Abnormal ventricular development in preterm neonates with visually normal MRIs

Jie Shi; Yalin Wang; Yi Lao; Rafael Ceschin; Liang Mi; Marvin D. Nelson; Ashok Panigrahy; Natasha Leporé

doi:10.1117/12.2213297

22 December 2015 Abnormal ventricular development in preterm neonates with visually normal MRIs

Jie Shi, Yalin Wang, Yi Lao, Rafael Ceschin, Liang Mi, Marvin D. Nelson, Ashok Panigrahy, Natasha Leporé

Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 96810H (2015) https://doi.org/10.1117/12.2213297
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador

Abstract

Children born preterm are at risk for a wide range of neurocognitive and neurobehavioral disorders. Some of these may stem from early brain abnormalities at the neonatal age. Hence, a precise characterization of neonatal neuroanatomy may help inform treatment strategies. In particular, the ventricles are often enlarged in neurocognitive disorders, due to atrophy of surrounding tissues. Here we present a new pipeline for the detection of morphological and relative pose differences in the ventricles of premature neonates compared to controls. To this end, we use a new hyperbolic Ricci flow based mapping of the ventricular surfaces of each subjects to the Poincaré disk. Resulting surfaces are then registered to a template, and a between group comparison is performed using multivariate tensor-based morphometry. We also statistically compare the relative pose of the ventricles within the brain between the two groups, by performing a Procrustes alignment between each subject's ventricles and an average shape. For both types of analyses, differences were found in the left ventricles between the two groups.

Citation Download Citation

Jie Shi, Yalin Wang, Yi Lao, Rafael Ceschin, Liang Mi, Marvin D. Nelson, Ashok Panigrahy, and Natasha Leporé "Abnormal ventricular development in preterm neonates with visually normal MRIs", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 96810H (22 December 2015); https://doi.org/10.1117/12.2213297

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