Neuroimage-Clinical最新文献

{"title":"Spatial and signal features of white matter integrity and associations with clinical factors: A CARDIA brain MRI study","authors":"Faezeh Vedaei ,&nbsp;Dhivya Srinivasan ,&nbsp;Drew Parker ,&nbsp;Guray Erus ,&nbsp;Sudipto Dolui ,&nbsp;Farzaneh A. Sorond ,&nbsp;David R. Jacobs Jr ,&nbsp;Lenore J. Launer ,&nbsp;Daniel T. Lackland ,&nbsp;Christos Davatzikos ,&nbsp;R.Nick Bryan ,&nbsp;Ilya M. Nasrallah","doi":"10.1016/j.nicl.2025.103768","DOIUrl":"10.1016/j.nicl.2025.103768","url":null,"abstract":"<div><div>White matter hyperintensities (WMH) may be indicative of age-related cerebrovascular diseases and contribute to cognitive and functional decline. Normal appearing WM (NAWM) adjacent to WMH, termed “penumbra,” is known to be vulnerable to future WMH pathology. WM integrity can be evaluated using multiple magnetic resonance imaging (MRI) modalities. We aimed to identify MRI features predictive of WMH growth and to compare the implications of these features based on spatial proximity to existing WMH versus signal features in baseline NAWM. We used baseline and 5-year follow-up MRI scans in 485 middle-aged participants form the Coronary Artery Risk Development in Young Adults (CARDIA). Multimodal MRI at baseline, including fluid attenuated inversion recovery (FLAIR), diffusion tensor imaging (DTI), and cerebral blood flow (CBF), was measured within WM ROIs including baseline WMH and regions that later developed into new WMH, within and external to the baseline penumbra. Overall, we found that 80% of new WMH appeared within the baseline penumbra. We also found lower fractional anisotropy (FA) and CBF and higher FLAIR and median diffusivity (MD) in NAWM at baseline in regions with subsequent WMH growth compared to those without WMH growth. For NAWM regions defined by signal features, subthreshold FA and suprathreshold MD and FLAIR abnormality at baseline were the most robust predictors of WMH growth. Baseline systolic blood pressure had significant associations with baseline abnormalities in NAWM and subsequently with cognitive decline, particularly for FA and MD measures. The findings support the use of DTI as the predictor of WMH growth, which is correlated with subtle, adverse WM alterations and cognitive function years before developing to WMH. The results may contribute to future clinical trials aimed at preserving WM integrity.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"46 ","pages":"Article 103768"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631899","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":"Diagnostic accuracy of neonatal structural MRI scores to predict 6-year motor outcomes of children born very preterm","authors":"Karen H. Mistry ,&nbsp;Samudragupta Bora ,&nbsp;Kerstin Pannek ,&nbsp;Alex M. Pagnozzi ,&nbsp;Simona Fiori ,&nbsp;Andrea Guzzetta ,&nbsp;Robert S. Ware ,&nbsp;Paul B. Colditz ,&nbsp;Roslyn N. Boyd ,&nbsp;Joanne M. George","doi":"10.1016/j.nicl.2024.103725","DOIUrl":"10.1016/j.nicl.2024.103725","url":null,"abstract":"<div><h3>Aims</h3><div>This study aimed to (1) evaluate associations between Early and Term structural MRI (sMRI) brain abnormality scores and adverse motor outcomes at 6-years corrected age (CA), (2) determine their diagnostic accuracy in predicting adverse motor outcomes and cerebral palsy (CP) at 6-years CA.</div></div><div><h3>Methods</h3><div>Infants born &lt; 31-weeks gestational age (GA) returning for 6-year follow-up were included. Early and Term sMRI were scored using a validated method, deriving white matter, cortical grey matter, deep grey matter, cerebellar and global brain abnormality scores (GBAS). At 6-years CA, Movement Assessment Battery for Children-2nd Edition (MABC-2) was administered. Linear regression assessed associations between Early and Term GBAS/subscale scores and 6-year MABC-2 total score. For diagnostic accuracy, sMRI scores were categorised as none/mild vs moderate/severe, MABC-2 cut-off ≤ 5th percentile, and CP as present/absent.</div></div><div><h3>Results</h3><div>Infants had Early MRI (n = 123) at mean PMA 32.5-weeks (median GA 28.4-weeks; mean birthweight 1101 g) and n = 114 had Term MRI (Mean PMA 40.8-weeks). Nine had CP and n = 116 had MABC-2 scores. Early (B: −1.92; p ≤ 0.001) and Term (B: −1.67; p ≤ 0.01) GBAS were negatively associated with MABC-2 scores. Both Early and Term GBAS had high specificity (Sp) and low sensitivity (Se) in predicting MABC-2 ≤ 5th percentile (Early: Se 36 %, Sp 82 %; Term: Se 28 %, Sp 93 %) and predicted CP with high Se and Sp (Early: Se 78 %, Sp 78 %; Term: Se 75 %, Sp 89 %).</div></div><div><h3>Conclusion</h3><div>High Sp of Early and Term MRI predicting an outcome on MABC-2 may help accurately identify infants unlikely to develop motor impairments at 6-years CA.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103725"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721883/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142866318","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":"Reorganization of cortical individualized differential structural covariance network is associated with regional morphometric changes in chronic subcortical stroke","authors":"Hongchuan Zhang ,&nbsp;Jun Guo ,&nbsp;Jingchun Liu ,&nbsp;Caihong Wang ,&nbsp;Hao Ding ,&nbsp;Tong Han ,&nbsp;Jingliang Cheng ,&nbsp;Chunshui Yu ,&nbsp;Wen Qin","doi":"10.1016/j.nicl.2025.103735","DOIUrl":"10.1016/j.nicl.2025.103735","url":null,"abstract":"<div><div>Patients with chronic subcortical stroke undergo regional and network morphometric reorganizations beyond the lesion site, but the interplay between network and regional reorganization remains poorly understood. We aimed to clarify the reorganization patterns of the individualized differential structural covariance networks (IDSCN) in chronic subcortical stroke and investigate their associations with regional gray matter volume (GMV) changes and functional recovery. Structural MRI from four datasets enrolled 112 patients with chronic subcortical stroke (81 male, age: 55.82 ± 7.79) and 122 matched healthy controls (HC) (74 male; age: 55.28 ± 7.54). Network-based statistics were employed to identify aberrant IDSCN, Spearman correlation was conducted to assess the association between IDSCN and regional GMV alterations, and partial correlation was utilized to investigate the association between abnormal IDSCN and functional recovery. We identified 133 connections with balanced increased and decreased IDSCN. Aberrant IDSCN involved more regions than local GMV alterations, local GMV alteration exhibited intricate correlations with IDSCN, which could explain partly IDSCN reorganization (p &lt; 0.05, corrected). Finally, abnormal IDSCN showed a weak association with long-term clinical recovery (p &lt; 0.01). These findings reinforce the theory of adaptive network reorganization post-stroke and suggest that IDSCN may provide further insights into cortical reorganization and functional rehabilitation beyond regional morphometric measures.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103735"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016498","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":"Posterior hippocampal sparing in Lewy body disorders with Alzheimer’s copathology: An in vivo MRI study","authors":"Jesse S. Cohen ,&nbsp;Jeffrey Phillips ,&nbsp;Sandhitsu R. Das ,&nbsp;Christopher A. Olm ,&nbsp;Hamsanandini Radhakrishnan ,&nbsp;Emma Rhodes ,&nbsp;Katheryn A.Q. Cousins ,&nbsp;Sharon X. Xie ,&nbsp;Ilya M. Nasrallah ,&nbsp;Paul A. Yushkevich ,&nbsp;David A. Wolk ,&nbsp;Edward B. Lee ,&nbsp;Daniel Weintraub ,&nbsp;David J. Irwin ,&nbsp;Corey T. McMillan","doi":"10.1016/j.nicl.2024.103714","DOIUrl":"10.1016/j.nicl.2024.103714","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;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.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;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&lt;sub&gt;1-42&lt;/sub&gt; &lt; 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.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;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).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;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":"Corrigendum to “A multimodal neuroimaging-based risk score for mild cognitive impairment” [NeuroImage: Clinical 45 (2025) 103719]","authors":"Elaheh Zendehrouh ,&nbsp;Mohammad S.E. Sendi ,&nbsp;Anees Abrol ,&nbsp;Ishaan Batta ,&nbsp;Reihaneh Hassanzadeh ,&nbsp;Vince D. Calhoun","doi":"10.1016/j.nicl.2024.103728","DOIUrl":"10.1016/j.nicl.2024.103728","url":null,"abstract":"","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"45 ","pages":"Article 103728"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911084","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}