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Use of normative distribution of gray to white matter ratio in orthogonal planes in human brain studies and computer-assisted neuroradiology

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Although the brain has been extensively studied, relationships of gray (GM) to white (WM) matters in individual sections as typically acquired and read radiologically have not yet been examined. A novel GM/WM-based approach with a compact whole brain representation is introduced and applied to study the brain and perform neuroimage processing.

Methods

The gray to white matter ratio GWR defined as GM/(GM+WM) was calculated for 3T T1-weighted axial, coronal, and sagittal sections of 75 normal subjects. The mean (normative) GWR curves were employed to describe the normal brain and quantify aging and to illustrate pathology detection and characterization.

Results

The mean GWR curves characterize the normal brain by only six, neuroanatomy-related numbers. The regions with a significant GWR decline with age surround the ventricular system. The GWR decline rate in males is higher (−0.17%/year) than females (−0.14%/year); moreover, males show a significantly higher decline in middle to elder group. The GWR decline from young (≤25 years) to middle (26–40 years) age group (males/females −0.31%/−0.34%/year) is significantly higher than that from middle to elder (>40 years) group (males/females −0.13/−0.07%/year).

Conclusion

The GWR-based analysis is useful to characterize normal brain, determine significant regions of interest, and quantify healthy aging. It has potential applications in brain compression, comparison, morphometry, normalization, and detecting and quantifying pathologies, which open new avenues in computer-assisted neuroradiology from screening to large brain databases searching.

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References

  1. Huber P (1982) Cerebral angiography, 2nd edn. Georg Thieme Verlag, Stuttgart

    Google Scholar 

  2. Kretschmann HJ, Weinrich W (2004) Cranial neuroimaging and clinical neuroanatomy, 3rd edn. Georg Thieme Verlag, Stuttgart

    Google Scholar 

  3. Harnsberger HR, Osborn AG, Ross J, Macdonald A (2006) Diagnostic and surgical imaging anatomy: brain, head and neck, spine. Amirsys, Salt Lake City

    Google Scholar 

  4. Schuenke M, Schulte E, Schumacher U, Ross L, Lamperti E, Voll MM, Wesker KH (2007) Head and neuroanatomy. Thieme atlas of anatomy series. Thieme, New York

    Google Scholar 

  5. Schaltenbrand G, Wahren W (1977) Atlas for stereotaxy of the human brain. Thieme, Stuttgart

    Google Scholar 

  6. Netter FH (1986) Nervous system, part 1: anatomy and physiology. Ciba collection of medical illustrations, vol 1. CIBA-GEIGY, New Jersey

    Google Scholar 

  7. Talairach J, Tournoux P (1988) Co-planar stereotactic atlas of the human brain. Georg Thieme Verlag/Thieme Medical Publishers, Stuttgart

    Google Scholar 

  8. Duvernoy HM (1999) The human brain: surface, three-dimensional sectional anatomy with MRI, and blood supply, 2nd edn. Springer, Wien

    Google Scholar 

  9. Mori S, Wakana S, van Zijl PCM, Nagae-Poetscher LM (2005) MRI atlas of human white matter. Elsevier Science, Amsterdam

    Google Scholar 

  10. Sundsten JW, Brinkley JF, Eno K, Prothero J (1994) The digital anatomist. Interactive brain atlas. CD ROM for the Macintosh. University of Washington, Seattle

    Google Scholar 

  11. Hoehne KH (2001) Voxel-Man, Brain and skull. Version 2.0. Springer, Heidelberg

    Google Scholar 

  12. Nowinski WL, Thirunavuukarasuu A (2004) The cerefy clinical brain atlas. Thieme, New York

    Google Scholar 

  13. Nowinski WL, Thirunavuukarasuu A, Volkau I, Marchenko Y, Runge VM (2009) The cerefy atlas of cerebral vasculature. Thieme, New York

    Google Scholar 

  14. Allen JS, Damasio H, Grabowski TJ, Bruss J, Zhang W (2003) Sexual dimorphism and asymmetries in the gray-white composition of human cerebrum. Neuroimage 18: 880–894

    Article  PubMed  Google Scholar 

  15. Kruggel F (2006) RI-based volumetry of head compartments: normative values of healthy adults. NeuroImage 30: 1–11

    Article  PubMed  CAS  Google Scholar 

  16. Harris GJ, Schlaepfer TE, Peng LW, Federman EB, Pearlson GD (1994) Magnetic resonance imaging evaluation of the effects of ageing on grey-white ratio in the human brain. Neuropathol Appl Neurobiol 20(3): 290–293

    Article  PubMed  CAS  Google Scholar 

  17. Luft AR, Skalej M, Schulz JB, Welte D, Kolb R, Burk K, Klockgether T, Voigt K (1999) Patterns of age-related shrinkage in cerebellum and brainstem observed in vivo using three-dimensional MRI volumetry. Cereb Cortex 9(7): 712–721

    Article  PubMed  CAS  Google Scholar 

  18. Courchesne E, Chisum HJ, Townsend J, Cowles A, Covington J, Egass B, Harwood M, Hinds S, Press GA (2000) Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology 216: 672–682

    PubMed  CAS  Google Scholar 

  19. Ashburner J, Friston KJ (2000) Voxel-based morphometry—the methods. NeuroImage 11(6 Pt 1): 805–821

    Article  PubMed  CAS  Google Scholar 

  20. Ashburner J, Friston KJ (2005) Unified segmentation. Neuroimage 26(3): 839–851

    Article  PubMed  Google Scholar 

  21. Gur RC, Bruce IT, Matsui M, Yan M, Bilker W, Hughett P, Gur RE (1999) Sex differences in brain gray and white matter in healthy young adults: correlations with cognitive performance. J Neurosci 19(10): 4065–4072

    PubMed  CAS  Google Scholar 

  22. Ge Y, Grossman RI, Babb JS, Rabin ML, Mannon LJ, Kolson DL (2002) Age-related total gray matter and white matter changes in normal adult brain. Part I: Volumetric MR imaging analysis. AJNR Am J Neuroradiol 23: 1327–1333

    PubMed  Google Scholar 

  23. Greenberg DL, Messer DF, Payne ME, Macfall JR, Provenzale JM, Steffens DC, Krishnan RR (2008) Aging gender, and the elderly adult brain: an examination of analytical strategies. Neurobiol Aging 29: 290–302

    Article  PubMed  Google Scholar 

  24. Smith CD, Chebrolu H, Wekstein DR, Schmitt FA, Markesbery WR (2007) Age and gender effects on human brain anatomy: a voxel based morphometric study in healthy elderly. Neurobiol Aging 28: 1075–1087

    Article  PubMed  Google Scholar 

  25. Cuadra MB, Cammoun L, Butz T, Cuisenaire O, Thiran J (2005) Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images. IEEE Trans Med Imaging 24(12): 1548–1565

    Article  PubMed  Google Scholar 

  26. Bevington PR (1969) Data reduction and error analysis for the physical sciences. McGraw-Hill, New York

    Google Scholar 

  27. Gehrels N (1986) Confidence limits for small number of events in astrophysical data. Astrophys J 303: 336–346

    Article  CAS  Google Scholar 

  28. Armitage P, Berry G, Matthews JNS (2002) Statistical methods in medical research, 4th edn. Blackwell Scientific Publishing, Oxford

    Book  Google Scholar 

  29. Schumaker L (2007) Spline functions: basic theory. Cambridge University Press, New York

    Book  Google Scholar 

  30. Whitwell JL (2009) Voxel-based morphometry: an automated technique for assessing structural changes in the brain. J Neurosci 29(31): 9661–9664

    Article  PubMed  CAS  Google Scholar 

  31. Goldszal AF, Davatzikos C, Pham DL et al (1998) An image-processing system for qualitative and quantitative volumetric analysis of brain images. J Comput Assist Tomogr 22(5): 827–837

    Article  PubMed  CAS  Google Scholar 

  32. Davatzikos C, Genc A, Xu D et al (2001) Voxel-based morphometry using the RAVENS maps: methods and validation using simulated longitudinal atrophy. NeuroImage 14(6): 1361–1369

    Article  PubMed  CAS  Google Scholar 

  33. Klauschen F, Goldman A, Barra V et al (2009) Evaluation of automated brain MR image segmentation and volumetry methods. Hum Brain Mapp 30: 1310–1327

    Article  PubMed  Google Scholar 

  34. Jack CR Jr, Bernstein MA, Fox NC et al (2008) The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. J Magn Reson Imaging 27(4): 685–691

    Article  PubMed  Google Scholar 

  35. Edelman RR, Dunkle E, Koktzoglou I et al (2009) Rapid whole-brain magnetic resonance imaging with isotropic resolution at 3 Tesla. Invest Radiol 44(1): 54–59

    Article  PubMed  Google Scholar 

  36. Kakeda S, Korogi Y, Hiai Y et al (2007) Detection of brain metastasis at 3T: comparison among SE, IR-FSE and 3D-GRE sequences. Eur Radiol 17(9): 2345–2351

    Article  PubMed  Google Scholar 

  37. Deoni SCL, Williams SCR, Jezzard P et al (2008) Standardized structural magnetic resonance imaging in multicentre studies using quantitative T1 and T2 imaging at 1.5 T. Neuroimage 40(2): 662–671

    Article  PubMed  Google Scholar 

  38. Coffey CE, Lucke JF, Saxton JA et al (1998) Sex differences in brain aging—a quantitative magnetic resonance study. Arch Neurol 55(2): 169–179

    Article  PubMed  CAS  Google Scholar 

  39. Lemaitre H, Crivello F, Grassiot B et al (2005) Age and sex related effects on neuroanatomy of healthy elderly. NeuroImage 23(3): 860–868

    Google Scholar 

  40. Jernigan TL, Gamst AC (2005) Changes in volume with age-consistency and interpretation of observed effects. Neurobiol Aging 26(9): 1271

    Article  PubMed  Google Scholar 

  41. Fotenos AF, Snyder AZ, Girton LE et al (2005) Normative estimates of cross sectional and longitudinal brain decline in ageing and AD. Neurology 64(6): 1032–1039

    PubMed  CAS  Google Scholar 

  42. Walhovd KB, Fjell AM, Reinvang I et al (2005) Effects of age on volume of cortex, white matter and subcortical structures. Neurobiol Aging 26(9): 1261–1270 (discussion 1275–1278)

    Article  PubMed  Google Scholar 

  43. Good CD, Johnsrude IS, Ashburner J et al (2001) A voxel based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14(1pt 1): 21–36

    Article  PubMed  CAS  Google Scholar 

  44. Allen JS, Bruss J, Brown CK et al (2005) Normal neuroanatomical variation due to age: the major lobes and a parcellation of the temporal region. Neurobiol Aging 26(9): 1245–1260 (discussion 1279–1282)

    Article  PubMed  Google Scholar 

  45. Joshi SH, Horn JD, Toga AW (2009) Interactive exploration of neuroanatomical meta-spaces. Front Neuroinformatics 3:Article 38

  46. Herskovits EH, Chen R (2008) Integrating data-mining support into a brain-image database using open-source components. Adv Med Sci 53(2): 172–181

    Article  PubMed  CAS  Google Scholar 

  47. Nowinski WL, Qian G, BhanuPrakash KN et al (2006) Fast Talairach transformation for magnetic resonance neuroimages. J Comput Assist Tomogr 30(4): 629–641

    Article  PubMed  Google Scholar 

  48. Nowinski WL, Bhanuprakash KN (2005) Dorso-ventral extension of the Talairach transformation and its automatic calculation for MR neuroimages. J Comput Assist Tomogr 29(6): 863–879

    Article  PubMed  Google Scholar 

  49. Chow SC, Shao J, Wang H (2008) Clinical size calculations in clinical research, 2nd edn. Chapman & Hall/CRC Biostatistic series, Boca Raton

    Google Scholar 

  50. Lerman J (1996) Study design in clinical research: sample size estimation and power analysis. Can J Anaesth 43(2): 184–191

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Biomedical Imaging Lab, Agency for Science Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore

    Wieslaw L. Nowinski & Varsha Gupta

  2. Department of Adult Psychiatry III, Institute of Mental Health, Woodbridge Hospital, 10 Buangkok View, Singapore, 539747, Singapore

    Wai Yen Chan & Kang Sim

  3. Department of Neuroradiology, National Neurosciences Institutes, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore

    Yih-Yian Sitoh

Authors
  1. Wieslaw L. Nowinski
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  2. Varsha Gupta
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  3. Wai Yen Chan
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  4. Yih-Yian Sitoh
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  5. Kang Sim
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Correspondence to Wieslaw L. Nowinski.

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Nowinski, W.L., Gupta, V., Chan, W.Y. et al. Use of normative distribution of gray to white matter ratio in orthogonal planes in human brain studies and computer-assisted neuroradiology. Int J CARS 6, 489–505 (2011). https://doi.org/10.1007/s11548-010-0538-0

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  • DOI: https://doi.org/10.1007/s11548-010-0538-0

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