Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging - Archive ouverte HAL Access content directly
Journal Articles NeuroImage Year : 2009

Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging

(1, 2) , (3) , (2) , (2, 4) , (3) , (5) , (6) , (7) , (7) , (7, 8, 9) , (3) , (2)
1
2
3
4
5
6
7
8
9

Abstract

We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification of hippocampal shape features. This approach uses spherical harmonics (SPHARM) coefficients to model the shape of the hippocampi, which are segmented from magnetic resonance images (MRI) using a fully automatic method that we previously developed. SPHARM coefficients are used as features in a classification procedure based on support vector machines (SVM). The most relevant features for classification are selected using a bagging strategy. We evaluate the accuracy of our method in a group of 23 patients with AD (10 males, 13 females, age+/-standard-deviation (SD)=73+/-6 years, mini-mental score (MMS)=24.4+/-2.8), 23 patients with amnestic MCI (10 males, 13 females, age+/-SD=74+/-8 years, MMS=27.3+/-1.4) and 25 elderly healthy controls (13 males, 12 females, age+/-SD=64+/-8 years), using leave-one-out cross-validation. For AD vs controls, we obtain a correct classification rate of 94%, a sensitivity of 96%, and a specificity of 92%. For MCI vs controls, we obtain a classification rate of 83%, a sensitivity of 83%, and a specificity of 84%. This accuracy is superior to that of hippocampal volumetry and is comparable to recently published SVM-based whole-brain classification methods, which relied on a different strategy. This new method may become a useful tool to assist in the diagnosis of Alzheimer's disease.
Fichier principal
Vignette du fichier
gerardin_hippoclassif_NeuroImage_postprint.pdf (2.23 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00805434 , version 1 (28-01-2019)

Identifiers

Cite

Emilie Gerardin, Gaël Chételat, Marie Chupin, Rémi Cuingnet, Béatrice Desgranges, et al.. Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging. NeuroImage, 2009, 47 (4), pp.1476-86. ⟨10.1016/j.neuroimage.2009.05.036⟩. ⟨hal-00805434⟩
240 View
314 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More