Special Section on Pioneers in Medical Imaging: Honoring the Memory of Robert F. Wagner

Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer’s disease progression

[+] Author Affiliations
Antonio Martinez-Torteya

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

Juan Rodriguez-Rojas

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

José M. Celaya-Padilla

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

Jorge I. Galván-Tejada

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

Victor Treviño

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Medicina, Departamento de Investigación e Innovación, Monterrey 64710, Mexico

Jose Tamez-Peña

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Ingeniería, Departamento de Ciencias Computacionales, Monterrey 64849, Mexico

Tecnológico de Monterrey, Cátedra de Bioinformática, Escuela de Medicina, Departamento de Investigación e Innovación, Monterrey 64710, Mexico

J. Med. Imag. 1(3), 031005 (Sep 15, 2014). doi:10.1117/1.JMI.1.3.031005
History: Received April 1, 2014; Revised July 27, 2014; Accepted August 22, 2014
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Abstract.  Early diagnoses of Alzheimer’s disease (AD) would confer many benefits. Several biomarkers have been proposed to achieve such a task, where features extracted from magnetic resonance imaging (MRI) have played an important role. However, studies have focused exclusively on morphological characteristics. This study aims to determine whether features relating to the signal and texture of the image could predict mild cognitive impairment (MCI) to AD progression. Clinical, biological, and positron emission tomography information and MRI images of 62 subjects from the AD neuroimaging initiative were used in this study, extracting 4150 features from each MRI. Within this multimodal database, a feature selection algorithm was used to obtain an accurate and small logistic regression model, generated by a methodology that yielded a mean blind test accuracy of 0.79. This model included six features, five of them obtained from the MRI images, and one obtained from genotyping. A risk analysis divided the subjects into low-risk and high-risk groups according to a prognostic index. The groups were statistically different (p-value=2.04e11). These results demonstrated that MRI features related to both signal and texture add MCI to AD predictive power, and supported the ongoing notion that multimodal biomarkers outperform single-modality ones.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Antonio Martinez-Torteya ; Juan Rodriguez-Rojas ; José M. Celaya-Padilla ; Jorge I. Galván-Tejada ; Victor Treviño, et al.
"Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer’s disease progression", J. Med. Imag. 1(3), 031005 (Sep 15, 2014). ; http://dx.doi.org/10.1117/1.JMI.1.3.031005


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