Journal of Neuroradiology最新文献

{"title":"Sporadic progressive ataxia and palatal tremor syndrome","authors":"Iasmim Portela Maifrede , Daniel Sabino de Oliveira , Thiago Cardoso Vale","doi":"10.1016/j.neurad.2025.101392","DOIUrl":"10.1016/j.neurad.2025.101392","url":null,"abstract":"","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"53 1","pages":"Article 101392"},"PeriodicalIF":3.3,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145365629","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":"Optimizing imaging protocols and clinical correlation in pediatric MRgLITT: A constructive appraisal of Hu et al","authors":"Parth Aphale, Himanshu Shekhar, Shashank Dokania","doi":"10.1016/j.neurad.2025.101393","DOIUrl":"10.1016/j.neurad.2025.101393","url":null,"abstract":"","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"53 1","pages":"Article 101393"},"PeriodicalIF":3.3,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145349662","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":"Time-of-day study on brain metabolism using proton magnetic resonance spectroscopy","authors":"Clément Giraud ,&nbsp;Arnaud Poinas ,&nbsp;Landoline Bonnin ,&nbsp;Luc Pellerin ,&nbsp;Carole Guillevin ,&nbsp;Rémy Guillevin","doi":"10.1016/j.neurad.2025.101395","DOIUrl":"10.1016/j.neurad.2025.101395","url":null,"abstract":"<div><div>Most human physiological processes follow circadian rhythms such as glucose metabolism and neuronal activity, thereby playing a major role in brain metabolism regulation. Proton Magnetic Resonance Spectroscopy (¹H-MRS) has become a valuable tool for quantification of brain metabolism in clinical settings. Nonetheless, only limited evidence of brain metabolism variation throughout the day has been found, restricted to specific brain regions or limited by a sample size. The aim of this study was to investigate time-of-day effect on brain metabolism in ¹H-MRS of different brain regions associated with circadian rhythms in healthy adults.</div><div>This prospective monocentric study included 39 healthy volunteers aged between 25 and 40 years. They underwent three 3T MRI examinations the same day at 7:30, 13:30 and 17:30. Two CSI MRS sequences were acquired to study brain regions of the basal ganglia and semi-oval center. A linear mixed model was used to investigate differences between session times, sex and brain hemisphere on acquired total Choline (tCho), total N-Acetyl-Aspartate (tNAA), and Lactate (Lac).</div><div>Models showed a significant decrease in tCho/tNAA in the last session of -1.60% (p = 0.017) and a lower value of tCho/tCr of -9.74% (p = 0.014) and tCho/tNAA of -7.98% (<em>p</em> = 0.044) for women as compared with men. In the right hemisphere a higher value of tNAA/tCr of +2.84% (p &lt; 0.001) was found, while tCho/tNAA was lower by -1.60% (p = 0.003) compared to the left hemisphere.</div><div>The metabolite ratios under investigation were not affected by circadian rhythms, except for a small decrease of tCho/tNAA at 17:30. However, sex and brain hemispheres had a significant impact on brain metabolism. While brain MRS examination for most common metabolites could be carried out at any time of day, it is still important to consider the patient’s sex and the side of the brain being examined.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"53 1","pages":"Article 101395"},"PeriodicalIF":3.3,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145338042","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":"Response to optimizing imaging protocols and clinical correlation in pediatric MRgLITT: A constructive appraisal of Hu et al","authors":"Alice Hu ,&nbsp;Lelio Guida ,&nbsp;Thomas Blauwblomme ,&nbsp;Nathalie Boddaert ,&nbsp;Volodia Dangouloff-Ros","doi":"10.1016/j.neurad.2025.101394","DOIUrl":"10.1016/j.neurad.2025.101394","url":null,"abstract":"","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"53 1","pages":"Article 101394"},"PeriodicalIF":3.3,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324071","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":"Deep learning models based on DWI-MRI for prognosis prediction in acute ischemic stroke receiving intravenous thrombolysis: Development and validation","authors":"Huan Yang ,&nbsp;Wenxi Wang ,&nbsp;Xin Zhao ,&nbsp;Qi Xuan ,&nbsp;Cao Jiang ,&nbsp;Bo Zhao","doi":"10.1016/j.neurad.2025.101391","DOIUrl":"10.1016/j.neurad.2025.101391","url":null,"abstract":"<div><h3>Objective</h3><div>To develop and validate predictive models based on diffusion-weighted imaging MRI (DWI-MRI) for assessing the prognosis of patients with acute ischemic stroke (AIS) treated with intravenous thrombolysis, and to compare the performance of deep learning versus traditional machine learning methods.</div></div><div><h3>Materials and methods</h3><div>A retrospective analysis was conducted on 682 AIS patients from two hospitals. Data from Hospital 1 were divided into a training set (70 %) and a test set (30 %), while data from Hospital 2 were used for external validation. Five predictive models were developed: Model A (clinical features), Model B (radiomic features based on DWI-MRI), Model C (deep learning features), Model D (clinical + radiomic features), and Model E (clinical + deep learning features). Performance metrics included Area Under the Curve (AUC), sensitivity, specificity, and accuracy.</div></div><div><h3>Results</h3><div>In the test set, Models A, B, and C achieved AUCs of 0.760, 0.820, and 0.857, respectively. The combined models, D and E, showed superior performance with AUCs of 0.904 and 0.925, respectively. Model E outperformed Model D and also demonstrated robust performance in external validation (AUC = 0.937).</div></div><div><h3>Conclusion</h3><div>Deep learning models integrating DWI-MRI and clinical features outperformed traditional methods, demonstrating strong generalizability in external validation. These models may support clinical decision-making in AIS prognosis.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101391"},"PeriodicalIF":3.3,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259878","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":"Distal vessel aspiration (DIVA) with the RED 043 catheter in acute ischaemic stroke","authors":"Vinicius Carraro do Nascimento ,&nbsp;Strahan Teoh ,&nbsp;Permesh Singh Dhillon ,&nbsp;Laetitia de Villiers ,&nbsp;Hal Rice","doi":"10.1016/j.neurad.2025.101390","DOIUrl":"10.1016/j.neurad.2025.101390","url":null,"abstract":"<div><div>Acute ischaemic stroke (AIS) due to medium vessel occlusion (MeVO) is increasingly recognised as the next frontier for endovascular mechanical thrombectomy (EMT).<span><span>¹</span></span>^,<span><span>²</span></span></div><div>A recognized method of recanalisation of MeVOs is the blind exchange/mini-pinning (BEMP), employing a stent retriever and a low profile aspiration catheter, such as the Penumbra 3MAX Reperfusion Catheter.<span><span>³</span></span></div><div>One potential disadvantage of this technique is the necesssity of stent retriever (SR), which may increase procedural risks, considering the smaller calibre and tortuous arteries.<span><span>⁴</span></span>^,<span><span>⁵</span></span> In addition, this may carry increased costs.</div><div>This technical video highlights the \"DIVA\" technique: RED 043 aspiration catheter navigate to the target occlusion over he Aristotle 24 200 cm microwave, without the use of a microcatheter or SR, as far as A4, M4 and P4 segments.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101390"},"PeriodicalIF":3.3,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259822","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":"Rescue technique for proximal flow diverter foreshortening leading to dislodgement into aneurysm","authors":"Yong Zhang ,&nbsp;Xiguang Fu ,&nbsp;Haoyu Zhu ,&nbsp;Chuhan Jiang","doi":"10.1016/j.neurad.2025.101389","DOIUrl":"10.1016/j.neurad.2025.101389","url":null,"abstract":"<div><div>Flow diverters (FDs) are an established treatment method for dissecting aneurysms.<span><span>1</span></span>, <span><span>2</span></span>, <span><span>3</span></span> However, device shortening post-deployment and subsequent migration into the aneurysm may pose significant risks.<span><span>⁴</span></span>^,<span><span>⁵</span></span> In this technical video (Video 1), we present a case of Pipeline Flex Shield deployment for a dissecting aneurysm in the M1 segment of the left middle cerebral artery, where proximal segment shortening with subsequent device migration into the aneurysm sac was observed during the 9-month follow-up evaluation. In this procedure, we successfully advanced a microwire-guided microcatheter through the proximal portion of the compromised stent. Utilizing an exchange technique, the original delivery catheter was replaced to facilitate deployment of a Lattice flow diverter. Final angiography confirmed adequate overlap between the two stents with re-established luminal patency in the parent artery. n analogous clinical scenarios, telescoping stent deployment within the shortened endoprosthesis may constitute a viable salvage strategy.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101389"},"PeriodicalIF":3.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145066305","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":"AI-assisted detection of cerebral aneurysms on 3D time-of-flight MR angiography: User variability and clinical implications","authors":"Liang Liao ,&nbsp;Ulysse Puel ,&nbsp;Ophélie Sabardu ,&nbsp;Oana Harsan ,&nbsp;Luana Lopes De Medeiros ,&nbsp;Wassim Abou Loukoul ,&nbsp;René Anxionnat ,&nbsp;Erwan Kerrien","doi":"10.1016/j.neurad.2025.101388","DOIUrl":"10.1016/j.neurad.2025.101388","url":null,"abstract":"<div><h3>Background</h3><div>The generalizability and reproducibility of AI-assisted detection for cerebral aneurysms on 3D time-of-flight MR angiography remain unclear. We aimed to evaluate physician performance using AI assistance, focusing on inter- and intra-user variability, identifying factors influencing performance and clinical implications.</div></div><div><h3>Methods</h3><div>In this retrospective study, four state-of-the-art AI models were hyperparameter-optimized on an in-house dataset (2019–2021) and evaluated via 5-fold cross-validation on a public external dataset. The two best-performing models were selected for evaluation on an expert-revised external dataset. Inclusion: saccular aneurysms without prior treatment. Five physicians, grouped by expertise, each performed two AI-assisted evaluations, one with each model. Lesion-wise sensitivity and false positives per case (FPs/case) were calculated for each physician–AI pair and AI models alone. Agreement was assessed using kappa. Aneurysm size comparisons used the Mann–Whitney U test.</div></div><div><h3>Results</h3><div>The in-house dataset included 132 patients with 206 aneurysms (mean size: 4.0 mm); the revised external dataset, 270 patients with 174 aneurysms (mean size: 3.7 mm). Standalone AI achieved 86.8 % sensitivity and 0.58 FPs/case. With AI assistance, non-experts achieved 72.1 % sensitivity and 0.037 FPs/case; experts, 88.6 % and 0.076 FPs/case; the intermediate-level physician, 78.5 % and 0.037 FPs/case. Intra-group agreement was 80 % for non-experts (kappa: 0.57, 95 % CI: 0.54–0.59) and 77.7 % for experts (kappa: 0.53, 95 % CI: 0.51–0.55). In experts, false positives were smaller than true positives (2.7 vs. 3.8 mm, <em>p</em> &lt; 0.001); no difference in non-experts (<em>p</em> = 0.09). Missed aneurysm locations were mainly model-dependent, while true- and false-positive locations reflected physician expertise. Non-experts more often rejected AI suggestions and added fewer annotations; experts were more conservative and added more.</div></div><div><h3>Conclusion</h3><div>Evaluating AI models in isolation provides an incomplete view of their clinical applicability. Detection performance and patterns differ between standalone AI and AI-assisted use, and are modulated by physician expertise. Rigorous external validation is essential before clinical deployment.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101388"},"PeriodicalIF":3.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145055861","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":"Differential cortical hemodynamics during standard and reversed visually guided navigation: An fNIRS-based investigation","authors":"Sang Seok Yeo ,&nbsp;Chae-Won Kwon ,&nbsp;In Hee Cho","doi":"10.1016/j.neurad.2025.101387","DOIUrl":"10.1016/j.neurad.2025.101387","url":null,"abstract":"<div><div>Visuospatial perception, which is based on the comprehension of objects and space, requires spatial attention to the surrounding environment. Stimulus-related elements that affect visuospatial tasks include object geometry, familiarity, complexity, and picture plane versus depth rotation. The dorsal stream pathway from the visual cortex, which is implicated in spatial processing, reflects the spatial component needed to orient the focus of attention to the location of the expected target stimulus. It is activated during spatial localization. While processing spatial information, visual, somatosensory, and auditory information is received from the inferotemporal cortex, medial and superior parietal cortices, and transverse temporal gyrus, and is projected directly toward the prefrontal cortex, which includes the premotor cortex. In this study 10 volunteers performed standard and reverse visually guided weight-shifting training tasks. This study aimed to investigate the hemodynamic response of the parietal to occipital cortex during these tasks using a 41-channel functional near-infrared spectroscopy system. During the standard navigation task, the right supramarginal gyrus showed a significant increase in oxy-hemoglobin (HbO) and total-hemoglobin (HbT) values. In contrast, the reverse navigation task showed significant increments in HbO values in the right angular gyrus (AG) and left somatosensory association cortex (SAC) and in HbT values in the left SAC and both AG. Thus, according to our results, spatial processing based on reversal may be different. Moreover, a difference in the amount of oxygen was observed. Further studies are required to understand the activated neural mechanisms when sensory inputs differ during spatial information processing.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101387"},"PeriodicalIF":3.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034607","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":"MRI versus CT before endovascular thrombectomy in the early time window: A systematic review and meta-analysis","authors":"Nourou Dine Adeniran Bankole ,&nbsp;Adnan Mujanovic ,&nbsp;Yao Christian Hugues Dokponou ,&nbsp;Corentin Provost ,&nbsp;Marco Pasi ,&nbsp;Hocine Redjem ,&nbsp;Mikael Mazighi ,&nbsp;Catherine Oppenheim ,&nbsp;Urs Fischer ,&nbsp;Thomas R Meinel ,&nbsp;Johannes Kaesmacher ,&nbsp;Grégoire Boulouis ,&nbsp;Fouzi Bala","doi":"10.1016/j.neurad.2025.101384","DOIUrl":"10.1016/j.neurad.2025.101384","url":null,"abstract":"<div><h3>Background</h3><div>Selection of acute stroke patients for endovascular thrombectomy (EVT) within 6 h from symptom onset can be done using MRI or CT. However, association of either imaging modality with better clinical outcomes or shorter workflow times is still not fully understood.</div></div><div><h3>Methods</h3><div>We searched Medline and Ovid-Embase for studies comparing outcomes and workflow metrics between patients selected for EVT using CT or MRI from inception to November 30, 2024. The primary outcome was the association of imaging modality with functional independence (modified Rankin Scale score, 0–2) at 90-days and workflow metrics. Pooled odds ratios with 95% CIs were calculated using a random-effects model.</div></div><div><h3>Results</h3><div>Nine studies with 11,202 patients (3018 with MRI vs 8184 with CT) were analysed. Patients selected with MRI had similar odds of 90-day mRS 0–2 (adjusted odds ratio [aOR] 1.1195% CI 0.84–1.47) and lower mortality (aOR 0.6695% CI 0.57–0.76) compared to those selected with CT. Door-to-imaging time (mean difference [MD] 11.2 min 95% CI 4.8 to 18.4) and door-to-intravenous thrombolysis initiation time (MD 10.1 min 95% CI 4.9 to 15.2) were longer in patients selected with MRI. However, door-to-arterial puncture time was similar between both groups (MD 6.8 min 95% CI -4.6 to 18.1).</div></div><div><h3>Conclusion</h3><div>In stroke patients undergoing EVT within 6 h from symptom onset, MRI before EVT could be a feasible alternative to CT without significant delays from door to puncture time. Randomized trials are needed before these findings can be generalized.</div></div>","PeriodicalId":50115,"journal":{"name":"Journal of Neuroradiology","volume":"52 6","pages":"Article 101384"},"PeriodicalIF":3.3,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004433","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}