Individuals with congenital heart defects (CHD) are vulnerable to long-lasting neurodevelopmental impairments. In this study, we found that youth with CHD had overall smaller total and regional volumes in the cerebellum, when compared to healthy controls of the same age. These differences were statistically significant in 18 of 26 bilateral cerebellar regions, but were not significant in lobules I, II, VI and IX as well as Crus I (bilaterally). These anatomical alterations in many regions could lead to functional impairments since the cerebellum plays a role in many aspects of behavior, including movement, cognition and emotional regulation.
Introduction
Congenital heart defects (CHD) are the most common neonatal malformations and are a leading cause of long-lasting neurodevelopmental impairments1,2. It is well known that the cerebellum coordinates voluntary movement, including posture, balance and speech and is involved in motor learning. However, recent work has also linked it to a range of non-motor functions such as cognition and emotional regulation and delineated the functional specificity of different regions3. The posterior lobe of the cerebellum is involved in cognition and connects to associative regions such as the prefrontal and parietal cortex, while the anterior cerebellum is involved in sensory-motor function. Structural abnormalities in the cerebellum have been identified in populations with neurodevelopmental disorders (e.g. autism spectrum disorder, attention deficit hyperactivity disorder)4,5, in preterm infants and those at risk for neonatal hypoxia6. Since CHD youth have long lasting impairments, the goal of the present study was to determine whether cerebellar anatomical alterations are present in this group. A secondary goal was to determine if any anatomical alterations occur over the entire cerebellum or are limited to specific regions, which may result in particular functional deficits.Methods
The participants included 46 youth aged 16 to 24 years born with complex CHD and 46 healthy controls matched for age and gender. The participants with CHD had all undergone open-heart surgery with cardiopulmonary bypass during the first two years of life. A 3T MRI System (Achieva X, Philips Healthcare, Best, The Netherlands) using a 32-channel head coil was used to acquire high resolution T1 weighted anatomical images (TR=8.1 ms, TE=3.7 ms, flip angle =8°, voxel size = 1.00 x 1.00 x 1.00 mm). These images were preprocessed using the minc-bpipe-library pipeline7,8, which corrects for bias field contrast inhomogeneity using the N4ITK algorithm9 and performs brain extraction (BEaST)10. All subjects were also processed using the CIVET-2.1.0 pipeline to obtain total brain volume (TBV) estimates11. All images were post-processed using the Multiple Automatically Generated Templates brain segmentation algorithm (MAGeT-Brain) (https://github.com/CobraLab/MAGeTbrain)12. The cerebellum was segmented into 26 bilateral regions using a set of high-resolution in vivo atlases of the cerebellum developed using MR imaging and a carefully validated manual segmentation protocol13. The segmentations were evaluated to ensure that quality was adequate using Display software13. The 26 regions included bilateral central white matter and the following bilateral lobules: (1) I precentral and II preculminate, (2) III intraculminate, (3) IV primary, (4) V superior posterior, (5) VI horizontal, (6) Crus I, (7) Crus II, (8) VIIB ansoparamedian, (9) VIIIA prepyramidal/prebiventer, (10) VIIIB prepyramidal/prebiventer, (11) IX intrabiventer and (12) X secondary. The overall cerebral and cerebellar volumes were compared between CHD individuals and controls using t-tests corrected for multiple comparisons. An ANCOVA was performed with SPSS (Version 23) comparing the size of the 26 regions of the cerebellum between the CHD individuals and controls, with TBV as a covariate. The results were corrected for multiple comparisons with Bonferroni adjustment.Results
The CHD individuals were found to have overall smaller total cerebral and cerebellar volumes (p<0.05) than controls. The ANCOVA results comparing the cerebellar regions indicated that 18 out of the 26 regions were smaller in the CHD group compared with controls (p<0.05). The eight regions that did not differ in size between the groups included lobules I, II, VI and IX as well as Crus I (bilaterally). The effect sizes from this analysis were small or moderate in most regions (e.g. partial eta squared ranging from 0.08 to 0.2 in lobules III-V, and Crus II), but were moderate or large in several posterior regions (greater than 0.200 in lobules VIIB, VIIIA, VIIIB and X), indicating that the differences between the two groups were largest in these areas.Discussion
In conclusion, youth with CHD had smaller regional cerebellar volumes, when compared to healthy controls, and this included 18 out of 26 regions of the cerebellum. Future studies could determine whether these anatomical alterations are associated with the impairments in executive function commonly reported in this population, considering the predominant role of the posterior cerebellum in higher order cognitive function and affective regulation.Conclusion
The results indicate that CHD youth are at risk for anatomical alterations including reduced cerebellar volume, which has also been shown with preterm infants6 and individuals with neurodevelopmental disorders4,5. This is consistent with previous research showing that the cerebellum is vulnerable to disrupted growth during early development6.1. McQuillen, P.S. & Miller, S.P. (2010). Congenital heart disease and brain development. Ann N Y Acad Sci, 1184, 68-86.
2. Hovels-Gurich, H.H., (2016). Factors influencing neurodevelopment after cardiac surgery during infancy. Front Pediatr, 4, 137.
3. Stoodley, C. J., Valera, E. M. & Schmahmann, J. D. (2012). Functional topography of the cerebellum for motor and cognitive tasks: An fMRI study. NeuroImage, 59, 1560–1570.
4. Amaral, D.G., Schumann, C.M. & Nordahl, C.W. (2008). Neuroanatomy of autism. Trends Neurosci., 31, 137–145.
5. Stoodley, C.J. (2016). The cerebellum and neurodevelopmental disorders. Cerebellum, 15(1),34-7.
6. Brossard-Racine M., du Plessis, A.J., & Limperopoulos, C. (2015). Developmental cerebellar cognitive affective syndrome in ex-preterm survivors following cerebellar injury. Cerebellum, 14(2),151-64.
7. Sadedin, S.P., Pope, B., & Oshlack, A. (2012). Bpipe: a tool for running and managing bioinformatics pipelines. Bioinformatics, 28(11), 1525-6.
8. Vincent, R.D., Neelin, P., Khalili-Mahani, N., Janke, A.L., Fonov, V.S., Robbins, S.M., … Evans, A. C. (2016). MINC 2.0: A flexible format for multi-modal images. Front Neuroinform, 10: 35.
9. Tustison, N.J., Avants, B.B., Cook, P.A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010). N4ITK: Improved N3 bias correction. IEEE Trans Med Imaging, 29(6), 1310–20.
10. Eskildsen, S.F., Coupe, P., Fonov, V., Manjon, J.V., Leung, K.K., Guizard, N… Alzheimer's Disease Neuroimaging Initiative (2012). BEaST: Brain extraction based on nonlocal segmentation technique. NeuroImage, 59(3), 2362-2373.
11. Zijdenbos, A.P., Forghani, R., & Evans, A.C. (2002). Automatic pipeline analysis of 3-D MRI data for clinical trials: Application to multiple sclerosis. IEEE Trans Med Imaging, 21, 1280–1291.
12. Chakravarty, M.M., Steadman, P., van Eede, M.C., Calcott, R.D., Gu, V., Shaw, P….Lerch, J.P.. (2013). Performing label-fusion-based segmentation using multiple automatically generated templates. Hum Brain Mapp, 34(10), 2635–54.
13. Park, M.T., Pipitone, J., Baer, L., Winterburn, J.L., Shah, Y., Chavez, S….Chakravarty, M.M. (2014). High-resolution atlases of the cerebellum and cerebellar lobules at 3T: Derivation and automated segmentation using multiple automatically generated templates. NeuroImage, 95, 217-231.