Neurobiology of Aging 31 (2010) 1601–1605 Whole brain atrophy rate predicts progression from MCI to Alzheimer’s disease Gabriela Spulber a,∗ , Eini Niskanen b,c,d , Stuart MacDonald e , Oded Smilovici f , Kewei Chen f , Eric M. Reiman f , Anne M. Jauhiainen a , Merja Hallikainen a , Susanna Tervo a , Lars-Olof Wahlund g , Ritva Vanninen h , Miia Kivipelto a,e , Hilkka Soininen a,d a Institute of Clinical Medicine, Unit of Neurology, Kuopio University, Kuopio, Finland b Department of Physics, Kuopio University, Kuopio, Finland c Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland d Department of Neurology, Kuopio University Hospital, Kuopio, Finland e Aging Research Center, Division of Geriatric Epidemiology, NVS, Karolinska Institutet, Stockholm, Sweden f Banner Alzheimer’s Institute, and Banner Good Samaritan Positron Emission Tomography Centre, and Arizona Alzheimer’s Consortium, Phoenix, AZ, USA g Division of Clinical Geriatric, NVS, Karolinska Institutet, Stockholm, Sweden h Department of Radiology, Kuopio University Hospital, Kuopio, Finland Received 18 November 2007; received in revised form 16 August 2008; accepted 24 August 2008 Available online 1 October 2008 Abstract For both clinical and research reasons, it is essential to identify which mild cognitive impairment (MCI) subjects subsequently progress to Alzheimer’s disease (AD). The prediction may be facilitated by accelerated whole brain atrophy exhibited by AD subjects. Iterative principal component analysis (IPCA) was used to characterize whole brain atrophy rates using sequential MRI scans for 102 MCI subjects from the Kuo- pio University Hospital. We modelled the likelihood of progression to probable AD, and found that each additional percent of annualized whole brain atrophy rate was associated with a higher odds ratio (OR) of progression (OR = 1.30, p = 0.01, 95% CI = 1.05–1.60). Our study demon- strates an association between whole brain atrophy rate and subsequent rate of clinical progression from MCI to AD. These findings suggest that IPCA could be an effective brain-imaging marker of progression to AD and useful tool for the evaluation of disease-modifying treatments. © 2008 Elsevier Inc. All rights reserved. Keywords: Alzheimer’s disease; Whole brain atrophy; Iterative principal component analysis; Mild cognitive impairment; MRI 1. Introduction Brain imaging is increasingly recognized as a useful tool not only for diagnosis, but also for indexing disease progres- sion and severity in Alzheimer’s disease (AD). Recently, a great deal of attention has been focused on the prodromal stage of AD, often referred to as mild cognitive impairment (MCI), which includes individuals with memory problems who do not meet criteria for dementia. Although MCI def- ∗ Corresponding author at: Institute of Clinical Medicine, Unit of Neurol- ogy, Kuopio University, Canthia Building, P.O. Box 1627, 70211 Kuopio, Finland. Tel.: +358 17 162227; fax: +358 17 162048. E-mail address: gabriela.spulber@uku.fi (G. Spulber). initions vary across studies (Petersen et al., 1997, 1999), those characterized with MCI consistently convert to AD with annual rates of 10–15% (Petersen et al., 1999). MCI is heterogeneous in its clinical presentation and should be considered in a broad clinical context (Ritchie and Touchon, 2000; Winblad et al., 2004). The clinical course for MCI indi- viduals may vary considerably (Palmer et al., 2002), likely reflecting different underlying causes (e.g., disease comor- bidity). Therefore, finding reliable and consistent predictors of AD progression risk is of crucial importance. Several studies have shown that regional atrophy patterns in the medial temporal lobe, prefrontal cortices, posterior cingulate and precuneus, using voxel-based morphometry (Bell-McGinty et al., 2005; Hämäläinen et al., 2007; Karas 0197-4580/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.neurobiolaging.2008.08.018