Abstract
Neurodegenerative diseases are often associated with loss of brain tissue volume. Our objective was to develop and evaluate a fully automated method to estimate cerebral volume from magnetic resonance images (MRI) of patients with multiple sclerosis (MS). In this study, MRI data from 17 normal subjects and 68 untreated MS patients was used to test the method. Each MRI volume was corrected for image intensity non-uniformity, intensity normalized, brain masked and tissue classified. The classification results were used to compute a normalized metric of cerebral volume based on the Brain to IntraCranial Capacity Ratio (BICCR).
This paper shows that the computation of BICCR using automated techniques provides a highly reproducible measurement of relative brain tissue volume that eliminates the need for precise repositioning. Initial results indicate that the measure is both robust and precise enough to monitor MS patients over time to estimate brain atrophy. In addition, brain atrophy may yield a more sensitive endpoint for treatment trials in MS and possibly for other neuro-degenerative diseases such as Huntington’s or Alzheimer’s disease.
Acknowledgements
Funding for this work was provided by the Medical Research Council of Canada.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
J. F. Kurtzke, “Rating neurologic impairment in multiple sclerosis: An expanded disability status scale,” Neurology, vol. 33, pp. 1444–1452, 1983.
B. D. Trapp, J. Peterson, R. M. Ransohoff, R. Rudick, S. Mork, and B. Lars, “Axonal transection in the lesions of multiple sclerosis,” New England Journal of Medicine, vol. 338, pp. 278-85, 1998.
J. Simon, L. Jacobs, M. Campion, et al. “A longitudinal study of brain atrophy in relapsing multiple sclerosis. the multiple sclerosis collaborative research group (MSCRG)., ” Neurology, vol. 53, no. 1, pp. 139-48, 1999.
R. Rudick, E. Fisher, J.-C. Lee, J. Simon, D. Miller, and L. Jacobs, “The effect of avonex (ifnβ-1a) on cerebral atrophy in relapsing multiple sclerosis,” Neurology, vol. 52, pp. A289–290, Apr 1999.
M. Filippi, G. Mastronardo, M. A. Rocca, C. Pereira, and G. Comi, “Quantitative volumetric analysis of brain magnetic resonance imaging from patients with multiple sclerosis,” J Neurol Sci, vol. 158, pp. 148-53, Jun 30 1998.
E. Fisher, R. Rudick, J. Tkach, J.-C. Lee, T. Masaryk, J. Simon, J. Cornhill, and J. Cohen, “Automated calculation of whole brain atrophy from magenetic resonance images for monitoring multiple sclerosis,” Neurology, vol. 52:A352, 1999.
J. G. Sled, A. P. Zijdenbos, and A. C. Evans, “A non-parametric method for automatic correction of intensity non-uniformity in MRI data,” IEEE Transactions on Medical Imaging, vol. 17, Feb. 1998.
A. C. Evans, D. L. Collins, and B. Milner, “An MRI-based stereotactic atlas from 250 young normal subjects,” Soc.Neurosci.Abstr., vol. 18, p. 408, 1992.
D. L. Collins, P. Neelin, T. M. Peters, and A. C. Evans, “Automatic 3D intersubject registration of MR volumetric data in standardized talairach space,” Journal of Computer Assisted Tomography, vol. 18, pp. 192–205, March/April 1994.
J. R. Mitchell, S. J. Karlik, D. H. Lee, M. Eliasziw, G. P. Rice, and A. Fenster, “Quantification of multiple sclerosis lesion volumes in 1.5 and 0.5T anisotropically filtered and unfiltered MR exams,” Medical Physics, vol. 23:115–126; 1996.
A. P. Zijdenbos, B. M. Dawant, R. A. Margolin, and A. C. Palmer, “Morphometric analysis of white matter lesions in MR images: Method and validation,” IEEE Transactions on Medical Imaging, vol. 13, pp. 716–724, Dec. 1994.
P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, pp. 629–639, July 1990.
G. Gerig, O. Kübler, R. Kikinis, and F. A. Jolesz, “Nonlinear anisotropic filtering of MRI data,” IEEE Transactions on Medical Imaging, vol. 11:221–232; 1992.
R. Duda and P. Hart, Pattern Recognition Scene Analysis. New York: Wiley, 1973.
J. Serra, Image Analysis, Mathematical Morphology. London: Academic Press, 1982.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Collins, D.L., Montagnat, J., Zijdenbos, A.P., Evans, A.C., Arnold, D.L. (2001). Automated Estimation of Brain Volume in Multiple Sclerosis with BICCR. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_12
Download citation
DOI: https://doi.org/10.1007/3-540-45729-1_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42245-7
Online ISBN: 978-3-540-45729-9
eBook Packages: Springer Book Archive