This application proposes to implement and extensively validate a new computational approach for analyzing anatomical structures in the brain using magnetic resonance imaging. This approach, called the continuous medial representation, is an innovative method that uses the shape of anatomical structures to characterize atrophy and to provide a natural coordinate system in which image information from multiple subjects in a population study can be combined with greater accuracy and higher statistical power than previously possible. The approach differs significantly from existing techniques that consider the brain as a whole, which necessarily limits the sensitivity and specificity of analyses on particular structures of interest. Preliminary results provide compelling support for the elegance of the approach and for its potential to conduct detailed studies of both anatomical and functional effects of disease and injury. ? The specific aims of the proposal are (1) to verify that cm-rep models can represent the hippocampus accurately, particularly in the presence of pathology; (2) to validate cross-subject normalization via the cm-rep method by examining how well it aligns hippocampal sub-fields; (3) to confirm preliminary findings indicating that shape-based normalization can improve the statistical power of group fMRI analysis; (4) to demonstrate that the cm-rep approach presents an improvement over volume-based and boundary-based methods for combined statistical analysis of hippocampal shape and multivariate/multimodal imaging data.
These aims will be achieved by applying the new technique to simulated and real imaging data from functional and structural studies involving temporal lobe epilepsy, Alzheimer's disease, and schizophrenia. This exploratory research, if successful, will clear the ground for a number of follow-up hypothesis-driven research studies addressing structural hippocampal abnormalities and functional recruitment of the hippocampus in memory tasks in various clinical populations.
The specific aims of this proposal can have an immediate impact on studies of the hippocampus in health and disease. The hippocampus, whose function involves encoding and consolidating new memories, is of central importance in some of the most common neurological disorders, including epilepsy and dementia. Refined analysis with the new approach proposed in this application promises to impact our understanding of these devastating disorders by detecting and pinpointing smaller, more focal changes in hippocampal anatomy and function than the current methods allow. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21NS061111-02
Application #
7502611
Study Section
Special Emphasis Panel (ZRG1-MDCN-K (51))
Program Officer
Liu, Yuan
Project Start
2007-09-30
Project End
2010-08-31
Budget Start
2008-09-01
Budget End
2010-08-31
Support Year
2
Fiscal Year
2008
Total Cost
$206,719
Indirect Cost
Name
University of Pennsylvania
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Pouch, Alison M; Yushkevich, Paul A; Jackson, Benjamin M et al. (2012) Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound. Med Phys 39:933-50
Das, Sandhitsu R; Avants, Brian B; Pluta, John et al. (2012) Measuring longitudinal change in the hippocampal formation from in vivo high-resolution T2-weighted MRI. Neuroimage 60:1266-79
Das, Sandhitsu R; Mechanic-Hamilton, Dawn; Pluta, John et al. (2011) Heterogeneity of functional activation during memory encoding across hippocampal subfields in temporal lobe epilepsy. Neuroimage 58:1121-30
Wang, Hongzhi; Das, Sandhitsu R; Suh, Jung Wook et al. (2011) A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain segmentation. Neuroimage 55:968-85
Yushkevich, Paul A; Wang, Hongzhi; Pluta, John et al. (2010) Nearly automatic segmentation of hippocampal subfields in in vivo focal T2-weighted MRI. Neuroimage 53:1208-24
Zhang, Hui; Awate, Suyash P; Das, Sandhitsu R et al. (2010) A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features. Med Image Anal 14:666-73
Awate, Suyash P; Yushkevich, Paul A; Song, Zhuang et al. (2010) Cerebral cortical folding analysis with multivariate modeling and testing: Studies on gender differences and neonatal development. Neuroimage 53:450-9
Sun, Hui; Frangi, Alejandro F; Wang, Hongzhi et al. (2010) Automatic cardiac MRI segmentation using a biventricular deformable medial model. Med Image Comput Comput Assist Interv 13:468-75
Wang, Hongzhi; Das, Sandhitsu; Pluta, John et al. (2010) Standing on the shoulders of giants: improving medical image segmentation via bias correction. Med Image Comput Comput Assist Interv 13:105-12
Yushkevich, Paul A; Avants, Brian B; Pluta, John et al. (2009) A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T. Neuroimage 44:385-98

Showing the most recent 10 out of 18 publications