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 language | English |
|---|---|
| Title of host publication | 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018 |
| Publisher | IEEE Computer Society |
| Pages | 985-989 |
| Number of pages | 5 |
| Volume | 2018-April |
| ISBN (Electronic) | 9781538636367 |
| DOIs | |
| Publication status | Published - 2018 May 23 |
| Externally published | Yes |
| Event | 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States Duration: 2018 Apr 4 → 2018 Apr 7 |
Other
| Other | 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 |
|---|---|
| Country | United States |
| City | Washington |
| Period | 18/4/4 → 18/4/7 |
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Keywords
- Brain Connectivity
- Cortex Morphology
- Growth and Shape
- Kinetcome
- Morphome
- Shape Similarity Networks
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
Cite this
Estimation of shape and growth brain network atlases for connectomic brain mapping in developing infants. / Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang.
2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. Vol. 2018-April IEEE Computer Society, 2018. p. 985-989.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
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
PY - 2018/5/23
Y1 - 2018/5/23
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.
AB - 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.
KW - Brain Connectivity
KW - Cortex Morphology
KW - Growth and Shape
KW - Kinetcome
KW - Morphome
KW - Shape Similarity Networks
UR - http://www.scopus.com/inward/record.url?scp=85048110211&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048110211&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2018.8363736
DO - 10.1109/ISBI.2018.8363736
M3 - Conference contribution
AN - SCOPUS:85048110211
VL - 2018-April
SP - 985
EP - 989
BT - 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PB - IEEE Computer Society
ER -