Aim: The purpose of this study is to classify the malformations of cortical development in children according to the embryological formation, localization, and neurodevelopmental findings. Seizure/epilepsy and electrophysiological findings have also been compared.

Material And Methods: Seventy-five children (age: 1 month-16.5 years; 56% male) followed with the diagnosis of malformation of cortical development, in Marmara University Pendik Research and Educational Hospital Department of Pediatric Neurology, were included in the study. Their epilepsy characteristics, electroencephalogram (EEG) findings, and prognosis were reported. Neurodevelopmental characteristics were evaluated by the Bayley Scales of Infant and Toddler Development (Bayley-III) for the ages of 0-42 months ( = 30); the Denver Developmental Screening Test-II (DDST-II) for ages 42 months-6 years ( = 11); and the Wechsler Intelligence Scales for Children (WISC-R), used for children 6 years and older ( = 34).

Results: The patients were classified as 44% premigrational (14.6% microcephaly, 24% tuberous sclerosis, 2.7% focal cortical dysplasia, 1.3% hemimegalencephaly, and 1.3% diffuse cortical dysgenesis); 17.3% migrational (14.6% lissencephaly, 2.7% heterotopia); and 38.6% postmigrational (14.6% schizencephaly, 24% polymicrogyria) developmentally. According to involved area, the classification was 34.7% hemispheric/multilobar, 33.3% diffuse, and 32% focal. Seventy-five percent of the patients had a history of epilepsy, and 92% were resistant to treatment. The seizures started before the age of 12 months in diffuse malformations, and epileptic encephalopathy was more common in microcephaly with a rate of 80% and lissencephaly with a rate of 54.5% in the first EEGs. Ninety-five percent of patients had at least one level of neurodevelopmental delay detected by DDST/Bayley-III; this was more common in patients with accompanying epilepsy ( < .05). As seen more commonly in patients with diffuse pathologies and intractable frequent seizures, mental retardation was detected by WISC-R in 64.5% of patients ( < .05).

Conclusion: In cases with cortical developmental malformation, epilepsy/EEG features and neurodevelopmental prognosis can be predicted depending on the developmental process and type and extent of involvement. Patients should be followed up closely with EEG.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8655965PMC
http://dx.doi.org/10.5152/TurkArchPediatr.2021.20148DOI Listing

Publication Analysis

Top Keywords

cortical development
12
neurodevelopmental findings
8
malformations cortical
8
percent patients
8
patients
7
cortical
6
neurodevelopmental
5
epilepsy
4
findings epilepsy
4
epilepsy malformations
4

Similar Publications

The link of FOXO1 and FOXO4 transcription factors to development of the lens.

Dev Dyn

January 2025

Department of Pathology and Genomic Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Background: The FOXOs regulate the transcription of many genes, including ones directly linked to pathways required for lens development. However, this transcription factor family has rarely been studied in the context of development, including the development of the lens. FOXO expression, regulation, and function during lens development remained unexplored.

View Article and Find Full Text PDF

Background: Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental outcome among children with a history of early institutional care. Prior research on institutionalized children suggested that accelerated physical growth in childhood is a risk factor for ADHD outcomes.

Methods: The current study examined physical and neurophysiological growth trajectories among institutionalized children randomized to foster care treatment (n = 59) or care as usual (n = 54), and never institutionalized children (n = 64) enrolled in the Bucharest Early Intervention Project (NCT00747396, clinicaltrials.

View Article and Find Full Text PDF

Kenny-Caffey Syndrome Type 2 (KCS2): A New Case Report and Patient Follow-Up Optimization.

J Clin Med

December 2024

Division of Endocrinology, Diabetes and Metabolism, ENDO-ERN Center for Rare Pediatric Endocrine Disorders, First Department of Pediatrics, Medical School, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, 11527 Athens, Greece.

Kenny-Caffey syndrome 2 (KCS2) is a rare cause of hypoparathyroidism, inherited in an autosomal dominant mode, resulting from pathogenic variants of the gene, which is implicated in intracellular pathways regulating parathormone (PTH) synthesis and skeletal and parathyroid gland development. : The case of a boy is reported, presenting with the characteristic and newly identified clinical, biochemical, radiological, and genetic abnormalities of KCS2. : The proband had noticeable dysmorphic features, and the closure of the anterior fontanel was delayed until the age of 4 years.

View Article and Find Full Text PDF

Investigating the physiological mechanisms in the motor cortex during rehabilitation exercises is crucial for assessing stroke patients' progress. This study developed a single-channel Jansen neural mass model to explore the relationship between model parameters and motor cortex mechanisms. Firstly, EEG signals were recorded from 11 healthy participants under 20%, 40%, and 60% maximum voluntary contraction, and alpha rhythm power spectral density characteristics were extracted using the Welch power spectrum method.

View Article and Find Full Text PDF

The Three-Class Annotation Method Improves the AI Detection of Early-Stage Osteosarcoma on Plain Radiographs: A Novel Approach for Rare Cancer Diagnosis.

Cancers (Basel)

December 2024

Science of Functional Recovery and Reconstruction, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8558, Japan.

: Developing high-performance artificial intelligence (AI) models for rare diseases is challenging owing to limited data availability. This study aimed to evaluate whether a novel three-class annotation method for preparing training data could enhance AI model performance in detecting osteosarcoma on plain radiographs compared to conventional single-class annotation. : We developed two annotation methods for the same dataset of 468 osteosarcoma X-rays and 378 normal radiographs: a conventional single-class annotation (1C model) and a novel three-class annotation method (3C model) that separately labeled intramedullary, cortical, and extramedullary tumor components.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!