Neuroradiology Journal最新文献

Bourgeoning vehicular accidents is leading to a rise in the traumatic brachial plexus injuries (TBPIs). Brachial plexus is a cardinal neural plexus catering to the sensory-motor function of the upper limb. Thus, prompt diagnosis and early management are must in case of TBPIs. Although no single modality is a universal gold standard across the full spectrum of TBPIs, Magnetic resonance imaging (MRI) forms the corner stone of imaging evaluation. Even with excellent resolution, clinching the diagnosis is an uphill task, as already complicated anatomy, becomes scrambled following trauma. Imaging plays a crucial role in management, as it not only diagnose TBPIs, but also accurately identify the site of injury and stratify it. Grading of TBPIs have bearing of management decisions and an accurate stratification, leads to significant reduction in morbidity. Modified Sunderland Classification is widespread accepted classification which can be correlated on MRI. Through this manuscript, the author has tried to simplify this correlation and provide an image guide for imagers along with a table summarizing the important take home points at last.

Computed tomography perfusion (CTP) imaging plays a pivotal role in the early evaluation of patients presenting with acute ischemic stroke (AIS), particularly by identifying candidates for endovascular thrombectomy. Accurate interpretation of CTP requires a structured approach that integrates technical understanding, clinical judgment, and recognition of the modality's limitations. This review was prompted by real clinical challenges faced by the senior author and aims to provide both a theoretical foundation and practical guidance for interpreting CTP. Key concepts are illustrated through real clinical scenarios and corresponding annotated images. In addition to reviewing current AHA/ASA guidelines, we discuss institutional best practices and highlight challenging clinical scenarios in which CTP can significantly influence treatment decisions. This article aims to equip clinicians with the knowledge and tools needed for consistent and effective use of CTP.

BackgroundCarotid artery stenting (CAS) is an established alternative to carotid endarterectomy for the treatment of atherosclerotic carotid stenosis. However, periprocedural ischemic stroke remains a concern, partly influenced by device selection and procedural technique. The optimal dilatation strategy, particularly the role of pre- and post-stenting balloon dilatation, remains debated. This study aimed to evaluate the safety and efficacy of CAS using pre-stenting dilatation alone compared with combined pre- and post-stenting dilatation.MethodsA retrospective analysis was conducted of 1248 CAS procedures performed in 1158 patients at a single neurovascular center (May 2009-December 2020). Baseline characteristics, procedural details, and outcomes were compared between cases with pre-stenting dilatation alone and those with additional post-stenting dilatation. The primary endpoint was the 30-day composite stroke rate; secondary outcomes included periprocedural adverse events and long-term in-stent restenosis (ISRS > 50%).ResultsPre-stenting dilatation was performed in all cases; additional post-stenting dilatation was used in 150 procedures (12%). The 30-day composite stroke rate was 2.6%, significantly lower in the pre-dilatation-alone group than in the combined group (2.1% vs. 7.2%; p = 0.003). At a median follow-up of 66 months, ISRS > 50% occurred in 5.9% of stents, with no significant difference between groups (5.9% vs. 5.7%).ConclusionsIn this large single-center experience, CAS using pre-stenting dilatation alone was associated with a lower periprocedural stroke rate and comparable long-term patency. These findings support a simplified procedural approach that may reduce embolic risk without compromising efficacy.

BackgroundIn vascular diseases such as arteriovenous malformations and dural arteriovenous fistulas, rare venous drainage routes can be identified angiographically.Case DescriptionA 50-year-old woman was transported to our hospital after she developed a sudden headache and unconsciousness. Computed tomography showed subarachnoid hemorrhage. A cerebral angiography disclosed an arteriovenous malformation (AVM) at the C2 level and a dural arteriovenous fistula (AVF) at C5/C6. The AVF drained through the posterior spinal vein to the inferior retrotonsillar vein. The AVM drained cranially to the anterior spinal vein flowing into the transverse medullary vein. The transverse medullary vein drained into the inferior retrotonsillar vein through a connecting vein. The connecting vein seemed very unusual.ConclusionsIn this case, a rare collateral vein connecting the transverse medullary vein and inferior retrotonsillar vein was observed.

BackgroundThe acute management of ruptured intracranial aneurysms sometimes requires stent placement, which necessitates the prompt initiation of an antiplatelet (APT) regimen, including Ticagrelor at our center.ObjectiveThis study aimed to assess patients with ruptured intracranial aneurysms who received Ticagrelor prior to or during aneurysm embolization. We evaluated procedural safety and clinical and imaging outcomes at 6 months follow-up.Patients and MethodsWe analyzed patients with aneurysmal subarachnoid hemorrhage treated with endovascular therapy (EVT) under a dual antiplatelet therapy (DAPT) regimen between January 2015 and January 2023, excluding those managed with surgical clipping. Safety profiles and clinical outcomes were systematically assessed.ResultsA total of 23 patients (69.6% female, mean age 58.6 ± 12.2 years) with ruptured aneurysms and subarachnoid hemorrhage underwent EVT with DAPT (Ticagrelor + Aspirin). Aneurysms were primarily located on the carotid (39.1%) and anterior communicating arteries (30.4%), with a median size of 5 mm. The median time from rupture to treatment was 1.5 days. Ischemic complications occurred in 30.4%, including procedure-related ischemia (21.7%) and post-procedure vasospasm (8.7%). Hemorrhagic complications were observed in 8.7%, with two patients experiencing asymptomatic post-procedure hemorrhage. Functional outcomes at 6 months showed 56.5% of patients with excellent recovery (mRS <2), while 17.4% died (mRS = 6), resulting in a 17.4% mortality rate.ConclusionTicagrelor appears feasible and generally safe for acute-phase management of aneurysmal subarachnoid hemorrhage, though complications and mortality highlight the need for cautious patient selection and further investigation.

BackgroundThe safety and efficacy of the middle meningeal artery embolization (MMAE) in patients with non-acute or chronic subdural hematoma (cSDH) has significant reporting within recent literature, however, mainly in the form of observational data.MethodsWe conducted a systematic review and meta-analysis including all available randomized clinical trials (RCTs) that compared MMAE in addition to standard of care (SOC) versus SOC alone for cSDH. The primary outcome was the rate of recurrence and reoperation. Secondary outcomes included serious adverse events (SAEs), mortality rate, independent ambulation (modified Rankin Scale (mRS) score 0-3), and changes in hematoma characteristics at 90 days. The fixed-effect or random-effects model was used based on the significancy of the heterogenicity (I² > 50%, P < .1).ResultsFindings showed significant superiority of MMAE over SOC in 90-day recurrence (RR = 0.55, 95% CI = 0.36-0.83, P = .0047, I² = 43.3%), reoperation within 180 days (RR = 0.38, 95% CI = 0.26-0.56, P < .001, I² = 0.0%), ambulatory functional outcome (RR = 1.034, 95% CI = 1.0-1.07, P = .0296, I² = 53.9%), SAE at any time (RR = 0.59, 95% CI = 0.38-0.94, P = .025, , I² = 0.0%), and 90-day any-cause mortality (RR = 0.29, 95% CI = 0.14-0.6, P = .0008, I² = 0.0%). Successful embolization and 30-day embolization-related complications occurred in 99.2% (95% CI = 94.54%-100%) and 1.18% (95% CI = 0.39%-2.31%) of patients, respectively. Additionally, subgroup analyses on major and pilot RCTs, comparison of embolic agents, and MMAE adjuvant to surgery versus surgery alone confirmed these findings.ConclusionMMAE appears to be safe and effective in the management of cSDH with low recurrence and SAE rate.

Background: Cauda equina syndrome (CES) is a rare but serious neurosurgical emergency. Back pain and sciatica are common presentations to A&E. Get It Right First Time (GIRFT) published guidance in February 2023 regarding the red flag symptoms and symptom duration requiring emergency MRI. This framework has been utilised by the orthopaedic service within our hospital. The aim of this study was to assess whether implementing GIRFT guidance could reduce CES related admissions without impacting the diagnostic yield for identifying this emergency.Methods: Retrospective review of all emergency MRI scans to exclude CES during two 6-month periods. GIRFT guidance was published in February 2023. Period 1 (01/08/2022-31/01/2023) was prior to GIRFT guidance and period 2 (01/08/2024-31/01/2025) was more than 1 year after GIRFT guidance. Statistical analysis was undertaken using Chisquared and Mann-Whitney testing. Results: There were 175 emergency MRI scans to exclude CES during period 1 versus 159 during period 2. After implementation of GIRFT guidance, there was a significant reduction in the percentage of patients requiring admission (42.77% vs 56.57%, p = 0.016) and an increase in the percentage of patients scanned on the day of presentation (61.64% vs 52.57%, p = 0.119). There was no change in the diagnostic yield of scans for identifying CES (4.57% vs 4.4%, p = 1). Conclusion: Our results show that utilisation of the GIRFT guidance reduced CES related admissions without negatively impacting diagnostic yield. These findings highlight the value of implementing GIRFT guidelines in neurosurgical and orthopaedic departments across the country.

This study evaluates the efficacy of deep learning models in identifying infarct tissue on computed tomography perfusion (CTP) scans from patients with acute ischemic stroke due to large vessel occlusion, specifically addressing the potential influence of varying noise reduction techniques implemented by different vendors. We analyzed CTP scans from 60 patients who underwent mechanical thrombectomy achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2c or 3, ensuring minimal changes in the infarct core between the initial CTP and follow-up MR imaging. Noise reduction techniques, including principal component analysis (PCA), wavelet, non-local means (NLM), and a no denoising approach, were employed to create hemodynamic parameter maps. Infarct regions identified on follow-up diffusion-weighted imaging (DWI) within 48 hours were co-registered with initial CTP scans and refined with ADC maps to serve as ground truth for training a data-augmented U-Net model. The performance of this convolutional neural network (CNN) was assessed using Dice coefficients across different denoising methods and infarct sizes, visualized through box plots for each parameter map. Our findings show no significant differences in model accuracy between PCA and other denoising methods, with minimal variation in Dice scores across techniques. This study confirms that CNNs are adaptable and capable of handling diverse processing schemas, indicating their potential to streamline diagnostic processes and effectively manage CTP input data quality variations.

ObjectivePredicting treatment response in patients with vestibular schwannomas (VSs) remains challenging. This study aimed to evaluate the use of pre-treatment normalized apparent diffusion coefficient (nADC) values and magnetic resonance (MR) imaging characteristics in predicting treatment outcomes in patients with VSs undergoing radiosurgery.MethodsThe MR images of 44 patients with VSs who underwent radiosurgery at our institution were retrospectively reviewed, and the patients were categorized into tumor control (n = 28) and progression (n = 16) groups based on treatment response after treatment initiation, with a median follow-up duration of 29.5 (13-115) months. Pre-treatment nADC values for the whole tumor and solid portion of the tumor were assessed for predictive significance. MRI characteristics were analyzed, including hemorrhage status, tumor morphology, and post-treatment loss of central enhancement. Interobserver reliability was also evaluated.ResultsEarly post-treatment enlargement was associated with tumor progression (p = .024). The mean pre-treatment nADC values for the solid part of the tumor were significantly higher in the tumor control group than in tumor progression group (1.32 vs 1.05, p = .005). The receiver operating characteristic curve analysis revealed a mean nADC of 1.18 as an optimal cutoff, with sensitivity and specificity of 76.2% and 86.7%, respectively, in predicting treatment response.ConclusionThe mean nADC values for the solid part of the tumor demonstrated predictive value for treatment response, with implications for treatment planning. Notably, early post-treatment enlargement was correlated with tumor progression. Incorporating these findings into clinical practice may refine treatment strategies for patients with VSs undergoing radiosurgery.

IntroductionThe prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). These techniques facilitate a detailed examination of the manifestations of these diseases. Recent research has demonstrated the potential of artificial intelligence (AI) in automating the diagnostic process, generating significant interest in this field.Materials and MethodsThis narrative review aims to compile and analyze articles related to the AI-assisted diagnosis of FTD and AD. We reviewed 31 articles published between 2012 and 2024, with 23 focusing on machine learning techniques and 8 on deep learning techniques. The studies utilized features extracted from both single imaging modalities and multi-modal approaches, and evaluated the performance of various classification models.ResultsAmong the machine learning studies, Support Vector Machines (SVM) exhibited the most favorable performance in classifying FTD and AD. In deep learning studies, the ResNet convolutional neural network outperformed other networks.ConclusionThis review highlights the utility of different imaging modalities as diagnostic aids in distinguishing between FTD and AD. However, it emphasizes the importance of incorporating clinical examinations and patient symptom evaluations to ensure comprehensive and accurate diagnoses.