Journal of Neuroimaging最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148097710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148097711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148063264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148097123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facial Nerve Tractography of Vestibular Schwannomas: A Systematic Review of MR Acquisition and Analysis Pipelines","authors":"Yunjia Ni,&nbsp;Shawn M. Stevens,&nbsp;Trenton House,&nbsp;Ashton Huppert Steed,&nbsp;Alma Jukic,&nbsp;Parvathy Hareesh,&nbsp;Anthony M. Asher,&nbsp;Kaith K. Almefty,&nbsp;Kris A. Smith,&nbsp;Randall W. Porter,&nbsp;Michael T. Lawton,&nbsp;Richard D. Dortch","doi":"10.1111/jon.70131","DOIUrl":"10.1111/jon.70131","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Facial nerve (CN VII) diffusion MR tractography is considered as a useful adjunct in pre-operative planning prior to vestibular schwannoma (VS) resection, especially in larger (Koos Grade III/IV) tumors. Since 2016, several systematic reviews have investigated the clinical value of CN VII tractography in VS, and all reported a “success rate” of at least 87% for predicting the pre-operative CN VII position. Yet in clinical practice, CN VII tractography has not yet been widely adopted into routine clinical practice. We suspected that underlying methodology and reporting metrics for existing tractography algorithms may be overestimating success rate. This motivated us to revisit the literature from a different perspective to unravel the caveats and nuances behind this technology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We screened all published works on PubMed related to pre-operative CN VII tractography in VS. Twenty-two studies were reviewed in detail.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We observed a strikingly high heterogeneity in tractography protocols in all domains of the tractography acquisition and analysis pipeline across studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These findings suggest that the reliability and reproducibility of CN VII tractography in large VS has been overestimated. We believe that employing standardized reporting metrics, including sensitivity, true predictive value, and false discovery rate, would increase the transparency of benchmarking over other commonly reported metrics (“success rate” or “concordance rate”). In addition, ongoing research should aim to systematically investigate and improve each step in the acquisition and analysis pipeline for CN VII tractography in VS.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13009313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147503933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative Choroid Plexus Gadolinium Enhancement Is Related to Diffuse Brain Tissue Injury in Multiple Sclerosis","authors":"Sneha Senthil,&nbsp;Ian Tagge,&nbsp;Dumitru Fetco,&nbsp;Cheng Hsun Hsieh,&nbsp;Haz-Edine Assemlal,&nbsp;Zahra Karimaghaloo,&nbsp;Emily Fetco,&nbsp;G. R. Wayne Moore,&nbsp;Douglas L. Arnold,&nbsp;David A. Rudko,&nbsp;Sridar Narayanan","doi":"10.1111/jon.70132","DOIUrl":"10.1111/jon.70132","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Recent studies suggest that disruptions of the blood–cerebrospinal fluid (CSF) barrier within the choroid plexus (ChP) may contribute to multiple sclerosis (MS) pathogenesis. We investigated the relationship between a quantitative marker of ChP enhancement and markers of focal and diffuse brain tissue injury in MS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A group of 34 MS participants and 21 healthy participants underwent 7T MRI including magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) and fluid attenuated inversion recovery (FLAIR) acquisitions. The MS group received contrast, and delta T1 (ΔT1) maps were computed to assess enhancement. ChP, white matter lesions (WML), normal-appearing white matter (NAWM), and gray matter (GM) were segmented. Pre-contrast quantitative T1 (qT1) values were compared between groups, and linear regression with mean ChP ΔT1 was performed for WML volume and pre-gadolinium (Gd) mean qT1 of WML, NAWM, and GM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Mean qT1 of ChP, NAWM, and GM, as well as ChP volume, were higher in MS compared to controls (<i>p</i> &lt; 0.001). ChP ΔT1 was significantly associated with pre-Gd qT1 of NAWM (<i>β</i> = 0.20, <i>R²</i> = 0.54, <i>p</i> &lt; 0.001) and GM (<i>β</i> = 0.18, <i>R²</i> = 0.49, <i>p</i> &lt; 0.001), but not WML volume (<i>p</i> = 0.3) or WML qT1 (<i>p</i> = 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The association between ChP enhancement and diffuse tissue injury, together with elevated qT1 values and ChP volumes in MS, supports a mechanism of brain injury involving CSF-mediated toxicity distinct from classic lesion pathology in MS.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12972605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proceedings of the 49th Annual Meeting of the American Society of Neuroimaging.","authors":"Adnan I Qureshi, Parvathi Rudrabhatla, Jennifer W McVige, Ryan Hakimi, Andrei Alexandrov","doi":"10.1111/jon.70135","DOIUrl":"https://doi.org/10.1111/jon.70135","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":"e70135"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147774174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Annual Meeting of the American Society of Neuroimaging Puerto Rico, January 2026.","authors":"","doi":"10.1111/jon.70136","DOIUrl":"https://doi.org/10.1111/jon.70136","url":null,"abstract":"","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":"e70136"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147774182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining Large Core Infarction: Comparing the Accuracy of Non-Contrast CT ASPECTS Versus CT Perfusion Core Volume","authors":"Ngoc Mai Le,&nbsp;Joseph Samaha,&nbsp;Ananya S. Iyyangar,&nbsp;Javier Gomez-Farias,&nbsp;Bruna Kfoury,&nbsp;Ritesh Bajaj,&nbsp;Connor Nguyen,&nbsp;Syed Shams,&nbsp;Camille Neal-Harris,&nbsp;Emmanuel Ebirim,&nbsp;Hussain Azeem,&nbsp;Anjan N. Ballekere,&nbsp;Saagar Dhanjani,&nbsp;Eunyoung Lee,&nbsp;Luca Giancardo,&nbsp;Sunil A. Sheth","doi":"10.1111/jon.70130","DOIUrl":"10.1111/jon.70130","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>We evaluated agreement and performance of non-contrast head-computerized tomography (NCHCT) and CT-perfusion (CTP) in identifying large core infarct in acute ischemic stroke (AIS) due to large vessel occlusion (LVO) undergoing endovascular therapy (EVT), using MRI as reference.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>From our prospective multicenter registry, we identified patients with LVO-AIS due to internal carotid artery or middle cerebral artery M1occlusions who underwent EVT between 2017 and 2024. Final infarct volume (FIV) was defined using 24–48 h post-EVT diffusion-weighted imaging magnetic resonance imaging (MRI-FIV). To limit infarct growth bias, only patients with CTP-to-EVT start time &lt;3 h were included. Large core infarct was defined at FIV thresholds: 50, 70, and 100 mL. The primary outcome was agreement between NCHCT and CTP in identifying large core infarct using kappa-statistics. Large core was considered if NCHCT-ASPECTS&lt;6 or rCBF&lt;30% volume&gt;70 mL on CTP (RAPID/Viz.AI). Secondary outcomes included classification accuracy of each modality relative to MRI-FIV using the area under the receiver operating characteristic curve (AUC-ROC). Sensitivity analyses were performed in subgroups with TICI 2c−3 and cases processed by RAPID.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 241 EVT-treated LVO-AIS patients, median NIHSS was 15 [IQR: 10−20], MRI-FIV 13.8 Ml [IQR: 5−41.0], ASPECTS 8 [IQR: 7−10], and CTP-predicted core 8 mL [IQR: 0−31.0]. CTP and NCHCT showed slight agreement in identifying large core (κ = 0.192) and weak-to-acceptable discrimination for identifying large core infarcts (AUC-ROC: 0.61−0.72 across MRI-FIV thresholds). Both modalities showed limited predictive ability for 90-day functional independence (AUC-ROC: 0.63−0.65). Similar findings were observed in sensitivity analyses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Among LVO-AIS EVT-treated patients, NCHCT and CTP demonstrated slight agreement in classifying small versus large core, and neither technique was effective at predicting FIV or clinical outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12937044/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147290117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Default Mode Network Resting State Connectivity Derived From Task-Based fMRI: A Validation Study in People With Epilepsy","authors":"Lea Wemheuer,&nbsp;Anna Doll,&nbsp;Martin Wegrzyn,&nbsp;Markus Mertens,&nbsp;Johanna Kissler,&nbsp;Christian G. Bien,&nbsp;Friedrich G. Woermann,&nbsp;Philip Grewe","doi":"10.1111/jon.70129","DOIUrl":"10.1111/jon.70129","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Resting state functional connectivity can be measured using resting state functional MRI (fMRI), but also task-dependent fMRI in blocked designs. The latter has been demonstrated in healthy participants but not yet validated in clinical cohorts. Since functional connectivity of resting state networks (e.g., default mode network [DMN] and somatomotor network [SMN]) is altered in people with epilepsy, and the impact of the disease on the quality of the intermittent resting state data is unclear, we aimed to validate the method using a clinical fMRI in people with epilepsy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We compared functional connectivity derived from a standard resting state with rest periods of a clinical language fMRI (intermittent resting state) of 92 people with focal epilepsy. Both methods were analyzed across different aspects of functional connectivity: topography, within-network connectivity, and group-level comparisons. Therefore, we conducted independent component analyses (ICAs), similarity-, regions of interest (ROI)-to-ROI-, and second-level seed-based analyses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Results indicated similar ICA-derived topography of DMN and SMN from both methods. Within-network connectivity also yielded comparable results. Seed-based analyses of left and right hippocampal connectivity in people with left and right temporal lobe epilepsy also revealed analogous results, with minor restrictions in right hippocampal connectivity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The intermittent resting state method produces highly similar results to a standard resting state method in people with epilepsy across different aspects of functional connectivity. It is, therefore, an efficient approach to gain insights into functional connectivity networks in a clinical cohort without performing an additional resting state fMRI.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"36 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12924090/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146258608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}