Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm

Kevin M Cook; Josepheen De Asis-Cruz; Sudeepta K Basu; Nickie Andescavage; Jonathan Murnick; Emma Spoehr; Adré J du Plessis; Catherine Limperopoulos

doi:10.3389/fnins.2023.1214080

Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm

Front Neurosci. 2023 Sep 1:17:1214080. doi: 10.3389/fnins.2023.1214080. eCollection 2023.

Authors

Kevin M Cook¹, Josepheen De Asis-Cruz¹, Sudeepta K Basu¹, Nickie Andescavage¹, Jonathan Murnick², Emma Spoehr¹, Adré J du Plessis³, Catherine Limperopoulos¹

Affiliations

¹ Developing Brain Institute, Children's National Hospital, Washington, DC, United States.
² Department of Diagnostic Imaging & Radiology, Children's National Health System, Children's National Hospital, Washington, DC, United States.
³ Prenatal Pediatrics Institute, Children's National Hospital, Washington, DC, United States.

Abstract

Introduction: The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike in-utero fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored.

Methods: From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex.

Results: A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r²_Adj range 0.143-0.401, p < 0048), with C and LE exhibited trending increases with age.

Discussion: This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to in utero fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.

Keywords: brain development; brain network; graph theory; prematurity; resting state fMRI; stress.

Abstract

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