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www.sci.utah.edu S C I I N S T I T U T E E X H I B I T EX P L O R E E X C I T E EX P E R I E N C E EX C H A N G E SCI On Relating Brain Shape With Neurological Disorders Prasanna Muralidharan, Nikhil Singh, Tom Fletcher and Sarang Joshi Motivation ● Brain imaging as a biomarker for neurological disorders such as Alzheimer's Disease (AD). ● Inferences from neuroanatomical shape changes for the purpose of early diagnosis and also to track disease progression. ● To study shape variation in brain structures within the population and over time (longitudinal studies) Alzheimer’s Disease ● Dementia characterized by severe behavioural, cognitive and functional impairment accompanied by neuroanatomical shape changes. ● Accelerated deterioration of mental functions and memory loss, to that compared in normal aging. ● Shape changes that occur during disease progression can be extracted from Magnetic Resonance (MR) brain images. Imaging and clinical data ● ADNI: about 800 subjects, structural MRI data for 6 timepoints at 6 months interval. ● Corresponding clinical test scores. ● Segmented brain structures such as corpus callosum, ventricles, etc ● We extract and identify shape deformation patterns in brain anatomy that relate to observed clinical scores depicting cognitive abilities. ● The methodology also enables us to quantify the amount of deformation in units of clinical response. Chaging shape along a parameter. Regression in shape space. MRI - sagittal slice. Shape variation in Corpus Callosum. Average 3D brain shape constructed from the population of 3D MRI images. Changing MMSE (Mini-mental state examination) for the average brain (26.53): Red corresponds to local expansion and blue to local contraction Supported by Alzheimer's Disease Neuroimaging Initiative (ADNI) (NIH grant U01AG024904), NIH grant 5R01EB007688, NIH grant P41 RR023953, NSF grant CNS-0751152 and the NSF CAREER grant 1054057 x M y i f(x i ) 18 19 20 21 22 23 24 25 26 26.53 27 28 29 30 f(x)

prasanna - Scientific Computing and Imaging Institute · Title: prasanna Created Date: 10/25/2011 12:21:47 PM

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    On Relating Brain Shape With Neurological DisordersPrasanna Muralidharan, Nikhil Singh, Tom Fletcher and Sarang Joshi

    Motivation● Brain imaging as a biomarker for neurological disorders such as Alzheimer's Disease (AD).● Inferences from neuroanatomical shape changes for the purpose of early diagnosis and also to track disease progression.● To study shape variation in brain structures within the population and over time (longitudinal studies)

    Alzheimer’s Disease● Dementia characterized by severe behavioural, cognitive and functional impairment accompanied by neuroanatomical shape changes.● Accelerated deterioration of mental functions and memory loss, to that compared in normal aging.● Shape changes that occur during disease progression can be extracted from Magnetic Resonance (MR) brain images.

    Imaging and clinical data● ADNI: about 800 subjects, structural MRI data for 6 timepoints at 6 months interval.● Corresponding clinical test scores.● Segmented brain structures such as corpus callosum, ventricles, etc

    ● We extract and identify shape deformation patterns in brain anatomy that relate to observed clinical scores depicting cognitive abilities.● The methodology also enables us to quantify the amount of deformation in units of clinical response.

    Chaging shape along a parameter. Regression in shape space. MRI - sagittal slice. Shape variation in Corpus Callosum.

    Average 3D brain shape constructed from the population of 3D MRI images.

    Changing MMSE (Mini-mental state examination) for the average brain (26.53): Red corresponds to local expansion and blue to local contraction

    Supported by Alzheimer's Disease Neuroimaging Initiative (ADNI) (NIH grant U01AG024904), NIH grant 5R01EB007688,NIH grant P41 RR023953, NSF grant CNS-0751152 and the NSF CAREER grant 1054057

    x M

    yi

    f(xi)

    18 19 20 21 22 23 24

    25 26 26.53 27 28 29 30

    f(x)