Color Fusion of Magnetic Resonance Images Improves Intracranial Volume Measurement in Studies of Aging

Abstract

Background: Comparison of intracranial volume (ICV) measurements in different subpopulations offers insight into age-related atrophic change and pathological loss of neuronal tissue. For such comparisons to be meaningful the accuracy of ICV measurement is paramount. Color magnetic resonance images (MRI) have been utilised in several research applications and are reported to show promise in the clinical arena. Methods: We selected a sample of 150 older community-dwelling individuals (age 71 to 72 years) representing a wide range of ICV, white matter lesions and atrophy. We compared the extraction of ICV by thresholding on T2*-weighted MR images followed by manual editing (reference standard) done by an analyst trained in brain anatomy, with thresholding plus computational morphological operations followed by manual editing on a framework of a color fusion technique (MCMxxxVI) and two automatic brain segmentation methods widely used, these last three done by two image analysts. Results: The range of ICV was 1074 to 1921 cm3 for the reference standard. The mean difference between the reference standard and the ICV measured using the technique that involved the color fusion was 2.7%, while it was 5.4% compared with any fully automatic technique. However, the 95% confidence interval of the difference between the reference standard and each method was similar: it was 7% for the segmentation aided by the color fusion and was 7% and 8.3% for the two fully automatic methods tested. Conclusion: For studies of aging, the use of color fusion MRI in ICV segmentation in a semi-automatic framework delivered best results compared with a reference standard manual method. Fully automated methods, while fast, all require manual editing to avoid significant errors and, in this post-processing step color fusion MRI is recommended.

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M. Hernandez, N. Royle, M. Jackson, S. Maniega, L. Penke, M. Bastin, I. Deary and J. Wardlaw, "Color Fusion of Magnetic Resonance Images Improves Intracranial Volume Measurement in Studies of Aging," Open Journal of Radiology, Vol. 2 No. 1, 2012, pp. 1-9. doi: 10.4236/ojrad.2012.21001.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] J. S. Allen, J. Bruss, C. K. Brown and H. Damasio, “The Major Lobes and a Parcellation of the Temporal Region,” Neurobiology of Aging, Vol. 26, No. 9, 2005, pp. 1245- 1260. doi:10.1016/j.neurobiolaging.2005.05.023
[2] D. D. Blatter, E. D. Bigler, S. D. Gale, S. C. Johnson, C. V. Anderson, B. M. Burnett, N. Parker, S. Kurth and S. D. Horn, “Quantitative Volumetric Analysis of Brain MR: Normative Database Spanning 5 Decades of Life,” American Journal of Neuroradiology, Vol. 16, No. 2, 1995, pp. 241-251.
[3] M. A. Ikram, H. A. Vrooman, H. A. Vernooij, F. van der Lijn, A. Hofman, A. van der Lugt, W. J. Niessen and M. M. Breteler, “Brain Tissue Volumes in the General Elderly Population: The Rotterdam Scan Study,” Neurobiology of Aging, Vol. 29, No. 6, 2008, pp. 882-890. doi:10.1016/j.neurobiolaging.2006.12.012
[4] R. I. Scahill, C. Frost, R. Jenkins, J. L. Whitwell, M. N. Rosser and N. C. Fox, “A Longitudinal Study of Brain Volume Changes in Normal Aging Using Serial Registered Magnetic Resonance Imaging,” Archives of Neurology, Vol. 60, No. 7, 2003, pp. 989-994. doi:10.1001/archneur.60.7.989
[5] Y. Ge, R. I. Grossman, J. S. Babb, M. L. Rabin and D. L. Kolson, “Age-Related Total Gray Matter and White Matter Changes in Normal Adult Brain. Part I: Volumetric MR Imaging Analysis,” American Journal of Neuroradiology, Vol. 23, No. 8, 2002, pp. 1327-1333.
[6] C. E. Coffey, G. Ratcliff, J. A. Saxton, N. R. Bryan, L. P. Fried and J. F. Lucke, “Cognitive Correlates of Human Brain Aging: A Quantitative Magnetic Resonance Imaging Investigation,” Journal of Neuropsychiatry & Clinical Neurosciences, Vol. 13, No. 4, 2001, pp. 471-485. doi:10.1176/appi.neuropsych.13.4.471
[7] R. T. Staff, A. D. Murray, I. J. Deary and L. J. Whalley, “Generality and Specificity in Cognitive Aging: A Volumetric Brain Analysis,” Neuroimage, Vol. 30, No. 4, 2006, pp. 1433-1440. doi:10.1016/j.neuroimage.2005.11.004
[8] G. Pengas, J. M. S. Pereira, G. B. Williams and P. J. Nestor, “Comparative Reliability of Total Intracranial Volume Estimation Methods and the Influence of Atrophy in a Longitudinal Semantic Dementia Cohort,” Journal of Neuroimaging, Vol. 19, No. 1, 2009, pp. 37-46. doi:10.1111/j.1552-6569.2008.00246.x
[9] K. J. Ferguson, J. M. Wardlaw, C. L. Edmond, I. J. Deary, A. M. J. McLullich and N. C. Fox, “Intracranial Area: A Validation Method for Estimating Intracranial Volume,” Journal of Neuroimaging, Vol. 15, No. 1, 2005, pp. 76-78. doi:10.1111/j.1552-6569.2005.tb00289.x
[10] R. N. K. Nandigam, Y. W. Chen, M. E. Gurol, J. Rosand, S. M. Greenberg and E. E. Smith, “Validation of Intracranial Area as a Surrogate Measure of Intracranial Volume When Using Clinical MRI” Journal of Neuroimaging, Vol. 17, No. 1, 2007, pp. 74-77. doi:10.1111/j.1552-6569.2006.00069.x
[11] J. M. Burns, B. B. Cronk, H. S. Anderson, J. E. Donelli, G. P. Thomas, A. Harsha, W. M. Brooks and R. H. Swerdlow, “Cardiorespiratory Fitness and Brain Atrophy in Early Alzheimer’s Disease,” Neurology, Vol. 71, No. 3, 2008, pp. 210-216. doi:10.1212/01.wnl.0000317094.86209.cb
[12] R. J. Thoma, M. Monnig, F. M. Hanlon, G. A. Miller, H. Petropoulos, A. R. Mayer, R. Yeo, M. Euler, P. Lysne, S. N. Moses and J. M. Canive, “Hippocampus Volume and Episodic Memory in Schizophrenia,” Journal of International Neuropsychological Society, Vol. 15, No. 2, 2009, pp. 182-195. doi:10.1017/S1355617709090225
[13] S. M. Smith, “Fast Robust Automated Brain Extraction,” Human Brain Mapping, Vol. 17, No. 3, 2010, pp. 143- 155. doi:10.1002/hbm.10062
[14] M. Battaglini, S. M. Smith, S. Brogi and N. De Stefano, “Enhanced Brain Extraction Improves the Accuracy of Brain Atrophy Estimation,” Neuroimage, Vol. 40, No. 2, 2008, pp. 583-589. doi:10.1016/j.neuroimage.2007.10.067
[15] G. N. Holland and P. A. Botomley, “A Color Display Technique for NMR Imaging,” Journal of Physics E: Scientific Instruments, Vol. 10, No. 7, 1977, pp. 14-16. doi:10.1088/0022-3735/10/7/014
[16] K. L. Weiss, S. O. Stiving, E. E. Herderick, J. F. Cornhill and D. W. Chakeres, “Hybrid Color MR Imaging Display,” American Journal of Roentgenology, Vol. 149, No. 4, 1987, pp. 825-829.
[17] M. C. Valdes Hernandez, K. J. Ferguson, F. Chapell and J. M. Wardlaw, “New Multispectral Data Fusion Technique in MRI for White Matter Lesion Segmentation: Method and Comparison with Thresholding in FLAIR Images,” European Radiology, Vol. 20, No. 7, 2010, pp. 1684- 1891. doi:10.1007/s00330-010-1718-6
[18] I. J. Deary, A. J. Gow, M. D. Taylor, J. Corley, C. Brett, V. Wilson, H. Campbell, L. J. Whalley, P. M. Visscher, D. J. Porteous and J. M. Starr, “The Lothian Birth Cohort 1936: A Study to Examine Influences on Cognitive Aging from Age 11 to Age 70 and Beyond,” Geriatrics, Vol. 7, 2007, pp. 28-33. doi:10.1186/1471-2318-7-28
[19] J. M. Wardlaw, M. E. Bastin, M. C. Valdes Hernandez, S. Munoz Maniega, N. A. Royle, Z. Morris, J. Clayden, E. Sandeman, E. Eadie, C. Murray, J. Starr and I. J. Deary, “Brain Aging, Cognition in Youth and Old Age, and Vascular Disease in the Lothian Birth Cohort 1936: Rationale, Design and Methodology of the Imaging Protocol,” International Journal of Stroke, 2011, Article in Press.
[20] J. M. Bland and D. G. Altman, “Statistical Methods for Assessing Agreement between Two Methods of Clinical Measurement,” Lancet, Vol. 327, No. 8476, 1986, pp. 307-310. doi:10.1016/S0140-6736(86)90837-8
[21] M. V. Vannier, R. L. Butterfield, D. Jordan, W. A. Murphy, R. G. Levit and M. Gado, “Multispectral Analysis of Magnetic Resonance Images,” Radiology, Vol. 154, No. 1, 1985, pp. 221-224.
[22] W. E. Phillips, H. K. Brown, J. Bouza and R. E. Figueroa, “Neuroradiologic MR Applications with Multiparametric Color Composite Display,” Magnetic Resonance Imaging, Vol. 14, No. 1, 1996, pp. 59-72. doi:10.1016/0730-725X(95)02043-S
[23] H. K. Brown, T. R. Hazelton and M. L. Silbiger, “Generation of Color Composites for Enhanced Tissue Differentiation in Magnetic Resonance Imaging of the Brain,” American Journal of Anatomy, Vol. 192, No. 1, 1991, pp. 23-34. doi:10.1002/aja.1001920104
[24] H. K. Brown, T. R. Hazelton, J. V. Fiorica, A. K. Parsons, L. P. Clarke and M. L. Silbiger, “Composite and Classified Color Display in MR Imaging of the Female Pelvis,” Magnetic Resonance Imaging, Vol. 10, No. 1, 1992, pp. 143-154. doi:10.1016/0730-725X(92)90384-C
[25] M. G. Wells, P. F. Sharp and A. N. Law, “Principles and Appraisal of Combined Images in NMR,” Medical and Biological Engineering and Computing, Vol. 27, No. 3, 1989, pp. 277-280. doi:10.1007/BF02441485
[26] B. Alfano, A. Brunetti, A. Ciarmiello and M. Salvatore, “Simultaneous Display of Multiple MR Parameters with ‘Quantitative Magnetic Color Imaging’,” Journal of Computer Assisted Tomography, Vol. 16, No. 4, 1992, pp. 634-640. doi:10.1097/00004728-199207000-00025
[27] R. L. Kamman, G. P. Stomp and H. J. Berendsen, “Unified Multiple-Feature Color Display for MR Images,” Magnetic Resonance in Medicine, Vol. 9, No. 2, 1989, pp. 53-55.
[28] H. K. Brown, T. R. Hazelton, A. K. Parsons, J. V. Fiorica, C. G. Berman and M. L. Silbiger, “PC-Based Multiparameter Full-Color Display for Tissue Segmentation in MRI of Adnexal Masses,” Journal of Computer Assisted Tomography, Vol. 17, No. 6, 1993, pp. 993-1005. doi:10.1097/00004728-199311000-00030

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