Publications Search Results

Now showing 1 - 2 of 2
  • Publication
    Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease
    ( 2016)
    Allen, G.I.
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    Amoroso, N.
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    Anghel, C.
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    Balagurusamy, V.
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    Bare, C.J.
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    Beaton, D.
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    Bellotti, R.
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    Bennett, D.A.
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    Boehme, K.L.
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    Boutros, P.C.
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    Caberlotto, L.
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    Caloian, C.
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    Campbell, F.
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    Chaibub Neto, E.
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    Chang, Y.-C.
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    Chen, B.
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    Chen, C.-Y.
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    Chien, T.-Y.
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    Clark, T.
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    Das, S.
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    Davatzikos, C.
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    Deng, J.
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    Dillenberger, D.
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    Dobson, R.J.B.
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    Dong, Q.
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    Doshi, J.
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    Duma, D.
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    Errico, R.
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    Erus, G.
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    Everett, E.
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    Fardo, D.W.
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    Friend, S.H.
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    Fröhlich, H.
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    Gan, J.
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    St George-Hyslop, P.
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    Ghosh, S.S.
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    Glaab, E.
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    Green, R.C.
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    Guan, Y.
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    Hong, M.-Y.
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    Huang, C.
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    Hwang, J.
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    Ibrahim, J.
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    Inglese, P.
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    Iyappan, A.
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    Jiang, Q.
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    Katsumata, Y.
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    Kauwe, J.S.K.
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    Klein, A.
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    Kong, D.
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    Krause, R.
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    Lalonde, E.
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    Lauria, M.
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    Lee, E.
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    Lin, X.
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    Liu, Z.
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    Livingstone, J.
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    Logsdon, B.A.
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    Lovestone, S.
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    Ma, T.-W.
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    Malhotra, A.
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    Mangravite, L.M.
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    Maxwell, T.J.
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    Merrill, E.
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    Nagorski, J.
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    Namasivayam, A.
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    Narayan, M.
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    Naz, M.
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    Newhouse, S.J.
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    Norman, T.C.
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    Nurtdinov, R.N.
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    Oyang, Y.-J.
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    Pawitan, Y.
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    Peng, S.
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    Peters, M.A.
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    Piccolo, S.R.
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    Praveen, P.
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    Priami, C.
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    Sabelnykova, V.Y.
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    Senger, P.
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    Shen, X.
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    Simmons, A.
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    Sotiras, A.
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    Stolovitzky, G.
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    Tangaro, S.
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    Tateo, A.
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    Tung, Y.-A.
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    Tustison, N.J.
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    Varol, E.
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    Vradenburg, G.
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    Weiner, M.W.
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    Xiao, G.
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    Xie, L.
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    Xie, Y.
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    Xu, J.
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    Yang, H.
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    Zhan, X.
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    Zhou, Y.
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    Zhu, F.
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    Zhu, H.
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    Zhu, S.
    Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
  • Publication
    Arterial spin labeling MRI study of age and gender effects on brain perfusion hemodynamics
    ( 2012)
    Liu, Y.
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    Zhu, X.
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    Feinberg, D.
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    Guenther, M.
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    Gregori, J.
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    Weiner, M.W.
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    Schuff, N.
    Normal aging is associated with diminished brain perfusion measured as cerebral blood flow (CBF), but previously it is difficult to accurately measure various aspects of perfusion hemodynamics including: bolus arrival times and delays through small arterioles, expressed as arterial-arteriole transit time. To study hemodynamics in greater detail, volumetric arterial spin labeling MRI with variable postlabeling delays was used together with a distributed, dual-compartment tracer model. The main goal was to determine how CBF and other perfusion hemodynamics vary with aging. Twenty cognitive normal female and 15 male subjects (age: 23-84 years old) were studied at 4 T. Arterial spin labeling measurements were performed in the posterior cingulate cortex, precuneus, and whole brain gray matter. CBF declined with advancing age (P < 0.001). Separately from variations in bolus arrival times, arterial-arteriole transit time increased with advancing age (P < 0.01). Finally, women had overall higher CBF values (P < 0.01) and shorter arterial-arteriole transit time (P < 0.01) than men, regardless of age. The findings imply that CBF and blood transit times are compromised in aging, and these changes together with differences between genders should be taken into account when studying brain perfusion.