Our goal is to develop an electronic system to archive, visualize, and quantity brain MRIs, linked with patients demographic, clinic, and diagnostic information. In this proposal, we will perform initial attempts to develop several key tools to establish this database, initially focused on pediatric population. Specifically, we will ) Create a pilot database, using existing clinical data acquired in Johns Hopkins Hospital, plenty available on PACS systems, and the JHU normal pediatric database (lbam.med.jhmi.edu). All relevant images will be normalized to common spatial coordinates, combined with structured demographic and clinical information, and de-identified. Then, the images will be segmented into various anatomical structures and each segment will be quantified for volume and intensities;and 2) Develop a prototype user interface (based on AtlasView software, www.mristudio.org) that will allow to navigate in the database, to view multiple images in different spaces and contrasts, to overlay the segmentation, to access the quantification, patient data, demographic, and clinic information. If we succeed, this electronic archive and the associated quantification tools will potentially become an important source for educational purposes, for sharing standardized research information and for aiding radiologic interpretation.

Public Health Relevance

We will develop an electronic system to achieve, visualize, and quantify brain MRIs, linked with patients demographic, clinic, and diagnostic information that will potentially become an important source for educational purposes, for sharing standardized research information and for aiding radiologic interpretation.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Research Grants (R03)
Project #
1R03EB014357-01A1
Application #
8383903
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Luo, James
Project Start
2012-08-01
Project End
2014-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
1
Fiscal Year
2012
Total Cost
$81,000
Indirect Cost
$31,000
Name
Johns Hopkins University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Faria, Andreia V; Ratnanather, J Tilak; Tward, Daniel J et al. (2016) Linking white matter and deep gray matter alterations in premanifest Huntington disease. Neuroimage Clin 11:450-60
Davis, Cameron L; Oishi, Kenichi; Faria, Andreia V et al. (2016) White matter tracts critical for recognition of sarcasm. Neurocase 22:22-9
Oishi, Kenichi; Faria, Andreia V; Hsu, John et al. (2015) Critical role of the right uncinate fasciculus in emotional empathy. Ann Neurol 77:68-74
Faria, Andreia V; Oishi, Kenichi; Yoshida, Shoko et al. (2015) Content-based image retrieval for brain MRI: an image-searching engine and population-based analysis to utilize past clinical data for future diagnosis. Neuroimage Clin 7:367-76
Faria, Andreia V; Sebastian, Rajani; Newhart, Melissa et al. (2014) Longitudinal Imaging and Deterioration in Word Comprehension in Primary Progressive Aphasia: Potential Clinical Significance. Aphasiology 28:948-963
Djamanakova, Aigerim; Tang, Xiaoying; Li, Xin et al. (2014) Tools for multiple granularity analysis of brain MRI data for individualized image analysis. Neuroimage 101:168-76
Race, D S; Tsapkini, K; Crinion, J et al. (2013) An area essential for linking word meanings to word forms: evidence from primary progressive aphasia. Brain Lang 127:167-76
Oishi, Kenichi; Faria, Andreia V; Yoshida, Shoko et al. (2013) Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging. Int J Dev Neurosci 31:512-24
Djamanakova, Aigerim; Faria, Andreia V; Hsu, John et al. (2013) Diffeomorphic brain mapping based on T1-weighted images: improvement of registration accuracy by multichannel mapping. J Magn Reson Imaging 37:76-84
Tang, Xiaoying; Oishi, Kenichi; Faria, Andreia V et al. (2013) Bayesian Parameter Estimation and Segmentation in the Multi-Atlas Random Orbit Model. PLoS One 8:e65591

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