T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease.
T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease.
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DOI：
10.1016/j.nicl.2015.02.016
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发表时间：
2015
影响因子：
4.2
通讯作者：
Borthakur, Arijitt
中科院分区：
文献类型：
--
作者：
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
在本研究中，我们评估了磁共振（MR）T1 ρ（T1ρ）成像和CSF生物标志物（T-tau、P-tau和Aβ-42）在轻度认知障碍（MCI）和对照受试者中表征阿尔茨海默病（AD）患者的性能。在知情同意的情况下，AD（n = 27）、MCI（n = 17）和对照组（n = 17）受试者在1.5 T临床扫描仪上接受了标准化临床评估和脑MRI。在四种不同的自旋锁脉冲持续时间（10、20、30和40 ms）下获得T1ρ图像。T1ρ图通过将信号强度作为自旋锁定脉冲持续时间的函数进行逐像素拟合来生成。计算内侧颞叶灰质（GM）和白色质（WM）的T1ρ值。使用T1ρ和CSF生物标志物作为变量进行二元逻辑回归以将每组分类。T1ρ能够预测77.3%的对照和40.0%的MCI，而CSF生物标志物预测81.8%的对照和46.7%的MCI。T1ρ和CSF生物标志物组合预测86.4%的对照和66.7%的MCI。当将对照与AD进行比较时，T1ρ预测68.2%的对照和73.9%的AD，而CSF生物标志物预测77.3%的对照和78.3%的AD。T1ρ和CSF生物标志物的组合将对照的预测率提高到81.8%，AD的预测率提高到82.6%。类似地，在比较MCI与AD时，T1ρ预测35.3% MCI和81.9% AD，而CSF生物标志物预测53.3% MCI和83.0% AD。CSF生物标志物和T1ρ共同能够预测59.3% MCI和84.6% AD。在受试者操作特征分析中，T1ρ显示出更高的敏感性，而CSF生物标志物显示出更高的特异性，以区分MCI和AD。未观察到T1ρ与CSF生物标志物之间、T1ρ与年龄之间以及CSF生物标志物与年龄之间的显著相关性。T1ρ和CSF生物标志物的联合应用有望提高AD的早期和特异性诊断。此外，从MCI到AD的疾病进展可能很容易使用这两个参数的组合进行跟踪。与对照组相比，在MCI和AD中观察到T1 rho增加。MCI组和AD组T-tau和P-tau蛋白水平升高，Aβ1-42水平降低。联合生物标志物有望改善AD的早期和特异性诊断。MCI到AD的进展可以使用这两种生物标志物的组合来跟踪。
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. Increased T1rho was observed in MCI and AD compared to controls. Increased T-tau and P-tau and decreased Aβ1-42 were observed in MCI and AD. Combined biomarkers have promise to improve early and specific diagnosis of AD. MCI to AD progression might be tracked using these two biomarkers in combination.
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影响因子：
--
作者：
Li LZ;Xu HN;Reddy R
通讯作者：
Reddy R
影响因子：
9.9
作者：
Jack, CR;Petersen, RC;Kokmen, E
通讯作者：
Kokmen, E
影响因子：
4.4
作者：
Borthakur, Arijitt;Gur, Tamar;Reddy, Ravinder
通讯作者：
Reddy, Ravinder
DOI：
10.1111/j.1552-6569.2010.00467.x
发表时间：
2011-04
期刊：
Journal of neuroimaging : official journal of the American Society of Neuroimaging
影响因子：
--
作者：
Haris M;Singh A;Cai K;McArdle E;Fenty M;Davatzikos C;Trojanowski JQ;Melhem ER;Clark CM;Borthakur A
通讯作者：
Borthakur A
影响因子：
38.1
作者：
Frisoni, Giovanni B.;Fox, Nick C.;Jack, Clifford R., Jr.;Scheltens, Philip;Thompson, Paul M.
通讯作者：
Thompson, Paul M.