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- Title
SROVNÁNÍ MR SKÓROVACÍCH SYSTÉMŮ V PREDIKCI NEUROLOGICKÉHO VÝVOJE NOVOROZENCE S HYPOXICKO-ISCHEMICKOU ENCEFALOPATIÍ SROVNÁNÍ MR SKÓROVACÍCH SYSTÉMŮ V PREDIKCI NEUROLOGICKÉHO VÝVOJE NOVOROZENCE S HYPOXICKO-ISCHEMICKOU ENCEFALOPATIÍ
- Authors
Zbrožková, Lenka Bakaj; Hálek, Jan; Michálková, Kamila; Langová, Kateřina; Heřman, Miroslav
- Abstract
Aims: 1. To evaluate and classify the brain MRI findings in neonates with hypoxic-ischemic encephalopathy who underwent therapeutic hypothermia using accessible MRI scoring systems. 2. To determine which scoring system is the best in prediciton of death or severe disability at the age of 18 months. Method: The brain MRI using standard sequences (T1, T2, T1 TIRR, DWI and ADC) was performed in 32 term neonates. The findings were classified by 5 different MRI scoring systems (Barkovich et al., Jyoti et al., Rutherford et al., Shankaran et al. and Rollins et al.) found in the electronic PudMed (Public/Publisher MEDLINE) database. The neurological outcome was evaluated according to the Czech Neonatal Society classification for monitoring of late neonatal morbidity at the age of 18th months. The degree of agreement of each MRI scoring system with neurological outcome at the age of 18th months was statistically analysed. Results: The pathological findings on brain MRI were present in 78.1%. The most common findings were changes of deep gray matter (thalami in 56.2%, basal ganglia in 40.6%) folloved by cortical and subcortical lesions (43.8%). Correlations between MRI scoring systems and neurological outcome were in all cases statistically significant. The strongest relationship was to Jyoti's scoring system (p < 0.0001). Conclusion: Brain MRI performed after the therapeutic hypothermia completition in neonates with hypoxic-ischemic encephalopathy is able to predict their neurological outcome. The best MRI scoring system in prediction of death or severe disability in children at the age of 18th months is Jyoti's scoring system.
- Publication
Czech Radiology / Ceska Radiologie, 2017, Vol 71, Issue 1, p56
- ISSN
1210-7883
- Publication type
Article