Characterizing growth patterns in longitudinal MRI using image contrast

Avantika Vardhan, Marcel Prastawa, Clement Vachet, Joseph Piven, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2014: Image Processing
    PublisherSPIE
    Volume9034
    ISBN (Print)9780819498274
    DOIs
    StatePublished - 2014
    EventMedical Imaging 2014: Image Processing - San Diego, CA, United States
    Duration: Feb 16 2014Feb 18 2014

    Other

    OtherMedical Imaging 2014: Image Processing
    CountryUnited States
    CitySan Diego, CA
    Period2/16/142/18/14

    Fingerprint

    image contrast
    Magnetic resonance imaging
    Brain
    Magnetic resonance
    Magnetic Resonance Spectroscopy
    Growth
    Biophysical Phenomena
    brain
    Chemical Phenomena
    Trajectories
    magnetic resonance
    Biomarkers
    Myelin Sheath
    Down Syndrome
    Nerve Fibers
    Synaptic Transmission
    scanners
    myelin sheath
    Scanning
    trajectories

    Keywords

    • Contrast
    • Contrast Change Trajectories
    • Early brain development
    • Reliability
    • Structural MRI
    • Time-based biomarkers

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics
    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Radiology Nuclear Medicine and imaging

    Cite this

    Vardhan, A., Prastawa, M., Vachet, C., Piven, J., & Gerig, G. (2014). Characterizing growth patterns in longitudinal MRI using image contrast. In Medical Imaging 2014: Image Processing (Vol. 9034). [90340D] SPIE. https://doi.org/10.1117/12.2043995

    Characterizing growth patterns in longitudinal MRI using image contrast. / Vardhan, Avantika; Prastawa, Marcel; Vachet, Clement; Piven, Joseph; Gerig, Guido.

    Medical Imaging 2014: Image Processing. Vol. 9034 SPIE, 2014. 90340D.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Vardhan, A, Prastawa, M, Vachet, C, Piven, J & Gerig, G 2014, Characterizing growth patterns in longitudinal MRI using image contrast. in Medical Imaging 2014: Image Processing. vol. 9034, 90340D, SPIE, Medical Imaging 2014: Image Processing, San Diego, CA, United States, 2/16/14. https://doi.org/10.1117/12.2043995
    Vardhan A, Prastawa M, Vachet C, Piven J, Gerig G. Characterizing growth patterns in longitudinal MRI using image contrast. In Medical Imaging 2014: Image Processing. Vol. 9034. SPIE. 2014. 90340D https://doi.org/10.1117/12.2043995
    Vardhan, Avantika ; Prastawa, Marcel ; Vachet, Clement ; Piven, Joseph ; Gerig, Guido. / Characterizing growth patterns in longitudinal MRI using image contrast. Medical Imaging 2014: Image Processing. Vol. 9034 SPIE, 2014.
    @inproceedings{ae976dd6867148da87badb0429b51ebf,
    title = "Characterizing growth patterns in longitudinal MRI using image contrast",
    abstract = "Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.",
    keywords = "Contrast, Contrast Change Trajectories, Early brain development, Reliability, Structural MRI, Time-based biomarkers",
    author = "Avantika Vardhan and Marcel Prastawa and Clement Vachet and Joseph Piven and Guido Gerig",
    year = "2014",
    doi = "10.1117/12.2043995",
    language = "English (US)",
    isbn = "9780819498274",
    volume = "9034",
    booktitle = "Medical Imaging 2014: Image Processing",
    publisher = "SPIE",

    }

    TY - GEN

    T1 - Characterizing growth patterns in longitudinal MRI using image contrast

    AU - Vardhan, Avantika

    AU - Prastawa, Marcel

    AU - Vachet, Clement

    AU - Piven, Joseph

    AU - Gerig, Guido

    PY - 2014

    Y1 - 2014

    N2 - Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.

    AB - Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.

    KW - Contrast

    KW - Contrast Change Trajectories

    KW - Early brain development

    KW - Reliability

    KW - Structural MRI

    KW - Time-based biomarkers

    UR - http://www.scopus.com/inward/record.url?scp=84902084348&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84902084348&partnerID=8YFLogxK

    U2 - 10.1117/12.2043995

    DO - 10.1117/12.2043995

    M3 - Conference contribution

    SN - 9780819498274

    VL - 9034

    BT - Medical Imaging 2014: Image Processing

    PB - SPIE

    ER -