Neuroimage-Clinical最新文献

{"title":"Resting-state functional near-infrared spectroscopy in neurodegenerative diseases – A systematic review","authors":"Franziska Albrecht ,&nbsp;Alexander Kvist ,&nbsp;Erika Franzén","doi":"10.1016/j.nicl.2025.103733","DOIUrl":"10.1016/j.nicl.2025.103733","url":null,"abstract":"<div><h3>Objective</h3><div>To systematically review and summarize alterations found in resting-state activity as measured via functional near-infrared spectroscopy (fNIRS) in neurodegenerative diseases.</div></div><div><h3>Background</h3><div>fNIRS is a novel and emerging neuroimaging method suitable for a variety of study designs. Resting-state is the measure of brain activity in the absence of a task, which has been investigated for yielding information about neurodegenerative diseases, mainly using magnetic resonance imaging. We aimed to systematically review the usage of resting-state fNIRS (rsfNIRS) in neurodegenerative diseases.</div></div><div><h3>Inclusion criteria</h3><div>Studies investigating people diagnosed with a neurodegenerative disease and resting-state activity obtained with fNIRS using at least two channels.</div></div><div><h3>Methods</h3><div>We searched three databases for publications. After the screening, 16 studies were included in the systematic review. The quality of the studies was assessed, and data were extracted. Data were qualitatively synthesized and in the case of at least 10 similar studies, a meta-analysis was planned.</div></div><div><h3>Results</h3><div>Most studies investigated Mild cognitive impairment (50%), followed by Alzheimer’s disease (25%). Other neurodegenerative diseases encompassed Parkinson’s disease, Multiple sclerosis, and Amyotrophic lateral sclerosis. All studies reported oxygenated hemoglobin. Still, studies were heterogeneous in terms of study design, measurement duration, fNIRS device, montage, pre-processing, and analyses. A meta-analysis was not considered possible due to this heterogeneity.</div></div><div><h3>Conclusion</h3><div>rsfNIRS shows promise in neurodegenerative disease, as most studies have observed resting-state alterations when compared to healthy controls. However, inconsistencies across studies limit data comparison and meta-analysis. Hence, we strongly advocate the application of fNIRS reporting guidelines and the establishment of rsfNIRS-specific guidelines. This will ensure reliable and comparable results in future research.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103733"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis","authors":"E. Premi ,&nbsp;V. Cantoni ,&nbsp;A. Benussi ,&nbsp;A. Iraji ,&nbsp;V.D. Calhoun ,&nbsp;D. Corbo ,&nbsp;R. Gasparotti ,&nbsp;M. Tinazzi ,&nbsp;B. Borroni ,&nbsp;M. Magoni","doi":"10.1016/j.nicl.2025.103731","DOIUrl":"10.1016/j.nicl.2025.103731","url":null,"abstract":"<div><div>The present study investigated spatial dynamic functional network connectivity (dFNC) in patients with functional hemiparesis (i.e., functional stroke mimics, FSM). The aim of this work was to assess static functional connectivity (large-scale) networks and dynamic brain states, which represent distinct dFNC patterns that reoccur in time and across subjects. Resting-state fMRI data were collected from 15 patients with FSM (mean age = 42.3 ± 9.4, female = 80 %) and 52 age-matched healthy controls (HC, mean age = 42.1 ± 8.6, female = 73 %).</div><div>Each patient underwent a resting-state functional MRI scan for spatial dFNC evaluation and transcranial magnetic stimulation protocols for indirect assessment of GABAergic and glutamatergic transmission. We considered three dynamic brain networks, i.e., the somatomotor network (SMN), the default mode network (DMN) and the salience network (SN), each summarized into four distinct recurring spatial configurations. Compared to HC, patients with FSM showed significant decreased dwell time, e.g. the time each individual spends in each spatial state of each network, in state 2 of the SMN (HC <em>vs</em>. FSM, 13.5 ± 27.1 <em>vs.</em> 1.9 ± 4.1, <em>p</em> = 0.044). Conversely, as compared to HC, FSM spent more time in state 1 of the DMN (10.8 ± 14.9 <em>vs.</em> 27.3 ± 38.9, <em>p</em> = 0.037) and in state 3 of the SN (23.1 ± 23.0 <em>vs.</em> 38.8 ± 38.2, <em>p</em> = 0.002). We found a significant correlation between the dwell time of impaired functional state of the SMN and measures of GABAergic neurotransmission (<em>r</em> = 0.581, <em>p</em> = 0.037). Specifically, longer impaired dwell time was associated with greater GABAergic inhibition. These findings demonstrate that FSM present altered functional brain network dynamics, which correlate with measures of GABAergic neurotransmission. Both dFNC and GABAergic neurotransmission may serve as potential targets for future intervention strategies.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103731"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11762193/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resting-state functional brain connectivity in female adolescents with first-onset anorexia nervosa","authors":"Katrien F.M. Bracké ,&nbsp;Laura Monteiro Rente Dias ,&nbsp;Marisha N. Meijer ,&nbsp;Cathelijne P.M. Steegers ,&nbsp;Laurinde F. den Heijer ,&nbsp;Tess van der Harst ,&nbsp;Marjolein H.G. Dremmen ,&nbsp;Meike W. Vernooij ,&nbsp;Gwen C. Dieleman ,&nbsp;Tonya White","doi":"10.1016/j.nicl.2025.103745","DOIUrl":"10.1016/j.nicl.2025.103745","url":null,"abstract":"<div><h3>Objective</h3><div>Women with anorexia nervosa (AN) have been shown to demonstrate differences in functional connectivity in brain regions associated with cognitive control, somatosensory processing, and emotion regulation. However, previous studies have been conducted on small samples and have inconsistent findings. Therefore, this study aimed to identify aberrant brain networks related to the core clinical symptoms of AN and to explore the longitudinal association with clinical outcome in a large population of adolescents experiencing their first episode of AN.</div></div><div><h3>Methods</h3><div>Functional MRI (fMRI) of brain resting-state functional connectivity (RS-FC) of female adolescents with first-onset AN (n = 56) were compared to age- and education-matched typically developing (TD) adolescents (n = 64). To account for the severity of underweight, separate analyses were performed to investigate differences in RS-FC between underweight AN participants and TD adolescents, as well as between underweight (n = 30) and weight-restored AN (n = 26) participants. Clinical outcomes, i.e. body mass index and eating disorder (ED) symptoms, were assessed at baseline and one-year follow-up. Independent component analyses (ICA) were used to extract the brain networks of interest: the default mode (DMN), left and right frontoparietal (FPN), and the insular (IN) networks. Linear regression analyses were conducted to assess differences in RS-FC between AN and TD participants, as well as to assess whether RS-FC was associated with clinical symptoms at baseline and at one-year of follow-up. Two statistical models were used: model 1 adjusted for age and socioeconomic status (SES), and model 2 additionally adjusted for baseline anxiety and depressive symptoms.</div></div><div><h3>Results</h3><div>Underweight AN participants had lower RS-FC between the DMN-IN, as well as between the FPN-IN compared to the TD adolescents. After correction for multiple testing, no significant differences in RS-FC were found between underweight AN participants and weight-restored AN participants, as well as between the whole AN group and the TD group. RS-FC was not associated with the severity of clinical symptoms at baseline nor at one-year of follow-up.</div></div><div><h3>Conclusion</h3><div>AN is associated with changes in RS-FC between the FPN-IN and DMN-IN during the underweight state. These changes in RS-FC were no longer observed in weight-restored AN participants, emphasizing the impact of underweight on RS-FC in AN. Changes in these brain networks may partly explain the impaired cognitive control and difficulties with emotion and behavioral regulation in individuals with AN during the underweight state.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103745"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143182388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural and functional changes of Post-Stroke Depression: A multimodal magnetic resonance imaging study","authors":"Qiuhong Lu ,&nbsp;Shunzu Lu ,&nbsp;Xue Wang ,&nbsp;Yanlan Huang ,&nbsp;Jie Liu ,&nbsp;Zhijian Liang","doi":"10.1016/j.nicl.2025.103743","DOIUrl":"10.1016/j.nicl.2025.103743","url":null,"abstract":"<div><div>This study investigated changes in gray matter volume (GMV), white matter microstructure, and spontaneous brain activity in post-stroke depression (PSD) using multiple MRI techniques, including neurite orientation dispersion and density imaging (NODDI). Changes in GMV, neurite density index (NDI), orientation dispersion index (ODI), fraction of isotropic water (ISO), diffusion tensor imaging (DTI) parameters, and the amplitude of frequency fluctuations (ALFF) were assessed between PSD (n = 20), post-stroke without depression (n = 20), and normal control (n = 20) groups. Receiver operating characteristic (ROC) curve analysis was performed to test the classification performance of the variant parameters of each MRI modality, each single MRI modality and multiple MRI modality. Compared to patients with post-stroke without depression (non-PSD), those with PSD showed increased ODI and ISO in the widespread white matter, as well as increased ALFF in the left pallidum. No significant differences in the GMV or DTI parameters were observed between the two groups. Furthermore, the ODI of the right superior longitudinal fasciculus and NODDI showed the best classification performance for PSD at their respective comparison level (the areas under the ROC curves (AUC) = 0.917(0.000), 0.933(0.000)). The model of NODDI-derived parameters combined with non-diffusion MRI modality parameters (i.e., GMV and ALFF) showed better diagnostic performance than that of DTI-derived parameters. These findings suggest that PSD is associated with structural and functional abnormalities that may contribute to depressive symptoms. Additionally, NODDI showed its advantages in the description of structural alterations in emotion-related white matter pathways and classification performance in PSD.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103743"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143082045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential patterning of dynamic brain states distinguish Parkinson’s disease patients with mild cognitive impairments","authors":"Aaron S. Kemp ,&nbsp;A. Journey Eubank ,&nbsp;Yahya Younus ,&nbsp;James E. Galvin ,&nbsp;Fred W. Prior ,&nbsp;Linda J. Larson-Prior","doi":"10.1016/j.nicl.2025.103779","DOIUrl":"10.1016/j.nicl.2025.103779","url":null,"abstract":"<div><div>Parkinson’s disease (PD) is a neurodegenerative disease which presents clinically with progressive impairments in motoric and cognitive functioning. Pathophysiologic mechanisms underlying these impairments are believed to be attributable to a breakdown in the spatiotemporal coordination of functional neural networks across multiple cortical and subcortical regions. The current investigation used resting state, functional magnetic resonance imaging (rs-fMRI) to determine whether the temporal characteristics or sequential patterning of dynamic functional network connectivity (dFNC) states could accurately distinguish among people with PD who had normal cognition (PD-NC, n = 18), those with PD who had mild cognitive impairment (PD-MCI, n = 15), and older-aged healthy control (HC, n = 22) individuals. Results indicated that the proportion of time during the rs-fMRI scan that was spent in each of three identified dFNC states (dwell time) differed among these three groups. Individuals in the PD-MCI group spent significantly more time in a dFNC state characterized by low functional network connectivity, relative to participants in both the PD-NC (p = 0.0226) and HC (p = 0.0027) cohorts and tend to spend less time in a state characterized by anti-correlated thalamo-cortical connectivity, relative to both the PD-NC (p = 0.016) and HC (p = 0.0562) groups. A machine-learning method using sequential pattern mining was also found to distinguish among the groups with moderate accuracies ranging from 0.53 to 0.80, revealing distinct sequential patterns in the temporal ordering of dFNC states. These findings underscore the potential of dFNC and sequential pattern mining as relevant methods for further exploration of the pathophysiologic underpinnings of cognitive impairment among people living with PD.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103779"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain network alterations in anorexia Nervosa: A Multi-Center structural connectivity study","authors":"Jun Kanzawa ,&nbsp;Ryo Kurokawa ,&nbsp;Tsunehiko Takamura ,&nbsp;Nobuhiro Nohara ,&nbsp;Kouhei Kamiya ,&nbsp;Yoshiya Moriguchi ,&nbsp;Yasuhiro Sato ,&nbsp;Yumi Hamamoto ,&nbsp;Tomotaka Shoji ,&nbsp;Tomohiko Muratsubaki ,&nbsp;Motoaki Sugiura ,&nbsp;Shin Fukudo ,&nbsp;Yoshiyuki Hirano ,&nbsp;Yusuke Sudo ,&nbsp;Rio Kamashita ,&nbsp;Sayo Hamatani ,&nbsp;Noriko Numata ,&nbsp;Koji Matsumoto ,&nbsp;Eiji Shimizu ,&nbsp;Naoki Kodama ,&nbsp;Osamu Abe","doi":"10.1016/j.nicl.2025.103737","DOIUrl":"10.1016/j.nicl.2025.103737","url":null,"abstract":"<div><div>Anorexia nervosa (AN) is a severe eating disorder characterized by intense fear of weight gain, distorted body image, and extreme food restriction. This research employed advanced diffusion MRI techniques including single-shell 3-tissue constrained spherical deconvolution, anatomically constrained tractography, and spherical deconvolution informed filtering of tractograms to analyze brain network alterations in AN. Diffusion MRI data from 81 AN patients and 98 healthy controls were obtained. The structural brain connectome was constructed based on nodes set in 84 brain regions, and graph theory analysis was conducted. Results showed that AN patients exhibited significantly higher clustering coefficient and local efficiency in several brain regions, including the left fusiform gyrus, bilateral orbitofrontal cortex, right entorhinal cortex, right lateral occipital gyrus, right superior temporal gyrus, and right insula. A trend towards higher global efficiency and small-worldness was also observed in AN patients, although not statistically significant. These findings suggest increased local connectivity and efficiency within regions associated with behavioral rigidity, emotional regulation, and disturbed body image among AN patients. This study contributes to the understanding of the neurological basis of AN by highlighting structural connectivity alterations in specific brain regions.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103737"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sweet spot for resting-state functional MRI effect of deep brain stimulation in dystonia lies in the lower pallidal area","authors":"Pavel Filip ,&nbsp;Andrej Lasica ,&nbsp;Dimitra Kiakou ,&nbsp;Karsten Mueller ,&nbsp;Jiří Keller ,&nbsp;Dušan Urgošík ,&nbsp;Daniel Novák ,&nbsp;Robert Jech","doi":"10.1016/j.nicl.2025.103750","DOIUrl":"10.1016/j.nicl.2025.103750","url":null,"abstract":"<div><h3>Introduction</h3><div>Deep brain stimulation (DBS) of the internal globus pallidus (GPi) is a well-established, effective treatment for dystonia. Substantial variability of therapeutic success has been the one of the drivers of an ongoing debate about proper stimulation site and settings, with several indications of the notional sweet spot pointing to the lower GPi or even subpallidal area.</div></div><div><h3>Methods</h3><div>The presented patient-blinded, random-order study with cross-sectional verification against healthy controls enrolled 17 GPi DBS idiopathic, cervical or generalised dystonia patients to compare the effect of the stimulation in the upper and lower GPi area, with the focus on sensorimotor network connectivity and local activity measured using functional magnetic resonance.</div></div><div><h3>Results</h3><div>Stimulation brought both these parameters to levels closer to the state detected in healthy controls. This effect was much more pronounced during the stimulation in the lower GPi area or beneath it than in slightly higher positions, with stimulation-related changes detected by both metrics of interest in the sensorimotor cortex, striatum, thalamus and cerebellum.</div></div><div><h3>Conclusions</h3><div>All in all, this study not only replicated the results of previous studies on GPi DBS as a modality restoring sensorimotor network connectivity and local activity in dystonia towards the levels in healthy population, but also showed that lower GPi area or even subpallidal structures, be it white matter or even small, but essential nodes in the zona incerta as nucleus basalis of Meynert, are important regions to consider when programming DBS in dystonia patients.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103750"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thalamic iron in multiple sclerosis: Waning support for the early-rise late-decline hypothesis","authors":"Fahad Salman ,&nbsp;Niels Bergsland ,&nbsp;Michael G. Dwyer ,&nbsp;Jack A Reeves ,&nbsp;Abhisri Ramesh ,&nbsp;Dejan Jakimovski ,&nbsp;Bianca Weinstock-Guttman ,&nbsp;Robert Zivadinov ,&nbsp;Ferdinand Schweser","doi":"10.1016/j.nicl.2025.103771","DOIUrl":"10.1016/j.nicl.2025.103771","url":null,"abstract":"<div><h3>Background</h3><div>Studies of thalamic iron levels in multiple sclerosis (MS) have yielded variable findings, potentially due to differences in study cohorts. For example, studies in relatively young cohorts (average ages below 40 years) have reported elevated susceptibility in people with MS (pwMS), whereas studies in older cohorts (above 40 years) found decreased susceptibility.</div></div><div><h3>Objective</h3><div>To test the “early-rise late-decline” hypothesis, which posits that age differences in study cohorts are responsible for conflicting findings regarding thalamic susceptibility in MS.</div></div><div><h3>Methods</h3><div>We chose to replicate one of the previous studies that showed evidence of elevated thalamic iron concentrations in younger pwMS (Rudko et al., 2014). We also replicated a study involving older pwMS (Pudlac et al., 2020) to serve as a control. We assessed thalamic susceptibility using the QSM processing and analysis methodology outlined by Rudko et al.</div></div><div><h3>Results</h3><div>Although cohort characteristics, QSM processing, and analytical methods were closely matched, we found significantly lower thalamic susceptibility in the younger pwMS compared to controls (−1.1 ± 7.8 vs. 5.4 ± 6.1 ppb; effect sizes: −0.35 to −0.91). Study outcomes were robust across a wide range of regularization parameters, with effect size differences influenced by background field removal regularization. A similar pattern was observed in the older cohort, where thalamic susceptibility was again lower in pwMS compared to controls (4.0 ± 9.5 vs. 9.6 ± 10.7 ppb; effect size: −0.55).</div></div><div><h3>Conclusions</h3><div>Our findings contradict the “early rise” hypothesis of thalamic iron levels in pwMS. The consistency of our results across multiple analyses suggests that QSM processing artifacts are unlikely to explain previous reports of increased thalamic iron. Instead, these variations may stem from demographic or clinical differences, such as geographical factors and treatment regimens.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103771"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Event-related potential markers of subjective cognitive decline and mild cognitive impairment during a sustained visuo-attentive task","authors":"A.A. Vergani ,&nbsp;S. Mazzeo ,&nbsp;V. Moschini ,&nbsp;R. Burali ,&nbsp;M. Lassi ,&nbsp;L.G. Amato ,&nbsp;J. Carpaneto ,&nbsp;G. Salvestrini ,&nbsp;C. Fabbiani ,&nbsp;G. Giacomucci ,&nbsp;C. Morinelli ,&nbsp;F. Emiliani ,&nbsp;M. Scarpino ,&nbsp;S. Bagnoli ,&nbsp;A. Ingannato ,&nbsp;B. Nacmias ,&nbsp;S. Padiglioni ,&nbsp;S. Sorbi ,&nbsp;V. Bessi ,&nbsp;A. Grippo ,&nbsp;A. Mazzoni","doi":"10.1016/j.nicl.2025.103760","DOIUrl":"10.1016/j.nicl.2025.103760","url":null,"abstract":"<div><div>Subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer’s disease stages lack well-defined electrophysiological correlates, creating a critical gap in the identification of robust biomarkers for early diagnosis and intervention. In this study, we analysed event-related potentials (ERPs) recorded during a sustained visual attention task in a cohort of 178 individuals (119 SCD, 40 MCI, and 19 healthy subjects, HS) to investigate sensory and cognitive processing alterations associated with these conditions. SCD patients exhibited significant attenuation in both sensory (P1, N1, P2) and cognitive (P300, P600, P900) components compared to HS, with cognitive components showing performance-related gains. In contrast, MCI patients did not show a further decrease in any ERP component compared to SCD. Instead, they exhibited compensatory enhancements, reversing the downward trend observed in SCD. This compensation resulted in a non-monotonic pattern of ERP alterations across clinical conditions, suggesting that MCI patients engage neural mechanisms to counterbalance sensory and cognitive deficits. These findings support the use of electrophysiological markers in support of medical decision-making, enhancing personalized prognosis and guiding targeted interventions in cognitive decline.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103760"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep learning approach versus expert clinician panel in the classification of posterior circulation infarction","authors":"Leon S. Edwards ,&nbsp;Milanka Visser ,&nbsp;Cecilia Cappelen-Smith ,&nbsp;Dennis Cordato ,&nbsp;Andrew Bivard ,&nbsp;Leonid Churilov ,&nbsp;Christopher Blair ,&nbsp;James Thomas ,&nbsp;Angela Dos Santos ,&nbsp;Longting Lin ,&nbsp;Chushuang Chen ,&nbsp;Carlos Garcia-Esperon ,&nbsp;Kenneth Butcher ,&nbsp;Tim Kleinig ,&nbsp;Phillip MC Choi ,&nbsp;Xin Cheng ,&nbsp;Qiang Dong ,&nbsp;Richard I. Aviv ,&nbsp;Mark W. Parsons ,&nbsp;on behalf of the INSPIRE Study Group","doi":"10.1016/j.nicl.2025.103732","DOIUrl":"10.1016/j.nicl.2025.103732","url":null,"abstract":"<div><h3>Background</h3><div>Posterior circulation infarction (POCI) is common. Imaging techniques such as non-contrast-CT (NCCT) and diffusion-weighted-magnetic-resonance-imaging commonly fail to detect hyperacute POCI. Studies suggest expert inspection of Computed Tomography Perfusion (CTP) improves diagnosis of POCI. In many settings, there is limited access to specialist expertise. Deep-learning has been successfully applied to automate imaging interpretation. This study aimed to develop and validate a deep-learning approach for the classification of POCI using CTP.</div></div><div><h3>Methods</h3><div>Data were analysed from 3541-patients from the International-stroke-perfusion-registry (INSPIRE). All patients with baseline multimodal-CT and follow-up imaging performed at 24–48 h were identified. A cohort of 541-patients was constructed on a 1:3 POCI-to −reference-ratio for model analysis. A 3D-Dense-Convolutional-Network (DenseNet) was trained to classify patients into POCI or non-POCI using CTP-deconvolved-maps. Six-stroke-experts also independently classified patients based upon stepwise access to multimodal CT (mCT) data. DenseNet results were compared against expert clinician results. Model and clinician performance was evaluated using area-under-the-receiver-operating-curve, sensitivity, specificity, accuracy and precision. Clinician agreement was measured with the Fleiss-Kappa-statistic.</div></div><div><h3>Results</h3><div>Best mean clinician diagnostic accuracy, sensitivity and agreement was demonstrated after review of all mCT data (AUC: 0.81, Sensitivity: 0.65, Fleiss-Kappa-statistic: 0.73). There was a spectrum of individual clinician results with an AUC-range of 0.73–0.86. Best DenseNet performance was recorded with an input combination of NCCT and delay-time maps. The DenseNet model was superior to the best mean clinician performance (AUC: 0.87) and was due to enhanced sensitivity (DenseNET: 0.77, Clinician: 0.65). The degree to which the DenseNet model outperformed each clinician ranged and was clinician specific (AUC improvement 0.01–0.14).</div></div><div><h3>Conclusion</h3><div>Comprehensive review of CTP improves diagnostic performance and agreement amongst clinicians. A DenseNet model was superior to best mean clinician performance. The degree of improvement varied by specific clinician. Development of a clinician-DenseNet approach may improve inter-clinician agreement and diagnostic accuracy. This approach may alleviate limited specialist services in resource constrained settings.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103732"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}