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Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls.
Neuroimage 2011; 54(2):1178-87N

Abstract

We have used multivariate data analysis, more specifically orthogonal partial least squares to latent structures (OPLS) analysis, to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI) and elderly control subjects combining both regional and global magnetic resonance imaging (MRI) volumetric measures. In this study, 117 AD patients, 122 MCI patients and 112 control subjects (from the AddNeuroMed study) were included. High-resolution sagittal 3D MP-RAGE datasets were acquired from each subject. Automated regional segmentation and manual outlining of the hippocampus were performed for each image. Altogether this yielded volumes of 24 different anatomically defined structures which were used for OPLS analysis. 17 randomly selected AD patients, 12 randomly selected control subjects and the 22 MCI subjects who converted to AD at 1-year follow up were excluded from the initial OPLS analysis to provide a small external test set for model validation. Comparing AD with controls we found a sensitivity of 87% and a specificity of 90% using hippocampal measures alone. Combining both global and regional measures resulted in a sensitivity of 90% and a specificity of 94%. This increase in sensitivity and specificity resulted in an increase of the positive likelihood ratio from 9 to 15. From the external test set, the model predicted 82% of the AD patients and 83% of the control subjects correctly. Finally, 73% of the MCI subjects which converted to AD at 1 year follow-up were shown to resemble AD patients more closely than controls. This method shows potential for distinguishing between different patient groups. Combining the different MRI measures together resulted in a significantly better classification than using them separately. OPLS also shows potential for predicting conversion from MCI to AD.

Authors+Show Affiliations

Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. eric.westman@ki.seNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

20800095

Citation

Westman, Eric, et al. "Multivariate Analysis of MRI Data for Alzheimer's Disease, Mild Cognitive Impairment and Healthy Controls." NeuroImage, vol. 54, no. 2, 2011, pp. 1178-87.
Westman E, Simmons A, Zhang Y, et al. Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls. Neuroimage. 2011;54(2):1178-87.
Westman, E., Simmons, A., Zhang, Y., Muehlboeck, J. S., Tunnard, C., Liu, Y., ... Wahlund, L. O. (2011). Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls. NeuroImage, 54(2), pp. 1178-87. doi:10.1016/j.neuroimage.2010.08.044.
Westman E, et al. Multivariate Analysis of MRI Data for Alzheimer's Disease, Mild Cognitive Impairment and Healthy Controls. Neuroimage. 2011 Jan 15;54(2):1178-87. PubMed PMID: 20800095.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls. AU - Westman,Eric, AU - Simmons,Andrew, AU - Zhang,Yi, AU - Muehlboeck,J-Sebastian, AU - Tunnard,Catherine, AU - Liu,Yawu, AU - Collins,Louis, AU - Evans,Alan, AU - Mecocci,Patrizia, AU - Vellas,Bruno, AU - Tsolaki,Magda, AU - Kłoszewska,Iwona, AU - Soininen,Hilkka, AU - Lovestone,Simon, AU - Spenger,Christian, AU - Wahlund,Lars-Olof, AU - ,, Y1 - 2010/08/25/ PY - 2010/06/03/received PY - 2010/08/06/revised PY - 2010/08/19/accepted PY - 2010/8/31/entrez PY - 2010/8/31/pubmed PY - 2011/4/6/medline SP - 1178 EP - 87 JF - NeuroImage JO - Neuroimage VL - 54 IS - 2 N2 - We have used multivariate data analysis, more specifically orthogonal partial least squares to latent structures (OPLS) analysis, to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI) and elderly control subjects combining both regional and global magnetic resonance imaging (MRI) volumetric measures. In this study, 117 AD patients, 122 MCI patients and 112 control subjects (from the AddNeuroMed study) were included. High-resolution sagittal 3D MP-RAGE datasets were acquired from each subject. Automated regional segmentation and manual outlining of the hippocampus were performed for each image. Altogether this yielded volumes of 24 different anatomically defined structures which were used for OPLS analysis. 17 randomly selected AD patients, 12 randomly selected control subjects and the 22 MCI subjects who converted to AD at 1-year follow up were excluded from the initial OPLS analysis to provide a small external test set for model validation. Comparing AD with controls we found a sensitivity of 87% and a specificity of 90% using hippocampal measures alone. Combining both global and regional measures resulted in a sensitivity of 90% and a specificity of 94%. This increase in sensitivity and specificity resulted in an increase of the positive likelihood ratio from 9 to 15. From the external test set, the model predicted 82% of the AD patients and 83% of the control subjects correctly. Finally, 73% of the MCI subjects which converted to AD at 1 year follow-up were shown to resemble AD patients more closely than controls. This method shows potential for distinguishing between different patient groups. Combining the different MRI measures together resulted in a significantly better classification than using them separately. OPLS also shows potential for predicting conversion from MCI to AD. SN - 1095-9572 UR - https://www.unboundmedicine.com/medline/citation/20800095/Multivariate_analysis_of_MRI_data_for_Alzheimer's_disease_mild_cognitive_impairment_and_healthy_controls_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1053-8119(10)01126-2 DB - PRIME DP - Unbound Medicine ER -