Epilepsy in Pediatric Patients-Evaluation of Brain Structures' Volume Using VolBrain Software.
Magdalena Maria WoźniakMonika ZbrojaMałgorzata MatuszekOlga PustelniakWeronika CyrankaKatarzyna DrelichEwa KopytoAndrzej MaterniakTomasz SłomkaMaciej CebulaAgnieszka BrodziszPublished in: Journal of clinical medicine (2022)
Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures-GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.
Keyphrases
- white matter
- resting state
- magnetic resonance imaging
- end stage renal disease
- cerebral ischemia
- ejection fraction
- high resolution
- magnetic resonance
- randomized controlled trial
- newly diagnosed
- chronic kidney disease
- systematic review
- deep learning
- peritoneal dialysis
- healthcare
- multiple sclerosis
- venous thromboembolism
- heart failure
- risk assessment
- brain injury
- pulmonary artery
- data analysis
- minimally invasive
- mass spectrometry
- subarachnoid hemorrhage
- coronary artery
- artificial intelligence
- pulmonary arterial hypertension
- big data
- human health
- clinical evaluation