Challenges in pediatric neuroimaging

Abstract

Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans.

Keywords: Fetal imaging; MRI; Neonatal imaging; Pediatric neuroimaging.

Figure 1. Normal 29-week premature neonate

T1 and T2 weighted brain MR images of 29-week gestational age premature infant. Note the simple sulcation pattern and high T2 and low T1 signal in the white matter due to minimal myelination.

Figure 2. Normal term neonate

T1 and T2 weighted brain MR images of late term neonate. Note the increasing depth and complexity of the sulci with formation of most tertiary and quaternary sulci. Brain water content is decreased on T2 weighted imaging, and early myelination is seen, notably in the posterior limb of the internal capsule.

Figure 3. Normal 6-month-old infant

T1 and T2 weighted brain MR images of 6-month-old infant. The sulcal pattern has matured further and myelination has progressed to the pre-and post-central gyri.

Figure 4. Normal 14-year-old child

T1 and T2 weighted brain MR images of 14-year-old child. An adult sulcation pattern is present, with all tertiary and quaternary sulci formed and fully developed. Myelination is complete with normal adult pattern of high T1 and low T2 white matter signal.

Figure 5. Proton MR spectroscopy of premature and term neonates

Note the low NAA to choline ratio which increases with increasing gestational age. Reprinted with permission from (Vigneron et al., 2001)

Figure 6. Neonatal diffusion tensor imaging

Neonates at 34 and 40 weeks gestational age. Note the reduced diffusivity and increased fractional anisotropy in the white matter. Reprinted with permission from (Partridge et al., 2005)

Figure 7. Maturation of the “baby connectome”: examples of brain networks at four different ages

(A) Anatomic T2 weighted MRI images. (B) Tractograms reconstructed based on DTI data. (C) Brain networks represented as weighted graphs. The size of the nodes is proportional to the node degree. (D) Binary connectivity matrices. Reprinted from (Tymofiyeva et al., 2013)

Figure 8. Motion Degradation

Motion corrupted T2 and diffusion weighted images (DWI) show signal dropout and wrap artifact when compared to images obtained with minimal motion.

Figure 9. Feed and swaddle

Neonate secured in bean bag wrap on MRI scanner table with hearing protection and head coil in place.

Figure 10. Neonatal Head Arrays

High channel count phased arrays designed to fit in an MR compatible incubator and sized to fit neonates of a range of gestational ages. Reprinted with permission from (Keil et al., 2011)

Figure 11. Phased array performance

Improved signal to noise seen on T1 weighted spoiled gradient echo images when 4-year-old (a and c) and adult (b and d) coils are used. Reprinted with permission from (Keil et al., 2011)

Figure 12. Prospective motion correction (PROMO)

The method uses spiral navigators to perform real-time rigid-body motion tracking and correction during the dead time of standard image acquisition. Reprinted with permission from (Brown et al., 2010)

Figure 13. Infant Brain Segmentation

Automatically segmented grey and white matter volumes in a 6-month-old, performed using deep neural networks. Reprinted with permission from (Wang et al., 2015)