Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants

Islem Rekik, Gang Li, Weili Lin, Dinggang Shen

Research output: Contribution to conferencePaper

2 Citations (Scopus)
25 Downloads (Pure)

Abstract

In vivo brain connectomics have heavily relied on using functional and diffusion Magnetic Resonance Imaging (MRI) modalities to examine functional and structural relationships between pairs of anatomical regions in the brain. However, research work on brain morphological (i.e., shape-to-shape) connections, which can be derived from T1-w and T2-w MR images, in both typical and atypical development or ageing is very scarce. Furthermore, the brain cannot be only regarded as a static shape, since it is a dynamic complex system that changes at functional, structural and morphological levels. Hence, examining the ‘connection’ between brain shape and its changes with time (e.g., growth) may help advance our understanding of connectomic brain dynamics as well as disorders that may affect it. To address these limitations, we unprecedentedly introduce two population-based shape and growth connectivity analysis tools that further extend the field of connectomics to brain morphology and dynamics: the morphome and the kinectome. Specifically, for a population of anatomically labelled shapes, the morphome identifies a network of anatomical shape regions that are connected when morphologically similar at a single timepoint, whereas the kinectome identifies anatomical shape regions that elicit similar evolution dynamics across successive timepoints. These proposed generic tools can be easily invested to examine how a baseline shape influences its deformation trajectory at later timepoints using any longitudinal shape data. We evaluated these tools on 23 infants, with right and left cortical surfaces reconstructed at birth, 3, 6, 9 and 12 months of age. Investigating the relationship between the neonatal morphome and the postnatal kinectome (from birth to 1 year of age) gave insights into brain connectivity at birth and how it develops over time.
Original languageEnglish
Pages985-989
Number of pages5
DOIs
Publication statusPublished - 24 May 2018
EventIEEE International Symposium on Biomedical Imaging - Omni Shoreham Hotel, Washington DC, United States
Duration: 4 Apr 20187 Apr 2018
http://biomedicalimaging.org/2018/

Conference

ConferenceIEEE International Symposium on Biomedical Imaging
Abbreviated titleISBI'18
CountryUnited States
CityWashington DC
Period4/04/187/04/18
Internet address

Fingerprint

Connectome
Brain mapping
Brain Mapping
Atlases
Brain
Growth
Parturition
Diffusion Magnetic Resonance Imaging
Population
Magnetic Resonance Imaging
Large scale systems
Research
Aging of materials
Trajectories

Keywords

  • Brain Connectivity
  • Cortex Morphology
  • Growth and Shape
  • Kinetcome
  • Morphome
  • Shape Similarity Networks

Cite this

Rekik, I., Li, G., Lin, W., & Shen, D. (2018). Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants. 985-989. Paper presented at IEEE International Symposium on Biomedical Imaging , Washington DC, United States. https://doi.org/10.1109/ISBI.2018.8363736
Rekik, Islem ; Li, Gang ; Lin, Weili ; Shen, Dinggang. / Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants. Paper presented at IEEE International Symposium on Biomedical Imaging , Washington DC, United States.5 p.
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author = "Islem Rekik and Gang Li and Weili Lin and Dinggang Shen",
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Rekik, I, Li, G, Lin, W & Shen, D 2018, 'Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants' Paper presented at IEEE International Symposium on Biomedical Imaging , Washington DC, United States, 4/04/18 - 7/04/18, pp. 985-989. https://doi.org/10.1109/ISBI.2018.8363736

Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants. / Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang.

2018. 985-989 Paper presented at IEEE International Symposium on Biomedical Imaging , Washington DC, United States.

Research output: Contribution to conferencePaper

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T1 - Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants

AU - Rekik, Islem

AU - Li, Gang

AU - Lin, Weili

AU - Shen, Dinggang

N1 - This work is funded by: MH100217, MH108914, MH107815, MH110274

PY - 2018/5/24

Y1 - 2018/5/24

N2 - In vivo brain connectomics have heavily relied on using functional and diffusion Magnetic Resonance Imaging (MRI) modalities to examine functional and structural relationships between pairs of anatomical regions in the brain. However, research work on brain morphological (i.e., shape-to-shape) connections, which can be derived from T1-w and T2-w MR images, in both typical and atypical development or ageing is very scarce. Furthermore, the brain cannot be only regarded as a static shape, since it is a dynamic complex system that changes at functional, structural and morphological levels. Hence, examining the ‘connection’ between brain shape and its changes with time (e.g., growth) may help advance our understanding of connectomic brain dynamics as well as disorders that may affect it. To address these limitations, we unprecedentedly introduce two population-based shape and growth connectivity analysis tools that further extend the field of connectomics to brain morphology and dynamics: the morphome and the kinectome. Specifically, for a population of anatomically labelled shapes, the morphome identifies a network of anatomical shape regions that are connected when morphologically similar at a single timepoint, whereas the kinectome identifies anatomical shape regions that elicit similar evolution dynamics across successive timepoints. These proposed generic tools can be easily invested to examine how a baseline shape influences its deformation trajectory at later timepoints using any longitudinal shape data. We evaluated these tools on 23 infants, with right and left cortical surfaces reconstructed at birth, 3, 6, 9 and 12 months of age. Investigating the relationship between the neonatal morphome and the postnatal kinectome (from birth to 1 year of age) gave insights into brain connectivity at birth and how it develops over time.

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Rekik I, Li G, Lin W, Shen D. Estimation of Shape and Growth Brain Network Atlases for Connectomic Brain Mapping in Developing Infants. 2018. Paper presented at IEEE International Symposium on Biomedical Imaging , Washington DC, United States. https://doi.org/10.1109/ISBI.2018.8363736