title: Hippocampal shape analysis of Alzheimer disease based on machine learning methods.
abstract: OBJECTIVE
  Alzheimer disease (AD) is a neurodegenerative disease characterized by progressive dementia. The hippocampus is particularly vulnerable to damage at the very earliest stages of AD. This article seeks to evaluate critical AD-associated regional changes in the hippocampus using machine learning methods.
  
  
  METHODS
  High-resolution MR images were acquired from 19 patients with AD and 20 age- and sex-matched healthy control subjects. Regional changes of bilateral hippocampi were characterized using computational anatomic mapping methods. A feature selection method for support vector machine and leave-1-out cross-validation was introduced to determine regional shape differences that minimized the error rate in the datasets.
  
  
  RESULTS
  Patients with AD showed significant deformations in the CA1 region of bilateral hippocampi, as well as the subiculum of the left hippocampus. There were also some changes in the CA2-4 subregions of the left hippocampus among patients with AD. Moreover, the left hippocampal surface showed greater variations than the right compared with those in healthy control subjects. The accuracies of leave-1-out cross-validation and 3-fold cross-validation experiments for assessing the reliability of these subregions were more than 80% in bilateral hippocampi.
  
  
  CONCLUSIONS
  Subtle and spatially complex deformation patterns of hippocampus between patients with AD and healthy control subjects can be detected by machine learning methods.
authors: Department of Bioengineering, Beijing University of Aeronautics and Astronautics, and Department of Radiology, Peking University First Hospital, Beijing, People's Republic of China.
authors: S
authors: S
authors: Li
authors: F
authors: F
authors: Shi
authors: F
authors: F
authors: Pu
authors: X
authors: X
authors: Li
authors: T
authors: T
authors: Jiang
authors: S
authors: S
authors: Xie
authors: Y
authors: Y
authors: Wang
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000473:pathology*; D001185:Artificial Intelligence; D005260:Female; D006624:Hippocampus / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
references: Psychiatry Clin Neurosci. 1998 Dec;52(6):593-9
references: 9895207
references: Neurology. 1998 Jun;50(6):1563-71
references: 9633695
references: Neuroimage. 2006 Mar;30(1):52-60
references: 16243546
references: Med Image Comput Comput Assist Interv. 2005;8(Pt 2):666-74
references: 16686017
references: Neuroimage. 2002 Sep;17(1):29-46
references: 12482066
references: Neurosci Lett. 1997 Jan 31;222(2):119-22
references: 9111743
references: Lancet. 1994 Sep 17;344(8925):769-72
references: 7916070
references: Arch Neurol. 2005 Nov;62(11):1718-22
references: 16286546
references: IEEE Trans Inf Technol Biomed. 2003 Sep;7(3):191-6
references: 14518732
references: J Psychiatr Res. 1975 Nov;12(3):189-98
references: 1202204
references: Ann Neurol. 1999 Mar;45(3):358-68
references: 10072051
references: Science. 1991 Sep 20;253(5026):1380-6
references: 1896849
references: Acta Neuropathol. 1991;82(4):239-59
references: 1759558
references: Neuroimage. 2000 Jun;11(6 Pt 1):805-21
references: 10860804
references: IEEE Trans Med Imaging. 1998 Feb;17(1):87-97
references: 9617910
references: Neurobiol Aging. 1997 Mar-Apr;18(2):131-8
references: 9258889
references: J Neural Transm Park Dis Dement Sect. 1995;9(1):73-86
references: 7605591
references: Cereb Cortex. 2001 Jan;11(1):1-16
references: 11113031
references: NeuroRx. 2004 Apr;1(2):196-205
references: 15717020
references: Neurology. 2001 Mar 27;56(6):820-1
references: 11274335
references: J Neurol Sci. 1992 Apr;108(2):168-77
references: 1517748
references: Neurology. 2003 Jan 28;60(2):253-60
references: 12552040
references: Neuroimage. 2004 Aug;22(4):1754-66
references: 15275931
references: Neurobiol Aging. 2003 Mar-Apr;24(2):221-31
references: 12498956
references: J Neurol Neurosurg Psychiatry. 2002 Dec;73(6):657-64
references: 12438466
references: Ann Neurol. 1986 Oct;20(4):472-81
references: 3789663
references: Brain Res. 1998 Sep 14;805(1-2):267-9
references: 9733982
references: Neuroimage. 2005 Mar;25(1):253-66
references: 15734360
references: J Neurosci. 2003 Feb 1;23(3):994-1005
references: 12574429
references: J Neuropathol Exp Neurol. 1998 Apr;57(4):323-8
references: 9600224
references: Arch Neurol. 2003 Jul;60(7):949-56
references: 12873851
references: Neurology. 1984 Jul;34(7):939-44
references: 6610841
references: J Magn Reson Imaging. 2004 Mar;19(3):274-82
references: 14994294
references: Neuroimage. 2005 May 1;25(4):1077-89
references: 15850726
references: J Neurol Neurosurg Psychiatry. 2001 Oct;71(4):441-7
references: 11561025
references: Neurology. 1992 Mar;42(3 Pt 1):631-9
references: 1549228
references: Inf Process Med Imaging. 2003 Jul;18:114-25
references: 15344451
references: Arch Neurol. 1998 Mar;55(3):326-35
references: 9520006
references: Neuroimage. 2005 Apr 15;25(3):783-92
references: 15808979
references: Neurology. 1986 Jul;36(7):879-87
references: 3487046
references: Neuroimage. 2004 Jan;21(1):46-57
references: 14741641
references: Neurobiol Aging. 2001 Sep-Oct;22(5):747-54
references: 11705634
references: Brain Res. 1998 Jul 13;799(1):148-55
references: 9666109
references: Neuroimage. 2003 Apr;18(4):895-907
references: 12725765
references: Neuroimage. 2001 Aug;14(2):298-309
references: 11467904
references: Neurosci Lett. 1995 Jan 23;184(2):141-4
references: 7724049