Corrigendum to "Event time analysis of longitudinal neuroimage data" [NeuroImage, 97, (15 August 2014), 9-18], doi: 10.1016/j.neuroimage.2014.04.015;Event time analysis of longitudinal neuroimage data

NeuroImage

Volumn 97, Issue , 2014, Pages 9-18

  Sabuncu, Mert R ^a,b   Bernal Rusiel, Jorge L ^a   Reuter, Martin ^a,c   Greve, Douglas N ^a   Fischl, Bruce ^a,b  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c Massachusetts Institute of Technology   (United States)

Author keywords

Cox regression; Event time analysis; Linear mixed effects models; Longitudinal studies; Survival analysis

Indexed keywords

AGED; ANALYTIC METHOD; ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; CORTICAL THICKNESS (BRAIN); DATA PROCESSING; EVENT TIME ANALYSIS; FEMALE; GRAY MATTER; HUMAN; IMAGE ANALYSIS; LINEAR MIXED EFFECT MODEL; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MASS UNIVARIATE METHOD; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; ONSET AGE; PRIORITY JOURNAL; PROPORTIONAL HAZARDS MODEL; SENSITIVITY ANALYSIS; STATISTICAL MODEL; VALIDATION STUDY; ANATOMY AND HISTOLOGY; BRAIN CORTEX; HIPPOCAMPUS; QUALITY CONTROL; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

BENCHMARKING; CEREBRAL CORTEX; DATA INTERPRETATION, STATISTICAL; HIPPOCAMPUS; HUMANS; LINEAR MODELS; LONGITUDINAL STUDIES; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; NEUROIMAGING; PROPORTIONAL HAZARDS MODELS;

EID: 84901292820     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.12.051     Document Type: Erratum

References (53)

1. Albin R.L., Young A.B., Penney J.B., Handelin B., Balfour R., Anderson K.D., Markel D.S., Tourtellotte W.W., Reiner A. Abnormalities of striatal projection neurons and N-methyl-d-aspartate receptors in presymptomatic Huntington's disease. N. Engl. J. Med. 1990, 322:1293-1298.
2. Benjamini Y., Krieger A.M., Yekutieli D. Adaptive linear step-up procedures that control the false discovery rate. Biometrika 2006, 93:491-507.
3. Bernal-Rusiel J.L., Greve D.N., Reuter M., Fischl B., Sabuncu M.R. Statistical analysis of longitudinal neuroimage data with linear mixed effects models. Neuroimage 2013, 66:249-260.
4. Bernal-Rusiel J.L., Reuter M., Greve D.N., Fischl B., Sabuncu M.R. Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data. Neuroimage 2013, 81.
5. Borgwardt S., McGuire P., Fusar-Poli P. Gray matters: mapping the transition to psychosis. Schizophr. Res. 2011, 133:63-67.
6. Buckner R.L., Snyder A.Z., Shannon B.J., LaRossa G., Sachs R., Fotenos A.F., Sheline Y.I., Klunk W.E., Mathis C.A., Morris J.C. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J. Neurosci. 2005, 25:7709-7717.
7. Chetelat G., Landeau B., Eustache F., Mezenge F., Viader F., de La Sayette V., Desgranges B., Baron J.C. Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study. Neuroimage 2005, 27:934-946.
8. Cox D.R. Regression models and life-tables. J. R. Stat. Soc. Ser. B Methodol. 1972, 187-220.
9. Cox D.R. Partial likelihood. Biometrika 1975, 62:269-276.
10. Dale A.M., Fischl B., Sereno M.I. Cortical surface-based analysis* 1: I. Segmentation and surface reconstruction. Neuroimage 1999, 9:179-194.
11. Desikan R.S., Cabral H.J., Fischl B., Guttmann C.R., Blacker D., Hyman B.T., Albert M.S., Killiany R.J. Temporoparietal MR imaging measures of atrophy in subjects with mild cognitive impairment that predict subsequent diagnosis of Alzheimer disease. Am. J. Neuroradiol. 2009, 30:532-538.
12. Desikan R.S., Cabral H.J., Settecase F., Hess C.P., Dillon W.P., Glastonbury C.M., Weiner M.W., Schmansky N.J., Salat D.H., Fischl B. Automated MRI measures predict progression to Alzheimer's disease. Neurobiol. Aging 2010, 31:1364-1374.
13. Devanand D., Pradhaban G., Liu X., Khandji A., De Santi S., Segal S., Rusinek H., Pelton G., Honig L., Mayeux R. Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology 2007, 68:828-836.
14. Dickerson B.C., Goncharova I., Sullivan M., Forchetti C., Wilson R., Bennett D., Beckett L., deToledo-Morrell L. MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer's disease. Neurobiol. Aging 2001, 22:747-754.
15. Dickerson B.C., Bakkour A., Salat D.H., Feczko E., Pacheco J., Greve D.N., Grodstein F., Wright C.I., Blacker D., Rosas H.D. 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 2009, 19:497-510.
16. Fischl B. FreeSurfer. Neuroimage 2012, 62(2):774-781.
17. Fischl B., Dale A.M. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl. Acad. Sci. 2000, 97:11050.
18. Fischl B., Sereno M.I., Dale A.M. Cortical surface-based analysis* 1: II: inflation, flattening, and a surface-based coordinate system. Neuroimage 1999, 9:195-207.
19. Fischl B., Sereno M.I., Tootell R.B.H., Dale A.M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 1999, 8:272-284.
20. Fisher L.D., Lin D. Time-dependent covariates in the Cox proportional-hazards regression model. Annu. Rev. Public Health 1999, 20:145-157.
21. Fitzmaurice G.M., Laird N.M., Ware J.H. Applied Longitudinal Analysis 2011, Wiley.
22. Forsberg A., Engler H., Almkvist O., Blomquist G., Hagman G., Wall A., Ringheim A., Langstrom B., Nordberg A. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol. Aging 2008, 29:1456-1465.
23. Gauthier S., Reisberg B., Zaudig M., Petersen R.C., Ritchie K., Broich K., Belleville S., Brodaty H., Bennett D., Chertkow H. Mild cognitive impairment. Lancet 2006, 367:1262-1270.
24. Geerlings M., Den Heijer T., Koudstaal P., Hofman A., Breteler M. History of depression, depressive symptoms, and medial temporal lobe atrophy and the risk of Alzheimer disease. Neurology 2008, 70:1258-1264.
25. Good P.I. Permutation Tests 2000, Wiley Online Library.
26. Hagler D.J., Saygin A.P., Sereno M.I. Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data. Neuroimage 2006, 33:1093-1103.
27. Han X., Jovicich J., Salat D., van der Kouwe A., Quinn B., Czanner S., Busa E., Pacheco J., Albert M., Killiany R. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage 2006, 32:180-194.
28. Jack C.R., Petersen R.C., Xu Y.C., Waring S.C., O'Brien P.C., Tangalos E.G., Smith G.E., Ivnik R.J., Kokmen E. Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997, 49:786-794.
29. Jack C.R., Petersen R.C., Grundman M., Jin S., Gamst A., Ward C.P., Sencakova D., Doody R.S., Thal L.J. Longitudinal MRI findings from the vitamin E and donepezil treatment study for MCI. Neurobiol. Aging 2008, 29:1285-1295.
30. Jack C.R., Weigand S.D., Shiung M.M., Przybelski S.A., O'Brien P.C., Gunter J.L., Knopman D.S., Boeve B.F., Smith G.E., Petersen R.C. Atrophy rates accelerate in amnestic mild cognitive impairment. Neurology 2008, 70:1740-1752.
31. Jack C.R., Vemuri P., Wiste H.J., Weigand S.D., Lesnick T.G., Lowe V., Kantarci K., Bernstein M.A., Senjem M.L., Gunter J.L. Shapes of the trajectories of 5 major biomarkers of Alzheimer disease. Arch. Neurol. 2012, 69(7):856-867. (archneurol. 2011.3405 v2011). 10.1001/archneurol.2011.3405.
32. Julkunen V., Niskanen E., Muehlboeck S., Pihlajamaki M., Kononen M., Hallikainen M., Kivipelto M., Tervo S., Vanninen R., Evans A. Cortical thickness analysis to detect progressive mild cognitive impairment: a reference to Alzheimer's disease. Dement. Geriatr. Cogn. Disord. 2009, 28:404-412.
33. Kalbfleisch J.D., Prentice R.L. The Statistical Analysis of Failure Time Data 2011, John Wiley & Sons.
34. Kleinbaum D.G., Klein M. Survival Analysis 2012, Springer.
35. 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, 15:995-1001.
36. Marcus K.J., Astrakas L.G., Zurakowski D., Zarifi M.K., Mintzopoulos D., Poussaint T.Y., Anthony D.C., De Girolami U., Black P.M., Tarbell N.J. Predicting survival of children with CNS tumors using proton magnetic resonance spectroscopic imaging biomarkers. Int. J. Oncol. 2007, 30:651.
37. Morgan V., Riches S., Thomas K., Vanas N., Parker C., Giles S., Desouza N. Diffusion-weighted magnetic resonance imaging for monitoring prostate cancer progression in patients managed by active surveillance. Br. J. Radiol. 2011, 84:31-37.
38. Nichols T.E., Holmes A.P. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Mapp. 2002, 15:1-25.
39. Reuter M., Fischl B. Avoiding asymmetry-induced bias in longitudinal image processing. Neuroimage 2011, 57:19-21.
40. Reuter M., Rosas H.D., Fischl B. Highly accurate inverse consistent registration: a robust approach. Neuroimage 2010, 53:1181-1196.
41. Reuter M., Schmansky N.J., Rosas H.D., Fischl B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 2012, 10.1016/j. neuroimage.2012.02.084.
42. Risacher S.L., Saykin A.J., West J.D., Shen L., Firpi H.A., McDonald B.C. Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Curr. Alzheimer Res. 2009, 6:347.
43. Sabuncu M.R. A Bayesian algorithm for image-based time-to-event Prediction. MLMI Workshop, MICCAI 2013 2013.
44. Sabuncu M.R., Desikan R.S., Sepulcre J., Yeo B.T.T., Liu H., Schmansky N.J., Reuter M., Weiner M.W., Buckner R.L., Sperling R.A. The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Arch. Neurol. 2011, 68:1040.
45. Sabuncu M.R., Buckner R.L., Smoller J.W., Lee P.H., Fischl B., Sperling R.A. The association between a polygenic Alzheimer score and cortical thickness in clinically normal subjects. Cereb. Cortex 2012, 22:2653-2661.
46. Stoub T., Bulgakova M., Leurgans S., Bennett D., Fleischman D., Turner D. MRI predictors of risk of incident Alzheimer disease: a longitudinal study. Neurology 2005, 64:1520-1524.
47. Sun D., Phillips L., Velakoulis D., Yung A., McGorry P.D., Wood S.J., van Erp T.G., Thompson P.M., Toga A.W., Cannon T.D. Progressive brain structural changes mapped as psychosis develops in at risk individuals. Schizophr. Res. 2009, 108:85-92.
48. Thirion B., Pinel P., Mriaux S., Roche A., Dehaene S., Poline J.B. Analysis of a large fMRI cohort: statistical and methodological issues for group analyses. Neuroimage 2007, 35:105-120.
49. Tintore M., Rovira A., Rio J., Tur C., Pelayo R., Nos C., Tellez N., Perkal H., Comabella M., Sastre-Garriga J. Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis?. Neurology 2008, 70:1079-1083.
50. Tsiatis A.A., Davidian M. Joint modeling of longitudinal and time-to-event data: an overview. Stat. Sin. 2004, 14:809-834.
51. Vemuri P., Weigand S.D., Knopman D.S., Kantarci K., Boeve B.F., Petersen R.C., Jack C.R. Time-to-event voxel-based techniques to assess regional atrophy associated with MCI risk of progression to AD. Neuroimage 2011, 54:985-991.
52. Verbeke G., Molenberghs G. Linear Mixed Models for Longitudinal Data 2000, Springer, N.Y.
53. Whitfield-Gabrieli S., Thermenos H.W., Milanovic S., Tsuang M.T., Faraone S.V., McCarley R.W., Shenton M.E., Green A.I., Nieto-Castanon A., LaViolette P. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc. Natl. Acad. Sci. 2009, 106:1279-1284.