MICCAI 2008 WORKSHOP Imaging the Early Developing Brain: Challenges and Potential Impact

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PROGRAM

ORGANIZERS

SUBMISSION

Organizers:

Guido Gerig (Utah)

John H. Gilmore (UNC)

Alan Evans (MNI)

Daniel Rueckert (Imperial College London)

Simon Warfield (Children’s Hospital Boston)

Rationale:

Imaging studies of early brain development get increasing attention as improved modeling of the pattern of normal development and of change from normal might lead to a better understanding of origin, timing and nature of morphologic and functional differences in neurodevelopmental disorders. Measuring the trajectory of growth via noninvasive imaging such as structural MRI and DTI, for example, will likely provide a vastly improved understanding of early brain development, changes due to delayed development or pathology, and its relationship to neuropsychiatric disorders.

Studying the age group from birth to 5 years, even including premature born babies, involves several major challenges which are specific to neuroimaging of this age group. Most important are the imaging of non-sedated infants with low failure rate, in particular in longitudinal studies, and the development of appropriate image analysis methodologies that can cope with low contrast-to-noise ratio, rapid change of size of brain structures, complex brightness changes in MRI reflecting rapid white matter structuring through myelination and axon elimination, rapid change and large variability of anatomical shapes, and locally varying contrast associated with early structuring. The study of growth trajectories by definition involves longitudinal imaging and will require application of computational tools for processing of 4D data (3D plus time) and statistical methods for longitudinal data analysis.

Goals of the workshop are the following:

· to introduce the topics of early brain development, pediatric imaging and its challenges, and association of structures and patterns observed in images to what is known about the underlying neurobiology,

· to introduce the clinical need and potential impact for studies of early brain development, including the need for normative data to model trajectories of normal brain development, the motivation for early diagnosis of children at risk for mental illness and neurological disorders, the ability to study rare diseases, monitoring treatment and intervention, and image modalities appropriate for this age group,

· to inform about publicly available image databases of pediatric imaging studies to test, validate and develop advanced computational tools,

· to discuss the current status of image analysis methodology and emerging new approaches to study early brain growth and change from normal (including segmentation, registration, atlas-building, computational anatomy tools, analysis of MRI, DTI, ultrasound, and more),

· to discuss validation and cross-method comparison of image analysis,

· and finally to do brainstorming on key issues critical to further advance the field.

Format:

The workshop includes invited talks by representatives from different institutions strongly involved in pediatric neuroimaging studies and analysis of such data and also short poster teaser presentations and posters of submitted abstracts. Participants are encouraged to use the discussion time after presentations and the brainstorming and panel sessions for a critical dialogue to clarify the state-of-the-art and formulate outstanding issues both w.r.t. imaging technology, image analysis challenges, and fundamental mathematical and algorithmic issues related to this type of longitudinal data presenting rapid change of contrast, size, shapes and appearance. The workshop will also inform about availability of image databases, pediatric atlases, and tools.

Participants will get pdf copies of talks and presentations (ready on CD at workshop).

Intended audience:

Researchers from medicine, biology, imaging, bioengineering, image analysis, and biostatistics, among others, who are interested or already involved in studies of early brain development in healthy and disease, and also researchers who are developing imaging/image analysis technologies which are of particular interest to study this type of image data.