Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls

Lerch, Jason P.; Pruessner, Jens; Zijdenbos, Alex P.; Collins, D. Louis; Teipel, Stefan J.; Hampel, Harald; Evans, Alan C.

doi:10.1016/j.neurobiolaging.2006.09.013

« Previous Next »Neurobiology of Aging
Volume 29, Issue 1 , Pages 23-30, January 2008

Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls

Jason P. Lerch
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada
Jens Pruessner
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada
- Alzheimer Memorial Center, Dementia Research Section and Memory Clinic, Department of Psychiatry, Ludwig-Maximilian University, Munich, Germany
Alex P. Zijdenbos
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada
D. Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada
Stefan J. Teipel
- Alzheimer Memorial Center, Dementia Research Section and Memory Clinic, Department of Psychiatry, Ludwig-Maximilian University, Munich, Germany
Harald Hampel
- Alzheimer Memorial Center, Dementia Research Section and Memory Clinic, Department of Psychiatry, Ludwig-Maximilian University, Munich, Germany
Alan C. Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada
- Corresponding author. Tel.: +1 514 398 8926; fax: +1 514 398 8952.

Received 17 May 2005; received in revised form 3 August 2006; accepted 13 September 2006. published online 15 November 2006.

Abstract

We investigated the potential of fully automated measurements of cortical thickness to reproduce the clinical diagnosis in Alzheimer's Disease (AD) using 19 patients and 17 healthy controls. Thickness maps were analyzed using three different discriminant techniques to separate patients from controls. All analyses were performed using leave-one-out cross-validation to avoid overtraining of the discriminants. The results show regionally variant patterns of discrimination ability, with over 90% accuracy obtained in the medial temporal lobes and other limbic structures. Multivariate discriminant analysis produced 100% accuracy with six different combinations, all involving the parahippocampal gyrus. We therefore propose automated measurements of cortical thickness as a tool to improve the clinical diagnosis of probable AD, as well as a research method to gain unique insight into the etiology of cortical pathology in the disease.

Keywords: Alzheimer's disease, Cortical thickness, Diagnosis, Magnetic resonance imaging