Artificial Intelligence and Deep Learning in Revolutionizing Brain Tumor Diagnosis and Treatment: A Narrative Review.

The emergence of artificial intelligence (AI) in the medical field holds promise in improving medical management, particularly in personalized strategies for the diagnosis and treatment of brain tumors. However, integrating AI into clinical practice has proven to be a challenge. Deep learning (DL) is very convenient for extracting relevant information from large amounts of data that has increased in medical history and imaging records, which shortens diagnosis time, that would otherwise overwhelm manual methods. In addition, DL aids in automated tumor segmentation, classification, and diagnosis. DL models such as the Brain Tumor Classification Model and the Inception-Resnet V2, or hybrid techniques that enhance these functions and combine DL networks with support vector machine and k-nearest neighbors, identify tumor phenotypes and brain metastases, allowing real-time decision-making and enhancing preoperative planning. AI algorithms and DL development facilitate radiological diagnostics such as computed tomography, positron emission tomography scans, and magnetic resonance imaging (MRI) by integrating two-dimensional and three-dimensional MRI using DenseNet and 3D convolutional neural network architectures, which enable precise tumor delineation. DL offers benefits in neuro-interventional procedures, and the shift toward computer-assisted interventions acknowledges the need for more accurate and efficient image analysis methods. Further research is needed to realize the potential impact of DL in improving these outcomes.

Intracranial vein of Galen malformation and its management: A case report.

Vein of Galen malformation (VOGM) is a rare congenital arteriovenous malformation affecting the pediatric population, characterized by a fistula between the diencephalon and a dilated vein of Galen. The present study reports the case of a 6-month-old male infant referred for developmental delays and abnormal head circumference. A clinical examination revealed macrocephaly, dilated scalp veins and neurological abnormalities. Neuroimaging confirmed a large VOGM with associated hydrocephalus. A multidisciplinary team devised a treatment plan involving endovascular embolization and ventriculoperitoneal shunt placement. The post-operative recovery exhibited an improvement in neurodevelopmental milestones and a reduced head circumference. Generally, the management of VOGM requires a comprehensive approach, including early diagnosis, precise imaging and timely intervention. The case described herein highlights the importance of interventional radiology in planning a management plan and the novel kissing microcatheter endovascular embolization technique.