Neuroradiology最新文献

This review seeks to provide neuroradiologists and clinicians with an imaging-based pattern recognition framework for primary mitochondrial disorders affecting the central nervous system (CNS). By utilising a comprehensive imaging phenotype approach to CNS mitochondrial disorders, it highlights the wide spectrum of neuroimaging patterns and the complexities they present in clinical settings. Using illustrative case examples, the review demonstrates how imaging acts as a vital bridge between clinical phenotypes and genotypes.

Purpose: To review recent advances in structural MRI post-processing for pediatric drug-resistant epilepsy, with emphasis on artificial intelligence-driven and quantitative techniques, including MELD-Graph, MAP18, FLAT1, and SUPR-FLAIR, and to evaluate their impact on lesion detection, epileptogenic zone localization, and presurgical planning.

Methods: Novel post-processing approaches were examined with respect to their computational foundations, imaging requirements, and diagnostic performance. Techniques employing machine learning, deep learning, voxel-based morphometry, cortical surface projection, and FLAIR/T1 ratio mapping were assessed for their applicability in children and their integration into multimodal evaluation pathways alongside electrophysiology and functional imaging.

Results: Advanced post-processing tools substantially increase sensitivity for detecting subtle cortical abnormalities, particularly in MRI-negative pediatric epilepsy. MELD-Graph identify features of focal cortical dysplasia through automated surface-based analysis and deep neural network classification, achieving notable lesion detection even when conventional MRI findings are normal. MAP18 provides complementary voxel-wise morphometric assessment, improving specificity and benefiting from optimized structural sequences. FLAT1 enhances lesion conspicuity by quantifying FLAIR/T1 signal relationships, while SUPR-FLAIR improves visualization of cortical signal abnormalities through normalized FLAIR intensity projection onto the cortical surface. When incorporated into multimodal diagnostic workflows, these methods refine epileptogenic zone localization, inform individualized surgical strategies, and can reduce reliance on invasive testing.

Conclusion: Advanced structural MRI post-processing is transforming the neuroradiological evaluation of pediatric drug-resistant epilepsy. By revealing subtle cortical abnormalities not visible on conventional imaging, these tools support more precise lesion characterization and surgical planning. Ongoing efforts toward standardization, clinical validation, and workflow integration will be essential to ensure widespread adoption and maximize clinical impact within precision-medicine approaches to pediatric epilepsy.

Background: Pretreatment determination of histological differentiation grade is critical for prognostic evaluation in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC). This study aimed to develop a contrast-enhanced CT (CECT)-based Vision Transformer (ViT) model for noninvasive evaluation of histological grades in LHSCC.

Methods: In this retrospective multicenter study, a total of 1,648 LHSCC patients who underwent CECT scans were enrolled from three hospitals in this study. Participants were divided into a training cohort (n = 1,239), an internal validation cohort (n = 310) from one hospital, and an external validation cohort (n = 99) from the other two hospitals. The diagnostic model integrates a pre-trained ViT for CECT feature extraction and an XGBoost classifier for prediction. The model's predictive performance was evaluated using the area under the curve (AUC), decision curve analysis (DCA), and calibration curve.

Results: The ViT model achieved AUCs of 0.887 (95%CI: 0.848-0.927) in internal validation and 0.796 (95%CI: 0.693-0.899) in external validation cohorts, significantly outperforming the conventional radiomics model (AUCs: 0.775, 95%CI: 0.714-0.837 and 0.544, 95%CI: 0.388-0.699; p < 0.001 and 0.002, respectively). Clinically, DCA demonstrated superior clinical utility, while calibration curves showed excellent prediction reliability. Gradient-weighted Class Activation Mapping visualization identified CT image regions most influential for the model's predictions, providing interpretability for clinical decision-making.

Conclusion: The ViT-based deep learning model developed in this study using CECT demonstrated excellent predictive performance for histological grading of LHSCC, with promising application for patient prognosis assessment.

Purpose: Guillain-Barré Syndrome (GBS) is an autoimmune disorder causing acute inflammatory polyneuropathy, resulting in muscle weakness. Timely diagnosis is critical to prevent complications such as respiratory failure and long-term disability. Ultrasound imaging of peripheral nerves, specifically assessing nerve cross-sectional area (CSA), has been suggested as a diagnostic tool for GBS. This systematic review aims to evaluate the utility of nerve ultrasound in diagnosing and monitoring GBS.

Methods: A systematic review was conducted following PRISMA guidelines, searching databases including PubMed, Scopus, Web of Science, and Cochrane Library up to December 2024. Studies that used ultrasound to assess peripheral nerve size in GBS patients compared to healthy controls or other neuropathy patients were included. Statistical analysis was conducted using Review Manager 5.4 software.

Results: Out of 848 studies, 25 met the inclusion criteria, with 12 included in the meta-analysis. A total of 528 patients with GBS were included. Ultrasound revealed significant increases in the CSA of cervical, peroneal, median, ulnar, and tibial nerves in GBS patients. Specifically, cervical nerve enlargement (MD: 1.45, P = 0.0008) and peroneal nerve enlargement (Mean Difference (MD): 2.09, P < 0.00001) were notable. Subgroup analysis revealed significant enlargement of the ulnar and tibial nerves across different anatomical regions.

Conclusion: Ultrasound imaging of peripheral nerves, particularly changes in CSA, provides valuable diagnostic insight for GBS, may be helpful in early recognition and intervention. Further studies are needed to establish consistent CSA patterns and improve diagnostic accuracy across various GBS subtypes.

Purpose: Herpes simplex virus 1 encephalitis (HSE) is the most common sporadic infectious encephalitis in Western countries, with a 70% mortality rate and only 9% of survivors free from neurological sequelae. While definitive diagnosis relies on cerebrospinal fluid testing, magnetic resonance imaging (MRI) plays a crucial role in identifying typical acute patterns and features. However, the imaging evolution of encephalitic lesions is not well understood. We aimed to identify and evaluate the prevalence and progression of cortical lesions, as well as the recurrence of these patterns in HSE and other encephalitic etiologies.

Methods: As a retrospective monocentric study, we included 40 patients with various etiological encephalitis from our institute. Each patient's lesions were assessed, by three experienced neuroradiologists, in the acute phase and associated with specific evolution patterns in the chronic phase.

Results: 10 out of 11 (91%) patients diagnosed with HSV-1 presented during chronic phase selective cortical liquefaction, identified as Cortical Melt Sign (CMS) (Fisher's exact p-value < 0.001). Moreover, this pattern was then correlated with acute diffusion restriction-potentially explaining CMS as a chronic imaging biomarker for HSE as a result of the acute inflammation.

Conclusion: These findings can aid in understanding the pathological mechanisms of herpetic encephalitis and guide differential diagnosis. Moreover, CMS could serve as a retrospective imaging marker in HSE.

Purpose: To evaluate the impact of super-resolution deep learning reconstruction (SR-DLR) algorithm on the evaluations of pituitary neuroendocrine tumor (PitNET) and on the image quality of pituitary MRI compared to conventional images with zero-filling interpolation (ZIP) technique.

Methods: This retrospective study included 29 patients with PitNET who underwent pituitary MRI imaging. T2-weighted coronal images were reconstructed with SR-DLR and ZIP. Three readers assessed the images in terms of pituitary stalk deviation, noise, sharpness, depiction of PitNET, and diagnostic acceptability. A radiologist placed circular or ovoid regions of interest (ROIs) on the lateral ventricle and the tumor, and signal-to-noise ratio (SNR) and contrast-to-noise ratio were calculated. The radiologist also placed a linear ROI crossing the septum pellucidum perpendicularly. From the signal intensity profile along this ROI, edge rise slope (ERS) and full width at half maximum (FWHM) were calculated.

Results: Inter-reader agreement in the evaluations of pituitary stalk deviation in SR-DLR (0.518) tended to be superior to that in ZIP (0.405). Scores in the qualitative image analyses in SR-DLR were significantly better than those in ZIP for all evaluation items (p < 0.001). SNR and CNR in SR-DLR were significantly higher compared to ZIP (p < 0.001). Results of ERS (5433/2177 in SR-DLR/ZIP) and FWHM (0.67/1.27 mm in SR-DLR/ZIP) indicated significantly enhanced spatial resolution in SR-DLR compared to ZIP.

Conclusion: SR-DLR tended to enhance inter-reader agreement in the evaluations of pituitary stalk deviation and significantly improved quality of pituitary MRI images compared to conventional ZIP images.

Introduction: Ventriculomegaly (VM) is the fetal central nervous system (CNS) anomaly most commonly represented in prenatal imaging. It is defined as a lateral ventricle of dimensions greater than or equal to 10 mm; it can be unilateral or bilateral. More generally, hydrocephalus is defined as an imbalance between brain parenchyma and cerebrospinal fluid (CSF) due to an abnormal increase of the latter within the ventricles in an almost bilateral manner. To identify ventriculomegaly and categorize its severity, the appropriate imaging and measurement methods are crucial. Clinical outcomes vary greatly because of the wide differential diagnosis. Furthermore, there is a significant chance that these causes may recur in subsequent pregnancies. Pregnancy care and counseling depend on a precise diagnosis of the underlying cause.

Materials and methods: We retrospectively reviewed our institutional fetal MR imaging database (4568 examinations) from 2005 until 2024. We focused on obstructive hydrocephalus and, according to rigorous inclusion/exclusion criteria (Table 1), we enrolled 201 cases.

Results: We analyzed isolated aqueduct stenosis (36.3%); hemorrhagic events (30.3%); rhombencephalosynapsis (7.5%); dural sinus malformation (6%); midline cysts (5.4%); diencephalic-mesencephalic junction (DMJ) dysplasia (3.5%); infectious lesions (3%); tumors (2.5%); Chiari 1 (1.5%); Walker Warburg disease (1%); not otherwise specified (3%).

Discussion: We discuss the different etiologies of obstructive hydrocephalus in our population and propose an etiology-based approach that allows the clinician and radiologist to reach the correct differential diagnosis and provide an indication for possible fetal surgery.

Conclusion: Hydrocephalus arises from embryological abnormalities or acquired insults, requiring precise neuroimaging for diagnosis and management. A thorough imaging approach aids in etiological diagnosis, surgical planning, and essential counseling.

Purpose: Hyperdense middle cerebral artery sign (HMCAS) is a phenomenon highly specific for acute ischaemic stroke (AIS) that can be found in brain non-contrast computed tomography (NCCT). Previous studies concerning its association with outcomes of patients undergoing mechanical thrombectomy (MT) are inconclusive. Our aim was to assess the relationship between HMCAS presence and long-term outcomes of AIS patients undergoing MT.

Methods: The study included anterior circulation AIS patients treated with MT in the University Hospital in [ANONYMIZED] from 2019 to 2021, in whom admission NCCT and one-year follow-up were available. The clinical, laboratory and imaging data, as well as following outcomes: the occurrence of successful recanalization [defined as modified treatment in cerebral infarction (mTICI) score 2b-3], haemorrhagic complications (ICH), 90-day and 365-day rates of mortality and good functional outcome [defined as modified Rankin Scale (mRS) score 0-2] were compared between groups of patients with and without HMCAS on initial NCCT. The association of HMCAS presence with the abovementioned outcomes was assessed using multivariate logistic regression analysis.

Results: Among 359 MT-treated patients with anterior circulation AIS, HMCAS was found in 244 (67.97%). The presence of HMCAS was independently associated with good functional outcome at 365 days (OR 1.956, 95% CI = 1.152-3.317, p = 0.013) as well as lower 90-day and 365-day mortality (OR = 0.464, 95% CI = 0.2517-0.856; p = 0.014 and OR 0.543, 95% CI: 0.313-0.940, p = 0.029, respectively).

Conclusion: The presence HMCAS on admission NCCT is associated with favourable long-term outcome in AIS patients undergoing MT.