Neuroradiology最新文献

Purpose

Head and neck emergencies in children are frequent cause of visits to the hospital. Imaging plays a critical role in the management of these patients. This review article aims to familiarize radiologists with the common clinical presentations encountered, imaging characteristics of nontraumatic pediatric head and neck emergencies, and improve their ability to recognize associated complications as well as be aware of common mimics.

Methods

We researched our database for commonly encountered nontraumatic head and neck emergencies in children. A literature search was done to compare and complete the list of conditions to be discussed in this review.

Results

The review was organized according to anatomical location of the emergent condition. Relevant anatomy has been discussed along with clinical presentation, imaging characteristics and complications. We have presented common mimics with each set of disorders. Key imaging characteristics have been delineated using radiology images.

Conclusion

Familiarity with the known complications of head and neck emergencies allows the radiologist to actively search for such findings, encourage early institution of appropriate therapy, and improve outcomes.

Introduction: The establishment of diagnostic reference levels (DRLs) is challenge for interventional neuroradiology (INR) due to the complexity and variability of its procedures.

Objective: The main objective of this systematic review is to analyse and compare DRLs in fluoroscopy-guided procedures in INR.

Methods: An observational study reporting DRLs in INR procedures, specifically cerebral arteriography, cerebral aneurysm embolisation, cerebral thrombectomy, embolisation of arteriovenous malformations (AVM), arteriovenous fistulas (AVF), retinoblastoma embolisation, and spinal cord arteriography. Comprehensive literature searches for relevant studies published between 2017 and 2023 were conducted using the Scopus, PubMed, and Web of Science databases.

Results: A total of 303 articles were identified through an extensive literature search, with 159 removed due to duplication. The title and abstract of 144 studies were assessed and excluded if they did not meet the inclusion criteria. Thirty-one out of the 144 articles were selected for a thorough full-text screening. Twenty-one articles were included in the review after the complete text screening.

Conclusion: The different conditions of patients undergoing INR procedures pose a barrier to the standardization of DRLs; nevertheless, they are extremely important for monitoring and optimising radiological practices.

Purpose: Low-field (LF) MRI scanners are common in many Low- and middle-Income countries, but they provide images with worse spatial resolution and contrast than high-field (HF) scanners. Image Quality Transfer (IQT) is a machine learning framework to enhance images based on high-quality references that has recently adapted to LF MRI. In this study we aim to assess if it can improve lesion visualisation compared to LF MRI scans in children with epilepsy.

Methods: T1-weighted, T2-weighted and FLAIR were acquired from 12 patients (5 to 18 years old, 7 males) with clinical diagnosis of intractable epilepsy on a 0.36T (LF) and a 1.5T scanner (HF). LF images were enhanced with IQT. Seven radiologists blindly evaluated the differentiation between normal grey matter (GM) and white matter (WM) and the extension and definition of epileptogenic lesions in LF, HF and IQT-enhanced images.

Results: When images were evaluated independently, GM-WM differentiation scores of IQT outputs were 26% higher, 17% higher and 12% lower than LF for T1, T2 and FLAIR. Lesion definition scores were 8-34% lower than LF, but became 3% higher than LF for FLAIR and T1 when images were seen side by side. Radiologists with expertise at HF scored IQT images higher than those with expertise at LF.

Conclusion: IQT generally improved the image quality assessments. Evaluation of pathology on IQT-enhanced images was affected by familiarity with HF/IQT image appearance. These preliminary results show that IQT could have an important impact on neuroradiology practice where HF MRI is not available.

Introduction: Gibbus deformity has been documented as a common musculoskeletal abnormality in mucopolysaccharidosis type I (Hurler syndrome, MPS IH), and its recognition often leads to the diagnosis of MPS IH. While the incidence has been described, the progression of gibbus deformities is not well known. Here we describe the natural history of gibbus deformity in a single center patient population using serial spinal MRI scans.

Methods: All spinal MRI scans in MPS IH patients were retrospectively reviewed. The presence, spinal location, and angulation of the gibbus deformities were collected. The angles between the superior endplate of the superior normal vertebral body and the inferior endplate of the inferior normal vertebral body were measured.

Results: 24 of 47 patients (51%) were found to have cervico-thoracic deformity on their cervical MRI scans, and 19 of those 24 (79%) patients were found to have progressive cervico-thoracic deformity with average change of angle of 17.1 degrees [range 3.9, 62.8] over 5.3 years. 7 of 8 patients who had thoraco-lumbar MRI were found to have thoraco-lumbar deformity, and 4 of those 7 patients (57%) were found to have progressive thoraco-lumbar deformity with the average increase angle of 16.7 degrees [range 3.3, 47.1] over an average of 4.1 years.

Conclusion: We found out that baseline spinal measurement cannot reliably predict the progression as multiple patients with normal alignment eventually developed severe deformity, whereases patients with severe deformity did not progress to require surgical intervention.

Background: Crossing Y-stent-assisted coiling (CYSAC) is a feasible yet technically challenging technique for the treatment of wide-neck bifurcation aneurysms (WNBAs).

Objective: To present mid-term results of Y-stent-assisted coiling (YSAC) using the LVIS EVO stent and to describe our "drill turn" technique for stent crossing.

Methods: This retrospective, observational study included 37 consecutive patients treated with YSAC using LVIS EVO stents at five centres between September 2020 and March 2023.

Results: Immediately after treatment, 31 of the 37 patients (83.8%) achieved Raymond-Roy occlusion classification (RROC) Class I occlusion, while 5 patients (13.5%) had Class II and 1 patient (2.7%) had Class III occlusion. The mean follow-up period was 32.8 months (range: 11-41 months), and all patients underwent follow-up imaging after ≥ 6 months. On follow-up imaging, 34 patients (92%), including all those with immediate RROC Class I occlusion, 2 with Class II, and 1 with Class III, showed Class I occlusion. One patient with RROC Class II occlusion demonstrated a gradual decrease in residual filling, while one large partially thrombosed middle cerebral artery aneurysm and one large basilar tip aneurysm (8%) with residual neck filling remained unchanged on the 6-month digital subtraction angiograph.

Conclusion: Utilizing the described drill turn technique, CYSAC with LVIS EVO stents was found to be feasible and safe for WNBA treatment, with high and stable occlusion rates observed during mid-term follow-up.

Purpose: The aim of our study was to assess the diagnostic performance of commercially available AI software for intracranial aneurysm detection and to determine if the AI system enhances the radiologist's accuracy in identifying aneurysms and reduces image analysis time.

Methods: TOF-MRA clinical brain examinations were analyzed using commercially available software and by an consultant neuroradiologist for the presence of intracranial aneurysms. The results were compared with the reference standard, to measure the sensitivity and specificity of the software and the consultant neuroradiologist. Furthermore, we examined the time required for the neuroradiologist to analyze the TOF-MRA image set, both with and without use of the AI software.

Results: In 500 TOF-MRI brain studies, 106 aneurysms were detected in 85 examinations by combining AI software with neuroradiologist readings. The neuroradiologist identified 98 aneurysms (92.5% sensitivity), while AI detected 77 aneurysms (72.6% sensitivity). Specificity and sensitivity were calculated from the combined effort as reference. Combining AI and neuroradiologist readings significantly improves detection reliability. Additionally, AI integration reduced TOF-MRA analysis time by 19 s (23% reduction).

Conclusions: Our findings indicate that the AI-based software can support neuroradiologists in interpreting brain TOF-MRA. A combined reading of the AI-based software and the neuroradiologist demonstrated higher reliability in identifying intracranial aneurysms as compared to reading by either neuroradiologist or software, thus improving diagnostic accuracy of the neuroradiologist. Simultaneously, reading time for the neuroradiologist was reduced by approximately one quarter.

Background: Neuropsychiatric Systemic Lupus Erythematosus (NPSLE) is a complex manifestation of Systemic Lupus Erythematosus (SLE) characterized by a wide range of neurological and psychiatric symptoms. This study aims to elucidate the patterns of Perfusion-Weighted MRI (PWI) in NPSLE patients compared to SLE patients without neuropsychiatric manifestations (non-NPSLE) and healthy controls (HCs).

Material and methods: A systematic search was conducted in PubMed/Medline, Embase, Web of Science, and Scopus for studies utilizing PWI in NPSLE patients published through April 14, 2024. Cerebral blood flow (CBF) data from NPSLE, non-NPSLE patients, and HCs were extracted for meta-analysis, using standardized mean difference (SMD) as an estimate measure. For studies lacking sufficient data for inclusion, CBF, cerebral blood volume (CBV), and mean transit time (MTT) were reviewed qualitatively.

Results: Our review included eight observational studies employing PWI techniques, including dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL). The meta-analysis of NPSLE compared to non-NPSLE incorporated four studies, encompassing 104 NPSLE patients and 90 non-NPSLE patients. The results revealed an SMD of -1.42 (95% CI: -2.85-0.00, I²: 94%) for CBF in NPSLE compared to non-NPSLE.

Conclusion: PWI reveals informative patterns of cerebral perfusion, showing a significant reduction in mean CBF in NPSLE patients compared to non-NPSLE patients. Our qualitative synthesis highlights these changes, particularly in the frontal and temporal lobes. However, the existing data exhibits considerable heterogeneity and limitations.

Purpose: This review highlights the importance of functional connectivity in pediatric neuroscience, focusing on its role in understanding neurodevelopment and potential applications in clinical practice. It discusses various techniques for analyzing brain connectivity and their implications for clinical interventions in neurodevelopmental disorders.

Methods: The principles and applications of independent component analysis and seed-based connectivity analysis in pediatric brain studies are outlined. Additionally, the use of graph analysis to enhance understanding of network organization and topology is reviewed, providing a comprehensive overview of connectivity methods across developmental stages, from fetuses to adolescents.

Results: Findings from the reviewed studies reveal that functional connectivity research has uncovered significant insights into the early formation of brain circuits in fetuses and neonates, particularly the prenatal origins of cognitive and sensory systems. Longitudinal research across childhood and adolescence demonstrates dynamic changes in brain connectivity, identifying critical periods of development and maturation that are essential for understanding neurodevelopmental trajectories and disorders.

Conclusion: Functional connectivity methods are crucial for advancing pediatric neuroscience. Techniques such as independent component analysis, seed-based connectivity analysis, and graph analysis offer valuable perspectives on brain development, creating new opportunities for early diagnosis and targeted interventions in neurodevelopmental disorders, thereby paving the way for personalized therapeutic strategies.

Objective: Research into the effectiveness and applicability of deep learning, radiomics, and their integrated models based on Magnetic Resonance Imaging (MRI) for preoperative differentiation between Primary Central Nervous System Lymphoma (PCNSL) and Glioblastoma (GBM), along with an exploration of the interpretability of these models.

Materials and methods: A retrospective analysis was performed on MRI images and clinical data from 261 patients across two medical centers. The data were split into a training set (n = 153, medical center 1) and an external test set (n = 108, medical center 2). Radiomic features were extracted using Pyradiomics to build the Radiomics Model. Deep learning networks, including the transformer-based MobileVIT Model and Convolutional Neural Networks (CNN) based ConvNeXt Model, were trained separately. By applying the "late fusion" theory, the radiomics model and deep learning model were fused to produce the optimal Max-Fusion Model. Additionally, Shapley Additive exPlanations (SHAP) and Grad-CAM were employed for interpretability analysis.

Results: In the external test set, the Radiomics Model achieved an Area under the receiver operating characteristic curve (AUC) of 0.86, the MobileVIT Model had an AUC of 0.91, the ConvNeXt Model demonstrated an AUC of 0.89, and the Max-Fusion Model showed an AUC of 0.92. The Delong test revealed a significant difference in AUC between the Max-Fusion Model and the Radiomics Model (P = 0.02).

Conclusion: The Max-Fusion Model, combining different models, presents superior performance in distinguishing PCNSL and GBM, highlighting the effectiveness of model fusion for enhanced decision-making in medical applications.

Clinical relevance statement: The preoperative non-invasive differentiation between PCNSL and GBM assists clinicians in selecting appropriate treatment regimens and clinical management strategies.

Introduction: Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown.

Methods: In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T₁-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P.

Results: With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL.

Conclusion: MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.