Neuroradiology最新文献

Purpose: Task-based fMRI (tb-fMRI) has emerged as a promising imaging modality for determination of language lateralization in patients undergoing neurosurgery, largely replacing the invasive gold standard Wada test. However, its applicability in pediatric populations remains uncertain due to the unique characteristics of the developing pediatric brain. This meta-analysis and systematic review aim to synthesize existing data on the concordance rates of tb-fMRI and the intracarotid amobarbital test (IAT) in children undergoing neurosurgery.

Methods: We systematically searched PubMed, Embase, Cochrane and PsycINFO through 2025 for observational studies reporting concordance rates of tb-fMRI and IAT for language laterality assessment in children.

Results: Fourteen studies were included in the systematic review, of which eight studies with 70 patients met the inclusion criteria in the meta-analysis. The pooled concordance rate between tb-fMRI/IAT was 81% (95% CI: 69% to 91%), with an overall sensitivity of 80% and specificity of 62%. The concordance was 86% (95% CI: 68% to 97%) for typical laterality and 85% (95% CI 68% to 96%) for atypical. There was no difference between groups for region-of-interest (ROI, p = 0.4943), paradigm (p = 0.3960) or interpretation method (p = 0.1501).

Conclusion: Concordance rates between tb-fMRI/IAT in pediatric patients show promising results. However, tb-fMRI demonstrates higher sensitivity in patients with typical left-lateralization, suggesting that confirmatory testing with Wada may still be warranted in cases without strong left-lateralization. These findings align with trends observed in the adult population, supporting the use of fMRI as a valuable tool in children.

Objective: In patients with non-lesional epilepsy, MR imaging detects no structural or functional abnormalities. The aim of this study was to determine whether subtle local reductions or increases in brain volume, undetectable to the human eye, can indicate an epileptic focus directly or indirectly. To address this, we performed brain volumetry using 7T MRI.

Methods: We evaluated 7T MRI in patients with non-lesional epilepsy as part of a retrospective study and a healthy control cohort from another prospective study. FastSurfer segmentations were performed using T1 MPRAGE. Additionally, we also performed volumetry of the hippocampal subfields, the thalamic nuclei and the brainstem. We created a control group matched for age and gender distribution.

Results: 7T segmentation as described above was possible in 14 patients with epilepsy and 27 participants of a control cohort. We detected a significant volume loss in the ipsilateral central lateral nucleus of thalamus, as well as a significant increase in the presubiculum body and the ipsilateral and contralateral entorhinal and medial orbitofrontal cortices.

Conclusion: High-resolution 7T MRI-based volumetric analysis in patients with non-lesional epilepsy revealed significant atrophy in brain regions commonly implicated in epileptogenesis. These structures exhibited strong sensitivity and specificity, highlighting the potential of volumetry as a diagnostic tool in the absence of visible lesions. Validation in larger, independent cohorts is required to confirm these findings and assess clinical applicability.

Background: The Low-profile visualized Intraluminal Support EVO (LVIS EVO) is a next-generation braided stent characterized by enhanced visibility and resheathability, and designed for stent-assisted coil embolization of intracranial aneurysms. Despite growing adoption, real-world data on its efficacy and safety remain limited.

Objective: This study aims to evaluate the safety and efficacy of the LVIS EVO stent in consecutive patients undergoing treatment for brain aneurysms.

Methods: We retrospectively analyzed all patients who underwent treatment of unruptured intracranial aneurysms with the LVIS EVO stent in a single tertiary center between January 2021 and January 2024. Baseline demographics, imaging and procedural characteristics, clinical outcomes, and clinical and radiological follow-up data were collected. The primary endpoints were successful deployment and complete aneurysm occlusion at follow-up as defined by the Raymond-Roy Occlusion Classification. Secondary endpoints included complication rate, modified Rankin Scale (mRS) at last clinical follow-up, and incidence of in-stent stenosis on last follow-up imaging.

Results: Thirty-four patients (64.7% women; median age: 52 years) were treated for 34 saccular aneurysms. Most of the aneurysms were previously ruptured and recanalized after initial treatment (20/34, 58.8%). They were mainly located at the middle cerebral artery (15/34, 44.1%) and the internal carotid artery terminus (8/34, 23.5%), with additional cases at the anterior communicating artery (7/34, 20.6%) and the posterior circulation (4/34, 11.8%). Median aneurysm neck size was 3.3 mm, with an aspect ratio of 1.2 and a dome-to-neck ratio of 1.3. Stent deployment was successful in 100% of cases. Immediate complete occlusion (RROCs I) was achieved in 82.4% of aneurysms. At a median radiological follow-up of 24 months, 91.2% of aneurysms remained completely occluded, and 97.1% were adequately occluded (RROC I-II). Two intraprocedural cases (5.9%) of in-stent thrombosis occurred and were managed successfully. One post-procedural symptomatic ischemic event occurred, but the patient was asymptomatic at the last clinical follow-up. There were no hemorrhagic or permanent ischemic complications. Asymptomatic in-stent stenosis occurred in 2 patients (5.9%). Clinical outcome was favorable (mRS ≤ 2) in 100% of cases at last follow-up.

Conclusion: The LVIS EVO stent demonstrates excellent technical success and sustained aneurysm occlusion with a low complication rate. These results support its safety and efficacy in the treatment of intracranial aneurysms, including previously ruptured lesions and anatomically complex locations.

Purpose: The optimal antiplatelet therapy for patients on continuous oral anticoagulants (OACs) who are undergoing coil embolization for unruptured intracranial aneurysms (UIAs) is remains unknown. This study evaluated the efficacy and safety of single- (SAPT) and dual antiplatelet therapy (DAPT) in patients taking OACs who underwent coil embolization for UIAs.

Methods: This retrospective multicenter study included patients taking OACs who underwent coil embolization for UIAs at 9 hospitals between January 2016 and August 2023. The primary outcome was a thromboembolic complication within 30 days post-procedure. The secondary outcome was a composite all bleeding events according to the Thrombolysis in Myocardial Infarction bleeding criteria.

Results: A total of 112 patients (mean [standard deviation] age, 67.3 [9.7]; 67 females [59.8%]) were included. Among them, 31 patients (27.7%) received SAPT, and 81 patients (72.3%) received DAPT. There was no significant difference in the thromboembolic event rate between the 2 groups (SAPT group: 2 of 31 [6.5%]; DAPT group: 3 of 81 [3.7%]; unadjusted hazard ratio [HR], 0.55 [95% CI, 0.09-3.30]; P = .52). However, the rate of all bleeding events after coil embolization in the DAPT group was significantly higher than that in the SAPT group (SAPT group: 2 of 31 [6.5%]; DAPT group: 22 of 81 [27.2%]; adjusted HR, 5.57 [95% CI, 1.30-23.83]; P = .02).

Conclusions: With respect to SAPT, DAPT was not associated with a reduction in thromboembolic complications in patients taking OACs who underwent coil embolization, but it was associated with an increase in all bleeding events.

Objectives: To explore a novel approach for the early prediction of malignant cerebral edema (MCE) in stroke patients using radiomics features extracted from dual-energy computed tomography angiography (DE-CTA) reconstructed images of infarcted brain tissue.

Materials and methods: This retrospective study enrolled 398 stroke patients who underwent DE-CTA between April 2016 and November 2022 from three medical centers. Patients were allocated into a training cohort (n = 227) and a test cohort (n = 171) based on their source institution. Radiomics features were extracted from DE-CTA reconstructions of the infarct tissue. Radiomics models were built for each reconstruction scan images and for a combined model using features from all images. Additionally, a nomogram model integrating significant radiomics features and clinical characteristics was developed. The diagnostic performance of all models was evaluated using receiver operating characteristic (ROC) curve analysis, calculating the area under the curve (AUC).

Results: Radiomics models based on each individual DE-CTA reconstruction demonstrated robust predictive performance. In the test cohort, the combined radiomics model integrating features from all DE-CTA reconstructions significantly superior predictive performance compared to most single-image models. In the test cohort, both the combined radiomics model (AUC = 0.950) and the nomogram model (AUC = 0.935) significantly outperformed the clinical model (AUC = 0.574), both p < 0.001. No significant difference in performance was observed between the nomogram and the radiomics model (p = 0.30).

Conclusions: Radiomics models derived from DE-CTA reconstructed images of infarcted tissue provide a reliable method for the early prediction of MCE development in stroke patients.

Purpose: Our systematic review aims to evaluate the application of artificial intelligence (AI) and machine learning (ML) techniques for the automatic segmentation, quantification, and treatment planning of brain arteriovenous malformations (AVMs).

Methods: A Preferred Reporting Items for systematic reviews and Meta-Analysis (PRISMA) guided systematic review was conducted using specific keywords and Boolean operators across PubMed, ScienceDirect, Scopus, and Web of Science. Studies were included based on the use of AI or machine learning (ML) models for imaging-based analysis of arteriovenous malformations (AVMs).

Results: There were thirteen studies with 3,010 individuals. The most popular modalities were TOF-MRA and MRI. U-Net, Dense U-Net, YOLO, SVM, and fuzzy c-means clustering were among the models. Across all experiments, the average Dice similarity score was 0.758. The models showed usefulness in bleeding risk assessment, corticospinal tract involvement, AVM diffuseness prediction, nidus segmentation, and stereotactic radiosurgery (SRS) planning. In tasks involving radiation planning and hemorrhagic risk, a number of models provided better or comparable predicted accuracy and showed good agreement with manual segmentations.

Conclusion: AI and ML show potential for AVM evaluation, with early studies suggesting they may support efficiency and standardization in diagnosis and treatment planning. Despite encouraging findings, model generalizability and clinical implementation remain limited. Future studies should focus on prospective validation, integration of multimodal imaging, and post-treatment segmentation to enhance clinical translation.

Background: The Carotid Plaque Reporting and Data System (Plaque-RADS) is a new quantitative grading system for plaque stability. Herein, high-resolution magnetic resonance imaging (HRMRI)-based Plaque-RADS(HRMRI-Plaque-RADS) classification was performed to characterize the different classifications in patients with cerebral infarction.

Methods: HRMRI images from patients with acute cerebral infarction (ACI) of the anterior cerebral circulation were collected retrospectively, and carotid plaques were categorized into the Plaque-RADS 1-4 subtypes. Plaque-RADS 1 and 2 were considered low-risk, and Plaque-RADS 3 and 4 as high-risk. After contrast agent injection, high-risk plaques were further classified as enhanced or non-enhanced. A mixed-effects logistic regression model was applied to identify relationships between plaque types and infarction.

Results: This study included 98 patients (age 65.6 ± 9.6 years; 88.8% male; 196 carotid arteries). The distribution of Plaque-RADS 1-4 plaques on the infarction side was: 7 (7.1%), 13 (13.2%), 49 (50.0%), and 29 (29.6%), respectively. Among the high-risk plaques, 50 (51%) were enhanced high-risk. The distribution of Plaque-RADS 1-4 plaques on the contralateral side was: 26 (26.5%), 21 (21.4%), 43 (43.9%), and 8 (8.2%), respectively, with 28 (28.6%) high-risk plaques classified as enhanced high-risk. The high-risk and enhanced high-risk plaque types were significantly associated with the infarction side (odds ratio [OR] = 3.71, 95% confidence interval [CI], 1.96-7.05; P < 0.001, after adjustment; OR = 3.05, 95%CI, 1.78-5.23; P < 0.001).

Conclusion: In ACI, HRMRI-Plaque-RADS based high-risk and enhanced high-risk plaques were associated with the infarction side. Plaque enhancement offered a supplement to the Plaque-RADS, and HRMRI based Plaque-RADS classification may effectively identify vulnerable plaques.

Objectives: To evaluate the safety and feasibility of the pusher-assisted catheterization (PAC) technique using the pEGASUS-HPC stent pusher instead of a microwire for accessing unruptured wide-necked cerebral aneurysms during Y-stent-assisted coiling.

Methods: In this multicenter retrospective study (July 2021- June 2025), 48 unruptured wide-necked cerebral aneurysms underwent Y-stent-assisted coiling using pEGASUS HPC stents. Based on the catheterization technique, cases were assigned to either the microwire-assisted catheterization (MAC, n = 23) or the stent pusher-assisted catheterization (PAC, n = 25) group. Clinical and procedural data were analyzed to compare safety and efficacy, focusing on success rates, required catheterization time, complications, and adverse events.

Results: The cohort had a mean age of 62.6 ± 9.8 years, with 64.3% of patients being female. In the MAC group, aneurysm catheterization was successful in all 23 cases (100%), with a mean catheterization time of 5.31 ± 1.2 min. In contrast, the PAC group achieved successful catheterization in 88% of cases (22/25), with a markedly reduced mean catheterization time of 0.82 ± 0.27 min-approximately 6.5 times faster than the conventional MAC technique (p < 0.001). Importantly, no procedure-related complications, such as perforations or dissections, were observed in either group.

Conclusion: In this multicenter retrospective feasibility and safety analysis, PAC appeared to enable faster aneurysm access during Y-stent-assisted coiling without an increase in intraprocedural complications. As clinical outcomes were not assessed, these findings should be regarded as technical proof-of-concept and require confirmation in prospective, outcome-driven studies.

Purpose: To perform a real-world clinical validation of a commercial AI tool for automatic MRI assessment in multiple sclerosis (MS) patients, evaluating its impact on assessment time, workflow, and accuracy in detecting new and enlarging lesions.

Methods: We prospectively enrolled MS patients undergoing routine follow-up MRI from September-December 2024. Current and prior MRI examinations were anonymized and assessed independently by four neuroradiologists with and without AI assistance (mdbrain v.4.11.0). Assessment times were recorded, and radiologists completed utility questionnaires. Lesion quantification was compared between radiologist alone, radiologist with AI, and AI alone. Performance metrics including sensitivity, specificity, and predictive values were calculated case-level for detecting new and enlarging lesions.

Results: The cohort included 112 MS patients scanned on 8 different MRI scanner models with varying protocols. Mean assessment time was reduced by 27 s when using AI versus without (p = 0.317). Radiologists found AI helpful in 87% of cases and reported difficulties in 11%. AI obtained negative predictive values of 0.89 for detecting new lesions when comparing to assessment without AI. Positive predictive values were low (0.35-0.65) due to false positive tendencies.

Conclusion: We prospectively validated an AI tool for MS MRI follow-up in a real-world setting. It showed modest, non-significant time savings and low positive predictive value, limiting research use. High negative predictive value supports triaging potential. Radiologists found the AI tool helpful for lesion counting and detecting small new lesions. Findings highlight the need for thorough clinical evaluation, especially in areas lacking definitive ground truth.