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

NeuroImage: Clinical

Arshi Rizwan¹  Kejia Cai²  Arijitt Borthakur²  Anup Singh²  John Q. Trojanowski³  Elias R. Melhem⁴  Mohammad Haris⁵  Santosh K. Yadav⁵  Deepak Kaura⁵  Ena Wang⁵  Francesco M. Marincola⁵  Christos Davatzikos⁶ 

[1] All India Institute of Medical Science, Ansari Nagar East, New Delhi, Delhi 110029, India;Center for Magnetic Resonance and Optical Imaging, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA;Department of Pathology & Lab Medicine, University of Pennsylvania, Philadelphia, PA, USA;Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA;Research Branch, Sidra Medical and Research Center, Doha, Qatar;Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA;

关键词: Alzheimer's disease;    Mild cognitive impairment;    Medial temporal lobe;    T1rho;    CSF biomarkers;   

DOI  :  10.1016/j.nicl.2015.02.016

来源: DOAJ

【 摘 要 】

In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T1ρ) 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. T1ρ images were obtained at four different spin-lock pulse duration (10, 20, 30 and 40 ms). T1ρ maps were generated by pixel-wise fitting of signal intensity as a function of the spin-lock pulse duration. T1ρ values from gray matter (GM) and white matter (WM) of medial temporal lobe were calculated. The binary logistic regression using T1ρ and CSF biomarkers as variables was performed to classify each group. T1ρ was able to predict 77.3% controls and 40.0% MCI while CSF biomarkers predicted 81.8% controls and 46.7% MCI. T1ρ and CSF biomarkers in combination predicted 86.4% controls and 66.7% MCI. When comparing controls with AD, T1ρ predicted 68.2% controls and 73.9% AD, while CSF biomarkers predicted 77.3% controls and 78.3% for AD. Combination of T1ρ and CSF biomarkers improved the prediction rate to 81.8% for controls and 82.6% for AD. Similarly, on comparing MCI with AD, T1ρ predicted 35.3% MCI and 81.9% AD, whereas CSF biomarkers predicted 53.3% MCI and 83.0% AD. Collectively CSF biomarkers and T1ρ were able to predict 59.3% MCI and 84.6% AD. On receiver operating characteristic analysis T1ρ showed higher sensitivity while CSF biomarkers showed greater specificity in delineating MCI and AD from controls. No significant correlation between T1ρ and CSF biomarkers, between T1ρ and age, and between CSF biomarkers and age was observed. The combined use of T1ρ 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.

【 授权许可】

Unknown