Diagnostic features of pediatric testicular yolk sac tumors: a 13-year retrospective analysis.

Background: Testicular yolk sac tumor (YST) is a rare neoplasm with limited practical guidance for preoperative diagnostic assessment. This study aims to conduct a retrospective analysis of the value of clinical profiles and MRI parameters in accurately diagnosing pediatric testicular YST while exploring characteristic indicators for these patients.

Methods: This retrospective study analyzed eighty patients with a testicular mass who underwent surgical treatment and preoperative MRI.

RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping.

Cardiac T1 mapping can evaluate various clinical symptoms of myocardial tissue. However, there is currently a lack of effective, robust, and efficient methods for motion correction in cardiac T1 mapping. In this paper, we propose a deep learning-based and topology-preserving image registration framework for motion correction in cardiac T1 mapping.

Trends in brain MRI and CP association using deep learning.

Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative body movements of children, potential infant recovery, a lack of a single vision modality, and no specific contrast or slice-range selection and association.

Pediatric mediastinal lymphatic malformation: misdiagnosis analysis and literature review.

Objectives: Mediastinal cystic lymphatic malformation (MCLM) in children is prone to misdiagnosis as cystic teratoma. We compared the clinical and radiologic features between the two diseases and performed a cross-comparison with previous research on adult cases. This study aims to identify characteristic pediatric manifestations to improve diagnostic accuracy.

Development and Validation of a Clinical Nomogram for Predicting Complications From Pediatric Multiple Magnet Ingestion: A Large Retrospective Study.

Introduction: This study aimed to develop and validate a reliable nomogram based on clinical factors to predict complications associated with pediatric multiple magnet ingestion, addressing the urgency and controversy surrounding its management.

Methods: Patients aged 0-18 years with multiple magnet ingestion diagnosed at the Shenzhen Children's Hospital between January 2017 and December 2023 were enrolled. Clinical data were analyzed using least absolute shrinkage and selection operator regression and multifactor logistic regression analyses to screen for risk factors.

Static and dynamic changes in amplitude of Low-Frequency fluctuations in patients with Self-Limited epilepsy with centrotemporal Spikes (SeLECTS): A Resting-State fMRI study.

Objective: This study aims to explore differences in the static and dynamic amplitude of low-frequency fluctuations (sALFF and dALFF) in resting-state functional MRI (rs-fMRI) data between patients with Benign childhood epilepsy with centrotemporal spikes (SeLECTS) and healthy controls (HCs).

Materials And Methods: We recruited 45 patient with SeLECTS and 55 HCs, employing rs-fMRI to assess brain activity. The analysis utilized a two-sample t-test for primary comparisons, supplemented by stratification and matching based on clinical and demographic characteristics to ensure comparability between groups.

Synthesizing PET images from high-field and ultra-high-field MR images using joint diffusion attention model.

Background: Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) stand as pivotal diagnostic tools for brain disorders, offering the potential for mutually enriching disease diagnostic perspectives. However, the costs associated with PET scans and the inherent radioactivity have limited the widespread application of PET. Furthermore, it is noteworthy to highlight the promising potential of high-field and ultra-high-field neuroimaging in cognitive neuroscience research and clinical practice.

Corrigendum to "Default mode network connectivity and social dysfunction in children with attention deficit/hyperactivity disorder" [Int. J. Clin. Health Psychol. 23 (4) (2023) 100393].

[This corrects the article DOI: 10.1016/j.ijchp.

DPP: deep phase prior for parallel imaging with wave encoding.

In Magnetic Resonance (MR) parallel imaging with virtual channel-expanded Wave encoding, limitations are imposed on the ability to comprehensively and accurately characterize the background phase. These limitations are primarily attributed to the calibration process relying solely on center low-frequency Auto-Calibration Signals (ACS) data for calibration.To tackle the challenge of accurately estimating the background phase in wave encoding, a novel deep neural network model guided by deep phase priors is proposed with integrated virtual conjugate coil (VCC) extension.

Anti-synthetase syndrome in a child with pneumomediastinum: a case report and literature review.

Background: Anti-synthetase syndrome (ASS) is a group of rare clinical subtypes within inflammatory myopathies, predominantly affecting adult females. Instances of critical illness associated with ASS in children are even rarer.

Case Presentation: We report the case of a 7-year-old boy finally diagnosed with ASS, combined with pneumomediastinum.

Deep learning-based automated lesion segmentation on pediatric focal cortical dysplasia II preoperative MRI: a reliable approach.

Objectives: Focal cortical dysplasia (FCD) represents one of the most common causes of refractory epilepsy in children. Deep learning demonstrates great power in tissue discrimination by analyzing MRI data. A prediction model was built and verified using 3D full-resolution nnU-Net for automatic lesion detection and segmentation of children with FCD II.

To explore the potential mechanisms of cognitive impairment in children with MRI-negative pharmacoresistant epilepsy due to focal cortical dysplasia: A pilot study from gray matter structure view.

Objectives: To investigate the characteristics of brain structure in children with focal cortical dysplasia (FCD)-induced pharmacoresistant epilepsy, and explore the potential mechanisms of cognitive impairment from the view of gray matter alteration.

Methods: 25 pharmacoresistant pediatric patients with pathologically confirmed focal cortical dysplasia (FCD), and 25 gender-matched healthy controls were included in this study. 3.

A Potential Mechanism of Neurological Impairment in Children With Infantile Spasm: Based on Microanatomic Structure Analysis Employing Voxel-Based Morphometry and Surface-Based Morphometry.

Background: Infantile epileptic spasms syndrome (IESS) would accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microwould accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microanatomic structure alteration.

PEARL: Cascaded Self-supervised Cross-fusion Learning For Parallel MRI Acceleration.

Supervised deep learning (SDL) methodology holds promise for accelerated magnetic resonance imaging (AMRI) but is hampered by the reliance on extensive training data. Some self-supervised frameworks, such as deep image prior (DIP), have emerged, eliminating the explicit training procedure but often struggling to remove noise and artifacts under significant degradation. This work introduces a novel self-supervised accelerated parallel MRI approach called PEARL, leveraging a multiple-stream joint deep decoder with two cross-fusion schemes to accurately reconstruct one or more target images from compressively sampled k-space.

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.

Background And Purpose: Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatric patients to have positive outcomes. The purpose of this study was to predict the effectiveness of antiseizure medication treatment in children with tuberous sclerosis complex-related epilepsy.

Materials And Methods: We conducted a retrospective study involving 300 children with tuberous sclerosis complex-related epilepsy.

[Clinical and imaging analysis of neurological complications in critically ill children infected with SARS-CoV-2 Omicron].

Objective: To summarize clinical predictors and imaging characteristics of critically ill children infected with SARS-CoV-2 Omicron with neurological complications in Shenzhen during the peak of the first round of infections.

Methods: The clinical data of 11 critically ill children with neurological complications infected with SARS-CoV-2 Omicron in Shenzhen Children's Hospital from December 12 to 31, 2022, were retrospectively collected and analyzed. Laboratory test results related to liver parenchymal injury, histiocytic injury, inflammation, and coagulation function were collected, and imaging characteristics including CT and/or magnetic resonance imaging (MRI) were analyzed.

A novel MRI feature, the cut green pepper sign, can help differentiate a suprasellar pilocytic astrocytoma from an adamantinomatous craniopharyngioma.

Objective: There are no specific magnetic resonance imaging (MRI) features that distinguish pilocytic astrocytoma (PA) from adamantinomatous craniopharyngioma (ACP). In this study we compared the frequency of a novel enhancement characteristic on MRI (called the cut green pepper sign) in PA and ACP.

Methods: Consecutive patients with PA (n = 24) and ACP (n = 36) in the suprasellar region were included in the analysis.

Default mode network connectivity and social dysfunction in children with Attention Deficit/Hyperactivity Disorder.

Objective: Attention Deficit/Hyperactivity Disorder (ADHD) negatively affects social functioning; however, its neurological underpinnings remain unclear. Altered Default Mode Network (DMN) connectivity may contribute to social dysfunction in ADHD. We investigated whether DMN's dynamic functional connectivity (dFC) alterations were associated with social dysfunction in individuals with ADHD.

Activation Map Reveals Language Impairment in Children with Benign Epilepsy with Centrotemporal Spikes (BECTS).

Objective: Neuropsychological evidence revealed language impairment in children with benign epilepsy with centrotemporal spikes (BECTS). This study investigates language function using task-activated fMRI.

Methods: We conducted a language task fMRI study on three groups on a 3.

Multiparametric MRI-Based Radiomics Signature with Machine Learning for Preoperative Prediction of Prognosis Stratification in Pediatric Medulloblastoma.

Rationale And Objectives: Despite advances in risk-stratified treatment strategies for children with medulloblastoma (MB), the prognosis for MB with short-term recurrence is extremely poor, and there is still a lack of evaluation of short-term recurrence risk or short-term survival. This study aimed to construct and validate a radiomics model for predicting the outcome of MB based on preoperative multiparametric magnetic resonance images (MRIs) and to provide an objective for clinical decision-making.

Materials And Methods: The clinical and imaging data of 64 patients with MB admitted to Shenzhen Children's Hospital from December 2012 to December 2021 and confirmed by pathology were retrospectively collected.

Effects of the SNAP-25 Mnll variant on hippocampal functional connectivity in children with attention deficit/hyperactivity disorder.

Objectives: Attention-deficit/hyperactivity disorder (ADHD) is one of the most widespread and highly heritable neurodevelopmental disorders affecting children worldwide. Although synaptosomal-associated protein 25 (SNAP-25) is a possible gene hypothesized to be associated with working memory deficits in ADHD, little is known about its specific impact on the hippocampus. The goal of the current study was to determine how variations in ADHD's SNAP-25 Mnll polymorphism (rs3746544) affect hippocampal functional connectivity (FC).