxyglucose Positron Emission Tomography, Computed Tomography, and Magnetic Resonance Imaging. Stroke. 2009;40:3718-3724.
  12. Lobbes MB, Heeneman S, Passos VL, Welten R, Kwee RM, van der Geest RJ, Wiethoff AJ, Caravan P, Misselwitz B, Daemen MJ, van Engelshoven JM, Leiner T, Kooi ME. Gadofosveset-enhanced magnetic resonance imaging of human carotid atherosclerotic plaques: A proof-of-concept study. Invest Radiol. 2010;45(5):275-281.
  13. Kwee RM, van Oostenbrugge RJ, Mess WH, Prins MH, van der Geest RJ, Ter Berg JW, Franke CL, Korten AG, Meems BJ, van Engelshoven JM, Wildberger JE, Kooi ME. Carotid plaques in transient ischemic attack and stroke patients: One-year follow-up study by magnetic resonance imaging. Invest Radiol. 2010;45(12):803-809.
  14. Gerretsen SC, Kooi ME, Kessels AG, Schalla S, Katoh M, van der Geest RJ, Manning WJ, Waltenberger J, van Engelshoven JM, Botnar RM, Leiner T. Visualization of coronary wall atherosclerosis in asymptomatic subjects and patients with coronary artery disease using magnetic resonance imaging. PLoS One. 2010 Sep 29;5(9):e12998.
  15. Te Boekhorst BC, van 't Klooster R, Bovens SM, van de Kolk KW, Cramer MJ, van Oosterhout MF, Doevendans PA, van der Geest RJ, Pasterkamp G, van Echteld CJ. Evaluation of multicontrast MRI including fat suppression and inversion recovery spin echo for identification of intra-plaque hemorrhage and lipid core in human carotid plaque using the mahalanobis distance measure. Magn Reson Med. 2011 Oct 13. doi: 10.1002/mrm.23191. [Epub ahead of print].
  16. van 't Klooster R, de Koning PJ, Dehnavi RA, Tamsma JT, de Roos A, Reiber JH, van der Geest RJ. Automatic lumen and outer wall segmentation of the carotid artery using deformable three-dimensional models in MR angiography and vessel wall images. Magn Reson Imaging. 2011;35(1):156-165.


Rob J. van der Geest, PhD
Division of Image Processing
Department of Radiology, 1-C2S
Leiden University Medical Center
P.O. Box 9600
2300 RC Leiden
The Netherlands
Tel. +31 (0)71 526 2138
Fax. +31 (0)71 526 6801