Neuroimage-Clinical最新文献

{"title":"Beyond language: empathy and emotion recognition deficits in primary progressive aphasias","authors":"Giulia Giacomucci ,&nbsp;Alice Pieri ,&nbsp;Valentina Moschini ,&nbsp;Chiara Crucitti ,&nbsp;Sonia Padiglioni ,&nbsp;Carmen Morinelli ,&nbsp;Giulia Galdo ,&nbsp;Filippo Emiliani ,&nbsp;Matilde Nerattini ,&nbsp;Silvia Bagnoli ,&nbsp;Assunta Ingannato ,&nbsp;Sandro Sorbi ,&nbsp;Benedetta Nacmias ,&nbsp;Valentina Berti ,&nbsp;Valentina Bessi","doi":"10.1016/j.nicl.2025.103852","DOIUrl":"10.1016/j.nicl.2025.103852","url":null,"abstract":"<div><div>Although primary progressive aphasia (PPA) is considered a language disorder, increasing evidence points to the presence of social cognition impairments in PPA variants. The aims of this study were to explore empathy and emotion recognition deficits in the three PPA variants (sv-PPA, lv-PPA, nfv-PPA) and to identify their neural correlates.</div><div>Eleven sv-PPA, 34 lv-PPA,11 nfv-PPA patients and 34 healthy controls (HC) were included in this study. Empathy was explored with the Interpersonal Reactivity Index (IRI) (Perspective Taking – PT, Fantasy – FT, Empathic Concern – EC, Personal Distress – PD), rated by caregivers before (T0) and after (T1) the onset of cognitive symptoms. Emotion recognition was evaluated with the Ekman 60Faces (EK-60F) Test and metabolic activity with [18F]FDG-PET.</div><div>In all PPA variants, PT score was reduced from T0 to T1 (sv-PPA <em>p</em> = 0.014, lv-PPA <em>p</em> &lt; 0.001, nfv-PPA <em>p</em> = 0.022) and PD score was increased (sv-PPA <em>p</em> = 0.033, lv-PPA <em>p</em> &lt; 0.001, nfv-PPA <em>p</em> = 0.009). Only lv-PPA showed a decrease of FT score (<em>p</em> = 0.024), while EC was spared in all three variants. Sv-PPA patients had the worst performances in the EK-60F Test, followed by lv-PPA and, lastly, by nfv-PPA.</div><div>Correlations between EK-60F scores and metabolic activity were found in sv-PPA and lv-PPA, highlighting the involvement of areas participating in the emotion recognition network: cingulate cortex, insula, temporal and orbitofrontal cortices and inferior frontal gyrus.</div><div>All PPA variants exhibited impairments in cognitive empathy (PT) and heightened emotional contagion (PD). The most severe deficits in emotion recognition were shown by sv-PPA, while nfv-PPA was the less impaired variant.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"48 ","pages":"Article 103852"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144769309","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":"Electric field variations across DLPFC targeting methods in TMS therapy for Alzheimer’s disease","authors":"Nianshuang Wu ,&nbsp;Yuxuan Shao ,&nbsp;Zhen Wu ,&nbsp;Shuxiang Zhu ,&nbsp;Penghao Wang ,&nbsp;Ziyan Zhu ,&nbsp;Cheng Zhang ,&nbsp;Changzhe Wu ,&nbsp;Xiaolin Huo ,&nbsp;Hua Lin ,&nbsp;Guanghao Zhang","doi":"10.1016/j.nicl.2025.103847","DOIUrl":"10.1016/j.nicl.2025.103847","url":null,"abstract":"<div><h3>Background</h3><div>The dorsolateral prefrontal cortex (DLPFC) is crucial for cognitive control and a primary target for transcranial magnetic stimulation (TMS) in Alzheimer’s disease (AD). However, understanding the distribution of TMS-induced electric field (E-field) across different targeting methods remains limited, as does its relationship to therapeutic outcomes.</div></div><div><h3>Objective</h3><div>This study assesses differences in TMS-induced E-field using functional versus anatomical targeting methods for DLPFC stimulation.</div></div><div><h3>Methods</h3><div>Functional and anatomical targets were identified in 30 (11 M/19F) AD patients and 30 (13 M/17F) age-matched healthy controls (HCs) using T1 and fMRI data. E-field characteristics, including magnitude (E_ROI) and normal component (E_⊥), were calculated via SimNIBS software for comparisons across stimulation targets.</div></div><div><h3>Results</h3><div>Functional targeting showed greater spatial dispersion compared to anatomical targeting in both groups. Significant E-field differences were observed between the functional target and adjacent anatomical regions when the coil was positioned over the functional target in both groups. Optimal coil orientation exhibited directional specificity: parallel alignment with the LOI E-field produced higher field intensity in the functional target compared to the anatomical target (AD patients: <em>P</em> &lt; 0.001; HCs: <em>P</em> = 0.052), while perpendicular orientation maintained functional stability with reduced anatomical interference (both groups: <em>P</em> &lt; 0.001). And significant variations in E-field ratios were observed across coil orientations.</div></div><div><h3>Conclusion</h3><div>This study reveals key E-field disparities across DLPFC targeting approaches and establishes coil orientation optimization as a critical strategy to improve TMS precision, offering actionable insights for developing personalized protocols in AD therapy that may enhance treatment efficacy while minimizing adverse effects.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"48 ","pages":"Article 103847"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679686","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":"Distinct neural mechanisms underlying cognitive difficulties in preterm children born at different stages of prematurity","authors":"Samson Nivins ,&nbsp;Nelly Padilla ,&nbsp;Hedvig Kvanta ,&nbsp;Gustaf Mårtensson ,&nbsp;Ulrika Ådén","doi":"10.1016/j.nicl.2025.103876","DOIUrl":"10.1016/j.nicl.2025.103876","url":null,"abstract":"<div><h3>Objectives</h3><div>To examine associations between low cognitive-performance and regional-and network-level brain changes at ages 9–10 in very-preterm, moderately-preterm, and full-term children, and explore whether these alterations predict ASD/ADHD symptoms at age 12.</div></div><div><h3>Methods</h3><div>This longitudinal population-based study included 9–10-year-old U.S. children from ABCD Study. Children underwent brain imaging and cognitive assessment using NIH Toolbox. Cortical thickness and subcortical volumes of preterm-children with low cognitive-performance (NIH composite score &lt; -1SD and &gt; -2SD) were compared with preterm and full-term peers with typical performance (≥-1SD). Structural covariance networks were also examined.</div></div><div><h3>Results</h3><div>Among 7281 children (mean age 9.9 ± 0.6 years; 52.2 % boys), 71 were very-preterm, 151 moderately-preterm, and 7056 full-term. Low cognitive-performance was most prevalent in very-preterm children (29.6 %), followed by moderately-preterm (24.0 %) and full-term children (16.2 %).</div><div>Very-preterm children with low cognitive-performance had thinner inferior temporal cortex (β = -0.58; p = 0.03), thinner fusiform gyrus (β = -0.62; p = 0.02), and larger amygdala volumes (β = 0.41; p = 0.05) compared to very-preterm children with typical performance. Moderately-preterm children with low cognitive-performance had smaller hippocampal volumes (β = -0.32; p = 0.01). Similar patterns were observed when comparing preterm children with low cognitive-performance to full-term peers with typical performance. Structural covariance network analysis revealed stronger covariance between the precuneus-postcentral gyrus pair among moderately-preterm children with low cognitive-performance. Individualized Differential Structural Covariance Network values extracted from this pair were positively associated with ASD/ADHD symptoms, though not statistically significance.</div></div><div><h3>Conclusion</h3><div>Low cognitive performance in preterm children is associated with distinct regional and network-level brain differences, differing by prematurity. Stronger hub covariance may reflect compensatory mechanisms, highlighting the need for prematurity-tailored interventions.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"48 ","pages":"Article 103876"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018394","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":"Corrigendum to “Disturbed hierarchy and mediation in reward-related circuits in depression”. [45 (2025) 103739]","authors":"Ruikun Yang ,&nbsp;Junxia Chen ,&nbsp;Suping Yue ,&nbsp;Yue Yu ,&nbsp;Jiamin Fan ,&nbsp;Yuling Luo ,&nbsp;Hui He ,&nbsp;Mingjun Duan ,&nbsp;Sisi Jiang ,&nbsp;Dezhong Yao ,&nbsp;Cheng Luo","doi":"10.1016/j.nicl.2025.103855","DOIUrl":"10.1016/j.nicl.2025.103855","url":null,"abstract":"","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"47 ","pages":"Article 103855"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144765792","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":"Deep convolutional neural networks outperform vanilla machine learning when predicting language outcomes after stroke","authors":"Thomas M.H. Hope ,&nbsp;Howard Bowman ,&nbsp;Alex P. Leff ,&nbsp;Cathy J. Price","doi":"10.1016/j.nicl.2025.103880","DOIUrl":"10.1016/j.nicl.2025.103880","url":null,"abstract":"<div><h3>Background</h3><div>Current medicine cannot confidently predict patients’ language skills after stroke. In recent years, researchers have sought to bridge this gap with machine learning. These models appear to benefit from access to features describing where and how much brain damage these patients have suffered. Given the very high dimensionality of structural brain imaging data, those brain lesion features are typically post-processed from the images themselves into tabular features. With the introduction of deep Convolutional Neural Networks (CNN), which appear to be much more robust to high dimensional data, it is natural to hope that much of this image post-processing might be unnecessary. But prior attempts to demonstrate this (in the area of post-stroke prognostics) have so far yielded only equivocal results – perhaps because the datasets that those studies could deploy were too small to properly constrain CNNs, which are famously ‘data-hungry’.</div></div><div><h3>Methods</h3><div>The study draws on a much larger dataset than has been employed in previous work like this, referring to patients whose language outcomes were assessed once during the chronic phase post-stroke, on or around the same days as they underwent high resolution MRI brain scans. Following the model of our own and others’ past work, we use state of the art ‘vanilla’ machine learning models (boosted ensembles) to predict a variety of language and cognitive outcomes scores. These models employ both demographic variables and features derived from the brain imaging data, which represent where brain damage has occurred. These are our baseline models. Next, we use deep CNNs to predict the same language scores for the same patients, drawing on both the demographic variables, and post-processed brain lesion images: i.e., multi-input models with one input for tabular features and another for 3-dimensional images. We compare the models using 5 × 2-fold cross-validation, with consistent folds.</div></div><div><h3>Results</h3><div>The CNN models consistently outperform the vanilla machine learning models, in this domain.</div></div><div><h3>Conclusions</h3><div>Deep CNNs offer state of the art performance when predicting language outcomes after stroke, outperforming vanilla machine learning and obviating the need to post-process lesion images into lesion features.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"48 ","pages":"Article 103880"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219053","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":"Corrigendum to “Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis” [Neuroimage: Clin. 42 (2024) 103598]","authors":"Cui Ci Voon ,&nbsp;Tun Wiltgen ,&nbsp;Benedikt Wiestler ,&nbsp;Sarah Schlaeger ,&nbsp;Mark Mühlau","doi":"10.1016/j.nicl.2024.103693","DOIUrl":"10.1016/j.nicl.2024.103693","url":null,"abstract":"","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103693"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565306","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":"Radiomics feature similarity: A novel approach for characterizing brain network changes in patients with behavioral variant frontotemporal dementia","authors":"Salvatore Nigro ,&nbsp;Marco Filardi ,&nbsp;Benedetta Tafuri ,&nbsp;Roberto De Blasi ,&nbsp;Maria Teresa Dell’Abate ,&nbsp;Alessia Giugno ,&nbsp;Valentina Gnoni ,&nbsp;Giammarco Milella ,&nbsp;Daniele Urso ,&nbsp;Chiara Zecca ,&nbsp;Stefano Zoccolella ,&nbsp;Giancarlo Logroscino","doi":"10.1016/j.nicl.2025.103780","DOIUrl":"10.1016/j.nicl.2025.103780","url":null,"abstract":"<div><h3>Introduction</h3><div>Network modeling is increasingly used to study brain alterations in neurological disorders. In this study, we apply a novel modeling approach based on the similarity of regional radiomics feature to characterize gray matter network changes in patients with behavioral variant frontotemporal dementia (bvFTD) using MRI data.</div></div><div><h3>Methods</h3><div>In this cross-sectional study, we assessed structural 3 T MRI data from twenty patients with bvFTD and 20 cognitively normal controls. Radiomics features were extracted from T1-weighted MRI based on cortical and subcortical brain segmentation. Similarity in radiomics features between brain regions was used to construct intra-individual structural gray matter networks. Regional mean connectivity strength (RMCS) and region-to-region radiomics similarity were compared between bvFTD patients and controls. Finally, associations between network measures, clinical data, and biological features were explored in bvFTD patients.</div></div><div><h3>Results</h3><div>Relative to controls, patients with bvFTD showed higher RMCS values in the superior frontal gyrus, right inferior temporal gyrus and right inferior parietal gyrus (FDR-corrected p &lt; 0.05). Patients with bvFTD also showed several edges of increased radiomics similarity in key components of the frontal, temporal, parietal and thalamic pathways compared to controls (FDR-corrected p &lt; 0.05). Network measures in frontotemporal circuits were associated with Mini-Mental State Examination scores and cerebrospinal fluid total-tau protein levels (Spearman r &gt; |0.7|, p &lt; 0.005).</div></div><div><h3>Conclusions</h3><div>Our study provides new insights into frontotemporal network changes associated with bvFTD, highlighting specific associations between network measures and clinical/biological features. Radiomics feature similarity analysis could represent a useful approach for characterizing brain changes in patients with frontotemporal dementia.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103780"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800414","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":"Detection of structural-functional coupling abnormalities using multimodal brain networks in Alzheimer’s disease: A comparison of three computational models","authors":"Yinping Lu ,&nbsp;Luyao Wang ,&nbsp;Toshiya Murai ,&nbsp;Jinglong Wu ,&nbsp;Dong Liang ,&nbsp;Zhilin Zhang","doi":"10.1016/j.nicl.2025.103764","DOIUrl":"10.1016/j.nicl.2025.103764","url":null,"abstract":"<div><div>Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by the disconnection of white matter fibers and disrupted functional connectivity of gray matter; however, the pathological mechanisms linking structural and functional changes remain unclear. This study aimed to explore the interaction between the structural and functional brain network in AD using advanced structural–functional coupling (S-F coupling) models to assess whether these changes correlate with cognitive function, Aβ deposition levels, and gene expression. In this study, we utilized multimodal magnetic resonance imaging data from 41 individuals with AD, 112 individuals with mild cognitive impairment, and 102 healthy controls to explore these mechanisms. We applied different computational models to examine the changes in the S-F coupling associated with AD. Our results showed that the communication and graph harmonic models demonstrated greater heterogeneity and were more sensitive than the statistical models in detecting AD-related pathological changes. In addition, S-F coupling increases with AD progression at the global, subnetwork, and regional node levels, especially in the medial prefrontal and anterior cingulate cortices. The S-F coupling of these regions also partially mediated cognitive decline and Aβ deposition. Furthermore, gene enrichment analysis revealed that changes in S-F coupling were strongly associated with the regulation of cellular catabolic processes. This study advances our understanding of the interaction between structural and functional connectivity and highlights the importance of S-F coupling in elucidating the neural mechanisms underlying cognitive decline in AD.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103764"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642667","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":"Striato-cortical connectivity patterns predict clinical profiles in Huntington’s disease","authors":"Audrey E. De Paepe ,&nbsp;Vasiliki Bikou ,&nbsp;Eylül Turan ,&nbsp;Alexis Pérez-Bellido ,&nbsp;Clara Garcia-Gorro ,&nbsp;Nadia Rodriguez-Dechicha ,&nbsp;Irene Vaquer ,&nbsp;Matilde Calopa ,&nbsp;Ruth de Diego-Balaguer ,&nbsp;Estela Camara","doi":"10.1016/j.nicl.2025.103788","DOIUrl":"10.1016/j.nicl.2025.103788","url":null,"abstract":"<div><h3>Background</h3><div>Huntington’s disease is an inherited neurodegenerative disorder affecting striato-cortical circuits, with significant heterogeneity in the severity and progression of symptoms and neurodegenerative patterns.</div></div><div><h3>Objectives</h3><div>To identify how distinct functional striato-cortical connectivity signatures may predict clinical profiles in Huntington’s disease.</div></div><div><h3>Methods</h3><div>Thirty-eight Huntington’s disease gene expansion carriers underwent cross-sectional motor, cognitive, and behavioral assessments and multimodal MRI. Principal component analysis was employed to characterize Huntington’s disease clinical profiles. Next, seed-based whole-brain functional connectivity maps were derived for three basal ganglia seeds (caudate nucleus, putamen, nucleus accumbens) to delineate cortico-striatal connections. Multiple linear regressions assessed relationships between resulting clinical profiles and seed-based resting-state functional connectivity maps. Finally, basal ganglia gray matter volumes were examined in relation to clinical profiles and connectivity.</div></div><div><h3>Results</h3><div>Principal component analysis identified two main clinical profiles in Huntington’s disease: motor-cognitive and behavioral. Multiple linear regression models revealed distinct functional neural signatures associated with each profile. Motor-cognitive symptoms related with a divergent connectivity pattern, specifically decreased connectivity between the caudate and putamen with executive and premotor areas, in contrast to increased connectivity between the ventral nucleus accumbens and executive network regions. Meanwhile, the behavioral profile was linked to decreased connectivity in limbic networks. Basal ganglia atrophy was associated with increased nucleus accumbens-cortical connectivity as well as motor-cognitive symptom severity.</div></div><div><h3>Conclusions</h3><div>Distinct Huntington’s disease clinical profiles can be characterized by predominantly motor-cognitive or behavioral disturbances, each related with unique functional and structural brain signatures. This substantiates that striato-cortical circuits exhibit functional interaction and potential reorganization.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103788"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868165","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":"Partial volume effect correction impairs the diagnostic utility of [18F]-THK-5351 PET in nonfluent-agrammatic variant primary progressive aphasia","authors":"Patrick J. Sommer ,&nbsp;Sebastian Schuster ,&nbsp;Oliver Goldhardt ,&nbsp;Nobuyuki Okamura ,&nbsp;Felix Mueller-Sarnowski ,&nbsp;Maximilian Scheifele ,&nbsp;Florian Eckenweber ,&nbsp;Annika Kreuzer ,&nbsp;Maria Griessl ,&nbsp;Peter Bartenstein ,&nbsp;Thomas Wegehaupt ,&nbsp;Lucas Wolski ,&nbsp;Josef Priller ,&nbsp;Axel Rominger ,&nbsp;Leonie Beyer ,&nbsp;Timo Grimmer ,&nbsp;Matthias Brendel","doi":"10.1016/j.nicl.2025.103789","DOIUrl":"10.1016/j.nicl.2025.103789","url":null,"abstract":"<div><h3>Objectives</h3><div>Partial volume effects in positron emission tomography occur frequently in neurodegenerative diseases due to increasing cortical atrophy during the disease course, and fronto-temporal dementia is often characterized by severe atrophy. The aim of this study was to challenge partial volume effect correction (PVEC) in patients with nonfluent-agrammatic variant primary progressive aphasia (nfv-PPA) imaged with [¹⁸F]-THK-5351 PET a marker of reactive neuroinflammatory astrogliosis as well as tau-binding.</div></div><div><h3>Methods</h3><div>Patients with nfv-PPA (n = 20) were imaged with [¹⁸F]-THK-5351 PET accompanied by structural magnetic resonance tomography imaging (MRI). Region specific cortical grey matter volumes and standard uptake value ratios (SUVr) of the Hammers atlas were compared with eight healthy control (HC) (n = 8) data before and after performing region-based voxel-wise PVEC. We evaluated regional coefficients of variance (CoV) and the number of regions with significant [¹⁸F]-THK-5351 PET signal differences between nfv-PPA and controls before and after PVEC. Additionally, a blinded visual read was performed by three nuclear medicine physicians (consensus) before and after PVEC.</div></div><div><h3>Results</h3><div>Prior to PVEC, [¹⁸F]-THK-5351 tracer uptake was significantly higher in the bilateral frontal cortex of patients with nfv-PPA when compared to HC (left &gt; right), despite significant grey matter atrophy in the same brain regions in patients with nfv-PPA. SUVr differences between nfv-PPA and HC were further increased by PVEC in frontal brain regions, but group level variance increased in parallel and reduced the number of significant differences between SUVr of nfv-PPA and HC (uncorrected: 10 significant regions, CoV[nfv-PPA]: 20.8 % ± 4.7 %, CoV[HC]: 7.9 % ± 2.4 %/PVEC: 3 significant regions, CoV[nfv-PPA]: 28.4 % ± 8.9 %, CoV[HC]: 9.8 % ± 2.5 %). Sensitivity/specificity of the visual read for detection of nfv-PPA was 0.85/1.00 without PVEC and 0.85/0.75 with PVEC.</div></div><div><h3>Conclusions</h3><div>[¹⁸F]-THK-5351 PET facilitates detection of pathological alterations in patients with nfvPPA with severe atrophy. PVEC increases quantitative SUVr differences between patients with nfv-PPA and HC but introduces a parallel increase of variance at the group level. Visual assessment of [¹⁸F]-THK-5351 images in patients with nfv-PPA is impaired by PVEC due to loss of specificity and does not support the use of PVEC even in patients with severe atrophy.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103789"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877363","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}