Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness

NeuroImage

Volumn 93, Issue P1, 2014, Pages 107-123

  Kim, Won Hwa ^a,c   Singh, Vikas ^a,b,c   Chung, Moo K ^b   Hinrichs, Chris ^a   Pachauri, Deepti ^a   Okonkwo, Ozioma C ^c,d   Johnson, Sterling C ^c,d  

^a University of Wisconsin   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

^c WILLIAM S MIDDLETON MEMORIAL VETERANS HOSPITAL   (United States)

^d UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

Alzheimer's disease; Cortical thickness discrimination; Graph wavelets; Multi resolution analysis; Non Euclidean wavelet; Shape analysis

Indexed keywords

AGED; ALZHEIMER DISEASE; ARTICLE; BRAIN CORTEX; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; CORTICAL THICKNESS (BRAIN); DIAGNOSTIC IMAGING; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; FOURIER TRANSFORMATION; HUMAN; IMAGE ANALYSIS; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; NON EUCLIDEAN WAVELET; NUCLEAR MAGNETIC RESONANCE IMAGING; OPTICAL RESOLUTION; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SIGNAL DETECTION; SIGNAL NOISE RATIO; STATISTICAL ANALYSIS; WAVELET ANALYSIS; ANATOMY AND HISTOLOGY; PATHOLOGY;

AGED; ALZHEIMER DISEASE; CEREBRAL CORTEX; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; MALE; WAVELET ANALYSIS;

EID: 84897043300     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.02.028     Document Type: Article

References (52)

1. Antoine J.-P., Demanet L., Jacques L., Vandergheynst P. Wavelets on the sphere: implementation and approximations. Appl. Comput. Harmon. Anal. 2002, 13(3):177-200.
2. Braak H., Braak E. Staging of Alzheimer's disease-related neurofibrillary changes. Neurobiol. Aging 1995, 16(3):271-278.
3. Cho Y., Seong J.-K., Jeong Y., Shin S.Y. Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data. NeuroImage 2012, 59(3):2217-2230.
4. Chung F.R. Spectral Graph Theory 1997, vol. 92. AMS Bookstore.
5. Chung M., Robbins S., Dalton K., et al. Cortical thickness analysis in autism with heat kernel smoothing. NeuroImage 2005, 25(4):1256-1265.
6. Chung M., Dalton K., Li S., et al. Weighted Fourier series representation and its application to quantifying the amount of gray matter. IEEE Trans. Med. Imaging 2007, 26(4):566-581.
7. Coifman R., Maggioni M. Diffusion wavelets. Appl. Comput. Harmon. Anal. 2006, 21(1):53-94.
8. Daubechies I. The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 1990, 36(5):961-1005.
9. de Leon M.J., George A.E., Reisberg B., Ferris S., Kluger A., Stylopoulos L.A., Miller J., La Regina M.E., Chen C., Cohen J. Alzheimer's disease: longitudinal CT studies of ventricular change. Am. J. Roentgenol. 1989, 152(6):1257-1262.
10. Dickerson B.C., Wolk D.A. MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults. Neurology 2012, 78(2):84-90.
11. Dickerson B.C., Feczko E., Augustinack J.C., Pacheco J., Morris J.C., Fischl B., Buckner R.L. Differential effects of aging and Alzheimer's disease on medial temporal lobe cortical thickness and surface area. Neurobiol. Aging 2009, 30(3):432-440.
12. Erkinjuntti T., Ketonen L., Sulkava R., Sipponen J., Vuorialho M., Iivanainen M. Do white matter changes on MRI and CT differentiate vascular dementia from Alzheimer's disease. J. Neurol. Neurosurg. Psychiatry 1987, 50(1):37-42.
13. Fischl B. Freesurfer. NeuroImage 2012, 62(2):774-781.
14. Freeden W., Windheuser U. Spherical wavelet transform and its discretization. Adv. Comput. Math. 1996, 5(1):51-94.
15. Hammond D., Vandergheynst P., Gribonval R. Wavelets on graphs via spectral graph theory. Appl. Comput. Harmon. Anal. 2011, 30(2):129-150.
16. Hinrichs C., Singh V., Mukherjee L., Xu G., Chung M.K., Johnson S.C. Spatially augmented LP boosting for ad classification with evaluations on the ADNI dataset. NeuroImage 2009, 48(1):138-149.
17. Hinrichs C., Dowling N.M., Johnson S.C., Singh V. MKL-based sample enrichment and customized outcomes enable smaller AD clinical trials. Machine Learning and Interpretation in Neuroimaging 2012, 124-131. Springer.
18. Hodsman A., Kisiel M., Adachi J., Fraher L., Watson P. Histomorphometric evidence for increased bone turnover without change in cortical thickness or porosity after 2years of cyclical hPTH (1-34) therapy in women with severe osteoporosis. Bone 2000, 27(2):311-318.
19. Hyde K.L., Lerch J.P., Zatorre R.J., Griffiths T.D., Evans A.C., Peretz I. Cortical thickness in congenital amusia: when less is better than more. J. Neurosci. 2007, 27(47):13028-13032.
20. Johnson S.C., Rue A.L., Hermann B.P., Xu G., Koscik R.L., Jonaitis E.M., Bendlin B.B., Hogan K.J., Roses A.D., Saunders A.M., Lutz M.W., Asthana S., Green R.C., Sager M.A. The effect of TOMM40 poly-T length on gray matter volume and cognition in middle-aged persons with APOE ε3/ε3 genotype. Alzheimers Dement. 2011, 7(4):456-465.
21. Kim W.H., Pachauri D., Hatt C., Chung M.K., Johnson S., Singh V. Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination. Adv. Neural Inf. Process. Syst. 2012, 25:1250-1258.
22. Lehmann M., Crutch S.J., Ridgway G.R., Ridha B.H., Barnes J., Warrington E.K., Rossor M.N., Fox N.C. Cortical thickness and voxel-based morphometry in posterior cortical atrophy and typical Alzheimer's disease. Neurobiol. Aging 2011, 32(8):1466-1476.
23. Lemaitre H., Goldman A.L., Sambataro F., Verchinski B.A., Meyer-Lindenberg A., Weinberger D.R., Mattay V.S. Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume. Neurobiol. Aging 2012, 33(3):617.e1-617.e9.
24. Leonardi N., Van De Ville D. Tight wavelet frames on multislice graphs. IEEE Trans. Signal Process. 2013, 61(13):3357-3367.
25. Lerch J.P., Pruessner J.C., Zijdenbos A., Hampel H., Teipel S.J., Evans A.C. Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. Cereb. Cortex 2005, 15(7):995-1001.
26. Lerch J.P., Pruessner J., Zijdenbos A.P., Collins D.L., Teipel S.J., Hampel H., Evans A.C. Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls. Neurobiol. Aging 2008, 29(1):23-30.
27. Lindeberg T. Scale-Space Theory in Computer Vision 1993, Springer.
28. Mallat S.G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 1989, 11(7):674-693.
29. Mallat S. A Wavelet Tour of Signal Processing 1999, Academic Press.
30. McKhann G., Drachman D., Folstein M., Katzman R., Price D., Stadlan E.M. 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 1984, 34(7):939-944.
31. Narang S.K., Ortega A. Perfect reconstruction two-channel wavelet filter banks for graph structured data. IEEE Trans. Signal Process. 2012, 60(6):2786-2799.
32. Newman D., Dougherty G., Al Obaid A., Al Hajrasy H. Limitations of clinical CT in assessing cortical thickness and density. Phys. Med. Biol. 1998, 43(3):619.
33. O'Donnell S., Noseworthy M.D., Levine B., Dennis M. Cortical thickness of the frontopolar area in typically developing children and adolescents. NeuroImage 2005, 24(4):948-954.
34. Pachauri D., Hinrichs C., Chung M., et al. Topology-based kernels with application to inference problems in Alzheimer's disease. IEEE Trans. Med. Imaging 2011, 30(10):1760-1770.
35. Palaniyappan L. Computing cortical surface measures in schizophrenia. Br. J. Psychiatry 2010, 196(5):414.
36. Panizzon M.S., Fennema-Notestine C., Eyler L.T., Jernigan T.L., Prom-Wormley E., Neale M., Jacobson K., Lyons M.J., Grant M.D., Franz C.E., et al. Distinct genetic influences on cortical surface area and cortical thickness. Cereb. Cortex 2009, 19(11):2728-2735.
37. Petersen R., Stevens J., Ganguli M., Tangalos E., Cummings J., DeKosky S. Practice parameter: early detection of dementia: mild cognitive impairment (an evidence-based review) report of the quality standards subcommittee of the american academy of neurology. Neurology 2001, 56(9):1133-1142.
38. Prevrhal S., Engelke K., Kalender W.A. Accuracy limits for the determination of cortical width and density: the influence of object size and CT imaging parameters. Phys. Med. Biol. 1999, 44(3):751.
39. Querbes O., Aubry F., Pariente J., Lotterie J.-A., Démonet J.-F., Duret V., Puel M., Berry I., Fort J.-C., Celsis P., et al. Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve. Brain 2009, 132(8):2036-2047.
40. Salat D.H., Buckner R.L., Snyder A.Z., Greve D.N., Desikan R.S., Busa E., Morris J.C., Dale A.M., Fischl B. Thinning of the cerebral cortex in aging. Cereb. Cortex 2004, 14(7):721-730.
41. Shaw P., Greenstein D., Lerch J., Clasen L., Lenroot R., Gogtay N., Evans A., Rapoport J., Giedd J. Intellectual ability and cortical development in children and adolescents. Nature 2006, 440(7084):676-679.
42. Shaw P., Lerch J., Greenstein D., Sharp W., Clasen L., Evans A., Giedd J., Castellanos F.X., Rapoport J. Longitudinal mapping of cortical thickness and clinical outcome in children and adolescents with attention-deficit/hyperactivity disorder. Arch. Gen. Psychiatry 2006, 63(5):540.
43. Sowell E.R., Thompson P.M., Leonard C.M., Welcome S.E., Kan E., Toga A.W. Longitudinal mapping of cortical thickness and brain growth in normal children. J. Neurosci. 2004, 24(38):8223-8231.
44. Sowell E.R., Peterson B.S., Kan E., Woods R.P., Yoshii J., Bansal R., Xu D., Zhu H., Thompson P.M., Toga A.W. Sex differences in cortical thickness mapped in 176 healthy individuals between 7 and 87years of age. Cereb. Cortex 2007, 17(7):1550-1560.
45. Thompson P.M., Hayashi K.M., Sowell E.R., Gogtay N., Giedd J.N., Rapoport J.L., De Zubicaray G.I., Janke A.L., Rose S.E., Semple J., et al. Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia. NeuroImage 2004, 23(Suppl. 1):S2-S18.
46. Thompson W.K., Hallmayer J., O'Hara R. Design considerations for characterizing psychiatric trajectories across the lifespan: application to effects of APOE-E4 on cerebral cortical thickness in Alzheimer's disease. Am. J. Psychiatr. 2011, 168(9):894-903.
47. Van De Ville D., Blu T., Unser M. Integrated wavelet processing and spatial statistical testing of fmri data. NeuroImage 2004, 23(4):1472-1485.
48. Whitwell J.L., Tosakulwong N., Weigand S.D., Senjem M.L., Lowe V.J., Gunter J.L., Boeve B.F., Knopman D.S., Dickerson B.C., Petersen R.C., Jack C.R. Does amyloid deposition produce a specific atrophic signature in cognitively normal subjects?. NeuroImage 2013, 2:249-257.
49. Wirth M., Madison C.M., Rabinovici G.D., Oh H., Landau S.M., Jagust W.J. Alzheimer's disease neurodegenerative biomarkers are associated with decreased cognitive function but not β -amyloid in cognitively normal older individuals. J. Neurosci. 2013, 33(13):5553-5563.
50. Wolz R., Julkunen V., Koikkalainen J., Niskanen E., Zhang D.P., Rueckert D., Soininen H., Lötjönen J., et al. Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease. PLoS One 2011, 6(10):e25446.
51. Yu P., Grant P.E., Qi Y., Han X., Ségonne F., Pienaar R., Busa E., Pacheco J., Makris N., Buckner R.L., et al. Cortical surface shape analysis based on spherical wavelets. IEEE Trans. Med. Imaging 2007, 26(4):582-597.
52. Zhang F., Hancock E.R. Graph spectral image smoothing using the heat kernel. Pattern Recogn. 2008, 41(11):3328-3342.