Neuroradiology Journal最新文献

We describe a novel application of photon-counting detector CT (PCD-CT) in neurovascular imaging by harnessing the improved spatial resolution, attenuation of electronic noise, and reduction of metal artifacts. The presented case offers the unique challenge of high-quality imaging for the assessment of treated and untreated intracranial saccular aneurysms, in the setting of metal artifacts from embolization coils. Our goal was to explore optimized reconstruction parameters for ultra-high-resolution imaging (UHR) using a dedicated, sharp neurovascular kernel (Hv72) and the highest strength of quantum iterative reconstruction (QIR-4) for detailed characterization of the vasculature. Virtual monoenergetic images (VMIs) and iterative metal artifact reduction (IMAR) were employed to investigate metal artifact reduction techniques. PCD-CT has the promising potential to enhance patient care in the follow-up of patients with treated aneurysms requiring more complex imaging parameters and image post-processing due to intracranial artifacts.

Background: The Woven EndoBridge 17 (WEB-17) is the latest advancement in the WEB device family. Comprehensive data on its occlusion rates, procedural complications, and mortality is lacking. This meta-analysis aimed to evaluate the efficacy and safety of the WEB-17 device in intracranial aneurysms (IAs).

Methods: A systematic literature search was conducted from inception to October 2023 across four databases for studies on IAs treated with WEB 17. Primary outcomes included adequate angiographic occlusion at last follow-up and a composite of intraprocedural and postprocedural complications. Comparative meta-analysis between WEB-17 and its predecessor versions (pvWEB) was performed. Subgroup analyses by IA rupture status were also conducted for the primary outcomes.

Results: Eleven studies with 880 patients and 933 IAs were included. Regarding efficacy, the rate of adequate occlusion at last follow-up was 91% (95% CI 86%-94%) and the complete occlusion rate was 69% (95% CI 65%-73%). Safety outcomes demonstrated a composite complication rate of 7% (95% CI 4%-11%), an intraprocedural complication rate of 7% (95% CI 5%-9%; I2 = 0%), and a postprocedural complication rate of 2% (95% CI 1%-5%; I2 = 0%). No differences were found between WEB-17 and pvWEB in terms of adequate occlusion (WEB-17: 87.7% vs pvWEB: 80.4%; OR = 1.35, 95% CI 0.71-2.55) and safety composite outcome (WEB-17: 8.7% vs pvWEB: 10%; OR = 1.05, 95% CI 0.51-2.16). Subgroup analysis did not evidence heterogeneity between subgroups.

Conclusions: The WEB-17 device demonstrates promising efficacy and safety profiles for the treatment of IAs. However, these results should be interpreted with caution due to the limited quality of evidence in the included studies. Further prospective, randomized studies are needed to validate these findings.

Purpose: Occlusion of the distal internal carotid artery can simulate a proximal occlusion of its cervical tract on CT angiography in patients with acute ischemic stroke, that is, pseudo-occlusion. As true and false carotid occlusions can present similarly on non-invasive imaging in patients undergoing endovascular treatment for stroke, our study aimed to evaluate clinical and technical differences of these conditions and the possible consequences of a misdiagnosis. Methods: We retrospectively reviewed consecutive patients who underwent mechanical thrombectomy for acute ischemic stroke at a single center between July 2015 and May 2022 and included patients with absent opacification of the cervical carotid artery on CT-angiography. Digital subtraction angiography (DSA) imaging and procedural data were evaluated to define the actual localization of the occlusion. We compared imaging and clinical data between patients with true and false carotid occlusion, including collateral circulation at CTA, revascularization grade, and clinical outcome at 3 months. Results: A total of 116 patients were included, 63 (54%) of whom had true occlusion of cervical internal carotid artery. Compared to the pseudo-occlusion group, collateral circulation at CTA was moderate to good in 75% of cases (vs 32%; p < 0.0001) and the mean ASPECT score at 24 h was 7 versus 2 (p < 0.0001). Modified Rankin scale 0-2 at 90 days was more frequent in patients with true occlusion than those with pseudo-occlusion (48 vs 11%; p = 0.0002). Conclusion: Pseudo-occlusion of the cervical internal carotid artery in patients with acute ischemic stroke appears to be associated with worst prognosis and poorer collateral circulation in comparison with tandem occlusion.

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.