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T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease

In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T(1ρ)) imaging and CSF biomarkers (T-tau, P-tau and Aβ-42) in characterization of Alzheimer's disease (AD) patients from mild cognitive impairment (MCI) and control subjects. With informed consent, AD (n =...

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Detalles Bibliográficos
Autores principales: Haris, Mohammad, Yadav, Santosh K., Rizwan, Arshi, Singh, Anup, Cai, Kejia, Kaura, Deepak, Wang, Ena, Davatzikos, Christos, Trojanowski, John Q., Melhem, Elias R., Marincola, Francesco M., Borthakur, Arijitt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4375645/
https://www.ncbi.nlm.nih.gov/pubmed/25844314
http://dx.doi.org/10.1016/j.nicl.2015.02.016
Descripción
Sumario:In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T(1ρ)) imaging and CSF biomarkers (T-tau, P-tau and Aβ-42) in characterization of Alzheimer's disease (AD) patients from mild cognitive impairment (MCI) and control subjects. With informed consent, AD (n = 27), MCI (n = 17) and control (n = 17) subjects underwent a standardized clinical assessment and brain MRI on a 1.5-T clinical-scanner. T(1ρ) images were obtained at four different spin-lock pulse duration (10, 20, 30 and 40 ms). T(1ρ) maps were generated by pixel-wise fitting of signal intensity as a function of the spin-lock pulse duration. T(1ρ) values from gray matter (GM) and white matter (WM) of medial temporal lobe were calculated. The binary logistic regression using T(1ρ) and CSF biomarkers as variables was performed to classify each group. T(1ρ) was able to predict 77.3% controls and 40.0% MCI while CSF biomarkers predicted 81.8% controls and 46.7% MCI. T(1ρ) and CSF biomarkers in combination predicted 86.4% controls and 66.7% MCI. When comparing controls with AD, T(1ρ) predicted 68.2% controls and 73.9% AD, while CSF biomarkers predicted 77.3% controls and 78.3% for AD. Combination of T(1ρ) and CSF biomarkers improved the prediction rate to 81.8% for controls and 82.6% for AD. Similarly, on comparing MCI with AD, T(1ρ) predicted 35.3% MCI and 81.9% AD, whereas CSF biomarkers predicted 53.3% MCI and 83.0% AD. Collectively CSF biomarkers and T(1ρ) were able to predict 59.3% MCI and 84.6% AD. On receiver operating characteristic analysis T(1ρ) showed higher sensitivity while CSF biomarkers showed greater specificity in delineating MCI and AD from controls. No significant correlation between T(1ρ) and CSF biomarkers, between T(1ρ) and age, and between CSF biomarkers and age was observed. The combined use of T(1ρ) and CSF biomarkers have promise to improve the early and specific diagnosis of AD. Furthermore, disease progression form MCI to AD might be easily tracked using these two parameters in combination.