Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals
Braz. J. Psychiatry (São Paulo, 1999, Impr.)
; 40(2): 181-191, Apr.-June 2018. tab, graf
Article
en En
| LILACS
| ID: biblio-959221
Biblioteca responsable:
BR1.1
ABSTRACT
Objective:
To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flow single-photon emission computed tomography (rCBF-SPECT) in Alzheimer's disease (AD).Method:
Brain T1-MRI, FDG-PET and rCBF-SPECT scans were acquired from a sample of mild AD patients (n=20) and healthy elderly controls (n=18). SVM-based diagnostic accuracy indices were calculated using whole-brain information and leave-one-out cross-validation.Results:
The accuracy obtained using PET and SPECT data were similar. PET accuracy was 68∼71% and area under curve (AUC) 0.77∼0.81; SPECT accuracy was 68∼74% and AUC 0.75∼0.79, and both had better performance than analysis with T1-MRI data (accuracy of 58%, AUC 0.67). The addition of PET or SPECT to MRI produced higher accuracy indices (68∼74%; AUC 0.74∼0.82) than T1-MRI alone, but these were not clearly superior to the isolated neurofunctional modalities.Conclusion:
In line with previous evidence, FDG-PET and rCBF-SPECT more accurately identified patients with AD than T1-MRI, and the addition of either PET or SPECT to T1-MRI data yielded increased accuracy. The comparable SPECT and PET performances, directly demonstrated for the first time in the present study, support the view that rCBF-SPECT still has a role to play in AD diagnosis.Palabras clave
Texto completo:
1
Banco de datos:
LILACS
Asunto principal:
Imagen por Resonancia Magnética
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Tomografía Computarizada de Emisión de Fotón Único
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Tomografía de Emisión de Positrones
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Enfermedad de Alzheimer
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Máquina de Vectores de Soporte
Tipo de estudio:
Diagnostic_studies
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Observational_studies
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Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Male
Idioma:
En
Año:
2018
Tipo del documento:
Article