Neuroradiology Journal最新文献

Background and purpose: Successful and complete reperfusion should be the aim of every endovascular thrombectomy (EVT) procedure. However, the effect of time delays on successful reperfusion in late window stroke patients presenting 6-to-24 h from onset has not been investigated.

Materials and methods: We pooled individual patient-level data from seven trials and registries for anterior circulation stroke patients treated with EVT between 6 and 24 h from onset. We explored the impact of delays across multiple interval times, including onset to hospital arrival; hospital arrival to arterial puncture; imaging to arterial puncture; and onset to arterial puncture. Our primary outcome was successful reperfusion, defined as a modified thrombolysis in cerebral infarction (mTICI) score of 2b-3. Logistic regression analyses were performed to assess the association between each of the interval times and successful reperfusion.

Results: We included 608 patients. The median age was 70 years (IQR 58-79), and 307 (50.5%) were females. Successful reperfusion was achieved in 494 (81.2%) patients. Patients with successful reperfusion had lower NIHSS scores (median 15 [IQR11-19] vs 17 [11-21], p = .02) and significantly shorter hospital arrival to arterial puncture time (90 min [60-150] vs 110 min [84.5-150], p = .01) than unsuccessful reperfusion. The odds of successful reperfusion decreased by 15% for every one-hour delay in arrival-to-puncture time (adjusted odds ratio 0.85, 95% CI: 0.75-0.95). Other workflow times did not impact the rate of successful reperfusion.

Conclusion: Faster hospital arrival to arterial puncture time is associated with higher odds of successful reperfusion in late window stroke patients.

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.

Introduction: The 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 methods: This 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.

Results: Among 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.

Conclusion: This 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.

Despite their similar nomenclature, Neurofibromatosis type 1 (NF1) and "Neurofibromatosis type 2" are discrete and clinically distinguishable entities. The name of "neurofibromatosis type 2" has been changed to NF2-related schwannomatosis, to reflect the fact that neurofibromas do not occur in this syndrome and therefore the name "Neurofibromatosis" is factually incorrect. Furthermore, multiple schwannomas, a hallmark feature of NF2, can also occur in patients with mutations in genes including SMARCB1 and LZTR1, all exhibiting overlapping clinical features. Current understanding suggests that schwannomatosis (SWN) encompasses a range of clinical presentations consisting of clearly defined, separate subtypes which share a common phenotype of schwannomas. Recognizing these newly emerging subtypes, the International Consensus Group on Neurofibromatosis Diagnostic Criteria (I-NF-DC) proposed a revised nomenclature for NF2 and related disorders in 2022. This review article focuses on this critical update in diagnostic terminology, highlighting the key gene-related SWN subtypes relevant to neuroradiologists. By emphasizing molecular testing alongside clinical features, the revised system facilitates a more precise diagnosis, potentially paving the way for personalized treatment strategies. Additionally, the flexible structure accommodates future discoveries of genes associated with SWN.

Background: The spinal arteriovenous malformations (sAVMs) have been challenging entities to diagnose and treat. The small structure, important function, and complex vascular anatomy of the spinal cord increase the difficulty of treating sAVMs.

Objective: The combining holistic and local perspectives in the diagnosis and treatment of sAVMs were provided to teach spinal vascular anatomy and AVMs.

Methods and results: A holistic view is to fully understand the anatomical and physiological effects of intracranial vascular lesions on the spinal cord circulatory system, as well as the anatomical and physiological effects of local sAVM on the entire spinal cord circulatory system, such as the relationship between lesions and surrounding blood vessels. The local view is to fully understand the macroscopic and microscopic vascular architectural characteristics of the lesion. The local view is closely related to the treatment of lesions and the holistic view is closely related to the effectiveness and side effects of treatment, which should be given attention in current clinical practice. The early diagnosis and treatment of sAVMs may improve outcomes.

Conclusion: A holistic and local perspective is essential to developing an understanding of the angioarchitecture, pathophysiology, natural history, treatment options, and classification of the different types of sAVMs.

Dual-energy CT (DECT), also known as spectral CT, has advanced diagnostic capabilities in head and neck pathologies beyond those of conventional single-energy CT (SECT). By having images at two distinct energy levels, DECT generates virtual monoenergetic images (VMIs), iodine maps, and quantitative features such as iodine concentration (IC) and spectral Hounsfield unit attenuation curves (SHUAC), which leads to enhancing tissue characterization, reducing artifacts, and differentiating head and neck pathologies. This review highlights DECT's applications in evaluating head and neck squamous cell carcinoma (SCC), thyroid cartilage invasion, cervical lymph node metastasis, radiation therapy planning, post-treatment assessment, and role in other head and neck conditions, such as infection and sialolithiasis. Additionally, it explores emerging applications of DECT in radiomics and artificial intelligence. The review also discusses about integrating DECT into clinical practice requires overcoming workflow challenges and ensuring radiologist proficiency with its diverse image reconstructions. As DECT technology evolves, its integration promises to further enhance the efficacy of managing head and neck pathologies.

Flow diversion is a transformative approach in neurointerventional surgery for intracranial aneurysms that relies heavily on effective antiplatelet therapy. The ideal approach, including the timing of treatment, the use of dual antiplatelet therapy (DAPT), and the number of flow-diverter devices to use, remains unknown. DAPT, which combines aspirin with a thienopyridine like clopidogrel, prasugrel, or ticagrelor, is the standard regimen, balancing thromboembolic protection and hemorrhagic risk. The variable response to clopidogrel, influenced by genetic polymorphisms, necessitates personalized treatment strategies. Alternatives like prasugrel and ticagrelor provide superior efficacy in specific scenarios but require careful consideration of bleeding risks and costs. Platelet function testing plays a critical role in tailoring antiplatelet regimens for patients undergoing flow diversion for intracranial aneurysms. Special considerations were made for ruptured aneurysms, and the implications of the extensive metallic surface of flow diverters on platelet activation were noted. Emerging technologies such as drug-eluting flow diverters and reversal agents for P2Y12 inhibitors suggest a potential shift toward more refined antiplatelet strategies in the future. Personalized medication that is compatible with the stent structure and metal is essential for optimizing patient outcomes in cerebral flow diversion procedures. Ongoing research and multidisciplinary collaboration will be key in refining these strategies and enhancing the safety and efficacy of neurointerventional treatments.

Background and purpose: Inter-hypothalamic adhesions (IHAs) are parenchymal tissue bridges traversing the third ventricle, previously reported only in the pediatric population. We aim to understand the prevalence of IHA in the adult population, assess their size and location, and ultimately investigate whether IHA volumes correlate with age.

Materials and methods: Patients who underwent routine high-resolution 3D T2WI MRI studies of the temporal bone/internal auditory canal at an otolaryngology clinic between 2008 and 2014 were consecutively selected. The presence of IHAs was confirmed when a parenchymal structure could be traced across the third ventricle, connecting bilateral hypothalamus, and was visible in at least two planes. They were classified based on their location within the third ventricle, considering their connection with hypothalamic nuclei. Patient clinical information were collected from electronic charts. The prevalence and volumes of IHAs were calculated. Associations between age and IHA volume, as well as between IHA type, age, volume, and gender, were analyzed.

Results: 779 patients, with a mean age of 54.7 years were included. Among them, 44 IHAs were identified within 41 patients, resulting in a prevalence of 5.26% in our cohort. Type 1 IHA was the most frequently encountered type, comprising 70.5% of all cases. No significant correlation was observed between IHA volumes and age. Additionally, no associations were found between IHA type and age, volume, or gender.

Conclusion: IHAs are not exclusive to the pediatric population; they are also present in adults, with a prevalence of 5.26% in patients undergoing temporal bone/internal auditory canal MRI.

Objective: Predicting 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.

Methods: The 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.

Results: Early 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.

Conclusion: The 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.

Gadolinium contrast medium can serve as an alternative to iodinated contrast medium when the latter is unsuitable. In this report, we describe a case of a carotid-ophthalmic aneurysm in which angiograms were obtained using gadolinium contrast medium for flow-diverter stent placement due to the patient's history of bronchial asthma and hypersensitivity reactions to iodinated contrast medium. To enhance the visibility of gadolinium contrast medium, which typically provides lower contrast compared to iodinated contrast medium, we employed a contrast-enhancing and noise-reducing protocol on our image-guided therapy system. We performed catheterization and established working angles guided by a roadmap based on previous magnetic resonance angiography, the position of which was adjusted using cone-beam computed tomography performed before the intervention. This approach helped reduce the amount of contrast medium required. The procedure was successful and did not induce hypersensitivity reactions, morbidity, or mortality. Thus, the efficacy of the contrast-enhancing imaging protocol and the magnetic resonance angiography-based roadmap was confirmed. Measures must be taken to address gadolinium contrast medium-specific adverse events, limitations on the amount of contrast medium used, and the issue of low-contrast angiograms.