Hierarchical anatomical brain networks for MCI prediction: Revisiting volumetric measures

PLoS ONE

Volumn 6, Issue 7, 2011, Pages

  Zhou, Luping ^a   Wang, Yaping ^a   Li, Yang ^a   Yap, Pew Thian ^a   Shen, Dinggang ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b ADNI)   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; AGED; AMYGDALOID NUCLEUS; ARTICLE; BRAIN; BRAIN FORNIX; BRAIN REGION; BRAIN VENTRICLE; CAPSULA INTERNA; CINGULATE GYRUS; CLASSIFICATION; CONTROLLED STUDY; ENTORHINAL CORTEX; FEMALE; GLOBUS PALLIDUS; HIERARCHICAL ANATOMICAL BRAIN NETWORK; HIPPOCAMPUS; HUMAN; LINGUAL GYRUS; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NEUROANATOMY; NUCLEAR MAGNETIC RESONANCE IMAGING; OCCIPITAL LOBE; PREDICTION; PREFRONTAL CORTEX; UNCUS; VOLUMETRY; BIOLOGICAL MODEL; NERVE CELL NETWORK; PATHOLOGY;

AGED; BRAIN; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MILD COGNITIVE IMPAIRMENT; MODELS, NEUROLOGICAL; NERVE NET;

EID: 79960471063     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0021935     Document Type: Article

References (37)

1. Chételat G, Baron J, (2003) Early diagnosis of alzheimer's disease: contribution of structural neuroimaging. Neuroimage 18: 525-541.
2. Jack C Jr, Petersen R, Xu Y, Waring S, O'Brien P, et al. (1997) Medial temporal atrophy on mri in normal aging and very mild alzheimer's disease. Neurology 49: 786-794.
3. Jack C Jr, Petersen R, Xu Y, O'Brien P, Smith G, et al. (1998) Rate of medial temporal lobe atrophy in typical aging and alzheimer's disease. Neurology 51: 993-999.
4. Fan Y, Shen D, Davatzikos C, (2005) Classification of structural images via highdimensional image warping, robust feature extraction, and svm. pp. 1-8 In: Proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention.
5. Fan Y, Shen D, Gur R, Davatzikosa C, (2007) Compare: classification of morphological patterns using adaptive regional elements. IEEE Trans Med Imaging 26: 93-105.
6. Fan Y, Batmanghelich N, Clark C, Davatzikos C, Initiative ADN, (2008) Spatial patterns of brain atrophy in mci patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline. Neuroimage 39: 1731-1743.
7. Fan Y, Resnick S, Wu X, Davatzikos C, (2008) Structural and functional biomarkers of prodromal alzheimer's disease: a high-dimensional pattern classification study. Neuroimage 41: 277-285.
8. Thompson P, Mega M, Woods R, Zoumalan C, Lindshield C, et al. (2001) Cortical change in alzheimer's disease detected with a disease-specific population-based brain atlas. Cereb Cortex 1: 1-16.
9. Thompson P, Hayashi K, de Zubicaray G, Janke A, Rose S, et al. (2003) Dynamics of gray matter loss in alzheimer's disease. Journal of Neuroscience 23: 994-1005.
10. Thompson P, Hayashi K, Sowell E, Gogtay N, Giedd J, et al. (2004) Mapping cortical change in alzheimer's disease, brain development, and schizophrenia. Journal of Neuroscience 23: S2-S18.
11. Dickerson B, Bakkour A, Salat D, Feczko E, Pacheco J, et al. (2009) The cortical signature of alzheimer's disease: regionally specific cortical thinning relates to symptom severity in very mild to mild ad dementia and is detectable in asymptomatic amyloid-positive individuals. Cereb Cortex 19: 497-510.
12. Lerch J, Pruessner J, Zijdenbos A, Collins D, Teipel S, et al. (2008) Automated cortical thickness measurements from mri can accurately separate alzheimer's patients from normal elderly controls. Neurobiol Aging 29: 23-30.
13. Convit A, De Leon M, Tarshish C, De Santi S, Tsui W, et al. (1997) Specific hippocampal volume reductions in individuals at risk for alzheimer's disease. Neurobiol Aging 18: 131-138.
14. Colliot O, Chtelat G, Chupin M, Desgranges B, Magnin B, et al. (2008) Discrimination between alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus. Radiology 248: 194-201.
15. Chupin M, G'erardin E, Cuingnet R, Boutet C, Lemieux L, et al. (2009) Fully automatic hippocampus segmentation and classification in alzheimer's disease and mild cognitive impairment applied on data from adni. Hippocampus 19: 579-587.
16. Klöppel S, Stonnington C, Chu C, Draganski B, Scahill R, et al. (2008) Automatic classification of mr scans in alzheimer's disease. Brain 131: 681-689.
17. Lao Z, Shen D, Xue Z, Karacali B, Resnick S, et al. (2004) Morphological classification of brains via high-dimensional shape transformations and machine learning methods. Neurobiol Aging 21: 46-57.
18. Magnin B, Mesrob L, Kinkingnhun S, Plgrini-Issac M, Colliot O, et al. (2009) Support vector machine-based classification of alzheimer's disease from whole-brain anatomical mri. Neuroradiology 51: 939-944.
19. Braak H, Braak E, (1995) Staging of alzheimer's disease-related neurofibrillary changes. Neurobiol Aging 16: 271-278.
20. Cuingnet R, Gerardin E, Tessieras J, Auzias G, Lehricy S, et al. (2010) Automatic classification of patients with alzheimer's disease from structural mri: A comparison of ten methods using the adni database. Neuroimage 56: 766-781.
21. Davatzikos C, Fan Y, Wu X, Shen D, Resnick S, (2008) Detection of prodromal alzheimer's disease via pattern classification of magnetic resonance imaging. Neurobiol Aging 29: 514-523.
22. Zhou L, Wang Y, Li Y, Yap P, Shen D, et al. (2011) Hierarchical anatomical brain networks for mci prediction by partial least square analysis. In: Proceedings of Computer Vision and Pattern Recognition 2011 (to appear).
23. Jack C Jr, Bernstein M, Fox N, Thompson P, Alexander G, et al. (2008) The alzheimer's disease neuroimaging initiative (adni): Mri methods. J Magn Reson Imaging 27: 685-691.
24. McKhann G, Drachman D, Folstein M, Katzman R, Price D, et al. (1984) Clinical diagnosis of alzheimer's disease: report of the nincds-adrda work group under the auspices of department of health and human services task force on alzheimer's disease. Neurology 34: 939-944.
25. Sled J, Zijdenbos A, Evans A, (1998) A nonparametric method for automatic correction of intensity nonuniformity in mri data. IEEE Trans Medical Imaging 17: 87-97.
26. Shen D, Davatzikos C, (2003) Very high resolution morphometry using mass-preserving deformations and hammer elastic registration. NeuroImage 18: 28-41.
27. Kabani N, MacDonald J, Holmes C, Evans A, (1998) A 3d atlas of the human brain. NeuroImage 7: S7-S17.
28. Bassett D, Bullmore E, (2006) Small-world brain networks. Neuroscientist 12: 512-523.
29. Achard S, Salvador R, Whitcher B, Suckling J, Bullmore E, (2006) A resilient, lowfrequency, smallworld human brain functional network with highly connected association cortical hubs. Journal of Neuroscience 26: 63-72.
30. Rosipal R, Kramer N, (2006) Overview and recent advances in partial least squares. Lecture Notes in Computer Science 3940: 34-51.
31. Guyon I, Weston J, Barnhill S, Vapnik V, (2002) Gene selection for cancer classification using support vector machines. Machine Learning 46: 389-442.
32. Long X, Wyatt C, (2010) An automatic unsupervised classification of mr images in alzheimers disease. In: Proceedings of Computer Vision and Pattern Recognition 2010.
33. Wold S, Johansson W, Cocchi M, (1993) Pls- partial least- squares projections to latent structures. 3D QSAR in Drug Design: Volume 1: Theory Methods and Applications 1: 523-550.
34. Pengas G, Hodges J, Watson P, Nestor P, (2010) Focal posterior cingulate atrophy in incipient alzheimer's disease. Neurobiol Aging 31: 25-33.
35. Copenhaver B, Rabin L, Saykin A, Roth R, Wishart H, et al. (2006) The fornix and mammillary bodies in older adults with alzheimer's disease, mild cognitive impairment, and cognitive complaints: a volumetric mri study. Psychiatry Res 147: 93-103.
36. Nestor S, Rupsingh R, Borrie M, Smith M, Accomazzi V, et al. (2008) Ventricular enlargement as a possible measure of alzheimer's disease progression validated using the alzheimer's disease neuroimaging initiative database. Brain 131: 2443-2454.
37. Bozzali M, Falini A, Franceschi M, Cercignani1 M, Zuffi M, et al. (2002) White matter damage in alzheimer's disease assessed in vivo using diffusion tensor magnetic resonance imaging. Journal of Neurol Neurosurg Psychiatry 72: 742-746.