Neuroimage-Clinical最新文献

{"title":"Posterior hippocampal sparing in Lewy body disorders with Alzheimer’s copathology: An in vivo MRI study","authors":"Jesse S. Cohen , Jeffrey Phillips , Sandhitsu R. Das , Christopher A. Olm , Hamsanandini Radhakrishnan , Emma Rhodes , Katheryn A.Q. Cousins , Sharon X. Xie , Ilya M. Nasrallah , Paul A. Yushkevich , David A. Wolk , Edward B. Lee , Daniel Weintraub , David J. Irwin , Corey T. McMillan","doi":"10.1016/j.nicl.2024.103714","DOIUrl":"10.1016/j.nicl.2024.103714","url":null,"abstract":"<div><h3>Background</h3><div>Lewy body disorders (LBD), encompassing Parkinson disease (PD), PD dementia (PDD), and dementia with Lewy bodies (DLB), are characterized by alpha-synuclein pathology but often are accompanied by Alzheimer’s disease (AD) neuropathological change (ADNC). The medial temporal lobe (MTL) is a primary locus of tau accumulation and associated neurodegeneration in AD. However, it is unclear the extent to which AD copathology in LBD (LBD/AD+) contributes to MTL-specific patterns of degeneration. We employ a MTL subregional segmentation strategy of T1-weighted (T1w) MRI in biomarker-supported or autopsy-confirmed LBD and LBD/AD+ to investigate the anatomic consequences of co-occurring LBD/AD+ pathology on neurodegeneration.</div></div><div><h3>Methods</h3><div>We studied 167 individuals with clinical diagnoses of LBD (PD, n = 124 (74.3 %); PDD, n = 11 (6.6 %); DLB, n = 32 (19.2 %)) with available T1w MRI and AD biomarkers or autopsy evidence of ADNC. Individuals were further biologically classified as LBD/AD+ based on hierarchical evidence of ADNC pathology: 1) AD “intermediate” or “high” by ABC neuropathologic criteria (n = 39 (23.4 %)); 2) positive amyloid PET (n = 2 (1.2 %)); or 3) CSF β-amyloid<sub>1-42</sub> < 185.7 pg/mL n = 126 (75.4 %)). The T1 Automated Segmentation of Hippocampal Subfields (ASHS) pipeline was used to compute volume and thickness measurements of MTL subregions in LBD/AD- and LBD/AD+. Linear regression tested the association of AD copathology and subregion volume/thickness, covarying for age and sex, and intracranial volume for volume measurements. Secondary analyses correlated MTL subregional volume/thickness with cognition and neuropathology.</div></div><div><h3>Results</h3><div>LBD/AD+ had decreased volume/thickness compared to LBD/AD- in all MTL subregions except posterior hippocampus. The greatest effect sizes were seen in Brodmann Area 35 (BA35) (Cohen’s d = 0.62, p = 0.002, β = 0.107 ± 0.034), and entorhinal cortex (ERC) (Cohen’s d = 0.56, p = 0.006, β = 0.088 ± 0.031). Smaller differences were seen in the parahippocampal cortex (PHC) (Cohen’s d = 0.5, p = 0.012, β = 0.082 ± 0.033), BA36 (Cohen’s d = 0.47, p = 0.021, β = 0.090 ± 0.039) and anterior hippocampus (Cohen’s d = 0.45, p = 0.029, β = 111.790 ± 50.595). Verbal memory scores positively correlated with volume/thickness in anterior and posterior hippocampus, BA35, ERC and PHC, while visuospatial memory positively correlated only in BA35. In the subset of participants with autopsy, lower ERC volume was associated with a higher tau load in ERC (adjusted odds ratio 0.013, 95 % CI [0.0002, 0.841], uncorrected p = 0.041).</div></div><div><h3>Conclusions</h3><div>Relative to LBD/AD-, LBD/AD+ has greater T1w MRI evidence of atrophy in multiple MTL subregions. Atrophy in MTL subregions associates with memory performance and tau pathological load. The observed pattern of atrophy largely follows expectation from AD Braak stages, except for poster","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103714"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11713745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830830","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":"Mechanisms underlying the spontaneous reorganization of depression network after stroke","authors":"Yirong Fang ,&nbsp;Xian Chao ,&nbsp;Zeyu Lu ,&nbsp;Hongmei Huang ,&nbsp;Ran Shi ,&nbsp;Dawei Yin ,&nbsp;Hao Chen ,&nbsp;Yanan Lu ,&nbsp;Jinjing Wang ,&nbsp;Peng Wang ,&nbsp;Xinfeng Liu ,&nbsp;Wen Sun","doi":"10.1016/j.nicl.2024.103723","DOIUrl":"10.1016/j.nicl.2024.103723","url":null,"abstract":"<div><div>Exploring the causal relationship between focal brain lesions and post-stroke depression (PSD) can provide therapeutic insights. However, a gap exists between causal and therapeutic information. Exploring post-stroke brain repair processes post-stroke could bridge this gap.</div><div>We defined a depression network using the normative connectome and investigated the predictive capacity of lesion-induced network damage on depressive symptoms in discovery cohort of 96 patients, at baseline and six months post-stroke. Stepwise functional connectivity (SFC) was used to examine topological changes in the depression network over time to identify patterns of network reorganization. The predictive value of reorganization information was evaluated for follow-up symptoms in discovery and validation cohort 1 (22 worsening PSD patients) as well as for treatment responsiveness in validation cohort 2 (23 antidepressant-treated patients). We evaluated the consistency of significant reorganization areas with neuromodulation targets. Spatial correlations of network reorganization patterns with gene expression and neurotransmitter maps were analyzed.</div><div>The predictive power of network damage for symptoms diminished at follow-up compared to baseline (Δadjusted R² = -0.070, p &lt; 0.001). Reorganization information effectively predicted symptoms at follow-up in the discovery cohort (adjust R² = 0.217, 95 %CI: 0.010 to 0.431), as well as symptom exacerbation (r = 0.421, p = 0.033) and treatment responsiveness (r = 0.587, p = 0.012) in the validation cohorts. Regions undergoing significant reorganization overlapped with neuromodulatory targets known to be effective in treating depression. The reorganization of the depression network was associated with immune-inflammatory responses gene expressions and gamma-aminobutyric acid.</div><div>Our findings may yield important insights into the repair mechanisms of PSD and provide a critical context for developing post-stroke treatment strategies.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103723"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11699604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824543","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":"Post-stroke outcome prediction based on lesion-derived features","authors":"Maedeh Khalilian ,&nbsp;Olivier Godefroy ,&nbsp;Martine Roussel ,&nbsp;Amir Mousavi ,&nbsp;Ardalan Aarabi","doi":"10.1016/j.nicl.2025.103747","DOIUrl":"10.1016/j.nicl.2025.103747","url":null,"abstract":"<div><div>Stroke-induced deficits result from both focal structural damage and widespread network disruption. This study investigated whether simulated measures of network disruption, derived from structural lesions, could predict functional impairments in stroke patients. We extracted four lesion-derived feature sets: lesion masks, probabilistic structural disconnection maps (pSDMs), structural and indirectly estimated functional connectivity strengths between brain regions, and topological properties of functional and structural brain networks to predict motor, executive, and processing speed deficits in 340 S patients, employing PCA-based ridge regression with leave-one-out cross validation.</div><div>The findings revealed that both structural disconnection map patterns and lesion masks were strong predictors of functional deficits. Lesion masks exhibited superior predictive performance relative to unthresholded pSDMs. Furthermore, applying a probability threshold to the pSDMs − retaining only disconnections present in a sufficient proportion of healthy subjects − significantly improved predictive performance. For motor deficits, thresholded SDMs (tSDMs) with thresholds of 0.9 and 0.5 produced the highest R² values, 0.95 for left motor deficits and 0.69 for right motor deficits, respectively. In the case of executive function and processing speed, the highest R² values were 0.58 and 0.64, achieved with tSDM thresholds of 0.3 and 0.5, respectively. Connectome-based features exhibited lower R² values, with structural connection strength alterations showing stronger associations with post-stroke scores compared to changes in functional connectivity. Nodal parameters (degree and clustering coefficient) had lower explanatory power than the SDM features and lesion masks.</div><div>Our findings underscore the effectiveness of lesion masks and thresholded SDMs in predicting post-stroke deficits. This study contributes to the growing body of evidence supporting the reliability of simulated structural networks as a complementary approach to lesion patterns and structural disconnection in predicting post-stroke outcomes.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103747"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143182711","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":"Atypical oscillatory and aperiodic signatures of visual sampling in developmental dyslexia","authors":"Alessia Santoni ,&nbsp;Giuseppe Di Dona ,&nbsp;David Melcher ,&nbsp;Laura Franchin ,&nbsp;Luca Ronconi","doi":"10.1016/j.nicl.2024.103720","DOIUrl":"10.1016/j.nicl.2024.103720","url":null,"abstract":"<div><div>Temporal processing deficits in Developmental Dyslexia (DD) have been documented extensively at the behavioral level, leading to the formulation of neural theories positing that such anomalies in parsing multisensory input rely on aberrant synchronization of neural oscillations or to an excessive level of neural noise. Despite reading being primarily supported by visual functions, experimental evidence supporting these theories remains scarce. Here, we tested 26 adults with DD (9 females) and 31 neurotypical controls (16 females) with a temporal segregation/integration task that required participants to either integrate or segregate two rapidly presented displays while their EEG activity was recorded. We confirmed a temporal sampling deficit in DD, which specifically affected the rapid segregation of visual input. While the ongoing alpha frequency and the excitation/inhibition (E/I) ratio (i.e., an index of neural noise quantified by the aperiodic exponent) were differently modulated based on task demands in typical readers, DD participants exhibited an impairment in alpha speed modulation and an altered E/I ratio that affected their rapid visual sampling. Nonetheless, an association between visual temporal sampling accuracy and both alpha frequency and the E/I ratio measured at rest were evident in the DD group, further confirming an anomalous interplay between alpha synchronization, the E/I ratio and active visual sampling. These results provide evidence that both trait- and state-like differences in alpha-band synchronization and neural noise levels coexist in the dyslexic brain and are synergistically responsible for cascade effects on visual sampling and reading.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103720"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11665574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792825","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":"Grey matter volume differences across Parkinson’s disease motor subtypes in the supplementary motor cortex","authors":"A. Martin ,&nbsp;J. Nassif ,&nbsp;L. Chaluvadi ,&nbsp;C. Schammel ,&nbsp;R. Newman-Norlund ,&nbsp;S. Bollmann ,&nbsp;J. Absher","doi":"10.1016/j.nicl.2024.103724","DOIUrl":"10.1016/j.nicl.2024.103724","url":null,"abstract":"<div><div>Parkinson’s Disease (PD) is the second most prevalent neurodegenerative disease worldwide due to loss of dopaminergic neurons projecting from the basal ganglia (BG). It is associated with various motor symptoms that are grouped into subtypes, each with different clinical presentations and disease progressions. Neuroimaging biomarkers focusing on regions a part of motor circuits projecting from the BG can distinguish and improve overall subtyping. The supplementary motor cortex (SMC) is well established in PD neuropathology and associated with freezing of gait and bradykinesia, but has not been thoroughly evaluated across subtypes. This study aims to identify volumetric differences of the SMC based on PD subtypes of tremor dominant (TD), postural instability with gait difficulty (PIGD), and akinetic rigid (AR) using data from Parkinson’s Progression Markers Initiative. To segment grey matter volume and extract region of interest values, voxel-based processing was used. Multi-factor ANCOVAs, Tukey Honest Significance Test, and Kruskal-Wallis were utilized for volumetric analyses (α &lt; 0.05). Subjects were classified and evaluated using TD, PIGD, and AR subtypes from the MDS-UPDRS rating scales. Inter-subtype differences in SMC GMV between TD and PIGD were significant in the right hemisphere for females (p = 0.01). No significant inter-subtype differences were found in the TD/AR system. These results support the use of broader motor networks, specifically the SMC in further understanding the neuropathological heterogeneity of PD. Furthermore, it reveals SMC differences across sexes, subtypes, and subtyping systems, calling for further evaluation of subtyping schemas, specifically regarding sex differences.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103724"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11699459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824611","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":"Consistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia","authors":"Yijie Zhang ,&nbsp;Shuzhan Gao ,&nbsp;Chuang Liang ,&nbsp;Juan Bustillo ,&nbsp;Peter Kochunov ,&nbsp;Jessica A. Turner ,&nbsp;Vince D. Calhoun ,&nbsp;Lei Wu ,&nbsp;Zening Fu ,&nbsp;Rongtao Jiang ,&nbsp;Daoqiang Zhang ,&nbsp;Jing Jiang ,&nbsp;Fan Wu ,&nbsp;Ting Peng ,&nbsp;Xijia Xu ,&nbsp;Shile Qi","doi":"10.1016/j.nicl.2024.103726","DOIUrl":"10.1016/j.nicl.2024.103726","url":null,"abstract":"<div><h3>Background and hypothesis</h3><div>Treatment-resistant schizophrenia (TR-SZ) and non-treatment-resistant schizophrenia (NTR-SZ) lack specific biomarkers to distinguish from each other. This investigation aims to identify consistent dysfunctional brain connections with different atlases, multiple feature selection strategies, and several classifiers in distinguishing TR-SZ and NTR-SZ.</div></div><div><h3>Study design</h3><div>55 TR-SZs, 239 NTR-SZs, and 87 healthy controls (HCs) were recruited from the Affiliated Brain Hospital of Nanjing Medical University. Resting-state functional connection (FC) matrices were constructed from automated anatomical labeling (AAL), Yeo-Networks (YEO) and Brainnetome (BNA) atlases. Two feature selection methods (Select From Model and Recursive Feature Elimination) and four classifiers (Adaptive Boost, Bernoulli Naïve Bayes, Gradient Boosting and Random Forest) were combined to identify the consistent FCs in distinguishing TR-SZ and HC, NTR-SZ and HC, TR-SZ and NTR-SZ.</div></div><div><h3>Study results</h3><div>The whole brain FCs, except the temporal-occipital FC, were consistent in distinguishing SZ and HC. Abnormal frontal-limbic, frontal-parietal and occipital-temporal FCs were consistent in distinguishing TR-SZ and NTR-SZ, that were further correlated with disease progression, symptoms and medication dosage. Moreover, the frontal-limbic and frontal-parietal FCs were highly consistent for the diagnosis of SZ (TR-SZ vs. HC, NTR-SZ vs. HC and TR-SZ vs. NTR-SZ). The BNA atlas achieved the highest classification accuracy (&gt;90 %) comparing with AAL and YEO in the most diagnostic tasks.</div></div><div><h3>Conclusions</h3><div>These results indicate that the frontal-limbic and the frontal-parietal FCs are the robust neural pathways in the diagnosis of SZ, whereas the frontal-limbic, frontal-parietal and occipital-temporal FCs may be informative in recognizing those TR-SZ in the clinical practice.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103726"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142866297","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":"“Actor-critic” dichotomous hyperactivation and hypoconnectivity in obsessive–compulsive disorder","authors":"Ana Araújo ,&nbsp;Isabel C. Duarte ,&nbsp;Teresa Sousa ,&nbsp;Sofia Meneses ,&nbsp;Ana T. Pereira ,&nbsp;Trevor Robbins ,&nbsp;António Macedo ,&nbsp;Miguel Castelo-Branco","doi":"10.1016/j.nicl.2024.103729","DOIUrl":"10.1016/j.nicl.2024.103729","url":null,"abstract":"<div><div>Dysfunctional response inhibition, mediated by the striatum and its connections, is thought to underly the clinical manifestations of obsessive–compulsive disorder (OCD). However, the exact neural mechanisms remain controversial. In this study, we undertook a novel approach by positing that a) inhibition is a dynamic construct inherently susceptible to numerous failures, which require error-processing, and b) the actor-critic framework of reinforcement learning can integrate neural patterns of inhibition and error-processing in OCD with their behavioural correlates. We invited nineteen adults with OCD and 21 age-matched healthy controls to perform an fMRI-adjusted stop-signal task. Then, we extracted brain activation and connectivity values regarding distinct task phases in the “actor” and “critic” regions, here corresponding to the caudate’s head and dorsal putamen, and midbrain’s nuclei (ventral tegmental area and substantia nigra). During response preparation phases of the inhibitory process, individuals with OCD exhibited decreased functional connectivity between the “critic” structures and frontal regions involved in cognitive and executive control. Activity analysis revealed task-related hyperactivation in the midbrain alongside error-processing-specific hyperactivation in the striatum, which was correlated with excessive behavioural slowness, also found in the clinical group. Finally, we identified a remarkable opponency between activity in the ventral tegmental area and caudate leading to direct increases and indirect decreases in symptom severity. We propose a unique “actor-critic”-based domain- and timing-dependent neural profile in OCD, reflecting “harm-avoidant” styles for response suppression, and influencing symptom severity. The dichotomy of hypoconnectivity and hyperactivation in the “critic” along with the opponent relationship between the “actor” and the “critic” in determining symptom severity suggests the implication of neural adaptation mechanisms in OCD with potential relevance for neurobiologically-driven therapies.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103729"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11762915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142958875","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":"Use of multi-modal non-contrast MRI to predict functional outcomes after stroke: A study using DP-pCASL, DTI, NODDI, and MAP MRI","authors":"Julia Diamandi ,&nbsp;Christian Raimondo ,&nbsp;Keenan Piper ,&nbsp;Joanna Roy ,&nbsp;Stephanie Serva ,&nbsp;Mahdi Alizadeh ,&nbsp;Adam Flanders ,&nbsp;Stavropoula Tjoumakaris ,&nbsp;Reid Gooch ,&nbsp;Pascal Jabbour ,&nbsp;Robert Rosenwasser ,&nbsp;Nikolaos Mouchtouris","doi":"10.1016/j.nicl.2025.103742","DOIUrl":"10.1016/j.nicl.2025.103742","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aims to assess whether water exchange rate (k_w), a surrogate for blood–brain barrier (BBB) permeability, is associated with functional outcomes in patients with acute ischemic stroke (AIS).</div></div><div><h3>Methods</h3><div>We studied 22 AIS patients enrolled from 1/2022 to 4/2024 who underwent multi-modal non-contrast imaging on a 3.0-Tesla scanner, including DP-pCASL, DTI, NODDI and MAP imaging. For each parametric map, the intensity and standard deviation (SD) were calculated for the infarcted region. The diffusion maps included were b0, Fractional Anisotropy (FA), Mean Diffusivity (MD), Intra-cellular Volume Fraction (ICVF), Free Water Fraction (FWF), and Orientation Dispersion Index (ODI), q-Space Mean Square Displacement (QMSD), Return-to-Axis Probability (RTAP), Return-to-Plane Probability (RTPP), Return-to-Origin Probability (RTOP), Propagator Anisotropy (PA), and non-Gaussianity (NG). The perfusion-based maps were cerebral blood flow (CBF), arterial transit time (ATT), and k_w. The outcome variable was modified Rankin Scale (mRS).</div></div><div><h3>Results</h3><div>Twenty-two patients were included. The average age was 69.5 ± 13.5, the mean NIHSS of 12.4 ± 7.7, and the median infarct of 25.7 (8.4–98.8) ml. Multivariable linear regression identified lower k_w (β = −0.029, p = 0.041), longer time to MRI (β = 0.012, p = 0.013) and larger stroke volume (β = 0.014, p = 0.006) as predictive of higher mRS. Higher CBF (β = 0.660, p = 0.003) and RTAP (β = 1.528, p = 0.010), and lower SD RTAP (β = −0.709, p = 0.016), RTPP (β = −2.132, p = 0.006), and NG (β = −1.036, p = 0.011) were identified as most predictive of k_w through multivariable linear regression analysis.</div></div><div><h3>Conclusions</h3><div>Lower k_w is predictive of higher mRS in patients with AIS. Increasing CBF and RTAP and lower SD RTAP, RTPP, and NG were correlated with higher k_w.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103742"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048588","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":"Lesion network mapping of REM Sleep Behaviour Disorder","authors":"H. Odd ,&nbsp;C. Dore ,&nbsp;S.H. Eriksson ,&nbsp;L. Heydrich ,&nbsp;P. Bargiotas ,&nbsp;J. Ashburner ,&nbsp;C. Lambert","doi":"10.1016/j.nicl.2025.103751","DOIUrl":"10.1016/j.nicl.2025.103751","url":null,"abstract":"<div><div>REM Sleep Behaviour Disorder (RBD) is a parasomnia characterised by dream enactment behaviour due to loss of sleep atonia during REM sleep. It is of considerable interest as idiopathic RBD is strongly associated with a high risk of future α-synuclein disorders. Whilst candidate brainstem structures for sleep atonia have been identified in animal studies, the precise mechanisms underpinning RBD in humans remain unclear. Here, we set out to empirically define a candidate anatomical RBD network using lesion network mapping. Our objective was to test the hypothesis that RBD is either due to damage to <em>canonical RBD nodes</em> previously identified in the animal literature, or disruption to the white matter connections between these nodes, or as a consequence of damage to some other brains regions.</div><div>All published cases of secondary RBD arising due to discrete brain lesions were reviewed and those providing sufficient detail to estimate the original lesion selected. This resulted in lesion masks for 25 unique RBD cases. These were combined to create a lesion probability map, demonstrating the area of maximal overlap. We also obtained MRI lesion masks for 15 pontine strokes that had undergone sleep polysomnography investigations confirming the absence of RBD. We subsequently used these as an exclusion mask and removed any intersecting voxels from the aforementioned region of maximal overlap, creating a single candidate region-of-interest (ROIs) within the pons. This remaining region overlapped directly with the locus coeruleus. As sleep atonia is unlikely to be lateralized, a contralateral ROI was created via a left–right flip, and both were warped to the 100 healthy adult Human Connectome dataset. Probabilistic tractography was run from each ROI to map and characterize the white-matter tracts and connectivity properties.</div><div>All reported lesions were within the brainstem but there was significant variability in location. Only half of these intersected with at least one of the six a priori RBD anatomical nodes assessed, however 72 % directly intersected with the white matter tracts created from the region of maximum overlap pontine ROIs, and the remainder were within 3.05 mm (±1.51 mm) of these tracts. 92 % of lesions were either at the level of region of maximum overlap or caudal to it.</div><div>These results suggest that RBD is a brainstem disconnection syndrome, where damage anywhere along the tract connecting the rostral locus coeruleus and medulla may result in failure of sleep atonia, in line with the animal literature. This implies idiopathic disease may emerge through different patterns of damage across this brainstem circuit. This observation may account for the both the paucity of brainstem neuroimaging results reported to date and the observed phenotypic variability seen in idiopathic RBD.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103751"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421553","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":"Multi-atlas multi-modality morphometry analysis of the South Texas Alzheimer’s Disease Research Center postmortem repository","authors":"Nicolas Honnorat ,&nbsp;Mariam Mojtabai ,&nbsp;Karl Li ,&nbsp;Jinqi Li ,&nbsp;David Michael Martinez ,&nbsp;Tanweer Rashid ,&nbsp;Morgan Smith ,&nbsp;Margaret E Flanagan ,&nbsp;Elyas Fadaee ,&nbsp;Morgan Fox Torres ,&nbsp;Mallory Keating ,&nbsp;Kevin Bieniek ,&nbsp;Sudha Seshadri ,&nbsp;Mohamad Habes","doi":"10.1016/j.nicl.2025.103752","DOIUrl":"10.1016/j.nicl.2025.103752","url":null,"abstract":"<div><div>Histopathology provides critical insights into the neurological processes inducing neurodegenerative diseases and their impact on the brain, but brain banks combining histology and neuroimaging data are difficult to create. As part of an ongoing global effort to establish new brain banks providing both high-quality neuroimaging scans and detailed histopathology examinations, the South Texas Alzheimer’s Disease Re- search Center postmortem repository was recently created with the specific purpose of studying comorbid dementias. As the repository is reaching a milestone of two hundred brain donations and a hundred curated MRI sessions are ready for processing, robust statistical analyses can now be conducted. In this work, we report the very first morphometry analysis conducted with this new data set. We describe the processing pipelines that were specifically developed to exploit the available MRI sequences, and we explain how we addressed several postmortem neuroimaging challenges, such as the separation of brain tissues from fixative fluids, the need for updated brain atlases, and the tissue contrast changes induced by brain fixation. In general, our results establish that a combination of structural MRI sequences can provide enough informa- tion for state-of-the-art Deep Learning algorithms to almost perfectly separate brain tissues from a formalin buffered solution. Regional brain volumes are challenging to measure in postmortem scans, but robust estimates sensitive to sex differences and age trends, reflecting clinical diagnosis, neuropathology findings, and the shrinkage induced by tissue fixation can be obtained. We hope that the new processing methods developed in this work, such as the lightweight Deep Networks we used to identify the formalin signal in multimodal MRI scans and the MRI synthesis tools we used to fix our anisotropic resolution brain scans, will inspire other research teams working with postmortem MRI scans.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103752"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463278","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}