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Feasibility of Multi-site Clinical Structural Neuroimaging Studies of Aging Using Legacy Data

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Abstract

The application of advances in biomedical computing to medical imaging research is enabling scientists to conduct quantitative clinical imaging studies using data collected across multiple sites to test new hypotheses on larger cohorts, increasing the power to detect subtle effects. Given that many research groups have valuable existing (legacy) data, one goal of the Morphometry Biomedical Informatics Research Network (BIRN) Testbed is to assess the feasibility of pooled analyses of legacy structural neuroimaging data in normal aging and Alzheimer’s disease. The present study examined whether such data could be meaningfully reanalyzed as a larger combined data set by using rigorous data curation, image analysis, and statistical modeling methods; in this case, to test the hypothesis that hippocampal volume decreases with age and to investigate findings of hippocampal asymmetry. This report describes our work with legacy T1-weighted magnetic resonance (MR) and demographic data related to normal aging that have been shared through the BIRN by three research sites. Results suggest that, in the present application, legacy MR data from multiple sites can be pooled to investigate questions of scientific interest. In particular, statistical analyses suggested that a mixed-effects model employing site as a random effect best fits the data, accounting for site-specific effects while taking advantage of expected comparability of age-related effects. In the combined sample from three sites, significant age-related decline of hippocampal volume and right-dominant hippocampal asymmetry were detected in healthy elderly controls. These expected findings support the feasibility of combining legacy data to investigate novel scientific questions.

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References

  • Allen, J. S., Bruss, J., Brown, C. K., & Damasio, H. (2005). Normal neuroanatomical variation due to age: The major lobes and a parcellation of the temporal region. Neurobiology Aging, 26(9), 1245–1260 (discussion 1279–1282).

    Article  Google Scholar 

  • Arnold, J. B., Liow, J. S., Schaper, K. A., Stern, J. J., Sled, J. G., Shattuck, D. W., et al. (2001). Qualitative and quantitative evaluation of six algorithms for correcting intensity nonuniformity effects. NeuroImage, 13(5), 931–943.

    Article  PubMed  CAS  Google Scholar 

  • Barnes, J., Scahill, R. I., Schott, J. M., Frost, C., Rossor, M. N., & Fox, N. C. (2005). Does Alzheimer’s disease affect hippocampal asymmetry? Evidence from a cross-sectional and longitudinal volumetric MRI study. Dementia and Geriatric Cognitive Disorders, 19(5–6), 338–344.

    Article  PubMed  Google Scholar 

  • Buckner, R. L., Head, D., Parker, J., Fotenos, A. F., Marcus, D., Morris, J. C., et al. (2004). A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. Neuroimage, 23(2), 724–738.

    Article  PubMed  Google Scholar 

  • Buckner, R. L., Snyder, A. Z., Shannon, B. J., LaRossa, G., Sachs, R., Fotenos, A. F., et al. (2005). Molecular, structural, and functional characterization of Alzheimer’s disease: Evidence for a relationship between default activity, amyloid, and memory. Journal of Neuroscience, 25(34), 7709–7717.

    Article  PubMed  CAS  Google Scholar 

  • Csernansky, J. G., Wang, L., Swank, J., Miller, J. P., Gado, M., McKeel, D., et al. (2005). Preclinical detection of Alzheimer’s disease: Hippocampal shape and volume predict dementia onset in the elderly. NeuroImage, 25(3), 783–792.

    Article  PubMed  CAS  Google Scholar 

  • Czanner, S., Han, X., Pacheco, J., Wallace, S., Busa, E., van der Kouwe, A., et al. (2006). Test–retest reliability assessment for longitudinal MRI studies: Effects of MRI system upgrade on morphometric analysis of structural MRI data. 12th Annual Organization for Human Brain Mapping Meeting, Florence, Italy.

  • Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage, 9(2), 179–194.

    Article  PubMed  CAS  Google Scholar 

  • Dale, A. M., & Sereno, M. I. (1993). Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: A linear approach. Journal of Cognitive Neuroscience, 5, 162–176.

    Article  Google Scholar 

  • Fennema-Notestine, C., Gollub, R., Fischl, B., Quinn, B., Pacheco, J., Gamst, A., et al. (2005). Feasibility of multi-site clinical structural neuroimaging studies of legacy data: Aging and Alzheimer’s disease. Society for Neuroscience (Abstract).

  • Fennema-Notestine, C., Ozyurt, I. B., Clark, C. P., Morris, S., Bischoff-Grethe, A., Bondi, M. W., et al. (2006). Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: Effects of diagnosis, bias correction, and slice location. Human Brain Mapping, 27(2), 99–113.

    Article  PubMed  Google Scholar 

  • Finton, M. J., Lucas, J. A., Rippeth, J. D., Bohac, D. L., Smith, G. E., Ivnik, R. J., et al. (2003). Cognitive asymmetries associated with apolipoprotein E genotype in patients with Alzheimer’s disease. Journal of the International Neuropsychological Society, 9(5), 751–759.

    Article  PubMed  CAS  Google Scholar 

  • Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.

    Article  PubMed  CAS  Google Scholar 

  • Fischl, B., Salat, D. H., van der Kouwe, A. J., Makris, N., Segonne, F., Quinn, B. T., et al. (2004a). Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23(Suppl 1), S69–S84.

    Article  PubMed  Google Scholar 

  • Fischl, B., Sereno, M. I., & Dale, A. M. (1999). Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207.

    Article  PubMed  CAS  Google Scholar 

  • Fischl, B., Van Der Kouwe, A., Destrieux, C., Halgren, E., Segonne, F., Salat, D. H., et al. (2004b). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14(1), 11–22.

    Article  PubMed  Google Scholar 

  • Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state.” A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.

    Article  PubMed  CAS  Google Scholar 

  • Fotenos, A. F., Snyder, A. Z., Girton, L. E., Morris, J. C., & Buckner, R. L. (2005). Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD. Neurology, 64(6), 1032–1039.

    PubMed  CAS  Google Scholar 

  • Hahn, H. K., & Peitgen, H.-O. (2000). The skull stripping problem in MRI solved by a single 3D watershed transform. Proc. MICCAI, LNCS 1935, 134–143.

  • Han, X., & Fischl, B. (2006). Intensity renormalization for improved brain MR image segmentation across scanner platforms. 12th Annual Organization for Human Brain Mapping Meeting, Florence, Italy.

  • Han, X., Jovicich, J., Salat, D., van der Kouwe, A., Quinn, B., Czanner, S., et al. (2006). Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer. NeuroImage, 32(1), 180–194.

    Article  PubMed  Google Scholar 

  • Head, D., Snyder, A. Z., Girton, L. E., Morris, J. C., & Buckner, R. L. (2005). Frontal-hippocampal double dissociation between normal aging and Alzheimer’s disease. Cerebral Cortex, 15(6), 732–739.

    Article  PubMed  Google Scholar 

  • Jack, C. R. Jr., Dickson, D. W., Parisi, J. E., Xu, Y. C., Cha, R. H., O’Brien, P. C., et al. (2002). Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology, 58(5), 750–757.

    PubMed  Google Scholar 

  • Jack, C. R. Jr., Shiung, M. M., Weigand, S. D., O’Brien, P. C., Gunter, J. L., Boeve, B. F., et al. (2005). Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology, 65(8), 1227–1231.

    Article  PubMed  Google Scholar 

  • Jack, C. R. Jr., Slomkowski, M., Gracon, S., Hoover, T. M., Felmlee, J. P., Stewart, K., et al. (2003). MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD. Neurology, 60(2), 253–260.

    Article  PubMed  Google Scholar 

  • Jack, C. R. Jr., Theodore, W. H., Cook, M., & McCarthy, G. (1995). MRI-based hippocampal volumetrics: Data acquisition, normal ranges, and optimal protocol. Magnetic Resonance Imaging, 13(8), 1057–1064.

    Article  PubMed  Google Scholar 

  • Jernigan, T. L., Archibald, S. L., Fennema-Notestine, C., Gamst, A. C., Stout, J. C., Bonner, J., et al. (2001a). Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiology Aging, 22(4), 581–594.

    Article  CAS  Google Scholar 

  • Jernigan, T. L., & Fennema-Notestine, C. (2004). White matter mapping is needed. Neurobiology Aging, 25(1), 37–39.

    Article  CAS  Google Scholar 

  • Jernigan, T. L., & Gamst, A. C. (2005). Changes in volume with age–consistency and interpretation of observed effects. Neurobiology Aging, 26(9), 1271–1274 (discussion 1275–1278).

    Article  Google Scholar 

  • Jernigan, T. L., Ostergaard, A. L., & Fennema-Notestine, C. (2001b). Mesial temporal, diencephalic, and striatal contributions to deficits in single word reading, word priming, and recognition memory. Journal of the International Neuropsychological Society, 7(1), 63–78.

    Article  PubMed  CAS  Google Scholar 

  • Jovicich, J., Czanner, S., Greve, D., Haley, E., van der Kouwe, A., Gollub, R., et al. (2005). Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. NeuroImage, 30(2), 436–443.

    Article  PubMed  Google Scholar 

  • Kantarci, K., & Jack, C. R. Jr. (2003). Neuroimaging in Alzheimer disease: an evidence-based review. Neuroimaging Clinics of North America, 13(2), 197–209.

    Article  PubMed  Google Scholar 

  • Killiany, R. J., Gomez-Isla, T., Moss, M., Kikinis, R., Sandor, T., Jolesz, F., et al. (2000). Use of structural magnetic resonance imaging to predict who will get Alzheimer’s disease. Annals of Neurology, 47(4), 430–439.

    Article  PubMed  CAS  Google Scholar 

  • Killiany, R. J., Hyman, B. T., Gomez-Isla, T., Moss, M. B., Kikinis, R., Jolesz, F., et al. (2002). MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology, 58(8), 1188–1196.

    PubMed  CAS  Google Scholar 

  • Mu, Q., Xie, J., Wen, Z., Weng, Y., & Shuyun, Z. (1999). A quantitative MR study of the hippocampal formation, the amygdala, and the temporal horn of the lateral ventricle in healthy subjects 40 to 90 years of age. American Journal of Neuroradiology, 20(2), 207–211.

    PubMed  CAS  Google Scholar 

  • Mueller, S. G., Weiner, M. W., Thal, L. J., Petersen, R. C., Jack, C., Jagust, W., et al. (2005). The Alzheimer’s disease neuroimaging initiative. Neuroimaging Clinics of North America, 15(4), 869–877, xi–xii.

    Article  PubMed  Google Scholar 

  • Murphy, C., Jernigan, T. L., & Fennema-Notestine, C. (2003). Left hippocampal volume loss in Alzheimer’s disease is reflected in performance on odor identification: a structural MRI study. Journal of the International Neuropsychological Society, 9(3), 459–471.

    Article  PubMed  Google Scholar 

  • Pedraza, O., Bowers, D., & Gilmore, R. (2004). Asymmetry of the hippocampus and amygdala in MRI volumetric measurements of normal adults. Journal of the International Neuropsychological Society, 10(5), 664–678.

    Article  PubMed  Google Scholar 

  • Raz, N., Gunning-Dixon, F., Head, D., Rodrigue, K. M., Williamson, A., & Acker, J. D. (2004). Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: Replicability of regional differences in volume. Neurobiology Aging, 25(3), 377–396.

    Article  Google Scholar 

  • Segonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D., Hahn, H. K., et al. (2004). A hybrid approach to the skull stripping problem in MRI. NeuroImage, 22(3), 1060–1075.

    Article  PubMed  CAS  Google Scholar 

  • Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging, 17(1), 87–97.

    Article  PubMed  CAS  Google Scholar 

  • Soininen, H., Partanen, K., Pitkanen, A., Hallikainen, M., Hanninen, T., Helisalmi, S., et al. (1995). Decreased hippocampal volume asymmetry on MRIs in nondemented elderly subjects carrying the apolipoprotein E epsilon 4 allele. Neurology, 45(2), 391–392.

    PubMed  CAS  Google Scholar 

  • Soininen, H. S., Partanen, K., Pitkanen, A., Vainio, P., Hanninen, T., Hallikainen, M., et al. (1994). Volumetric MRI analysis of the amygdala and the hippocampus in subjects with age-associated memory impairment: Correlation to visual and verbal memory. Neurology, 44(9), 1660–1668.

    PubMed  CAS  Google Scholar 

  • Stein, C. (1981). Estimation of the mean of a multivariate normal distribution. Annals of Statistics, 9(6), 1135–1151.

    Google Scholar 

  • van de Pol, L. A., Hensel, A., Barkhof, F., Gertz, H. J., Scheltens, P., & van der Flier, W. M. (2006). Hippocampal atrophy in Alzheimer disease: Age matters. Neurology, 66(2), 236–238.

    Article  PubMed  Google Scholar 

  • Walhovd, K. B., Fjell, A. M., Reinvang, I., Lundervold, A., Dale, A. M., Eilertsen, D. E., et al. (2005). Effects of age on volumes of cortex, white matter and subcortical structures. Neurobiology Aging, 26(9), 1261–1270 (discussion 1275–1268).

    Article  Google Scholar 

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Acknowledgments

This research was supported by a grant (#U24 RR021382) to the Morphometry Biomedical Informatics Research Network (BIRN, http://www.nbirn.net), that is funded by the National Center for Research Resources at the National Institutes of Health, U.S.A. Additional support was provided by: the University of California, San Diego, Department of Medicine; San Diego ADRC NIA P50 AG05131; Washington University, St. Louis ADRC NIA P50 AG05681; NIA R01 AG12674, R01 AG06849, PO1 AG04953, and P01 AG03991; a Research Enhancement Award Program and VA Merit Review grant from the Department of Veterans Affairs Medical Research Service; Howard Hughes Medical Institute; NCRR R01 RR16594-01A1, M01 RR00827, P41 RR14075, and P41 RR13642; Mental Illness and Neuroscience Discovery (MIND) Institute; NINDS R01 NS052585-01; NIH Roadmap for Medical Research U54 EB005149; and NIBIB R01 EB002010. Anders M. Dale is a founder and holds equity in CorTechs Labs, Inc, and also serves on the Scientific Advisory Board. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies.

Work based on these MRI data have been published separately for studies performed within each site locally, including: UCSD (Jernigan et al. 2001a, b; Murphy et al. 2003; Jernigan and Fennema-Notestine 2004; Jernigan and Gamst 2005; Fennema-Notestine et al. 2006); MGH/BWH (Killiany et al. 2000, Killiany et al. 2002); and WashU (Buckner et al. 2004, 2005, Fotenos et al. 2005, Head et al. 2005). Preliminary findings related to the combined data analysis were presented at the Society for Neuroscience 2005 meeting (Fennema-Notestine et al. 2005); work related to the combined data has not been published elsewhere.

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Correspondence to Christine Fennema-Notestine.

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Brad Dickerson and Randy L. Gollub contributed equally.

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Fennema-Notestine, C., Gamst, A.C., Quinn, B.T. et al. Feasibility of Multi-site Clinical Structural Neuroimaging Studies of Aging Using Legacy Data. Neuroinform 5, 235–245 (2007). https://doi.org/10.1007/s12021-007-9003-9

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