Brain susceptibility changes in neurologically asymptomatic pediatric patients with Wilson's disease: evaluation with quantitative susceptibility mapping.
Sibel SaracogluKazim Ziya GumusSelim DoganayGonca KocAyse Kacar BayramDuran ArslanHakan GumusPublished in: Acta radiologica (Stockholm, Sweden : 1987) (2018)
Background Wilson's disease (WD) is a copper metabolism disorder that causes hepatolenticular degeneration. It is important to diagnose WD before central nervous system involvement. Purpose To demonstrate the early susceptibility changes associated with the copper accumulation in the brain of neurologically asymptomatic pediatric patients with WD using quantitative susceptibility mapping (QSM). Material and Methods Twelve patients with neurologically asymptomatic WD (mean age = 13.7 ± 3.3 years) and 14 age-matched controls were prospectively examined using a 1.5-T clinical scanner. Routine magnetic resonance (MR) sequences and a three-dimensional multi-echo spoiled gradient echo (GRE) sequence were used and QSM maps were reproduced. The quantitative susceptibility of corpus striatum, thalamus, substantia nigra, and pons were analyzed with the region of interest analysis on QSM maps. The susceptibility values of two groups were statistically compared using a two-sample t-test. Results Conventional MR images of the patients and control group were similar. However increased magnetic susceptibility in the thalamus, pons and left posterior putamen were observed in the patients compared to the control group ( p < 0.05). Conclusion We observed statistically increased susceptibility values in the brains of neurologically asymptomatic patients with WD although the conventional MR images were normal. This might be compatible with early brain impairment, before neurological symptoms occur.
Keyphrases
- magnetic resonance
- end stage renal disease
- high resolution
- chronic kidney disease
- ejection fraction
- peritoneal dialysis
- resting state
- deep learning
- prognostic factors
- computed tomography
- magnetic resonance imaging
- depressive symptoms
- convolutional neural network
- functional connectivity
- clinical practice
- mass spectrometry
- physical activity
- machine learning
- young adults
- diffusion weighted imaging
- cerebrospinal fluid
- molecularly imprinted