A Voxel-Based Morphometry of Gray Matter Volume Reduction in Patients with Mild Cognitive Impairment

화소 기반 형태분석 방법을 이용한 경도인지장애 환자의 회백질 용적감소의 정량적 분석

  • Yoo, Bo-Eun (Department of Psychiatry, St. Mary's Hospital, The Catholic University of Korea College of Medicine) ;
  • Hahn, Chang-Tae (Department of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine) ;
  • Lee, Chang-Uk (Department of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine) ;
  • Hong, Seung-Chul (Department of Psychiatry, St. Vincent Hospital, The Catholic University of Korea College of Medicine) ;
  • Lim, Hyun-Kook (Department of Psychiatry, St. Vincent Hospital, The Catholic University of Korea College of Medicine)
  • 유보은 (가톨릭대학교 의과대학 성모병원 정신과학교실) ;
  • 한창태 (가톨릭대학교 의과대학 서울성모병원 정신과학교실) ;
  • 이창욱 (가톨릭대학교 의과대학 서울성모병원 정신과학교실) ;
  • 홍승철 (가톨릭대학교 의과대학 성빈센트병원 정신과학교실) ;
  • 임현국 (가톨릭대학교 의과대학 성빈센트병원 정신과학교실)
  • Received : 2011.04.18
  • Accepted : 2011.08.05
  • Published : 2011.11.30

Abstract

Objectives Optimized voxel based morphometry (VBM) has been increasingly applied to investigate differences in the brain morphology between a group of patients with mild cognitive impairment (MCI) and control subjects. Optimized VBM permits comparison of gray matter (GM) volume at voxel-level from the entire brain. The purpose of this study was to assess the regional GM volume change measured by optimized VBM in MCI subjects compared to controls. Methods Twenty patients with MCI and 20 control subjects with normal cognition were recruited for this study. We applied the optimized VBM protocol to the image data including study-specific template and the modulation of the data with the Jacobian determinants. GM volume differences between the MCI subjects and the control subjects and their correlations with the neuropsychological performances were investigated. Results Optimized VBM analysis revealed GM volume reduction in hippocampus, precentral gyrus, insula and parietal operculum in the MCI group compared to the control group (family wise error corrected p < 0.05). Korean version of the Consortium to Establish a Registry for Alzheimer's disease (CERAD-K) word list recall scores were significantly correlated with the GM volumes of hippocampus, precuneus and posterior cingulate in the MCI group (FWE corrected p < 0.05). Conclusions The results confirm previous findings of atrophic changes in medial temporal lobe and parietal lobe in the MCI group and suggest that these abnormalities may be related with cognitive decline and prognosis in patients with MCI.

Keywords

References

  1. Petersen RC, Roberts RO, Knopman DS, Boeve BF, Geda YE, Ivnik RJ, et al. Mild cognitive impairment: ten years later. Arch Neurol 2009;66:1447-1455. https://doi.org/10.1001/archneurol.2009.266
  2. Linn RT, Wolf PA, Bachman DL, Knoefel JE, Cobb JL, Belanger AJ, et al. The 'preclinical phase' of probable Alzheimer's disease. A 13- year prospective study of the Framingham cohort. Arch Neurol 1995; 52:485-490. https://doi.org/10.1001/archneur.1995.00540290075020
  3. Ries ML, Carlsson CM, Rowley HA, Sager MA, Gleason CE, Asthana S, et al. Magnetic resonance imaging characterization of brain structure and function in mild cognitive impairment: a review. J Am Geriatr Soc 2008;56:920-934. https://doi.org/10.1111/j.1532-5415.2008.01684.x
  4. Stoub TR, deToledo-Morrell L, Stebbins GT, Leurgans S, Bennett DA, Shah RC. Hippocampal disconnection contributes to memory dysfunction in individuals at risk for Alzheimer's disease. Proc Natl Acad Sci U S A 2006;103:10041-10045. https://doi.org/10.1073/pnas.0603414103
  5. Becker JT, Davis SW, Hayashi KM, Meltzer CC, Toga AW, Lopez OL, et al. Three-dimensional patterns of hippocampal atrophy in mild cognitive impairment. Arch Neurol 2006;63:97-101. https://doi.org/10.1001/archneur.63.1.97
  6. Ashburner J, Friston KJ. Voxel-based morphometry--the methods. Neuroimage 2000;11:805-821. https://doi.org/10.1006/nimg.2000.0582
  7. Jack CR Jr, Petersen RC, Xu YC, O'Brien PC, Smith GE, Ivnik RJ, et al. Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 1999;52:1397-1403. https://doi.org/10.1212/WNL.52.7.1397
  8. Pennanen C, Kivipelto M, Tuomainen S, Hartikainen P, Hanninen T, Laakso MP, et al. Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging 2004;25:303-310. https://doi.org/10.1016/S0197-4580(03)00084-8
  9. Kovacevic S, Rafii MS, Brewer JB, Alzheimer's Disease Neuroimaging Initiative. High-throughput, fully automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment. Alzheimer Dis Assoc Disord 2009;23:139-145. https://doi.org/10.1097/WAD.0b013e318192e745
  10. Driscoll I, Davatzikos C, An Y, Wu X, Shen D, Kraut M, et al. Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. Neurology 2009;72:1906-1913. https://doi.org/10.1212/WNL.0b013e3181a82634
  11. Smith CD, Chebrolu H, Wekstein DR, Schmitt FA, Jicha GA, Cooper G, et al. Brain structural alterations before mild cognitive impairment. Neurology 2007;68:1268-1273. https://doi.org/10.1212/01.wnl.0000259542.54830.34
  12. Bookstein FL. "Voxel-based morphometry" should not be used with imperfectly registered images. Neuroimage 2001;14:1454-1462. https://doi.org/10.1006/nimg.2001.0770
  13. Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001;14:21-36. https://doi.org/10.1006/nimg.2001.0786
  14. Good CD, Scahill RI, Fox NC, Ashburner J, Friston KJ, Chan D, et al. Automatic differentiation of anatomical patterns in the human brain: validation with studies of degenerative dementias. Neuroimage 2002; 17:29-46. https://doi.org/10.1006/nimg.2002.1202
  15. Lee JH, Lee KU, Lee DY, Kim KW, Jhoo JH, Kim JH, et al. Development of the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K): clinical and neuropsychological assessment batteries. J Gerontol B Psychol Sci Soc Sci 2002;57:P47-P53. https://doi.org/10.1093/geronb/57.1.P47
  16. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991;82:239-259. https://doi.org/10.1007/BF00308809
  17. Price JL, Morris JC. Tangles and plaques in nondemented aging and "preclinical" Alzheimer's disease. Ann Neurol 1999;45:358-368. https://doi.org/10.1002/1531-8249(199903)45:3<358::AID-ANA12>3.0.CO;2-X
  18. Grundman M, Sencakova D, Jack CR Jr, Petersen RC, Kim HT, Schultz A, et al. Brain MRI hippocampal volume and prediction of clinical status in a mild cognitive impairment trial. J Mol Neurosci 2002;19:23-27. https://doi.org/10.1007/s12031-002-0006-6
  19. Karas GB, Burton EJ, Rombouts SA, van Schijndel RA, O'Brien JT, Scheltens P, et al. A comprehensive study of gray matter loss in patients with Alzheimer's disease using optimized voxel-based morphometry. Neuroimage 2003;18:895-907. https://doi.org/10.1016/S1053-8119(03)00041-7
  20. Karas GB, Scheltens P, Rombouts SA, Visser PJ, van Schijndel RA, Fox NC, et al. Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease. Neuroimage 2004;23:708-716. https://doi.org/10.1016/j.neuroimage.2004.07.006
  21. Killiany RJ, Hyman BT, Gomez-Isla T, Moss MB, Kikinis R, Jolesz F, et al. MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology 2002;58:1188-1196. https://doi.org/10.1212/WNL.58.8.1188
  22. Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995; 36:1238-1248.
  23. Pennanen C, Testa C, Laakso MP, Hallikainen M, Helkala EL, Hanninen T, et al. A voxel based morphometry study on mild cognitive impairment. J Neurol Neurosurg Psychiatry 2005;76:11-14. https://doi.org/10.1136/jnnp.2004.035600
  24. Bottino CM, Castro CC, Gomes RL, Buchpiguel CA, Marchetti RL, Neto MR. Volumetric MRI measurements can differentiate Alzheimer's disease, mild cognitive impairment, and normal aging. Int Psychogeriatr 2002;14:59-72. https://doi.org/10.1017/S1041610202008281
  25. Muller MJ, Greverus D, Dellani PR, Weibrich C, Wille PR, Scheurich A, et al. Functional implications of hippocampal volume and diffusivity in mild cognitive impairment. Neuroimage 2005;28:1033- 1042. https://doi.org/10.1016/j.neuroimage.2005.06.029
  26. Zhang H, Trollor JN, Wen W, Zhu W, Crawford JD, Kochan NA, et al. Grey matter atrophy of basal forebrain and hippocampus in mild cognitive impairment. J Neurol Neurosurg Psychiatry 2011;82:487- 493. https://doi.org/10.1136/jnnp.2010.217133
  27. Cao Q, Jiang K, Zhang M, Liu Y, Xiao S, Zuo C, et al. Brain glucose metabolism and neuropsychological test in patients with mild cognitive impairment. Chin Med J (Engl) 2003;116:1235-1238.
  28. Karas G, Sluimer J, Goekoop R, van der Flier W, Rombouts SA, Vrenken H, et al. Amnestic mild cognitive impairment: structural MR imaging findings predictive of conversion to Alzheimer disease. AJNR Am J Neuroradiol 2008;29:944-949. https://doi.org/10.3174/ajnr.A0949
  29. Valeria Santoro Bahia. Pain and apathy. Dementia & Neuropsychologia 2008;2(4):362-365.
  30. Palmer K, Di Iulio F, Varsi AE, Gianni W, Sancesario G, Caltagirone C, et al. Neuropsychiatric predictors of progression from amnesticmild cognitive impairment to Alzheimer's disease: the role of depression and apathy. J Alzheimers Dis 2010;20:175-183.
  31. Delbeuck X, Van der Linden M, Collette F. Alzheimer's disease as a disconnection syndrome? Neuropsychol Rev 2003;13:79-92. https://doi.org/10.1023/A:1023832305702
  32. Mesulam MM, Nobre AC, Kim YH, Parrish TB, Gitelman DR. Heterogeneity of cingulate contributions to spatial attention. Neuroimage 2001;13:1065-1072.