» Articles » PMID: 25234033

A Prospective Longitudinal Brain Morphometry Study of Children with Sickle Cell Disease

Overview
Specialty Neurology
Date 2014 Sep 20
PMID 25234033
Citations 17
Authors
Affiliations
Soon will be listed here.
Abstract

Background And Purpose: Age-related changes in brain morphology are crucial to understanding the neurobiology of sickle cell disease. We hypothesized that the growth trajectories for total GM volume, total WM volume, and regional GM volumes are altered in children with sickle cell disease compared with controls.

Materials And Methods: We analyzed T1-weighted images of the brains of 28 children with sickle cell disease (mean baseline age, 98 months; female/male ratio, 15:13) and 28 healthy age- and sex-matched controls (mean baseline age, 99 months; female/male ratio, 16:12). The total number of MR imaging examinations was 141 (2-4 for each subject with sickle cell disease, 2-3 for each control subject). Total GM volume, total WM volume, and regional GM volumes were measured by using an automated method. We used the multilevel-model-for-change approach to model growth trajectories.

Results: Total GM volume in subjects with sickle cell disease decreased linearly at a rate of 411 mm(3) per month. For controls, the trajectory of total GM volume was quadratic; we did not observe a significant linear decline. For subjects with sickle cell disease, we found 35 brain structures that demonstrated age-related GM volume reduction. Total WM volume in subjects with sickle cell disease increased at a rate of 452 mm(3) per month, while the trajectory of controls was quadratic.

Conclusions: There was a significant age-related decrease in total GM volume in children with sickle cell disease. The GM volume reduction was spatially distributed widely across the brain, primarily in the frontal, parietal, and occipital lobes. Total WM volume in subjects with sickle cell disease increased at a lower rate than for controls.

Citing Articles

Brain Volumes and Cognition in Patients with Sickle Cell Anaemia: A Systematic Review and Meta-Analysis.

Hamdule S, Kirkham F Children (Basel). 2023; 10(8).

PMID: 37628359 PMC: 10453222. DOI: 10.3390/children10081360.


Neuroimaging and Cognitive Function in Sickle Cell Disease: A Systematic Review.

Abdi S, de Haan M, Kirkham F Children (Basel). 2023; 10(3).

PMID: 36980090 PMC: 10047189. DOI: 10.3390/children10030532.


Effects of regional brain volumes on cognition in sickle cell anemia: A developmental perspective.

Hamdule S, Kolbel M, Stotesbury H, Murdoch R, Clayden J, Sahota S Front Neurol. 2023; 14:1101223.

PMID: 36860579 PMC: 9968851. DOI: 10.3389/fneur.2023.1101223.


MRI detection of brain abnormality in sickle cell disease.

Stotesbury H, Kawadler J, Saunders D, Kirkham F Expert Rev Hematol. 2021; 14(5):473-491.

PMID: 33612034 PMC: 8315209. DOI: 10.1080/17474086.2021.1893687.


Functional Connectivity Decreases with Metabolic Stress in Sickle Cell Disease.

Fields M, Mirro A, Guilliams K, Binkley M, Gil Diaz L, Tan J Ann Neurol. 2020; 88(5):995-1008.

PMID: 32869335 PMC: 7592195. DOI: 10.1002/ana.25891.


References
1.
Vayo M, Lipowsky H, Karp N, Schmalzer E, Chein S . A model of microvascular oxygen transport in sickle cell disease. Microvasc Res. 1985; 30(2):195-206. DOI: 10.1016/0026-2862(85)90050-0. View

2.
Tzarouchi L, Astrakas L, Zikou A, Xydis V, Kosta P, Andronikou S . Periventricular leukomalacia in preterm children: assessment of grey and white matter and cerebrospinal fluid changes by MRI. Pediatr Radiol. 2009; 39(12):1327-32. DOI: 10.1007/s00247-009-1389-0. View

3.
Hyder F, Shulman R, Rothman D . A model for the regulation of cerebral oxygen delivery. J Appl Physiol (1985). 1998; 85(2):554-64. DOI: 10.1152/jappl.1998.85.2.554. View

4.
Evans A . The NIH MRI study of normal brain development. Neuroimage. 2005; 30(1):184-202. DOI: 10.1016/j.neuroimage.2005.09.068. View

5.
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N . Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002; 15(1):273-89. DOI: 10.1006/nimg.2001.0978. View