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Distinguishing tumours from other conditions is a primary challenge in paediatric neuro-radiology. This paper aims to describe mimics, which are non-neoplastic conditions that have features similar to a neoplastic process caused by a non-neoplastic entity, and chameleons, which are uncommon presentations of brain tumours that are mistaken for other diagnoses. By doing so, we aim to raise awareness of these conditions and prevent inappropriate investigations or treatment in children. When suspecting a brain tumour, a detailed history, physical examination, and appropriate laboratory investigations can provide important clues about the nature of the lesion and narrow the list of possible differential diagnoses. Presented here is a collection of cases that have puzzled us for various reasons, including the absence of symptoms, coincidental timing, or misleading radiological features. Included in this pictorial essay are cases in which only a biopsy has helped us to make the correct diagnosis, as well as cases in which an unsuccessful biopsy has allowed us to evaluate hypotheses that were previously unaddressed. The paper also highlights the limited knowledge we have about the intercausality between malformations and later onset tumours, and the spectrum of manifestations that metabolic and genetic disorders can have., Competing Interests: Declarations. Ethical approval: Not applicable. Informed consent: Not applicable. Conflict of interest: The authors certify that there is no conflict of interest with any financial organisation regarding the material discussed in the manuscript., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Purpose: Neuronal ceroid lipofuscinoses are a group of neurodegenerative disorders. Recently, enzyme replacement therapy (ERT) was approved for neuronal ceroid lipofuscinosis type 2 (CLN2), a subtype of neuronal ceroid lipofuscinoses. The aim of this study was to quantify brain volume loss in CLN2 disease in patients on ERT in comparison with a natural history cohort using MRI., Materials and Methods: Nineteen (14 female, 5 male) patients with CLN2 disease at 1 UK center were studied using serial 3D T1-weighted MRI (follow-up time, 1-9 years). Brain segmentation was performed using FreeSurfer. Volume measurements for supratentorial gray and white matter, deep gray matter (basal ganglia/thalami), the lateral ventricles, and cerebellar gray and white matter were recorded. The volume change with time was analyzed using a linear mixed-effects model excluding scans before treatment onset. Comparison was made with a published natural history cohort of 12 patients (8 female, 4 male), which was re-analyzed using the same method., Results: Brain volume loss of all segmented brain regions was much slower in treated patients compared with the natural history cohort. For example, supratentorial gray matter volume in treated patients decreased by a mean of 3% (SD, 0.74%) ( P < .001) annually compared with an annual volume loss of a mean of 16.8% (SD, 1.5%) ( P < .001) in the natural history cohort., Conclusions: Our treatment cohort showed a significantly slower rate of brain parenchymal volume loss compared with a natural history cohort in several anatomic regions. Our results complement prior clinical data that found a positive response to ERT. We demonstrate that automated MRI volumetry is a sensitive tool to monitor treatment response in children with CLN2 disease., (© 2024 by American Journal of Neuroradiology.)

Background: Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking., Methods: The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG., Results: The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient., Conclusions: The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Purpose: Duplication of the pituitary gland is a rare developmental anomaly. Multiple associated craniofacial malformations have previously been reported with the largest series to date consisting of five patients. In this multi-institutional series of ten patients, we present a detailed review of the imaging features and discuss a possible overarching pathogenesis that would explain most of the detected malformations., Materials and Methods: Inclusion criteria for this retrospective imaging review were the presence of a pituitary stalk and gland duplication and the characteristic appearance of the hypothalamic ventral midline. In addition to the clinical presentation, we recorded the imaging findings of ten patients (9 female) through onsite and online reviews. Genetic analysis was available for six patients., Results: The duplicated pituitary stalk and gland showed normal imaging appearances in all patients. Mammillary bodies were clearly identified lateral to the characteristic prominence of the hypothalamic ventral midline. Strands of tissue extending to the anterior dura ("limited ventral myeloschisis") were noted at the medulla oblongata in 10, and at the cervical spinal cord in 7 patients. The medulla oblongata showed a "butterfly" appearance on axial images in 9 patients. Ten patients had cervical segmentation anomalies ("zipper"-like), 9 anterior-posterior brainstem patterning defects (small pons, elongated medulla), and corpus callosum measurements were abnormal in all patients. Three patients each presented with diencephalic-mesencephalic junction abnormalities and 4 with an anterior mesencephalic "cap". An oropharyngeal teratoma was present in four patients. Genetics was normal in three of the six patients studied; the remainder were found to have mutations in EFNB1 and a gene variant of GIT1 , two copies of 7. And 8. exon of SMN1 gene, and 2.126 megabase duplication at bands q11.1 and q11.2 of one chromosome 15, respectively., Conclusions: Duplication of the pituitary gland presents as well-defined craniofacial and cervical spine malformation phenotype. Axial mesoderm duplication generating an excess of Sonic Hedgehog may be the primary embryological driver leading to this condition., Abbreviations: CFNS＝ Craniofrontonasal Syndrome; DPG＝ Duplication of the Pituitary Gland; SHH＝ Sonic Hedgehog., Competing Interests: The authors have no conflicts of interest to disclose regarding the subject of this article., (© 2024 by American Journal of Neuroradiology.)

Purpose: Normative ADC values of the pineal gland in young children are currently lacking, however, these are potentially useful in the differential diagnosis of pineal involvement in trilateral retinoblastoma, which is challenging when the size of the tumor is less than 10-15 mm. The main objective of this study was to establish ADC reference values of the normal pineal gland in a large cohort of children between 0 and 4 years., Methods: This retrospective study was conducted in a tertiary pediatric hospital. We collected 64 patients with normal MRI examination (between 2017 and 2024) and clinical indication unrelated to the pineal gland, and divided them into 5 age groups (0 to 4 years). Gland size and mean ADC values were calculated, using the ellipsoid formula and ROI/histogram analysis, respectively. The established values were tested in three cases of trilateral retinoblastoma (10 to 20 months)., Results: Mean ADC values were always above 1000 × 10 - 6 mm 2 /s, while in patients with trilateral retinoblastoma they were around 800 × 10 - 6 mm 2 /s. Pineal ADC values were identical in both genders. The volume of the pineal gland showed a tendency to increase with age., Conclusions: We present ADC reference data for the pineal gland in children under 4 years of age. The distribution of mean ADC values of trilateral retinoblastoma was significantly different from the normative values, hence, the use DWI/ADC may help to identify small trilateral retinoblastoma in children with ocular pathology., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Purpose: Sotos syndrome is a rare autosomal dominant condition caused by pathogenic mutations in the NSD1 gene that presents with craniofacial dysmorphism, overgrowth, seizures, and neurodevelopmental delay. Macrocephaly, ventriculomegaly, and corpus callosal dysmorphism are typical neuroimaging features that have been described in the medical literature. The purpose of this study was to expand on the neuroimaging phenotype by detailed analysis of a large cohort of patients with genetically proved Sotos syndrome., Materials and Methods: This multicenter, multinational, retrospective observational cohort study systematically analyzed the clinical characteristics and neuroimaging features of 77 individuals with genetically diagnosed Sotos syndrome, via central consensus review with 3 pediatric neuroradiologists., Results: In addition to previously described features, malformations of cortical development were identified in most patients (95.0%), typically dysgyria (92.2%) and polymicrogyria (22.1%), varying in location and distribution. Incomplete rotation of the hippocampus was observed in 50.6% of patients and was associated with other imaging findings, in particular with dysgyria (100% versus 84.2%, P  = .012)., Conclusions: Our findings show a link between the genetic-biochemical basis and the neuroimaging features and aid in better understanding the underlying clinical manifestations and possible treatment options. These findings have yet to be described to this extent and correspond with recent studies that show that NSD1 participates in brain development and has interactions with other known relevant genetic pathways., (© 2024 by American Journal of Neuroradiology.)

Background and Objective: Epilepsy affects approximately 50 million people worldwide, with 30-40% of patients not responding to medication, necessitating alternative therapies such as surgical intervention. However, the accurate localization of epileptogenic lesions, particularly in pediatric magnetic resonance imaging (MRI)-negative drug-resistant epilepsy, remains a challenge. This paper reviews advanced neuroimaging techniques aimed at improving the detection of such lesions to enhance surgical outcomes., Methods: A comprehensive literature search was conducted using PubMed, focusing on advanced MRI sequences, focal epilepsy, and the integration of artificial intelligence (AI) in the diagnostic process., Key Content and Findings: New MRI sequences, including magnetization prepared 2 rapid gradient echo (MP2RAGE), edge-enhancing gradient echo (EDGE), and fluid and white matter suppression (FLAWS), have demonstrated enhanced capabilities in detecting subtle epileptogenic lesions. Quantitative MRI techniques, notably magnetic resonance fingerprinting (MRF), alongside innovative post-processing methods, are emphasized for their effectiveness in delineating cortical malformations, whether used alone or in combination with ultra-high field MRI systems. Furthermore, the integration of AI in radiology is progressing, providing significant support in accurately localizing lesions, and potentially optimizing pre-surgical planning., Conclusions: While advanced neuroimaging and AI offer significant improvements in the diagnostic process for epilepsy, some challenges remain. These include long acquisition times, the need for extensive data analysis, and a lack of large, standardized datasets for AI validation. However, the future holds promise as research continues to integrate these technologies into clinical practice. These efforts will improve the clinical applicability and effectiveness of these advanced techniques in epilepsy management, paving the way for more accurate diagnoses and better patient outcomes., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-24-166/coif). F.D.A. serves as an unpaid editorial board member of Translational Pediatrics from March 2024 to February 2026. The other authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

The differential diagnosis of supratentorial brain tumours in children can be challenging, especially considering the recent changes to the WHO classification of CNS tumours published in 2021. Many new tumour types have been proposed which frequently present in children and young adults and their imaging features are currently being described by the neuroradiology community. The purpose of this article is to provide guidance to residents and fellows new to the field of paediatric neuroradiology on how to evaluate an MRI of a patient with a newly diagnosed supratentorial tumour. Six different approaches are discussed including: 1. Tumour types, briefly discussing the main changes to the recent WHO classification of CNS tumours, 2. Patient age and its influence on incidence rates of specific tumour types, 3. Growth patterns, 4. Tumour location and how defining the correct location helps in narrowing down the differential diagnoses and 5. Imaging features of the tumour on DWI, SWI, FLAIR and post contrast sequences., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Cortically-based brain tumors in children constitute a unique set of tumors with variably aggressive biological behavior. As radiologists play an integral role on the multidisciplinary medical team, a clinically useful and easy-to-follow flowchart for the differential diagnoses of these complex brain tumors is essential.This proposed algorithm tree provides the latest insights into the typical imaging characteristics and epidemiologic data that differentiate the tumor entities, taking into perspective the 2021 World Health Organization's classification and highlighting classic as well as newly identified pathologic subtypes using current molecular understanding.ABBREVIATIONS: Astroblastoma=AB) Angiocentric glioma (AG) Atypical teratoid rhabdoid tumor (ATRT) Central Nervous System tumor (CNS) CNS neuroblastoma FOXR2-activated (NB-FOXR2) Desmoplastic infantile glioma/astrocytoma (DIG/DIA) Diffuse hemispheric glioma, H3 G34-mutant (DHG) Diffuse glioneuronal tumor with oligodendroglioma-like features and nuclear clusters (DGONC) Dysembryoplastic neuroepithelial tumor (DNET) Embryonal Tumors with Multilayered Rosettes (ETMR) Ependymoma (EP) Focal cortical dysplasia (FCD) Ganglioglioma/gangliocytoma (GG) Infant-type hemispheric glioma (IHG) Intracranial pressure (ICP) Long-term epilepsy-associated tumors (LEATs) Pediatric diffuse low-grade gliomas (pLGG) MR spectroscopy (MRS) Multinodular and vacuolating neuronal tumor (MVNT) Overall survival (OS) Pediatric diffuse high-grade gliomas (pHGG)., Competing Interests: The authors declare no conflicts of interest related to the content of this article., (© 2024 by American Journal of Neuroradiology.)