Ji Hoon Phi

Dysembryoplastic neuroepithelial tumor (DNET) is a benign, pediatric brain tumor characterized by focal seizures, often progressing to drug-resistant epilepsy. Satellite lesions (SLs), small lesions adjacent to the main tumor mass typically embedded within normal parenchyma, are identified in approximately 50% of DNET cases and may contribute to recurrent seizures if not totally removed. However, detailed histopathological descriptions of SL remain limited to date. We report on an 8-year-old boy with medically intractable seizures and a T2 hyperintense mass in the left frontal lobe with smaller deep-seated SLs. The lesions were near totally removed, with deep-seated SLs successfully removed by performing a wider resection including the adjacent normal white matter with the aid of intraoperative ultrasonography, rather than through direct visual inspection. Histological analysis of deep-seated SLs showed homogeneous, typical DNET features identical to the main mass, including glioneuronal columns with oligodendrocyte-like cells and floating neurons within a mucoid matrix, confirming that deep-seated SLs are true tumors. In order to reduce the risk of recurrence, maximal safe resection of deep-seated SLs with the aid of ultrasonography might be helpful.

BACKGROUND: Focal cerebral arteriopathy-inflammatory type (FCA-i) is a leading cause of pediatric arterial ischemic stroke, but diagnostic challenges persist, particularly in East Asian populations where moyamoya disease (MMD) prevalence is high. The focal cerebral arteriopathy severity score quantifies arteriopathy severity but has not been validated in East Asian cohorts. We aimed to validate the focal cerebral arteriopathy severity score in Korean pediatric patients with FCA-i and compare temporal progression patterns with unilateral MMD. METHODS: We conducted a retrospective cohort study of children with arterial ischemic stroke presenting to Seoul National University Hospital between January 2002 and December 2024. Patients were classified according to the Childhood Arterial Ischemic Stroke Standardized Classification and Diagnostic Evaluation criteria. The focal cerebral arteriopathy severity score was applied to serial magnetic resonance angiograms at baseline, peak severity, and final follow-up. RESULTS: Among 216 children with arterial ischemic stroke, 132 patients (61.1%) demonstrated arteriopathy, including 49 with FCA-i (median age, 8.6 [interquartile range (IQR), 6.4–11.3] years; 55% male), 60 with MMD (median age, 5.7 [IQR, 3.1–9.2] years; 43% male), and 13 with arterial dissection (median age, 7.0 [IQR, 3.1–10.4] years; 62% male). In FCA-i patients, the severity score correlated significantly with baseline infarct burden (ρ=0.42; P =0.0069) and exhibited characteristic monophasic evolution with early peak at 2 months followed by gradual recovery reaching lowest values at 11 months. Patients with unilateral MMD demonstrated consistently higher severity scores at all timepoints compared with FCA-i (baseline: 6.0 versus 2.0; final: 8.0 versus 3.0; P <0.001) without radiographic recovery. A baseline severity score ≥8.0 predicted contralateral progression in unilateral MMD with an area under the curve of 0.962 (sensitivity, 0.83; specificity, 0.91). CONCLUSIONS: The focal cerebral arteriopathy severity score demonstrates validity as a dynamic biomarker for monitoring FCA-i in Korean pediatric patients, exhibiting characteristic monophasic recovery patterns that distinguish it from progressive unilateral MMD.

Severe preterm intraventricular hemorrhage (IVH) with post-hemorrhagic ventricular dilatation (PHVD) may be difficult to manage when the clot burden is extensive and complete endoscopic evacuation is limited by clinical instability and rigid-scope constraints. We describe a staged clearance strategy in a preterm infant with bilateral grade IV IVH and progressive PHVD. Bilateral external ventricular drains (EVDs) were inserted for cerebrospinal fluid diversion. Low-dose intraventricular recombinant tissue plasminogen activator (0.1-0.3 mg per ventricle) was started 48 hours later and repeated every 48 hours for four sessions with a 2-hour dwell time under serial bedside cranial ultrasonographic surveillance. Sequential rigid neuroendoscopic lavage (NEL) was then performed, followed by 7 days of continuous ventricular irrigation using a bilateral inflow-outflow EVD configuration and a buffered glucose-containing artificial cerebrospinal fluid solution. No interval rebleeding, sustained intracranial hypertension, electrolyte instability, or culture-proven ventriculitis occurred during treatment. Ventricular size remained stable after drain removal, and no ventriculoperitoneal shunt had been required through the latest outpatient follow-up on postnatal day 157 (HD 151). This report presents a single-case conceptual proof-of-concept and technical feasibility experience for selected severe preterm IVH in a rigid-scope setting, rather than evidence of efficacy.

This Pediatric Issue of the Journal of Korean Neurosurgical Society addresses the digital and robotic transformation of pediatric neurosurgery. It reviews the emerging applications of artificial intelligence and related technologies across diagnosis, monitoring, surgical practice, education, and communication, while also considering the unique scientific and ethical challenges of their use in children. Together, these articles offer a timely perspective on the future of safer, more precise, and more personalized pediatric neurosurgical care.

Neurocritical care relies on continuous assessment of neurological function and physiology under time pressure, yet bedside teams must interpret high-frequency, multimodal data that include hemodynamic waveforms, intracranial pressure (ICP), electroencephalography (EEG), near-infrared spectroscopy, neuroimaging, and electronic health record (EHR) context. Artificial intelligence (AI) and machine learning are increasingly used to fuse these biosignals, reduce interobserver variability, and generate dynamic risk estimates that can support monitoring, early warning, and prognostication. In pediatric and neonatal populations, where developmental physiology and smaller case volumes amplify uncertainty, AI-enabled tools have shown particularly strong performance in selected domains. Examples include prediction of impending intracranial hypertension using features from arterial blood pressure and ICP waveforms, automated EEG trend analysis for neurodevelopmental outcome prediction after perinatal asphyxia, magnetic resonance imagingbased neuroprognostication in neonatal hypoxic-ischemic encephalopathy, and interoperable EHR-based models for mortality and new morbidity risk stratification in the intensive care unit. However, many studies remain retrospective, and generalizability across institutions can be limited by differences in data capture, clinical practice, and outcome definitions. This review summarizes clinically relevant applications of multimodal biosignal analysis in neurocritical care, highlights validation and implementation considerations, and proposes priorities for future pediatric translation, including multisite evaluation, calibration, explainability, and prospective impact studies.

Purpose: To characterize long-term radiological progression after resection of dysembryoplastic neuroepithelial tumors (DNETs) and identify prognostic factors, focusing on satellite lesions (SLs) and extent of resection. Methods: We retrospectively reviewed 84 patients with pathologically confirmed DNETs who underwent surgery at a single institution. Tumor location and satellite lesions (SLs) were assessed on preoperative MRI. Tumor progression-free survival (PFS) was analyzed using Kaplan–Meier analysis with log‑rank tests and Cox regression, and seizure recurrence was compared using Fisher’s exact test. Results: Over a median follow-up of 9.3 years, 24 patients (29%) demonstrated radiological progression. No progression occurred after gross total resection (GTR) (0/43), whereas 24/41 (59%) progressed after non-GTR (10-year PFS, 100% vs. 33.7%). SL-positive tumors showed higher progression than SL-negative tumors (44% vs. 10%) and remained independently associated with progression (hazard ratio [HR], 4.89; 95% CI, 1.57–15.23). Younger age at surgery and central lobe involvement were additional independent predictors. Seizure recurrence was more frequent in patients with radiological progression (67% vs. 20%). Conclusion: GTR provides excellent long‑term tumor control in DNET. When GTR is not achievable, SLs and central lobe involvement—particularly in younger patients—identify a high‑risk subgroup requiring maximal safe resection and close surveillance.

In spatial proteomics, multiplexed immunofluorescence (mIF) enables high‐plex visualization of protein expression in preserved tissue, offering insights into tumor heterogeneity and the microenvironment. While MACSima and PhenoCycler‐Fusion employ distinct strategies, direct comparisons under biologically controlled in vivo conditions remain limited. We applied both platforms to sagittal formalin‐fixed, paraffin‐embedded (FFPE) sections from an orthotopic xenograft mouse model of human medulloblastoma (MB), featuring leptomeningeal seeding (LMS). These longitudinal sections spanning brain and spinal cord allowed simultaneous assessment of areas with distinct cellular architecture. Fifteen‐marker mIF was performed. MACSima utilized MICS technology with MACS iQ View for automated workflows; PhenoCycler‐Fusion used a DNA‐barcoded antibody system and QuPath for open‐ended image processing. Segmentation was evaluated using identical MACSima data. Both platforms enabled high‐plex imaging mIF while preserving tissue morphology. DAPI, Ki‐67, and Actin were consistently detected across both systems. Ki‐67 expression localized to densely packed tumor regions and was also observed in lower‐density areas. Analyzing MACSima data, MACS iQ View detected fewer cells but a higher Ki‐67 positive rate in dense regions; conversely, QuPath detected more cells but with a lower positivity rate. In low‐density areas, both tools yielded similar results. These differences reflect distinct segmentation algorithms and thresholding strategies. This study confirms both platforms support mIF‐based spatial proteomic analysis in complex, heterogeneous tissues. However, analysis tools influence quantification. Therefore, standardization of algorithmic settings and additional validation are crucial for precise data interpretation. This research provides practical insights for platform selection in basic, translational, and clinical applications by directly evaluating staining, image acquisition, and analysis pipelines.