Tracking Alzheimer's disease.
Journal: 2007/April - Annals of the New York Academy of Sciences
ISSN: 0077-8923
Abstract:
Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span. We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer's disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.
Relations:
Content
Citations
(71)
References
(120)
Grants
(600)
Diseases
(2)
Conditions
(1)
Chemicals
(1)
Organisms
(1)
Anatomy
(2)
Affiliates
(1)
Similar articles
Articles by the same authors
Discussion board
Ann N Y Acad Sci 1097: 183-214

Tracking Alzheimer’s Disease

+2 authors
Department of Neurology, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, California, USA
Neuropsychiatric Institute, UCLA School of Medicine, Los Angeles, California, USA
Centre for Magnetic Resonance, University of Queensland, Brisbane, Australia
Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Address for correspondence: Dr. Paul Thompson, Department of Neurology, Laboratory of Neuro Imaging, UCLA School of Medicine, 635 Charles E. Young Drive South, Suite 225E, Los Angeles, CA 90095-7332, USA. Voice: 310-206-2101; fax: 310-206-5518. ude.alcu.inol@nospmoht

Abstract

Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span. We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer’s disease (AD) and mild cognitive impairment (MCI).We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer’s disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

Keywords: MRI, Alzheimer’s disease, aging, MCI, dementia, brain degeneration, PET
Abstract

REFERENCES

REFERENCES

References

  • 1. Jorm AF, Korten AE, Henderson ASThe prevalence of dementia: a quantitative integration of the literature. Acta Psychiatr. Scand. 1987;76:465–479. Review. [[PubMed][Google Scholar]
  • 2. Jack CR, Jr, Slomkowski M, Gracon S, et al MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD. Neurology. 2003;60:253–260.[Google Scholar]
  • 3. Fox NC, Black RS, Gilman S, et al. AN1792(QS-21)-201 Study 2005. Effects of Abeta immunization (AN1792) on MRI measures of cerebral volume in Alzheimer disease. Neurology. 64:1563–1572.[PubMed]
  • 4. Silverman DHS, Thompson PMStructural and functional neuroimaging: focusing on mild cognitive impairment. Appl. Neurol. 2006;2:10–24.[PubMed][Google Scholar]
  • 5. Sowell ER, Peterson BS, Thompson PM, et al Mapping cortical change across the human lifespan. Nat. Neurosci. 2003;6:309–315.[PubMed][Google Scholar]
  • 6. Apostolova LG, Clark DG, Zoumalan C, et al. 3D mapping of gray matter atrophy in semantic dementia and frontal variant frontotemporal dementia. International Conference on Alzheimer’s Disease (ICAD2006); Madrid, Spain. 2006. [PubMed]
  • 7. Thompson PM, Dutton RA, Hayashi KM, et al Thinning of the cerebral cortex in HIV/AIDS Reflects CD4 T-lymphocyte decline. Proc. Natl. Acad. Sci. 2005;102:15647–15652.[Google Scholar]
  • 8. Thompson PM, Lee AD, Dutton RA, et al Abnormal cortical complexity and thickness profiles mapped in williams syndrome. J. Neurosci. 2005;25:4146–4158.[Google Scholar]
  • 9. Chiang MC, Dutton RA, Hayashi KM, et al Fluid registration of medical images using jensen-rényi divergence reveals 3D profile of brain atrophy in HIV/AIDS. IEEE Int. Symp. Biomed. Imag. (ISBI2006) 2006[PubMed][Google Scholar]
  • 10. Lepore N, Brun CA, Chou YY, et al. Generalized tensor-based morphometry of HIV/AIDS using multivariate statistics on strain matrices and their application to HIV/AIDS. In: Gee JC, Thompson PM, editors. submitted to IEEE Transactions on Medical Imaging Special Issue on Computational Neuroanatomy; 2006. to appear March 2007 [submitted, July 1, 2006] [PubMed]
  • 11. Smith SM, Zhang Y, Jenkinson M, et al Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage. 2002;17:479–489.[PubMed][Google Scholar]
  • 12. Thompson PM, Hayashi KM, Sowell ER, et al Mapping cortical change in Alzheimer’s disease, brain development, and schizophrenia, Special Issue on Mathematics in Brain Imaging. In: Thompson PM, Miller MI, Ratnanather JT, Poldrack R, Nichols TE, editors. NeuroImage. Vol. 23. 2004. pp. S2–S18. [PubMed][Google Scholar]
  • 13. Barrio JR, Huang S-C, Cole GM, et al PET imaging of tangles and plaques in Alzheimer disease. J. Nucl. Med. 1999;40 Suppl:70P–71P.[PubMed][Google Scholar]
  • 14. Shoghi-Jadid K, Small GW, Agdeppa ED, et al Localization of neurofibrillary tangles and beta-amyloid plaques in the brains of living patients with Alzheimer disease. Am. J. Geriatr. Psychiatry. 2002;10:24–35.[PubMed][Google Scholar]
  • 15. Klunk WE, Lopresti BJ, Ikonomovic MD, et al Binding of the positron emission tomography tracer Pittsburgh compound-B reflects the amount of amyloid-beta in Alzheimer’s disease brain but not in transgenic mouse brain. J. Neurosci. 2005;25:10598–10660.[Google Scholar]
  • 16. Kepe V, Barrio JR, Huang SC, et al Serotonin 1A receptors in the living brain of Alzheimer’s disease patients. Proc. Natl. Acad. Sci. USA. 2006;103:702–707. Epub 2006 Jan 9. [Google Scholar]
  • 17. Small GW, Kepe V, Ercoli L, et al PET of brain amyloid and tau in mild cognitive impairment. N. Engl. J. Med. 2006;355(25):2652–2663.[PubMed][Google Scholar]
  • 18. Petersen RC, Smith GE, Waring SC, et al Mild cognitive impairment: clinical characterization and outcome. Arch. Neurol. 1999;56:303–308. [erratum appears in Arch Neurol 1999 Jun;56(6):760] [[PubMed][Google Scholar]
  • 19. Petersen RCAging, mild cognitive impairment, and Alzheimer’s disease. Neurol. Clin. 2000;18:789–806.[PubMed][Google Scholar]
  • 20. Becker JT, Davis SW, Hayashi KM, et al 3D patterns of hippocampal atrophy in mild cognitive impairment. Arch. Neurol. 2006;63:97–101.[PubMed][Google Scholar]
  • 21. Apostolova LG, Steiner CA, Akopyan GG, et al 3D gray matter atrophy mapping in mild cognitive impairment and mild Alzheimer’s disease. 2007 [submitted]
  • 22. Carmichael OT, Thompson PM, Dutton RA, et al Mapping ventricular changes related to dementia and mild cognitive impairment in a large community-based cohort. IEEE Int. Symp. Biomed. Imag. (ISBI2006) 2006[PubMed][Google Scholar]
  • 23. Price JL, Morris JCTangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann. Neurol. 1999;45:358–368.[PubMed][Google Scholar]
  • 24. Kordower JH, Chu Y, Stebbins GT, et al Loss and atrophy of layer II entorhinal cortex neurons in elderly people with mild cognitive impairment. Ann. Neurol. 2001;49:202–213.[PubMed][Google Scholar]
  • 25. Leow AD, Klunder AD, Jack CR, et al Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. Neuroimage. 2006;31:627–640. Epub 2006 Feb 15. [Google Scholar]
  • 26. Bartzokis G, Sultzer D, Mintz J, et al In vivo evaluation of brain iron in Alzheimer’s disease and normal subjects using MRI. Biol.Psychiatry. 1994;35:480–487.[PubMed][Google Scholar]
  • 27. Bartzokis G, Tishler TA, Lu PH, et al Brain ferritin iron may influence age- and gender-related risks of neurodegeneration. Neurobiol. Aging. 2007;28:414–423.[PubMed][Google Scholar]
  • 28. Thompson PM, Hayashi KM, de Zubicaray G, et al Dynamics of gray matter loss in Alzheimer’s Disease. J. Neurosci. 2003;23:994–1005.[Google Scholar]
  • 29. Braak H, Braak ENeuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–259.[PubMed][Google Scholar]
  • 30. Braak H, Braak EStaging of Alzheimer-related cortical destruction. Int. Psychogeriatr. 1997;9 Suppl 1:257–261. discussion 269–272. [[PubMed][Google Scholar]
  • 31. Gomez-Isla T, Price JL, McKeel DW, et al Profound loss of layer II entorhinal cortex neurons occurs in very mild Alzheimer’s disease. J. Neurosci. 1996;16:4491–4500.[Google Scholar]
  • 32. Frisoni GB, Laakso MP, Beltramello A, et al Hippocampal and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer’s disease. Neurology. 1999;52:91–100.[PubMed][Google Scholar]
  • 33. Laakso MP, Partanen K, Riekkinen P, et al Hippocampal volumes in Alzheimer’s disease, Parkinson’s disease, with and without dementia, and in vascular dementia: an MRI study. Neurology. 1996;46:678–681.[PubMed][Google Scholar]
  • 34. Laakso MP, Soininen H, Partanen K, et al MRI of the hippocampus in Alzheimer’s disease: sensitivity, specificity, and analysis of the incorrectly classified subjects. Neurobiol. Aging. 1998;19:23–31.[PubMed][Google Scholar]
  • 35. Dickerson BC, Goncharova I, Sullivan MP, et al MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol. Aging. 2001;22:747–754.[PubMed][Google Scholar]
  • 36. Thal LJHow to define treatment success using cholinesterase inhibitors. Int. J. Geriatr. Psychiatry. 2002;17:388–390.[PubMed][Google Scholar]
  • 37. Pearson RCA, Esiri MM, Hiorns RW, et al Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer’s disease. Proc. Natl. Acad. Sci. USA. 1985;82:4531–4534.[Google Scholar]
  • 38. Arnold SE, Hyman BT, Flory J, et al The topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer’s disease. Cereb. Cortex. 1991;1:103–116.[PubMed][Google Scholar]
  • 39. Brun A, Englund ERegional pattern of degeneration in Alzheimer’s disease: neuronal loss and histopathologic grading. Histopathology. 1981;5:549–564.[PubMed][Google Scholar]
  • 40. Hyman BT, Van Hoesen GW, Damasio ARMemory-related neural systems in Alzheimer’s disease: an anatomic study. Neurology. 1990;40:1721–1730.[PubMed][Google Scholar]
  • 41. Mesulam MMA plasticity-based theory of the pathogenesis of Alzheimer’s disease. Ann. N.Y. Acad. Sci. 2000;924:42–52.[PubMed][Google Scholar]
  • 42. Gogtay N, Giedd JN, Lusk L, et al Dynamic mapping of human cortical development during childhood and adolescence. Proc. Natl. Acad. Sci. 2004;101:8174–8179.[Google Scholar]
  • 43. Yakovlev PI, Lecours AR. The myelogenetic cycles of regional maturation of the brain. In: Minkowski A, editor. Regional Development of the Brain in Early Life. Oxford: Blackwell Scientific; 1967. pp. 3–70. [PubMed]
  • 44. Benes FM, Turtle M, Khan Y, Farol PMyelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Arch. Gen. Psychiatry. 1994;51:477–484.[PubMed][Google Scholar]
  • 45. Thompson PM, Vidal C, Giedd JN, et al Mapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophrenia. Proc. Natl. Acad. Sci. USA. 2001;98:11650–11655.[Google Scholar]
  • 46. Cannon TD, Thompson PM, van Erp T, et al Cortex mapping reveals heteromodal gray matter deficits in monozygotic twins discordant for schizophrenia. Proc. Natl. Acad. Sci. USA. 2002;99:3228–3233.[Google Scholar]
  • 47. Pantelis C, Velakoulis D, McGorry PD, et al Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet. 2003;361:281–288.[PubMed][Google Scholar]
  • 48. Sun D, Velakoulis D, Yung A, et al Brain structural change during the development of psychosis: a longitudinal MRI study. 2007 submitted. [PubMed]
  • 49. Bartzokis G, Cummings JL, Sultzer D, et al White matter structural integrity in healthy aging adults and patients with Alzheimer disease: a magnetic resonance imaging study. Arch. Neurol. 2003;60:393–398.[PubMed][Google Scholar]
  • 50. Bartzokis G, Sultzer D, Lu PH, et al Heterogeneous age-related breakdown of white matter structural integrity: implications for cortical “disconnection” in aging and Alzheimer’s disease. Neurobiol. Aging. 2004;25:843–851.[PubMed][Google Scholar]
  • 51. Salat DH, Buckner RL, Snyder AZ, et al Thinning of the cerebral cortex in aging. Cereb. Cortex. 2004;14:721–730. Epub 2004 Mar 28. [[PubMed][Google Scholar]
  • 52. Ballmaier M, O’Brien JT, Burton EJ, et al Comparing gray matter loss profiles between dementia with Lewy bodies and Alzheimer’s disease using cortical pattern matching: diagnosis and gender effects. Neuroimage. 2004a;23:325–335.[PubMed][Google Scholar]
  • 53. Harvey GT, Hughes J, McKeith IG, et al Magnetic resonance imaging differences between dementia with Lewy bodies and Alzheimer’s disease: a pilot study. Psychol. Med. 1999;29:181–187.[PubMed][Google Scholar]
  • 54. McKeith IG, Dickson DW, Lowe J, et al Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology. 2005;65:1863–1872. Epub 2005 Oct 19. [[PubMed][Google Scholar]
  • 55. Masliah E, DeTeresa RM, Mallory ME, Hansen LAChanges in pathological findings at autopsy in AIDS cases for the last 15 years. AIDS. 2000;14:69–74.[PubMed][Google Scholar]
  • 56. Apostolova LG, Lu P, Rogers S, et al 3D mapping of language networks in clinical and pre-clinical Alzheimer’s disease. 2007 [submitted]
  • 57. Cummings JL, Apostolova LG, Akopyan GG, et al. Structural correlates of apathy in Alzheimer’s Disease; Annual Meeting of the American Academy of Neurology; San Diego, CA. 2006. [PubMed]
  • 58. Lu A, Leow AD, Lee AD, et al. Growth pattern abnormalities in childhood-onset schizophrenia visualized using tensor-based morphometry. 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 59. Thompson PM, Cannon TD, Narr KL, et al Genetic influences on brain structure. Nat. Neurosci. 2001;4:1253–1258.[PubMed][Google Scholar]
  • 60. Gray JR, Thompson PMNeurobiology of intelligence: science and ethics. Nat. Rev. Neurosci. 2004;5:471–482.[PubMed][Google Scholar]
  • 61. McDaniel MA, Nguyen NT. A meta-analysis of the relationship between MRI-assessed brain volume and intelligence. Presented at Proc Int. Soc. Intel. Res.; Nashville, TN. 2002. [PubMed]
  • 62. Ballmaier M, Kumar A, Thompson PM, et al Localizing gray matter deficits in late onset depression using computational cortical pattern matching methods. Am. J. Psychiatry. 2004;161:2091–2099.[PubMed][Google Scholar]
  • 63. Pievani M, Testa C, Sabattoli F, et al. Structural correlates of age at onset in Alzheimer’s disease: a cortical pattern matching study. 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 64. Fox NC, Cousens S, Scahill R, et al Using serial registered brain magnetic resonance imaging to measure disease progression in Alzheimer disease: power calculations and estimates of sample size to detect treatment effects. Arch. Neurol. 2000;57:339–344.[PubMed][Google Scholar]
  • 65. Baron JC, Chetelat G, Desgranges B, et al In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. Neuroimage. 2001;14:298–309.[PubMed][Google Scholar]
  • 66. Fox NC, Crum WR, Scahill RI, et al Imaging of onset and progression of Alzheimer’s disease with voxel-compression mapping of serial magnetic resonance images. Lancet. 2001;358:201–205.[PubMed][Google Scholar]
  • 67. Leow AD, Huang SC, Geng A, et al. Inverse Consistent Mapping in 3D Deformable Image Registration: its Construction and Statistical Properties. Information Processing in Medical Imaging (IPMI) 2005; Colorado. July 11–15; Glenwood Springs.2005. [[PubMed]
  • 68. Medina D, Detoledo-Morrell L, Urresta F, et al White matter changes in mild cognitive impairment and AD: a diffusion tensor imaging study. Neurobiol. Aging. 2006;27:663–672.[PubMed][Google Scholar]
  • 69. Fischl B, Dale AMMeasuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl. Acad. Sci. USA. 2000;97:11050–11055.[Google Scholar]
  • 70. Sowell ER, Peterson BS, Thompson PM, et al Sex differences in cortical thickness mapped in 176 healthy individuals between 7 and 87 years. 2006 [Epub ahead of print]
  • 71. Thompson PM, Hayashi KM, de Zubicaray G, et al Mapping hippocampal and ventricular change in Alzheimer’s Disease. Neuroimage. 2004;22:1754–1766.[PubMed][Google Scholar]
  • 72. De Santi S, de Leon MJ, Rusinek H, et al Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol Aging. 2001;22:529–539.[PubMed][Google Scholar]
  • 73. Callen DJ, Black SE, Gao F, et al Beyond the hippocampus: MRI volumetry confirms widespread limbic atrophy in AD. Neurology. 2001;57:1669–1674.[PubMed][Google Scholar]
  • 74. Du AT, Schuff N, Amend D, et al Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry. 2001;71:441–447.[Google Scholar]
  • 75. Soininen HS, Partanen K, Pitkanen A, et al Volumetric MRI analysis of the amygdala and the hippocampus in subjects with age-associated memory impairment: correlation to visual and verbal memory. Neurology. 1994;44:1660–1668.[PubMed][Google Scholar]
  • 76. Jack CR, Petersen RC, Xu YC, et al Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology. 1999;52:1397–1403.[Google Scholar]
  • 77. Visser PJ, Verhey FRJ, Hofman PAM, et al Medial temporal lobe atrophy predicts Alzheimer’s disease in patients with minor cognitive impairment. J. Neurol. Neurosurg. Psychiatry. 2002;72:491–497.[Google Scholar]
  • 78. Pennanen C, Kivipelto M, Tuomainen S, et al Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol. Aging. 2004;25:303–310.[PubMed][Google Scholar]
  • 79. Dickerson BC, Salat DH, Bates JF, et al Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol. 2004;56:27–35.[Google Scholar]
  • 80. Killiany RJ, Hyman BT, Gomez-Isla T, et al MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology. 2002;58:1188–1196.[PubMed][Google Scholar]
  • 81. de Leon MJ, Golomb J, George AE, et al The radiologic prediction of Alzheimer disease: the atrophic hippocampal formation. AJNR Am. J. Neuroradiol. 1993;14:897–906.[PubMed][Google Scholar]
  • 82. Visser PJ, Scheltens P, Verhey FRJ, et al Medial temporal lobe atrophy and memory dysfunction as predictors for dementia in subjects with mild cognitive impairment. J. Neurol. 1999;246:477–485.[PubMed][Google Scholar]
  • 83. Laakso MP, Lehtovirta M, Partanen K, et al Hippocampus in AD: a 3-year follow-up MRI study. Biol. Psychiatry. 2000;47:557–561.[PubMed][Google Scholar]
  • 84. Killiany RJ, Gomez-Isla T, Moss M, et al Use of structural magnetic resonance imaging to predict who will get Alzheimer’s disease. Ann. Neurol. 2000;47:430–439.[PubMed][Google Scholar]
  • 85. Csernansky JG, Wang L, Joshi S, et al Early DAT is distinguished from aging by high dimensional mapping of the hippocampus. Neurology. 2000;55:1636–1643.[PubMed][Google Scholar]
  • 86. Becker JT, Hayashi KM, Seaman JL, et al Alteration in Hippocampal and Caudate Nucleus Structure in HIV/AIDS Revealed by Three-Dimensional Mapping. 2007 [submitted] [PubMed]
  • 87. Bell-McGinty S, Lopez OL, Meltzer CC, et al Differential cortical atrophy in subgroups of mild cognitive impairment. Arch. Neurol. 2005;62:1393–1397.[PubMed][Google Scholar]
  • 88. Frisoni G, Sabattoli F, Lee AD, et al In vivo neuropathology of the hippocampal formation in AD: a radial mapping MR-based study. Neuroimage. 2006;32:104–110.[PubMed][Google Scholar]
  • 89. Narr KL, Bilder RM, Toga AW, et al Mapping cortical thickness and gray matter concentration in first episode schizophrenia. Cereb. Cortex. 2005;15:708–719.[PubMed][Google Scholar]
  • 90. Gogtay N, Nugent TF, Herman D, et al Dynamic mapping of human hippocampal development during childhood and adolescence. Hippocampus. 2006;16:664–672.[PubMed][Google Scholar]
  • 91. Thompson PM, Hayashi KM, Simon S, et al Structural abnormalities in the brains of human subjects who use methamphetamine. J. Neurosci. 2004;24:6028–6036.[Google Scholar]
  • 92. Lin JJ, Salamon N, Lee AD, et al 3D pre-operative maps of hippocampal atrophy predict surgical outcomes in temporal lobe epilepsy. Neurology. 2005;65:1094–1097.[Google Scholar]
  • 93. Bearden CE, Thompson PM, Dalwani M, et al Cortical gray matter density increases in lithium-treated patients with bipolar disorder. Biol. Psychiatry. 2007 [In press] [Google Scholar]
  • 94. Butters MA, Aizenstein HJ, Hayashi KM, et al Three-dimensional mapping reveals decreased volume of the caudate nucleus in late-life depression. Biol. Psychiatry. 2007 [submitted] [Google Scholar]
  • 95. Van Hoesen GW, Augustinack JC, Dierking J, et al. The parahippocampal gyrus in Alzheimer’s disease. Clinical and preclinical neuroanatomical correlates. Ann. N. Y. Acad. Sci. 2000;911:254–274.[PubMed]
  • 96. Roybal DJ, Dutton RA, Hayashi KM, et al. Mapping ApoE4 and Gender Effects on Hippocampal Atrophic Rates: A Longitudinal MRI Study of Normal Aging, 2005; Annual Scientific Meeting of the American Geriatric Society (AGS); May 11–15; Orlando, FL. 2005. [PubMed]
  • 97. Ashburner J, Csernansky JG, Davatzikos C, et al Computer-assisted imaging to assess brain structure in healthy and diseased brains. Lancet. 2003;2:78–88.[PubMed][Google Scholar]
  • 98. Good CD, Johnsrude IS, Ashburner J, et al A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage. 2001;14:21–36.[PubMed][Google Scholar]
  • 99. Ashburner J, Friston KJVoxel-based morphometry–the methods. Neuroimage. 2000;11:805–821.[PubMed][Google Scholar]
  • 100. Ashburner J, Friston KJWhy voxel-based morphometry should be used. Neuroimage. 2001;14:1238–1243.[PubMed][Google Scholar]
  • 101. Bookstein FVoxel-based morphometry should not be used with imperfectly registered images. Neuroimage. 2001;14:1454–1462.[PubMed][Google Scholar]
  • 102. Davatzikos C, Genc A, Xu D, Resnick SMVoxel-based morphometry using the RAVENS maps: methods and validation using simulated longitudinal atrophy. Neuroimage. 2001a;14:1361–1369.[PubMed][Google Scholar]
  • 103. Thacker N‘Tutorial: A Critical Analysis of VBM,’ 2003, 2003.[PubMed]
  • 104. Crum WR, Griffin LD, Hill DL, Hawkes DJZen and the art of medical image registration: correspondence, homology, and quality. Neuroimage. 2003;20:1425–1437. Review. [[PubMed][Google Scholar]
  • 105. Sowell ER, Thompson PM, Welcome SE, et al Cortical abnormalities in children and adolescents with attention-deficit hyperactivity disorder. Lancet. 2003;362:1699–1707.[PubMed][Google Scholar]
  • 106. Selemon LD, Rajkowska G, Goldman-Rakic PS. Abnormally high neuronal density in the schizophrenic cortex. A morphometric analysis of prefrontal area 9 and occipital area 17. Arch. Gen. Psychiatry. 1995;52:805–818. discussion 819–20. [[PubMed]
  • 107. Raz N, et al Selective aging of the human cerebral cortex observed in vivo: differential vulnerability of the prefrontal gray matter. Cereb. Cortex. 1997;7:268–282.[PubMed][Google Scholar]
  • 108. Magnotta VA, et al Quantitative in vivo measurement of gyrification in the human brain: changes associated with aging. Cereb. Cortex. 1999;9:151–160.[PubMed][Google Scholar]
  • 109. Shaw P, Greenstein D, Lerch J, et al Intellectual ability and cortical development in children and adolescents. Nature. 2006;440:676–679.[PubMed][Google Scholar]
  • 110. Vidal CN, Hayashi KM, Geaga JA, et al Dynamically spreading frontal and cingulate deficits mapped in adolescents with schizophrenia. Arch. Gen. Psychiatry. 2006;63:25–34.[PubMed][Google Scholar]
  • 111. Luders E, Narr KL, Thompson PM, et al. Gender Effects on Cortical Thickness; 11th Annual Meeting of the Organization for Human Brain Mapping (OHBM); Toronto, Canada. 2005. pp. 12–16. [PubMed]
  • 112. Lerch JP, Pruessner JC, Zijdenbos A, et al Focal decline of cortical thickness in Alzheimer’s disease identified by computational neuroanatomy. Cereb Cortex. 2004;15:995–1001. Epub 2004 Nov 10. [[PubMed][Google Scholar]
  • 113. Narr KL, Toga AW, Szeszko P, et al Cortical thinning in cingulate and occipital cortices in first episode schizophrenia. Biol. Psychiatry. 2005;58:32–40.[PubMed][Google Scholar]
  • 114. Sowell ER, Thompson PM, Leonard CM, et al Longitudinal mapping of cortical thickness and brain growth in normal children. J. Neurol. Sci. 2004;24:8223–8231.[Google Scholar]
  • 115. Lu LH, Leonard CM, Thompson PM, et al Normal developmental changes in inferior frontal gray matter are associated with improvement in phonological processing: a longitudinal MRI analysis. Cerebral Cortex. 2006 [June 16 Epub ahead of print.] [[PubMed][Google Scholar]
  • 116. Sowell ER, Thompson PM, Mattson SN, et al Regional brain shape abnormalities persist into adolescence after heavy prenatal alcohol exposure. Cereb. Cortex. 2002a;12:856–865.[PubMed][Google Scholar]
  • 117. Gogtay N, Ordonez A, Herman DH, et al Dynamic mapping of cortical brain development in pediatric bipolar illness. J. Child Psychol. Psychiatry. 2007 [In press] [[PubMed][Google Scholar]
  • 118. Bearden CE, Dutton RA, van Erp TGM, et al. Abnormal cortical thickness and cortical asymmetry mapped in children with 22q11.2 Microdeletions; 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 119. Lin JJ, Salamon N, Lee AD, et al Reduced Cortical Thickness & Complexity Mapped in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis. Cerebral Cortex. 2006 [In press] [[PubMed][Google Scholar]
  • 120. Cannon TD, Hennah W, van Erp TGM, et al DISC1/TRAX haplotypes associate with schizophrenia, reduced prefrontal gray matter, and impaired short- and long-term memory. Arch. Gen. Psychiatry. 2005;62:1205–1213.[PubMed][Google Scholar]
  • 121. Zeineh MM, Engel SA, Thompson PM, Bookheimer SDynamics of the hippocampus during encoding and retrieval of face-name pairs. Science. 2003;299:577–580.[PubMed][Google Scholar]
  • 122. Le Bihan D, Breton E, Lallemand D, et al MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401–407.[PubMed][Google Scholar]
  • 123. Moseley ME, Cohen Y, Kucharczyk J, et al Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology. 1990;176:439–445.[PubMed][Google Scholar]
  • 124. Basser PJ, Mattiello J, LeBihan DEstimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. B. 1994;103:247–254.[PubMed][Google Scholar]
  • 125. Kantarci K, Jack CR, Jr, Xu YC, et al Regional metabolic patterns in mild cognitive impairment and Alzheimer’s disease: A 1H MRS study. Neurology. 2000;55:210–217.[Google Scholar]
  • 126. Kantarci K, Jack CR, Jr, Xu YC, et al Mild cognitive impairment and Alzheimer disease: regional diffusivity of water. Radiology. 2001;219:101–107.[Google Scholar]
  • 127. Sandson TA, Felician O, Edelman RR, Warach SDiffusion-weighted magnetic resonance imaging in Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 1999;10:166–171.[PubMed][Google Scholar]
  • 128. Schott JM, Price SL, Frost C, et al Measuring atrophy in Alzheimer disease: a serial MRI study over 6 and 12 months. Neurology. 2005;65:119–124.[PubMed][Google Scholar]
  • 129. Thompson PM, Giedd JN, Woods RP, et al Growth patterns in the developing brain detected by using continuum-mechanical tensor maps. Nature. 2000;404:190–193.[PubMed][Google Scholar]
  • 130. Janke AL, Zubicaray GD, Rose SE, et al 4D deformation modeling of cortical disease progression in Alzheimer’s dementia. Magn Reson Med. 2001;46:661–666.[PubMed][Google Scholar]
  • 131. Studholme C, Cardenas V, Schuff N, et al. Detecting Spatially Consistent Structural Differences in Alzheimer’s and Fronto Temporal Dementia Using Deformation Morphometry; Conference Series on Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) 2001; 2001. pp. 41–48. [PubMed]
  • 132. Chiang MC, Leow AD, Dutton RA, et al. Fluid registration of diffusion tensor imaging using information theory. In: Gee JC, Thompson PM, editors. Submitted to IEEE Transactions on Medical Imaging, Special Issue on Computational Neuroanatomy. 2006. to appear March 2007 [submitted, June 29, 2006] [PubMed]
  • 133. Leow AD, Soares JC, Hayashi KM, et al Asymmetrical effects of lithium on brain structure mapped in healthy individuals. 2006 [submitted] [PubMed]
  • 134. Thompson PM, Toga AWCortical diseases and cortical localization [Review Article] Nature Encyclopedia of the Life Sciences (ELS), 2003. 2003[PubMed][Google Scholar]
  • 135. Leow AD, Lee AD, Chiang MC, et al. Analysis of Regional Brain Atrophy in a Single Case of Semantic Dementia Using Serial MRI with Inverse-Consistent Non-Rigid Registration; 11th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 12–16; Toronto, Canada. 2005. [PubMed]
  • 136. Lee AD, Leow AD, Lu A, et al. Tensor-Based Morphometry Reveals 3D Profile of Altered Brain Structure in Fragile X Syndrome; 61st Annual Scientific Convention of the Society of Biological Psychiatry (SOBP); May 18–20; Toronto, Ontario, Canada. 2006. [PubMed]
  • 137. Chiang MC, Reiss AL, Dutton RA, et al. 3D Pattern of Brain Volume Reduction in Williams Syndrome Visualized using Tensor-Based Morphometry; 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 138. Foland LC, Altshuler LL, Leow AD, et al. A Tensor-Based Morphometric Study of Bipolar Disorder; 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 139. Lepore N, Chou YY, Brun CA, et al. Genetic Influences on Brain Structure and Fiber Architecture Mapped Using Diffusion Tensor Imaging and Tensor-Based Morphometry in Twins; 12th Annual Meeting of the Organization for Human Brain Mapping (OHBM); June 11–15; Florence, Italy. 2006. [PubMed]
  • 140. Jack CR, Jr, Petersen RC, Xu Y, et al Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology. 2000;55:484–489.[Google Scholar]
  • 141. Bernstein MA, Lin C, Borowski BJ, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): The MR Imaging Protocol. Presented at State-of-the-Art Cardiovascular and Neuro MRI, a Joint Workshop of the ISMRM and CSR; September; Beijing, China. 2005. [PubMed]
  • 142. Archer HA, Edison P, Brooks DJ, et al Amyloid load and cerebral atrophy in Alzheimer’s disease: An (11)C-PIB positron emission tomography study. Ann Neurol. 2006;60:145–147. [Epub ahead of print] [[PubMed][Google Scholar]
  • 143. Kochunov PK, et al Relationship among neuroimaging markers of merebral atrophy during normal aging. Human Brain Mapping. 2007 Feb 8; [Epub ahead of print] [PubMed][Google Scholar]
  • 144. Jack CR, Jr, Petersen RC, Xu YC, et al Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology. 1997;49:786–794.[Google Scholar]
  • 145. Xu Y, et al Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. Neurology. 2000;54(9):1760–1767.[PubMed][Google Scholar]
  • 146. Chetelat G, Desgranges B, De La Sayette V, et al Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Neuroreport. 2002;13:1939–1943.[PubMed][Google Scholar]
  • 147. Kochunov P, et al Age-related morphology trends of cortical sulci. Human Brain Mapping. 2005;26(3):210–220.[PubMed][Google Scholar]
  • 148. Burggren AC, et al Reduced cortical thickness in hippocampal subregions in people at genetic risk for Alzheimer’s disease. 2007 [submitted] [PubMed]
  • 149. Rose SE, et al Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment. J. Neurol. Neurosurg. Psychiatry. 2006;77(10):1122–1128.[Google Scholar]
Collaboration tool especially designed for Life Science professionals.Drag-and-drop any entity to your messages.