Author name cluster

Anup Singh

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers

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YNICL Journal 2015 Journal Article

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

Mohammad Haris
Santosh K. Yadav
Arshi Rizwan
Anup Singh
Kejia Cai
Deepak Kaura
Ena Wang
Christos Davatzikos

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.

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YNIMG Journal 2013 Journal Article

Imaging of glutamate in the spinal cord using GluCEST

Feliks Kogan
Anup Singh
Catherine Debrosse
Mohammad Haris
Kejia Cai
Ravi Prakash Nanga
Mark Elliott
Hari Hariharan

Glutamate (Glu) is the most abundant excitatory neurotransmitter in the brain and spinal cord. The concentration of Glu is altered in a range of neurologic disorders that affect the spinal cord including multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and spinal cord injury. Currently available magnetic resonance spectroscopy (MRS) methods for measuring Glu are limited to low spatial resolution, which makes it difficult to measure differences in gray and white matter glutamate. Recently, it has been shown that Glu exhibits a concentration dependent chemical exchange saturation transfer (CEST) effect between its amine (-NH2) group protons and bulk water protons (GluCEST). Here, we demonstrate the feasibility of imaging glutamate in the spinal cord at 7T using the GluCEST technique. Results from healthy human volunteers (N =7) showed a significantly higher (p <0. 001) GluCESTasym from gray matter (6. 6±0. 3%) compared to white matter (4. 8±0. 4%). Potential overlap of CEST signals from other spinal cord metabolites with the observed GluCESTasym is discussed. This noninvasive approach potentially opens the way to image Glu in vivo in the spinal cord and to monitor its alteration in many disease conditions.

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YNIMG Journal 2011 Journal Article

In vivo mapping of brain myo-inositol

Mohammad Haris
Kejia Cai
Anup Singh
Hari Hariharan
Ravinder Reddy

Myo-Inositol (MI) is one of the most abundant metabolites in the human brain located mainly in glial cells and functions as an osmolyte. The concentration of MI is altered in many brain disorders including Alzheimer's disease and brain tumors. Currently available magnetic resonance spectroscopy (MRS) methods for measuring MI are limited to low spatial resolution. Here, we demonstrate that the hydroxyl protons on MI exhibit chemical exchange with bulk water and saturation of these protons leads to reduction in bulk water signal through a mechanism known as chemical exchange saturation transfer (CEST). The hydroxyl proton exchange rate (k =600s−1) is determined to be in the slow to intermediate exchange regime on the NMR time scale (chemical shift (∆ω)> k), suggesting that the CEST effect of MI (MICEST) can be imaged at high fields such as 7T (∆ω =1. 2×103 rad/s) and 9. 4T (∆ω =1. 6×103 rad/s). Using optimized imaging parameters, concentration dependent broad CEST asymmetry between ~0. 2 and 1. 5ppm with a peak at ~0. 6ppm from bulk water was observed. Further, it is demonstrated that MICEST detection is feasible in the human brain at ultra high fields (7T) without exceeding the allowed limits on radiofrequency specific absorption rate. Results from healthy human volunteers (N =5) showed significantly higher (p =0. 03) MICEST effect from white matter (5. 2±0. 5%) compared to gray matter (4. 3±0. 5%). The mean coefficient of variations for intra-subject MICEST contrast in WM and GM were 0. 49 and 0. 58 respectively. Potential overlap of CEST signals from other brain metabolites with the observed MICEST map is discussed. This noninvasive approach potentially opens the way to image MI in vivo and to monitor its alteration in many disease conditions.

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