Combined Use of MRI, fMRIand Cognitive Data for Alzheimer’s Disease: Preliminary Results

Chiara Dachena,Sergio Casu,Alessandro Fanti,Matteo Bruno Lodi,Giuseppe Mazzarella

doi:10.3390/app9153156

Chiara Dachena, Sergio Casu + Show 3 more

Open Access

https://doi.org/10.3390/app9153156

Copy DOI

Abstract

MRI can favor clinical diagnosis providing morphological and functional information of several neurological disorders. This paper deals with the problem of exploiting both data, in a combined way, to develop a tool able to support clinicians in the study and diagnosis of Alzheimer’s Disease (AD). In this work, 69 subjects from the ADNI open database, 33 AD patients and 36 healthy controls, were analyzed. The possible existence of a relationship between brain structure modifications and altered functions between patients and healthy controls was investigated performing a correlation analysis on brain volume, calculated from the MRI image, the clustering coefficient, derived from fRMI acquisitions, and the Mini Mental Score Examination (MMSE). A statistically-significant correlation was found only in four ROIs after Bonferroni’s correction. The correlation analysis alone was still not sufficient to provide a reliable and powerful clinical tool in AD diagnosis however. Therefore, a machine learning strategy was studied by training a set of support vector machine classifiers comparing different features. The use of a unimodal approach led to unsatisfactory results, whereas the multimodal approach, i.e., the synergistic combination of MRI, fMRI, and MMSE features, resulted in an accuracy of 95.65%, a specificity of 97.22%, and a sensibility of 93.93%.

Highlights

Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging of the brain are popular methods of inquiry in neuroscience [1]
The findings presented in this work demonstrate that, instead of exploiting one type of measurement, using the combined and synergistic information from different imaging techniques and the clinical data from Mini Mental Score Examination (MMSE) enhanced the Alzheimer’s Disease (AD) classification, with an accuracy of 95.65%, a sensitivity of 93.93%, and a specificity of 97.22%
A Mann–Whitney U-test was performed to explore the statistical differences of the normalized whole brain volume between the AD patient group and the control group [71]

Summary

Introduction

Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI) of the brain are popular methods of inquiry in neuroscience [1]. These techniques are exploited to obtain important morphological and functional information in a non-invasive way [2]. The adjustment of the cited parameters provides a good image reconstruction with a high SNR. The imaging modalities, such as computed tomography and MRI, ensure good tissue contrast and spatial resolution [2,5], which favor an adequate tissue segmentation. The possibility of detecting structural abnormalities depends on the segmentation accuracy, which in turn may improve the diseases’ diagnosis [6,7,8]

Objectives

Methods

Results

Conclusion