BACKGROUND AND PURPOSE:The cerebellum is increasingly recognized as a key contributor to language and cognitive processing, but its dynamic network alterations in poststroke aphasia remain poorly understood. This study investigated dynamic cerebellar networks in patients with poststroke aphasia using resting-state functional MRI. We examined intracerebellar and cerebellar-cortical dynamic functional connectivity and quantified their temporal properties and graph-theoretical topology. MATERIALS AND METHODS:Seventy-seven right-handed patients with poststroke aphasia and 79 healthy controls underwent 3T resting-state functional MRI. Dynamic cerebellar functional networks were constructed using the Seitzman-27 cerebellar atlas. A sliding window approach (30 TR window, 1 TR step) was applied, followed by K-means clustering to identify distinct connectivity states. Graph-theoretical analyses were performed to quantify state-specific network topology. The variability of dynamic functional connectivity between the cerebellar and cortical regions was calculated. Partial correlation analyses were performed to examine the relationships among dynamic network measures, lesion volume, and language and cognitive function. RESULTS:Two cerebellar dynamic functional connectivity states were identified in poststroke aphasia: a predominant segregated state (78.93%) with widespread reductions in connectivity and decreased clustering coefficient (d = -1.29), characteristic path length (d = -0.62), and local efficiency (d = -1.11) but higher global efficiency (d = 1.06) and a less frequent integrated state (21.07%) with enhanced connectivity and a higher clustering coefficient (d = 0.57) and characteristic path length (d = 0.70) and diminished global efficiency (d = -1.25) and small-worldness (d = -0.92) and small-world index (d = -0.89). Poststroke aphasia showed reduced variability of dynamic functional connectivity between the cerebellar and cortical regions involved in language and cognition (Gaussian random field correction, voxel-level P < .001, cluster-level P < .05). Lesion volume negatively correlated with Aphasia Quotient, repetition, memory, executive function, and attention (P < .005). State-specific network metrics and variability measures were associated with language and cognitive performance independent of lesion volume. CONCLUSIONS:Patients with poststroke aphasia exhibited a segregated cerebellar state with reduced intracerebellar connectivity and efficiency and an integrated state with enhanced connectivity and small-world properties, together with reduced variability in cerebellar-cortical connections to language- and cognition-related regions. These state-specific network alterations were linked to distinct behavioral domains independent of lesion volume, highlighting a dissociation between structural constraints and dynamic, lesion-independent plasticity.

Post-stroke aphasia (PSA) is a prevalent complication of left-hemispheric stroke, yet cerebellar contributions to language and cognition remain insufficiently characterized at the network level. We investigated cerebellar functional network topology in PSA and its associations with language and cognitive performance. Seventy-three right-handed PSA patients and 75 matched healthy controls underwent 3T resting-state functional magnetic resonance imaging (rs-fMRI). The cerebellum was parcellated using the Seitzman-27 atlas, which assigns cerebellar ROIs to canonical large-scale networks, allowing network-specific characterization and interpretable comparisons across functional systems. Global and nodal topological metrics and ROI-to-ROI functional connectivity were quantified, and their relationships with language and non-language cognition were assessed. Small-world organization was preserved in both groups, but PSA patients showed significant reductions in the small-world index, clustering coefficient, and local efficiency, indicating impaired network segregation and local processing. Nodal analysis revealed decreased degree centrality in the frontoparietal network and increased degree centrality in the dorsal somatomotor network. Functional connectivity was reduced within the default mode and frontoparietal networks, while connectivity between frontoparietal and dorsal somatomotor regions increased (FDR-corrected). Lower clustering coefficient and local efficiency were associated with poorer auditory comprehension, memory, and reasoning. Lesion volume was associated with worse language and cognitive outcomes but was not associated with global cerebellar network measures after covariate adjustment. These findings provide novel network-level evidence of altered cerebellar topology in PSA, extending prior cortical-focused models. The results suggest that cerebellar network disruption is associated with language and cognitive deficits and may inform the development of network-based imaging markers and motivate future longitudinal and intervention studies in aphasia.

Previous studies have found that the pathology of post-stroke aphasia might be related to abnormalities in the white matter connectivity. However, it is still unclear about the neural mechanism of white matter impairment in the post-stroke aphasia. The present study attempted to detect the alteration of the brain white matter structural network in the post-stroke aphasia. We recruited 16 PSA patients who suffered from post-stroke aphasia and 14 healthy controls and acquired their diffusion-tensor imaging data. We performed a deterministic white matter fiber tracking to construct white matter structural network and estimated network topological properties by using graph theory. We also assessed the between-group differences in these parameters and estimated the correlations between the abnormal parameters and clinical assessments in the patients. The patients showed higher shortest path length, higher normalized clustering coefficient, and lower global efficiency than the controls. We found abnormal nodal parameters in the frontal, parietal, basal ganglia, and limbic regions in the patient group. From the rich-club analysis, we found that the patient group showed higher rich-club connections and lower feeder connections than the control group, and had a new rich-club region, the right fusiform gyrus. In summary, this study detected the abnormal both nodal and global parameters of the brain white matter structural network in the post-stroke aphasia. These findings may provide insights into understanding the abnormal brain network and impairment of language function in the post-stroke aphasia.

PURPOSE:By integrating visual knowledge into radiomics, we aim to develop an interpretable and robust radiomic model based on Gadolinium-free MRI for preoperative identification of 1p/19q co-deletion in IDH-mutant adult-type diffuse gliomas. MATERIALS AND METHODS:MRI from 215 surgically confirmed IDH-mutant Adult-type Diffuse Glioma patients were collected from two centers and split into training, internal and external validation set. For knowledge-guided radiomics, features driven from T1WI, T2WI, and FLAIR demonstrating high interreader stability were extracted from the training set. Features significantly associated with four visual features (T2-FLAIR mismatch, homogeneity, enhancement, and calcification) were identified, and hierarchical clustering and Max-Relevance and Min-Redundancy were used to eliminate multicollinearity and redundancy. Stability selection using Lasso was performed for robust feature selection. Two classifiers (Support Vector Machines and Extreme Gradient Boosting) were trained with nested cross-validation for 1p/19q co-deletion prediction. For comparison, regular radiomic models without visual guidance were developed to evaluate the superiority of the knowledge-guided radiomics. This retrospective study was approved by the institutional review board of the centers and the requirement for informed consent was waived. RESULTS:The knowledge-guided Support Vector Machines model achieved AUCs of 0.893 (95 %CI: 0.859-0.928) and 0.839 (95 % CI: 0.794-0.885) in the internal and external validation sets. The two regular radiomics models demonstrated various performance degradation, especially in the external set (AUCs: 0.681-0.767). The knowledge-guided radiomics model of either classifier outperformed corresponding regular radiomics across most performance metrics (p < 0.01) in the validation sets. CONCLUSIONS:The knowledge-guided radiomic framework improves preoperative prediction of 1p/19q co-deletion in IDH-mutant adult-type diffuse gliomas, offering enhanced model interpretability and cross-center generalizability.

Purpose Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in detecting malignancies is limited. While Deep learning (DL) models based on magnetic resonance imaging (MRI) are common in medicine, they are less studied for parotid gland tumors. This study used a 2.5D imaging approach (Incorporating Inter-Slice Information) to train a DL model to differentiate between benign and malignant PGTs.Methods This retrospective study included 122 parotid tumor patients, using MRI and clinical features to build predictive models. In the traditional model, univariate analysis identified statistically significant features, which were then used in multivariate logistic regression to determine independent predictors. The model was built using four-fold cross-validation. The deep learning model was trained using 2D and 2.5D imaging approaches, with a transformer-based architecture employed for transfer learning. The model’s performance was evaluated using the area under the receiver operating characteristic curve (AUC) and confusion matrix metrics.Results In the traditional model, boundary and peritumoral invasion were identified as independent predictors for PGTs, and the model was constructed based on these features. The model achieved an AUC of 0.79 but demonstrated low sensitivity (0.54). In contrast, the DL model based on 2.5D T2 fat-suppressed images showed superior performance, with an AUC of 0.86 and a sensitivity of 0.78.Conclusion The 2.5D imaging technique, when integrated with a transformer-based transfer learning model, demonstrates significant efficacy in differentiating between PGTs.

Non-invasive brain stimulation (NIBS) modalities—including transcranial magnetic stimulation (TMS), theta-burst stimulation (TBS), and transcranial direct current stimulation (tDCS)—have emerged as promising approaches to promote language recovery in post-stroke aphasia by engaging both functional and structural neuroplasticity. This structured narrative review integrates recent multimodal evidence from functional magnetic resonance imaging (fMRI), DTI, and connectome analyses to delineate the stage-dependent mechanisms underlying NIBS-induced modulation of language networks. Findings across studies suggest a dynamic pattern of reorganization: acute-phase hypoactivation of left-hemisphere language areas and diffuse right-hemisphere disinhibition give way to bilateral upregulation in the subacute phase, followed by gradual restoration of left-dominant connectivity during the chronic stage, which may be limited by persistent contralesional hyperactivity. Low-frequency TMS or continuous TBS targeting right-hemisphere homologues can suppress maladaptive overcompensation, whereas high-frequency TMS or intermittent TBS applied to residual left-hemisphere sites enhances excitability and network centrality. Bilateral or neuronavigation-guided tDCS, particularly when combined with language training, rebalances interhemispheric excitability and supports sustained gains in naming and fluency. DTI-derived increases in arcuate and uncinate fasciculi integrity correlate with clinical improvement, while contralesional temporoparietal cortical thickening reflects concurrent structural remodeling.

Objective The present study aimed to investigate the functional connectivity (FC) of the anterior and posterior hypothalamus with the whole brain in insomnia disorder (ID) patients. Additionally, we explored the relationship between FC values and serum levels of arousal-promoting neurotransmitters (orexin-A and histamine) in ID patients. Methods This study enrolled 30 ID patients and 30 age- and gender-matched healthy controls. Resting-state functional magnetic resonance imaging (RS-fMRI) was employed to assess the FC of the anterior and posterior hypothalamus with the whole brain. Serum concentrations of orexin-A and histamine were measured using enzyme-linked immunosorbent assay (ELISA). Moreover, Spearman correlation analysis was conducted to investigate the relationship between FC values and serum levels of arousal-promoting neurotransmitters in ID patients. Results Our findings showed decreased FC between the posterior hypothalamus and several brain regions including the bilateral orbital superior frontal gyrus, the bilateral angular gyrus, the right anterior cingulate cortex, the left precuneus, and the right medial superior frontal gyrus in ID patients. Additionally, decreased FC was observed between the anterior hypothalamus and the right anterior cingulate cortex among ID patients. Compared to the healthy controls, ID patients showed significantly elevated serum concentrations of orexin-A and histamine. Furthermore, we identified a positive correlation between the FC of the right medial superior frontal gyrus with posterior hypothalamus and histamine levels in ID patients. Conclusion ID patients exhibited aberrant FC in brain regions related to sleep-wake regulation, particularly involving the default mode network and anterior cingulate cortex, which may correlate with the peripheral levels of histamine. These findings contribute to our understanding of the potential neuroimaging and neurohumoral mechanism underlying ID patients.

BACKGROUND:The best treatment option for patients with resectable gastric cancer is radical gastric cancer surgery. However, the postoperative overall survival rate is low. Lymphovascular invasion (LVI) is a risk factor for cancer recurrence and a stand-alone predictor of a poor post-operative prognosis for gastric cancer (GC) patients. Current evaluation of tumor LVI performed on histological specimens, which can only be assessed after surgery, is also limited by intra-tumoural heterogeneity via biopsy. This study explored the value of CT volume perfusion in assessing tumors' lymphovascular invasion of gastric cancer. METHODS:59 gastric cancer patients confirmed by pathology who underwent both computed tomography (CT) volume perfusion examinations and gastrectomy surgery were prospectively included. Tumour lymphovascular invasion (LVI, positive or negative) was evaluated. The relationship between clinicopathological variables associated with LVI and CT perfusion parameters was analyzed by univariate analysis, followed by multivariate logistic regression analysis and receiver operating characteristic (ROC) analysis. RESULTS:The LVI-positive and LVI-negative groups differed significantly in terms of time to start (TTS), mean transit time (MTT), Tmax, and flow extraction product (FEP). Both FEP (odds ratio (OR), 1.048; 95% confidence interval (CI): 1.005-1.092) and MTT (OR, 0.549; 95% CI: 0.351-0.858) have the potential to be employed as independent predictors of LVI (both p < 0.05). There were different correlations between LVI, lower MTT and greater FEP. The specificity of MTT (87.88%) was higher than that of FEP (72.73%), while the sensitivity of MTT (53.85%) was lower than that of FEP (57.69%). Compared to MTT and FEP alone, the combination demonstrated a comparatively higher area under the curve (AUC) (0.797) and sensitivity (84.62%). CONCLUSIONS:CT volume perfusion helps evaluate LVI in gastric cancer before surgery. MTT and FEP are independent predictors for LVI, and the combination variation has better diagnostic performance. Clinical Trial Register: Jiangmen Central Hospital, https://www.chictr.org.cn/showproj.html?proj=24375, ChiCTR1800014455.

Traumatic axonal injury (TAI) may result in the disruption of brain functional networks and is strongly associated with cognitive impairment. However, the neural mechanisms affecting the neurocognitive function after TAI remain to be elucidated. We collected the resting-state functional magnetic resonance imaging data from 28 patients with TAI and 28 matched healthy controls. An automated anatomical labeling atlas was used to construct a functional brain connectome. We utilized a graph theoretical approach to investigate the alterations in global and regional network topologies, and network-based statistics analysis was utilized to localize the connected networks more precisely. The current study revealed that patients with TAI and healthy controls both showed a typical small-world topology of the functional brain networks. However, patients with TAI exhibited a significantly lower local efficiency compared to healthy controls, whereas no significant difference emerged in other small-world properties (Cp, Lp, γ, λ, and σ) and global efficiency. Moreover, patients with TAI exhibited aberrant nodal centralities in some regions, including the frontal lobes, parietal lobes, caudate nucleus, and cerebellum bilaterally, and right olfactory cortex. The network-based statistics results showed alterations in the long-distance functional connections in the subnetwork in patients with TAI, involving these brain regions with significantly altered nodal centralities. These alterations suggest that brain networks of individuals with TAI present aberrant topological attributes that are associated with cognitive impairment, which could be potential biomarkers for predicting cognitive dysfunction and help understanding the neuropathological mechanisms in patients with TAI.

Background Previous studies on primary angle-closure glaucoma (PACG) primarily focused on local brain regions or global abnormal brain activity; however, the alteration of interhemispheric functional homotopy and its possible cause of brain-wide functional connectivity abnormalities have not been well-studied. Little is known about whether brain functional alteration could be used to differentiate from healthy controls (HCs) and its correlation with neurocognitive impairment. Methods Forty patients with PACG and 40 age- and sex-matched healthy controls were recruited for this study; resting-state functional magnetic resonance imaging (rs-fMRI), and clinical data were collected. We used the voxel-mirrored homotopic connectivity (VMHC) method to explore between-group differences and selected brain regions with statistically significant differences as regions of interest for whole-brain functional connectivity analysis. Partial correlation was used to evaluate the association between abnormal VMHC values in significantly different regions and clinical parameters, with with age and sex as covariates. Finally, the support vector machine (SVM) model was performed in classification prediction of PACG. Results Compared with healthy controls, patients with PACG exhibited significantly decreased VMHC values in the lingual gyrus, insula, cuneus, and pre- and post-central gyri; no regions exhibited increased VMHC values. Subsequent functional connectivity analysis revealed extensive functional changes in functional networks, particularly the default mode, salience, visual, and sensorimotor networks. The SVM model showed good performance in classification prediction of PACG, with an area under curve (AUC) of 0.85. Conclusion Altered functional homotopy of the visual cortex, sensorimotor network, and insula may lead to impairment of visual function in PACG, suggesting that patients with PACG may have visual information interaction and integration dysfunction.

White matter (WM) fiber alterations in patients with obstructive sleep apnea (OSA) is associated with cognitive impairment, which can be alleviated by continuous positive airway pressure (CPAP). In this study, we aimed to investigate the changes in WM in patients with OSA at baseline (pre-CPAP) and 3 months after CPAP adherence treatment (post-CPAP), and to provide a basis for understanding the reversible changes after WM alteration in this disease. Magnetic resonance imaging (MRI) was performed on 20 severely untreated patients with OSA and 20 good sleepers. Tract-based spatial statistics was used to evaluate the fractional anisotropy (FA), mean diffusion coefficient, axial diffusion coefficient, and radial diffusion coefficient (RD) of WM. To assess the efficacy of treatment, 20 patients with pre-CPAP OSA underwent MRI again 3 months later. A correlation analysis was conducted to evaluate the relationship between WM injury and clinical evaluation. Compared with good sleepers, patients with OSA had decreased FA and increased RD in the anterior thalamic radiation, forceps major, inferior fronto-occipital tract, inferior longitudinal tract, and superior longitudinal tract, and decreased FA in the uncinate fasciculus, corticospinal tract, and cingulate gyrus (P < 0.05). No significant change in WM in patients with post-CPAP OSA compared with those with pre-CPAP OSA. Abnormal changes in WM in untreated patients with OSA were associated with oxygen saturation, Montreal cognitive score, and the apnea hypoventilation index. WM fiber was extensively alteration in patients with severe OSA, which is associated with cognitive impairment. Meanwhile, cognitive recovery was not accompanied by reversible changes in WM microstructure after short-term CPAP therapy.

鼻咽解剖位置深在，病变种类繁多，CT及MRI是鼻咽病变治疗前主要评估手段。不同鼻咽病变影像表现不同，但也存在较多重叠，临床工作中需从病变位置、形态、边界、信号及密度特征、强化方式、与邻近组织结构关系、有无骨质破坏或淋巴结转移等方面进行综合分析，并结合临床鼻咽镜及实验室检查进一步明确诊断，从而提升诊断准确性。笔者系统总结鼻咽病变影像诊断思路，并归纳分析鼻咽病变的影像诊断要点，在治疗前明确诊断及病变范围，从而为临床治疗决策提供重要支持证据。

The hippocampus is involved in various cognitive function, including memory. Hippocampal structural and functional abnormalities have been observed in patients with obstructive sleep apnoea (OSA), but the functional connectivity (FC) patterns among hippocampal subdivisions in OSA patients remain unclear. The purpose of this study was to investigate the changes in FC between hippocampal subdivisions and their relationship with neurocognitive function in male patients with OSA. Resting-state fMRI were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers. The hippocampus was divided into anterior, middle, and posterior parts, and the differences in FC between hippocampal subdivisions and other brain regions were determined. Correlation analysis was used to explore the relationships between abnormal FC of hippocampal subdivisions and clinical characteristics in patients with OSA. Our results revealed increased FC in the OSA group between the left anterior hippocampus and left middle temporal gyrus; between the left middle hippocampus and the left inferior frontal gyrus, right anterior central gyrus, and left anterior central gyrus; between the left posterior hippocampus and right middle frontal gyrus; between the right middle hippocampus and left inferior frontal gyrus; and between the right posterior hippocampus and left middle frontal gyrus. These FC abnormalities predominantly manifested in the sensorimotor network, fronto-parietal network, and semantic/default mode network, which are closely related to the neurocognitive impairment observed in OSA patients. This study advances our understanding of the potential pathophysiological mechanism of neurocognitive dysfunction in OSA.

Obstructive sleep apnea (OSA), a common respiratory sleep disorder, is often associated with mild cognitive impairment (MCI), which is a precursor stage to Alzheimer’s disease (AD). However, the neuroimaging changes in patients with OSA with/without MCI are still under discussion. This study aimed to investigate the temporal variability of spontaneous brain activity in OSA. Fifty-two OSA patients (26 with OSA with MCI (OSA-MCI), 26 OSA without MCI (OSA-nMCI), and 26 healthy controls (HCs) underwent MRI scans and scale questionnaires. A dynamic amplitude of low-frequency fluctuation (dALFF) evaluation was performed to examine the time-varying nature of OSA-MCI and OSA-nMCI. Compared with OSA-MCI, OSA-nMCI had increased dALFF in the posterior cerebellar and right superior frontal gyrus; compared with HCs, OSA-nMCI patients showed increased dALFF in the right posterior cerebellum. A positive correlation between the bilateral posterior cerebellar lobes and right superior frontal gyrus was observed in OSA-MCI patients; however, in OSA-nMCI patients, a positive correlation was observed only between the bilateral posterior cerebellar lobes. The dALFF value of the left posterior cerebellar lobe was positively correlated with the apnea-hypopnea index (AHI), epworth sleepiness scale (ESS) score, and arousal index in OSA-nMCIs, while the dALFF value of the right posterior cerebellum was positively correlated with the AHI and negatively correlated with the lowest oxygen saturation (SaO2). This study argues that OSA-nMCIs and OSA-MCIs exhibit different temporal variabilities in dynamic brain functions, OSA-nMCIs may have variable intermediate states. We concluded that the functional abnormalities of the cerebellar-prefrontal cortex pathway in OSA-MCIs may cause cognitive impairment with OSA.

Aphasia is characterized by the disability of spontaneous conversation, listening, understanding, retelling, naming, reading, or writing. However, the neural mechanisms of language damage after stroke are still under discussion. This study aimed to investigate the global and nodal characterization of the functional networks in patients with aphasic stroke based on resting-state functional MRI (fMRI). Twenty-four right-handed patients with aphasia after stroke and 19 healthy controls (HC) underwent a 3-TfMRI scan. A whole-brain large-scale functional connectivity network was then constructed based on Power's atlas of 264 functional regions of interest, and the global and nodal topological properties of these networks were analyzed using graph theory approaches. The results showed that patients with aphasia had decreased in small-worldness (sigma), normalized clustering coefficient (gamma), and local efficiency (E-loc) values. Furthermore, E-loc was positively correlated with language ability, retelling, naming, and listening comprehension in patients with aphasia. Patients with aphasia also had decreased nodal degree and decreased nodal efficiency in the left postcentral gyrus, central opercular cortex, and insular cortex. Our results suggest that the global and local topology attributes were altered by injury in patients with aphasic stroke. We argue that the local efficiency of brain networks might be used as a potential indicator of basic speech function in patients with aphasia.

目的 分析肺隐球菌病(PC)的CT表现,提高对PC的CT诊断水平.方法 回顾性分析2 9 例经病理或病原学检测证实为PC患者的临床及CT资料.结果 2 9 例中 1 0 例有基础疾病,1 8 例有咳嗽、咳痰,1 6 例胸痛或胸闷,7 例体检或其他原因发现.CT分型:①孤立结节、肿块型 6 例;②多发结节、肿块型 5 例;③单发或多发实变型 9 例;④实变与结节、肿块混合型 8 例;⑤弥漫混合型 1 例.2 3 例分布于肺外周带,6 例随机分布;8 例见"晕征",9 例见空洞,1 7 例见"充气支气管征".2 6 例增强扫描均表现为延迟性强化,2 3 例均匀强化,3 例不均匀强化;其中 1 9 例CT平扫+增强扫描,4 例轻度强化,1 0 例中度强化,5 例明显强化;1 9 例动脉期见"CT血管造影征".结论 CT出现"充气支气管征"、"血管造影征"、"晕征"对诊断 PC有一定价值;增强扫描多表现中度均匀延迟性强化.

Neuroimaging studies have demonstrated that autism spectrum disorder (ASD) is accompanied by abnormal functional and structural features in specific brain regions of the default mode network (DMN). However, little is known about the alterations of the topological organization and the functional connectivity (FC) of the DMN in ASD patients. Thirty-seven ASD patients and 38 healthy control (HC) participants underwent a resting-state functional magnetic resonance imaging scan. Twenty DMN subregions were specifically selected to construct the DMN architecture. We applied graph theory approaches to the topological configuration and compare the FC patterns of the DMN. We then examined the relationships between the neuroimaging measures of the DMN and clinical characteristics in patients with ASD. The current study revealed that both the ASD and HC participants showed a small-world regimen in the DMN; however there were no significant differences in global network measures. Compared with the HC group, the ASD group exhibited significantly decreased nodal centralities in the bilateral anterior medial prefrontal cortex and increased nodal centralities in the right lateral temporal cortex and the right retrosplenial cortex. Patients with ASD displayed significantly reduced and increased FC within the DMN. Our findings demonstrated that ASD patients showed a pattern of disrupted FC metrics and nodal network metrics in the DMN, which could be a potential biomarker for objective ASD diagnoses and for the level of autism spectrum traits.

Pre-treatment survival prediction plays a key role in many diseases. We aimed to determine the prognostic value of pre-treatment Magnetic Resonance Imaging (MRI) based radiomic score for disease-free survival (DFS) in patients with early-stage (IB-IIA) cervical cancer. Methods: A total of 248 patients with early-stage cervical cancer underwent radical hysterectomy were included from two institutions between January 1, 2011 and December 31, 2017, whose MR imaging data, clinicopathological data and DFS data were collected. Patients data were randomly divided into the training cohort (n = 166) and the validation cohort (n=82). Radiomic features were extracted from the pre-treatment T2-weighted (T2w) and contrast-enhanced T1-weighted (CET1w) MR imagings for each patient. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazard model were applied to construct radiomic score (Rad-score). According to the cutoff of Rad-score, patients were divided into low- and high- risk groups. Pearson's correlation and Kaplan-Meier analysis were used to evaluate the association of Rad-score with DFS. A combined model incorporating Rad-score, lymph node metastasis (LNM) and lymphovascular space invasion (LVI) by multivariate Cox proportional hazard model was constructed to estimate DFS individually. Results: Higher Rad-scores were significantly associated with worse DFS in the training and validation cohorts (P<0.001 and P=0.011, respectively). The Rad-score demonstrated better prognostic performance in estimating DFS (C-index, 0.753; 95% CI: 0.696-0.805) than the clinicopathological features (C-index, 0.632; 95% CI: 0.567-0.700). However, the combined model showed no significant improvement (C-index, 0.714; 95%CI: 0.642-0.784). Conclusion: The results demonstrated that MRI-derived Rad-score can be used as a prognostic biomarker for patients with early-stage (IB-IIA) cervical cancer, which can facilitate clinical decision-making.

目的 研究阻塞性睡眠呼吸暂停(OSA)患者前、后默认网络功能连接情况,探讨OSA患者认知功能损害的潜在神经生理机制.方法 采集43例OSA患者(OSA组)及43名健康男性(HC组)的静息态磁共振脑功能成像(rs-fMRI)和临床量表评估数据.选用基于种子点的功能连接方法,分别以内侧前额叶(mPFC)和后扣带回(PCC)为种子点计算其与全脑的功能连接值,组间的功能连接差异比较采用双样本t检验.结果 与HC组相比,OSA组mPFC与左侧小脑后叶功能连接减低,而与左侧顶下小叶、双侧额中回、左侧额下回功能连接增高;OSA组PCC与双侧中央后回、右侧中央前回功能连接减低,而与右侧小脑后叶功能连接增高.结论 OSA患者前、后默认网络功能连接存在显著差异,这可能为进一步理解OSA认知功能的损害提供了新的视角.

目的 基于静息态功能磁共振(rs-fMRI)技术采用图论分析方法研究阻塞性睡眠呼吸暂停(OSA)患者功能脑网络的拓扑属性改变.方法 搜集未经治疗的男性重度OSA患者及正常睡眠组(GS组)各45例并采集被试的多导睡眠监测、临床量表评分及rs-fMRI数据.采用AAL模板构建功能脑网络,通过图论方法比较功能脑网络的整体和局部网络拓扑属性,并分析拓扑属性与临床变量之间的关系.结果 OSA及GS组均存在高效的“小世界”网络属性.然而OSA患者小世界指数(σ),标准化聚类系数(γ),整体效率(Eglob)值显著减低,最短路径长度(Lp),标准化最短路径长度(λ)值显著增高,且部分默认网络(DMN)、突显网络(SN)和中央执行网络(CEN)脑区节点中心性受损.OSA患者整体网络属性与爱泼沃斯嗜睡量表(ESS)评分、蒙特利尔认知量表(MoCA)评分和血氧饱和度显著相关.结论 虽然OSA患者功能脑网络具有“小世界”属性,但其功能整合和功能分离受损,且部分DMN、SN和CEN脑区的节点中心性存在异常破坏.OSA患者功能脑网络的拓扑属性异常可能是认知功能障碍的潜在生物学标志.