Neuroradiology最新文献

{"title":"Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance.","authors":"Stefan Cornelissen, Sammy M Schouten, Patrick P J H Langenhuizen, Henricus P M Kunst, Jeroen B Verheul, Peter H N De With","doi":"10.1007/s00234-025-03611-3","DOIUrl":"https://doi.org/10.1007/s00234-025-03611-3","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.</p><p><strong>Methods: </strong>This retrospective study employed MR images, including follow-up, from 1,015 patients (median age: 59, 511 men), resulting in 1,856 unique scans. Two nnU-Net models were trained using fivefold cross-validation to create a single-center segmentation model, along with a multi-center model using additional publicly available data. Geometric-based segmentation metrics (e.g. the Dice score) were used to evaluate model performance. To quantitatively assess the clinimetric reliability of the models, automated tumor volumes from a separate test set were compared to human inter-observer variability using the limits of agreement with the mean (LOAM) procedure. Additionally, new agreement limits that include automated annotations are calculated.</p><p><strong>Results: </strong>Both models performed comparable to current state-of-the-art VS segmentation models, with median Dice scores of 91.6% and 91.9% for the single and multi-center models, respectively. There is a stark difference in clinimetric performance between both models: automated tumor volumes of the multi-center model fell within human agreement limits in 73% of the cases, compared to 44% for the single-center model. Newly calculated agreement limits including the single-center model, resulted in very high and wide limits. For the multi-center model, the new agreement limits were comparable to human inter-observer variability.</p><p><strong>Conclusion: </strong>Models with excellent geometric-based metrics do not necessarily imply high clinimetric reliability, demonstrating the need to clinimetrically evaluate models as part of the clinical implementation process. The multi-center model displayed high reliability, warranting its possible future use in clinical practice. However, caution should be exercised when employing the model for small tumors, as the reliability was found to be volume-dependent.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780764","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":"A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.","authors":"ChenGang Yuan, Hang Qu, HuMing Dai, HaiXiao Jiang, DeMao Cao, LiYing Shao, LiangXue Zhou, AiJun Peng","doi":"10.1007/s00234-025-03599-w","DOIUrl":"https://doi.org/10.1007/s00234-025-03599-w","url":null,"abstract":"<p><strong>Purpose: </strong>Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was developed using preoperative MRI to assist clinicians in diagnosing pituitary microadenomas.</p><p><strong>Method: </strong>Sixty patients with pathologically diagnosed pituitary microadenomas, including hyperprolactinemia (n = 19), growth hormone microadenomas (n = 17), and adrenocorticotropin microadenomas (n = 24), were enrolled. An image edge-supervised same receptive field semantic segmentation network was developed based on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted images.</p><p><strong>Results: </strong>The mean Intersection over Unions of our neural network model were 0.7013 ± 0.3400, 0.7295 ± 0.321, and 0.8053 ± 0.3052 for the test sets of T1-weighted, T2-weighted, and contrast-enhanced T1-weighted sequences, respectively, while the Dice Similarity Coefficient values were 0.8075 ± 0.3895, 0.8192 ± 0.3733, and 0.8860 ± 0.3443 for the corresponding sequences. The performance on contrast-enhanced T1-weighted images was better than that of the other two MR sequences.</p><p><strong>Conclusions: </strong>The image edge-supervised same receptive field segmentation network can potentially be used to precisely identify pituitary microadenomas automatically with preoperative MRI. The developed model exhibited good performance with contrast-enhanced T1-weighted images and could help neurosurgeons accurately determine the locations of pituitary microadenomas.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780762","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":"Using generative adversarial deep learning networks to synthesize cerebrovascular reactivity imaging from pre-acetazolamide arterial spin labeling in moyamoya disease.","authors":"Guangming Zhu, Bin Jiang, Hui Chen, Jeremy J Heit, Micah Etter, G Alex Hishaw, Tobias D Faizy, Gary Steinberg, Max Wintermark","doi":"10.1007/s00234-025-03605-1","DOIUrl":"https://doi.org/10.1007/s00234-025-03605-1","url":null,"abstract":"<p><strong>Background: </strong>Cerebrovascular reactivity (CVR) assesses vascular health in various brain conditions, but CVR measurement requires a challenge to cerebral perfusion such as the administration of acetazolamide(ACZ), thus limiting widespread use. We determined whether generative adversarial networks (GANs) can create CVR images from baseline pre-ACZ arterial spin labeling (ASL) MRI.</p><p><strong>Methods: </strong>This study included 203 Moyamoya cases with a total of 3248 pre- and post-ACZ ASL Cerebral Blood Flow (CBF) images. Reference CVRs were generated from these CBF slices. From this set, 2640 slices were used to train a Pixel-to-Pixel GAN consisting of a generator and discriminator network, with the remaining 608 slices reserved as a testing set. Following training, the pre-ACZ CBF in the testing set was introduced to the trained model to generate synthesized CVR. The quality of the synthesized CVR was evaluated with structural similarity index(SSI), spatial correlation coefficient(SCC), and the root mean squared error(RMSE), compared with reference CVR. The segmentations of the low CVR regions were compared using the Dice similarity coefficient (DSC). Reference and synthesized CVRs in single-slice and individual-hemisphere settings were reviewed to assess CVR status, with Cohen's Kappa measuring consistency.</p><p><strong>Results: </strong>The mean SSIs of the CVR of training and testing sets were 0.943 ± 0.019 and 0.943 ± 0.020. The mean SCCs of the CVR of training and testing sets were 0.988 ± 0.009 and 0.987 ± 0.011. The mean RMSEs of the CVR are 0.077 ± 0.015 and 0.079 ± 0.018. Mean DSC of low CVR area of testing sets was 0.593 ± 0.128. Visual interpretation yielded Cohen's Kappa values of 0.896 and 0.813 for the training and testing sets in the single-slice setting, and 0.781 and 0.730 in the individual-hemisphere setting.</p><p><strong>Conclusions: </strong>Synthesized CVR by GANs from baseline ASL without challenge may be a useful alternative in detecting vascular deficits in clinical applications when ACZ challenge is not feasible.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780766","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":"Retrograde recanalization for vertebral artery occlusion without a stump (REVANS): a technical note.","authors":"Jian Wang, Xin Jiang, Hongbo Zheng, Li He, Fayun Hu","doi":"10.1007/s00234-025-03602-4","DOIUrl":"https://doi.org/10.1007/s00234-025-03602-4","url":null,"abstract":"<p><p>Recent case reports suggest that endovascular recanalization may be safe and feasible for vertebral artery occlusion (VAO) patients without a stump, however, comprehensive management strategies for endovascular recanalization remain poorly understood. In this technical note, we describe the REVANS technique in patients with VAO lacking a stump. The REVANS technique demonstrates promise as a viable option for managing symptomatic non-acute VAO without a visible stump. This approach leverages cervical collateral vessels to retrogradely access and recanalize occluded vertebral artery segments, offering potential benefits in improving patient outcomes.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772870","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":"Development of a machine learning model to predict changes in neuroimaging profiles among acute ischemic stroke patients following delayed transfer for endovascular thrombectomy.","authors":"Huanwen Chen, Paige Skorseth, Scott Rewinkel, Daniel Kim, Sonesh Amin, Scott Shakal, Ryan Priest, Gary Nesbit, Wayne Clark, Marco Colasurdo","doi":"10.1007/s00234-025-03600-6","DOIUrl":"https://doi.org/10.1007/s00234-025-03600-6","url":null,"abstract":"<p><strong>Introduction: </strong>Endovascular thrombectomy (EVT) patient selection depends on neuroimaging. However, interhospital transfer delays can lead to neuroimaging changes, whether and when repeat imaging is necessary are unclear. Herein, we develop a machine learning model (MLM) to predict vessel recanalization, ischemia progression, and imaging stability for EVT candidates who experience delayed interhospital transfer.</p><p><strong>Methods: </strong>This retrospective study included EVT candidates with internal carotid or middle cerebral artery occlusion stroke transferred 1.5-6.0 h after initial imaging. Clinical and radiographic data were collected. A gradient-boosted tree-based MLM (XGBoost) was trained and optimized on 66% of the cohort (randomly selected) using 10-fold cross-validation, and the MLM was independently validated on the remaining, untouched 33% of the study cohort. Model performance was assessed using areas under the receiver operating characteristics curve (AUC) for discrimination, F1 scores for precision/recall, and Brier scores for calibration.</p><p><strong>Results: </strong>Among 317 patients, 69.4% had stable imaging, 14.5% showed ischemia progression (ASPECTS drop ≥ 2), and 16.1% had vessel recanalization. The MLM was developed and optimized in the training cohort (n = 212). NIH stroke scale improvement, onset-to-imaging time, intravenous thrombolysis, initial ASPECTS, and collateral score were important features. In the validation cohort (n = 105), the MLM achieved AUCs of 0.81 (95%CI 0.72-0.90) for imaging stability, 0.82 (95%CI 0.72-0.91) for ischemia progression, and 0.89 (95%CI 0.77-1.00) for vessel recanalization. F1 scores were 0.87 and 0.95 for stability and no recanalization, with Brier scores of 0.17 and 0.08, respectively.</p><p><strong>Conclusion: </strong>Our MLM accurately predicts imaging changes among EVT candidates who experienced transfer delays.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143764527","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":"Endovascular treatment of dural arteriovenous fistula in a neonate through transcarotid approach.","authors":"Cesar Augusto Ferreira Alves Filho, Fausto Oliveira Braga, José Alberto Almeida Filho, Rodrigo Twardowski Scherer, Filipi Fim Andreão, Sávio Batista, Paulo José da Mata Pereira, Paulo Niemeyer Filho, Elias Tanus","doi":"10.1007/s00234-025-03598-x","DOIUrl":"https://doi.org/10.1007/s00234-025-03598-x","url":null,"abstract":"<p><p>We present a rare case of endovascular transarterial treatment in a newborn with symptomatic dural arteriovenous fistula (DAVF). Through direct carotid puncture, complete occlusion of the fistula was achieved in a single session. This therapeutic approach demonstrates safety and efficacy in neonatal DAVF treatment. The patient showed significant improvement, with symptoms resolved and complications absent. The successful outcome highlights the importance of early recognition and prompt intervention in pediatric DAVFs.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143764532","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":"Patterns of abnormal magnetic susceptibility in the brain: an image-based review.","authors":"Kendal Weger, Carrie Carr, V Michelle Silvera, Michael Oien, Heidi Edmonson, Bobby Do, Jason Little","doi":"10.1007/s00234-025-03588-z","DOIUrl":"https://doi.org/10.1007/s00234-025-03588-z","url":null,"abstract":"<p><strong>Purpose: </strong>This article is designed to facilitate a systematic approach to formulating a radiologic differential diagnosis based on the pattern of abnormal magnetic susceptibility on MRI. Susceptibility-weighted imaging (SWI) is a three-dimensional sequence with excellent spatial resolution and superior contrast resolution. It originated from and has largely replaced two-dimensional T2^* weighted sequences. Currently, SWI refers to any high-spatial resolution susceptibility-enhanced sequence from different MR vendors.</p><p><strong>Methods: </strong>There are many entities that have specific patterns unique on SWI. We chose both entities that are commonly encountered in the clinical practice and unusual entities that may present as challenges in making the diagnosis. Each entity is discussed in detail, focusing on salient imaging features seen with SWI and key differences highlighted from other entities.</p><p><strong>Results: </strong>In the first category, lesions with randomly distributed susceptibility abnormalities are described. Further classification is made based on the presence of foci of susceptibility located diffusely through the brain (e.g. diffuse axonal injury) noting the subtleties of the shape, size, and preferential distribution of these foci. Special attention is also directed toward entities that, while random in location, are associated with a specific lesion (e.g. abscess). Finally, clues to correctly diagnose the various pathologies are provided. In the second category, the focus is on lesions that can be classified based upon anatomic locations whether peripheral (e.g. sulcal hemosiderin) versus central distribution.</p><p><strong>Conclusion: </strong>Knowledge of the patterns of susceptibility on SWI and the physics behind this technique are essential for facilitating MR interpretation.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753653","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":"Machine learning radiomics for H3K27M mutation prediction in gliomas: A systematic review and meta-analysis.","authors":"Bardia Hajikarimloo, Salem M Tos, Alireza Kooshki, Mohammadamin Sabbagh Alvani, Mohammad Shahir Eftekhar, Arman Hasanzade, Roozbeh Tavanaei, Mohammadhosein Akhlaghpasand, Rana Hashemi, Mohammadreza Ghaffarzadeh-Esfahani, Ibrahim Mohammadzadeh, Mohammad Amin Habibi","doi":"10.1007/s00234-025-03597-y","DOIUrl":"https://doi.org/10.1007/s00234-025-03597-y","url":null,"abstract":"<p><strong>Purpose: </strong>Noninvasive prediction and identification of the H3K27M mutation play an important role in optimizing therapeutic strategies and improving outcomes in gliomas. In this systematic review and meta-analysis, we aimed to evaluate the performance of machine learning (ML)-based models in predicting H3K27M mutation in gliomas.</p><p><strong>Methods: </strong>Literature records were retrieved on September 16th, 2024, in PubMed, Embase, Scopus, and Web of Science. Records were screened according to the eligibility criteria, and the data from the included studies were extracted. The meta-analysis, sensitivity analysis, and meta-regression were conducted using R software.</p><p><strong>Results: </strong>A total of 15 studies were included in our study. Our meta-analysis demonstrated a pooled AUC, sensitivity, and specificity of 0.87 (95% CI: 0.77-0.97), 92% (95% CI: 83%-96%), and 89% (95% CI: 86%-91%)), respectively. The subgroup meta-analysis revealed that despite the higher sensitivity of the deep learning (DL) models, the sensitivity is not superior to ML (P = 0.6). In contrast, the ML-based pooled specificity was significantly higher (P < 0.01). The meta-analysis revealed a 78.1 (95% CI: 33.3 - 183.5). The SROC curve indicated an AUC of 0.921, and the estimated sensitivity is 0.898 concurrent with the false positive rate of 0.126, which indicates high sensitivity with a low false positive rate.</p><p><strong>Conclusion: </strong>Our systematic review and meta-analysis demonstrated that ML-based magnetic resonance imaging (MRI) radiomics models are associated with promising diagnostic performance in predicting H3K27M mutation in gliomas.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753652","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":"The Australian Diagnostic Criteria for Contrast-Induced Encephalopathy.","authors":"Frederick P Mariajoseph, Leon T Lai, Adrian Praeger, Ronil V Chandra, Justin Moore, Hamed Asadi, Laetitia de Villiers, Tony Goldschlager, Calvin Gan, Kevin Zhou, Albert Ho Yuen Chiu, Ferdinand Miteff, Ramon Martin Banez, Thanh Phan, Davor Pavlin-Premrl, Winston Chong, Sophie Dunkerton, Anoop Madan, Lee-Anne Slater","doi":"10.1007/s00234-025-03601-5","DOIUrl":"https://doi.org/10.1007/s00234-025-03601-5","url":null,"abstract":"<p><strong>Introduction: </strong>Contrast-induced encephalopathy (CIE) is a recognised complication of contrast administration, however diagnosis remains challenging due to its symptom overlap with other neurological conditions and the absence of formal diagnostic criteria.</p><p><strong>Methods: </strong>A modified Delphi study was performed. Consultant physicians with active clinical experience with CIE patients were invited from neurovascular centres in Australia. Initial diagnostic items were derived from an extensive literature review and analysis of local institutional cases across Australia. Three Delphi rounds were conducted. Consensus was defined as ≥ 75% agreement.</p><p><strong>Results: </strong>Seventeen neurovascular specialists from nine neurovascular centres participated (81.0% response rate) between May 2024 and July 2024. In round 1, 15 diagnostic items were presented to participants, which were revised and one additional criteria suggested. In round 2, 14/16 diagnostic items achieved consensus. In round three 14/14 items achieved consensus. Ultimately, a 14-item diagnostic criteria was developed based on participant consensus. The absolute criteria exclude CIE if symptom onset is more than 24 h after contrast administration, or if symptoms can be explained by vessel occlusion/territory ischaemia, intracranial haemorrhage, epilepsy, metabolic derangement, intracranial malignancy or head trauma. The supporting criteria indicate that CIE is more probable if symptoms are reversible, correspond with the distribution of contrast administration, or are associated with reversible contrast staining, cerebral oedema or cortical/subcortical MRI signal change.</p><p><strong>Conclusion: </strong>This study proposes a 14-item diagnostic criteria for CIE based on expert consensus in Australia. Further research is needed to refine CIE as a clinical entity.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143743288","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":"Transradial versus transfemoral access in diagnostic cerebral angiography: a comprehensive systematic review and meta-analysis of clinical outcomes and complications.","authors":"Abdelrahman M Hamouda, Tasnim El Gazar, Mohamed Ahmed Ali, Saroj Kumar Jha, Mark Cwajna, Nicholas Kendall, Mohamed Derhab, Sherief Ghozy, Zach Pennington, Rahul Kumar, Kogulavadanan Arumaithurai, Waleed Brinjikji, David F Kallmes","doi":"10.1007/s00234-025-03581-6","DOIUrl":"https://doi.org/10.1007/s00234-025-03581-6","url":null,"abstract":"<p><strong>Background: </strong>Diagnostic Cerebral Angiography (CA) is a relatively common procedure that provides detailed evaluation of the brain's blood vessels. With the growing preference for Transradial artery (TRA) access over Transfemoral artery (TFA) access, our review aims to compare clinical outcomes and complications between these two approaches.</p><p><strong>Methods: </strong>We carried out a systematic review using PubMed, Embase, Web of Science, Scopus databases, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Inclusion was limited to studies that exclusively compared TRA versus TFA approaches for cerebral diagnostic purposes.</p><p><strong>Results: </strong>Our study included 27 studies encompassing a total of 12,806 patients. The TRA arm comprised 6,284 patients with a median age of 57.9 years, and 46.4% were male. The TFA arm included 6,522 patients with a median age of 59.0 years, and 44.8% were male. Our analysis revealed that the TFA group had a higher successful Cerebral Angiography (CA) rate (OR = 0.62, p = 0.03), and lower crossover rate (OR: 2.85, p < 0.01) compared to the TRA group. However, the TRA group demonstrated a significantly lower rate of total complications (OR: 0.52, p < 0.01) and shorter hospital length of stay (LOS) in hours ([MD]: -33.25, p < 0.001) compared to the TFA group. There were no significant differences between groups in terms of procedural metrics.</p><p><strong>Conclusion: </strong>Our review highlighted the superiority of the transfemoral artery approach in terms of success rates and lower crossover rates. However, transradial artery access may be preferred due to its association with lower complication rates and shorter hospital stays, aligning with patient-centered outcomes.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143743296","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}