Clinical Neuroradiology最新文献

{"title":"Redefining First Pass in the New Era of Super-Large-Bore Aspiration Catheters.","authors":"Mayank Goyal, Sophia Hohenstatt","doi":"10.1007/s00062-026-01655-3","DOIUrl":"10.1007/s00062-026-01655-3","url":null,"abstract":"","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1133-1135"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DICOM-Based Quantification of MRI Artifact from Auditory Implants: a Technical Note Comparing Bone-Conduction- and Cochlear Implants.","authors":"Benjamin Straub, Susan Arndt, Horst Urbach, Lucas I Becker","doi":"10.1007/s00062-026-01675-z","DOIUrl":"10.1007/s00062-026-01675-z","url":null,"abstract":"<p><strong>Purpose: </strong>MRI in patients with auditory implants is limited by implant-related signal void, geometric distortion, and intravoxel dephasing. Artifact extent is often described qualitatively. We aimed to quantify MRI artifact burden from a novel transcutaneous bone-conduction implant (SentioTM) and to compare it with cochlear implant controls under routine, label-compliant 1.5 T clinical conditions.</p><p><strong>Methods: </strong>We retrospectively analyzed MRI examinations of patients with a SentioTM implant (n = 7) and cochlear implant controls (n = 5). All scans were performed at 1.5 T, the manufacturer-approved field strength for the SentioTM Ti implant, on the same scanner using routine transverse turbo spin-echo sequences (T2-weighted and T1-weighted; 5‑mm slice thickness). Artifacts were quantified slice-by-slice with a custom Python-based DICOM pipeline. The artifact-to-brain ratio (ABR, %) and maximum void area (cm²) were computed; ABRmax (peak slice) served as patient-level summary. Groups were compared using the Mann-Whitney U test and Cliff's delta.</p><p><strong>Results: </strong>SentioTM implants showed smaller and more confined artifacts. Median ABRmax was 1.1% [IQR 0.2] with a median maximum void area of 1.7 cm² [IQR 0.4]. Cochlear implant controls showed larger artifacts (ABRmax 2.6% [IQR 1.0]; median maximum void area 3.8 cm² [IQR 2.0]; p = 0.007-0.01; δ = 0.81-0.89). Supratentorial diagnostic image quality outside the immediate implant region was preserved in all T2w/T1w SentioTM examinations and partially preserved in 3/5 cochlear implant examinations.</p><p><strong>Conclusion: </strong>Quantitative artifact assessment using ABRmax is feasible in routine 1.5 T MRI. Under identical protocol conditions, the SentioTM implant produced a smaller and more localized MRI artifact burden than the cochlear implant controls examined here. Routine turbo spin-echo imaging remained diagnostically useful outside the implant region.</p>","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1113-1117"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148148746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Accuracy of Machine Learning Models in Predicting Functional Outcome of Thrombectomy for Acute Posterior Circulation Artery Occlusion: a Systematic Review and Meta-Analysis.","authors":"Luciano Falcão, Karina de Lima Andrade Pereira, Kenzo Ogasawara Donato, João Victor Pereira Gonzalez, Victor Arthur Ohannesian, Anderson Matheus Pereira da Silva, João Vitor Andrade Fernandes, Rafael Hummes Müller, Ocílio Ribeiro Gonçalves, Davi J F Solla, Hasan T Ozgur, Ahmet Günkan","doi":"10.1007/s00062-026-01637-5","DOIUrl":"10.1007/s00062-026-01637-5","url":null,"abstract":"<p><strong>Background: </strong>Mechanical thrombectomy (MT) is the standard treatment for acute posterior circulation artery occlusion (PCAO), but predicting outcomes remains challenging. Existing prognostic models combine clinical, imaging, and procedural variables but show inconsistent performance. Our objective is to evaluate the diagnostic accuracy of Machine Learning (ML) models in predicting favorable functional outcomes of thrombectomy for acute PCAO.</p><p><strong>Methods: </strong>We conducted a systematic review and bivariate diagnostic meta-analysis of PubMed, Embase, and Web of Science. Eligible studies evaluated ML predicting favorable outcomes (Modified Rankin Scale of 0 to 3 at hospital discharge or at 90 days) after MT for PCAO. Pooled sensitivity, specificity, and area under the summary receiver operating characteristic curve (AUC) were calculated with a bivariate random-effects model.</p><p><strong>Results: </strong>Five studies including 1739 patients met inclusion criteria. Pooled sensitivity was 78% (95% CI: 59-89%; I² = 89.29%) and specificity was 80% (95% CI: 74-85%; I² = 46.06%) for a favorable outcome. The Summary Receiver Operating Characteristic (SROC) curve yielded an AUC of 83% (95% CI: 80-86%). Subgroup analyses revealed that studies including patients with successful reperfusion (mTICI ≥ 2b) had significantly lower sensitivity and specificity. Random forest-based models achieved greater specificity, and multicenter studies demonstrated inferior specificity compared to single-center designs.</p><p><strong>Conclusions: </strong>ML models demonstrate good diagnostic accuracy in predicting functional outcomes after thrombectomy for acute PCAO. Integration of these models into clinical practice may support individualized decision-making and resource allocation, although prospective validation and improved reporting are needed before routine implementation.</p>","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"819-830"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147389494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Process, Performance, and Outcome Goals in Neurointervention Trials: Lessons from Sports Psychology.","authors":"Umberto Pensato, Johanna Ospel","doi":"10.1007/s00062-026-01663-3","DOIUrl":"10.1007/s00062-026-01663-3","url":null,"abstract":"","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1141-1142"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"General Versus Non-General Anesthesia in Endovascular Treatment for Posterior Circulation Stroke: a Systematic Review and Meta-analysis.","authors":"Lucca Tamara Alves Carretta, Rudolfh Batista Arend, Henrique Padilha Gnoatto, Victor Luiz Ferreira Kauer, Bruna Lara Zardin, Filipe Virgilio Ribeiro, Mariana Letícia de Bastos Maximiano, Anderson Silva Corin, Nicole Baptista de Oliveira, Tassiane Cristina Morais, Fernando Rocha Oliveira, Leandro de Assis Barbosa, Alex Roman, Hasan T Ozgur, Ahmet Günkan","doi":"10.1007/s00062-026-01621-z","DOIUrl":"10.1007/s00062-026-01621-z","url":null,"abstract":"<p><strong>Purpose: </strong>This systematic review and meta-analysis aimed to compare general anesthesia (GA) versus non-GA effects on clinical and procedural outcomes during endovascular therapy (EVT) for posterior circulation stroke.</p><p><strong>Methods: </strong>Following PRISMA 2020, we systematically searched PubMed, Cochrane, Web of Science, Scopus, Embase until June-2025 for comparative studies on GA vs. non-GA in posterior circulation EVT. Data on 90-day mortality, intracranial hemorrhage (any, aICH; symptomatic, sICH), functional independence (modified Rankin Scale [mRS] 0‑2/0-3), and successful recanalization (mTICI 2b-3) were extracted.</p><p><strong>Results: </strong>Fourteen studies, 3899 patients (1950 GA, 1949 non-GA) were included. No significant differences between GA and non-GA were found for 90-day all-cause mortality (OR 1.23; 95% CI: 0.92-1.63), aICH (OR 0.72; 95% CI: 0.45-1.14), sICH (OR 0.79; 95% CI: 0.58-1.06), or functional independence. However, GA significantly increased the odds of successful recanalization (mTICI 2b-3) (OR 1.24; 95% CI: 1.01-1.52; p = 0.0389).</p><p><strong>Conclusion: </strong>In posterior circulation EVT, GA enhances mTICI 2b‑3 but offers no demonstrable clinical advantage or disadvantage over non-GA for mortality, aICH sICH, or functional independence. An individualized anesthetic approach, balancing procedural stability against physiological risks, is advised. Future randomized trials with optimized physiological management are crucial to align technical and clinical gains.</p>","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"805-817"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147289177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Initial Multicenter Evaluation of a Novel Anchoring Exchange Device: AI-based Quantitative Distal Tip-Motion Analysis.","authors":"Kenichi Kono, Nobuyuki Sakai, Yuya Sakakura, Takeshi Fujimoto, Yoshinori Akiyama, Fuminori Shimizu","doi":"10.1007/s00062-026-01650-8","DOIUrl":"10.1007/s00062-026-01650-8","url":null,"abstract":"<p><strong>Purpose: </strong>Exchange maneuvers during intracranial angioplasty and stent deployment can cause unintended distal tip motion, potentially leading to vessel injury. We evaluated a novel anchoring exchange device (Medilizer; Medikit, Tokyo, Japan), a 320-cm 0.014-inch wire with a retrievable self-expanding stent at the distal tip, designed to stabilize the distal position during exchange maneuvers and approved for clinical use in Japan.</p><p><strong>Methods: </strong>We compared exchange maneuvers using conventional wires with those using a Medilizer during angioplasty of intracranial stenosis performed at three institutions. Biplane fluoroscopic sequences (frontal and lateral views) were analyzed using an AI-assisted tracking system to quantify the trajectory length of distal tip motion in each view.</p><p><strong>Results: </strong>Seventeen consecutive procedures (10 conventional wire cases and 7 Medilizer cases) were included. In one Medilizer case, the distal tip was outside the field of view in one projection, which was excluded from the analysis. Consequently, 20 conventional wire and 13 Medilizer views were analyzed. The trajectory length of the distal tip was significantly shorter with the Medilizer than with conventional wires (3.3 ± 1.5 mm vs. 35.9 ± 20.0 mm; p < 0.001), corresponding to an approximately 90% reduction. No adverse events occurred in any of the 17 procedures.</p><p><strong>Conclusion: </strong>Even in this initial cohort, the magnitude of improvement in distal tip motion strongly suggests clinically meaningful stability advantages of this anchoring exchange device. Furthermore, AI-assisted quantitative evaluation can provide an objective measure of endovascular device performance, warranting further validation studies.</p>","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"953-962"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147671007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plaque-Level Machine Learning Prediction of Intraplaque Hemorrhage in Carotid Arteries Using Computed Tomography Angiography.","authors":"Juan Long, Xiaohan Liu, He Zhang, Zhen Wang, Yang Wu, Chong Meng, He Zhang, Zhongxiao Liu, Aiyun Sun, Chunfeng Hu, Kai Xu, Yankai Meng","doi":"10.1007/s00062-026-01656-2","DOIUrl":"10.1007/s00062-026-01656-2","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Carotid artery plaques, especially those with intraplaque hemorrhage (IPH), are significant contributors to ischemic stroke. Although high-resolution magnetic resonance vessel-wall imaging (HR-MR-VWI) is the gold standard for assessing plaque vulnerability, its limited availability and high cost pose challenges. Computed tomography angiography (CTA) offers a more accessible, non-invasive alternative, but its ability to detect IPH and assess plaque instability remains underexplored. Machine learning techniques have shown promise in improving the prediction of carotid plaque vulnerability using CTA.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;This study aimed to develop and validate a machine learning model using CTA to predict IPH in carotid plaques. The model integrated key imaging features, including plaque composition, vascular lumen geometry, and perivascular adipose tissue (PVAT), with HR-MR-VWI serving as the reference standard. The goal was to evaluate the model's potential for non-invasive plaque vulnerability prediction, particularly in clinical settings where MRI is not available.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A retrospective analysis was conducted on patients who underwent both carotid CTA and HR-MR-VWI within one month. Key plaque features, including composition, vascular lumen geometry, and PVAT, were extracted from CTA. The dataset was split into training (70%) and validation (30%) sets. Feature selection was performed using LASSO regression, followed by model development with logistic regression, random forest, XGBoost, and support vector machine (SVM). Hyperparameter tuning was performed using 10-fold cross-validation. Model performance was assessed using AUC, ROC curves, calibration curves, precision-recall curves, and confusion matrices. SHAP analysis was employed to evaluate the importance of each feature.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In the validation cohort, the Random Forest model achieved an AUC of 0.679, sensitivity of 86.0%, specificity of 45.6%, accuracy of 63.0%, positive predictive value (PPV) of 54.4%, and negative predictive value (NPV) of 81.2%. Feature selection using LASSO regression identified perivascular adipose tissue (PVAT) attenuation, maximum diameter stenosis (MDS), and fibrotic volume (FV) as the most important predictors. SHAP analysis confirmed MDS as the most influential feature, followed by FV and PVAT. The model demonstrated good calibration, with predicted probabilities aligning closely with observed outcomes. Decision Curve Analysis (DCA) showed that the Random Forest model provided the highest net benefit at higher decision thresholds, supporting its clinical potential for predicting plaque vulnerability.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study demonstrates the potential of a CTA-based machine learning model for predicting carotid plaque vulnerability, with PVAT, MDS, and FV as key predictors. While the model shows good sensitivity, its moderate specificity suggest","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1023-1037"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"61. Jahrestagung der Deutschen Gesellschaft für Neuroradiologie e. V.","authors":"","doi":"10.1007/s00062-026-01715-8","DOIUrl":"10.1007/s00062-026-01715-8","url":null,"abstract":"","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1-138"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148966916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MR Elastography Findings in a Cytotoxic Lesion of the Corpus Callosum (CLOCC): a Case Report with Longitudinal Follow-up.","authors":"Hannah Mies, Peter Arthur Ringleb, Ralph Sinkus, Katharina Schregel","doi":"10.1007/s00062-026-01649-1","DOIUrl":"10.1007/s00062-026-01649-1","url":null,"abstract":"","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"1125-1131"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147671026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Deep Learning Reconstruction for Detection of Early Ischemic Changes in NCCT: Comparison with ASIR-V in Acute Stroke.","authors":"Michal Pula, Adrian Korbecki, Krzysztof Winiarczyk, Arkadiusz Kacała, Kamil Litwinowicz, Michal Sobanski, Julita Nadwodna, Agata Zdanowicz-Ratajczyk, Maciej Guziński","doi":"10.1007/s00062-026-01645-5","DOIUrl":"10.1007/s00062-026-01645-5","url":null,"abstract":"<p><strong>Purpose: </strong>Evaluation of the impact of Deep Learning Image Reconstruction (DLIR) compared to Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) on image quality and early ischemic changes detection on non-contrast computed tomography (NCCT) in stroke suspected patients. A secondary objective was to determine the potential influence of reconstruction algorithm on ASPECT scoring relative to automated e-ASPECT score.</p><p><strong>Methods: </strong>Consecutive patients undergoing NCCT within 6 hours of symptom onset were retrospectively included. Images were reconstructed using ASIR-V and high-strength DLIR. Four readers with varying experience independently assessed subjective image quality, gray-white matter differentiation, diagnostic confidence, presence of ischemic lesions and ASPECTS scoring. Diagnostic performance (accuracy, sensitivity, specificity) was calculated using e-ASPECTS as reference. Evaluation time was recorded.</p><p><strong>Results: </strong>DLIR significantly improved subjective image quality and gray-white matter contrast compared with ASIR-V (odds ratios 2.96-3.96; p 0.001). Diagnostic performance for detecting early ischemic changes showed no significant difference, with similar accuracy, sensitivity and specificity. Evaluation time did not differ. A trend toward higher specificity and reduced bias for ASPECTS ≥6 was observed with DLIR, but mixed-model analysis did not confirm statistical significance.</p><p><strong>Conclusion: </strong>DLIR improves subjective image quality in acute stroke NCCT but does not significantly improve detection accuracy or ASPECTS scoring compared with ASIR-V. A tendency toward improved specificity was observed; further studies with larger cohorts are needed.</p>","PeriodicalId":10391,"journal":{"name":"Clinical Neuroradiology","volume":" ","pages":"941-951"},"PeriodicalIF":2.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13521977/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}