HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) All Versions of this Article: 2481070876v1 248/1/194    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Colliot, O. Articles by Lehéricy, S. PubMed PubMed Citation Articles by Colliot, O. Articles by Lehéricy, S.

Discrimination between Alzheimer Disease, Mild Cognitive Impairment, and Normal Aging by Using Automated Segmentation of the Hippocampus¹

¹ From the Cognitive Neuroscience and Brain Imaging Laboratory, Centre National de la Recherche Scientifique, UPR640-LENA (O.C., M.C., L.G.), Institut National de la Santé et de la Recherche Médical (INSERM) U678 (B.M., H.B.), INSERM U610 (B.M., B.Dubois, S.L.), and Department of Neuroradiology, Center for Neuroimaging Research (S.L.), Université Pierre et Marie Curie-Paris 6, Hôpital de la Pitié-Salpêtrière, 47, boulevard de l'Hôpital, 75651 Paris Cedex 13, France; and INSERM–Ecole Pratique des Hautes Etudes, Université de Caen Basse-Normandie, U923, E0218, Cyceron, Centre Hospitalo-Universitaire de Caen, Caen, France (G.C., B.Desgranges, F.E.). Received May 18, 2007; revision requested July 26; revision received October 10; accepted December 28; final version accepted January 29, 2008. Address correspondence to O.C. (e-mail: olivier.colliot{at}chups.jussieu.fr).

Purpose: To prospectively evaluate the accuracy of automated hippocampal volumetry to help distinguish between patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and elderly controls, by using established criteria for patients with AD and MCI as the reference standard.

Materials and Methods: The regional ethics committee approved the study and written informed consent was obtained from all participants. The study included 25 patients with AD (11 men, 14 women; mean age ± standard deviation [SD], 73 years ± 6; Mini-Mental State Examination (MMSE) score, 24.4 ± 2.7), 24 patients with amnestic MCI (10 men, 14 women; mean age ± SD, 74 years ± 8; MMSE score, 27.2 ± 1.4) and 25 elderly healthy controls (13 men, 12 women; mean age ± SD, 64 years ± 8). For each participant, the hippocampi were automatically segmented on three-dimensional T1-weighted magnetic resonance (MR) images with high spatial resolution. Segmentation was performed by using recently developed software that allows fast segmentation with minimal user input. Group differences in hippocampal volume were assessed by using Student t tests. To obtain robust estimates of P values, the correct classification rate, sensitivity, and specificity, bootstrap methods were used.

Results: Significant hippocampal volume reductions were detected in all groups of patients (–32% in AD patients vs controls, P < .001; –19% in MCI patients vs controls, P < .001; and –15% in AD patients vs MCI patients, P < .01). Individual classification on the basis of hippocampal volume resulted in 84% correct classification (sensitivity, 84%; specificity, 84%) between AD patients and controls and 73% correct classification (sensitivity, 75%; specificity, 70%) between MCI patients and controls.

Conclusion: This automated method can serve as an alternative to manual tracing and may thus prove useful in assisting with the diagnosis of AD.

© RSNA, 2008