This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.The long-range objectives of this line of investigation are two fold: 1) to add to the classification value of the American Spinal Injury Association (ASIA) Impairment Scale by establishing imaging criteria for chronic spinal cord Injury (SCI), 2) to understand the variables that contribute to residual neurological function and to the enhanced capacity for recovery. Development of imaging correlates of the integrity of spinal cord white matter is needed for optimizing design of clinical trials in SCI and related neurological diseases. The resource investigators have successfully optimized methods to quantitatively evaluate the integrity of spinal cord white matter using Diffusion Tensor Imaging (DTI) and Magnetization Transfer (MT) imaging and shown that this could be correlated with neurological function in chronic non-traumatic SCI (patients with adrenomyeloneuropathy, AMN). The development of these imaging modalities have enabled us to obtain high spatial resolution images of the cervical spinal cord and sufficient SNR to distinguish gray and white matter contrast allowing visualization of specific neuronal tracks in the spinal cord at a field of 1.5 Tesla. The goal of the proposed study is to determine the feasibility of using Diffusion Tensor Imaging (DTI), Magnetization Transfer (MT) imaging, and MRS to define the integrity of white matter pathways important for functional classification of individuals with chronic SCI.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR015241-08
Application #
7724143
Study Section
Special Emphasis Panel (ZRG1-SBIB-K (40))
Project Start
2008-09-01
Project End
2009-08-31
Budget Start
2008-09-01
Budget End
2009-08-31
Support Year
8
Fiscal Year
2008
Total Cost
$22,050
Indirect Cost
Name
Hugo W. Moser Research Institute Kennedy Krieger
Department
Type
DUNS #
155342439
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Aboud, Katherine S; Barquero, Laura A; Cutting, Laurie E (2018) Prefrontal mediation of the reading network predicts intervention response in dyslexia. Cortex 101:96-106
Albert, Marilyn; Zhu, Yuxin; Moghekar, Abhay et al. (2018) Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years. Brain :
Calabresi, Peter A; van Zijl, Peter Cm (2017) Ultra-high-field (7.0 Tesla and above) MRI is now necessary to make the next step forward in understanding MS pathophysiology - Commentary. Mult Scler 23:376-377
Gross, Alden L; Mungas, Dan M; Leoutsakos, Jeannie-Marie S et al. (2016) Alzheimer's disease severity, objectively determined and measured. Alzheimers Dement (Amst) 4:159-168
Harrison, D M; Li, X; Liu, H et al. (2016) Lesion Heterogeneity on High-Field Susceptibility MRI Is Associated with Multiple Sclerosis Severity. AJNR Am J Neuroradiol 37:1447-53
Bailey, Stephen; Hoeft, Fumiko; Aboud, Katherine et al. (2016) Anomalous gray matter patterns in specific reading comprehension deficit are independent of dyslexia. Ann Dyslexia 66:256-274
Tang, Xiaoying; Holland, Dominic; Dale, Anders M et al. (2015) APOE Affects the Volume and Shape of the Amygdala and the Hippocampus in Mild Cognitive Impairment and Alzheimer's Disease: Age Matters. J Alzheimers Dis 47:645-60
Harrison, Daniel M; Oh, Jiwon; Roy, Snehashis et al. (2015) Thalamic lesions in multiple sclerosis by 7T MRI: Clinical implications and relationship to cortical pathology. Mult Scler 21:1139-50
Matsui, Joy T; Vaidya, Jatin G; Wassermann, Demian et al. (2015) Prefrontal cortex white matter tracts in prodromal Huntington disease. Hum Brain Mapp 36:3717-32
Tang, Xiaoying; Holland, Dominic; Dale, Anders M et al. (2015) Baseline shape diffeomorphometry patterns of subcortical and ventricular structures in predicting conversion of mild cognitive impairment to Alzheimer's disease. J Alzheimers Dis 44:599-611

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