Quantitative parameter analysis of pretreatment dual-energy computed tomography in nasopharyngeal carcinoma cervical lymph node characteristics and prediction of radiotherapy sensitivity.

BACKGROUND: Treatment efficacy may differ among patients with nasopharyngeal carcinoma (NPC) at similar tumor-node-metastasis stages. Moreover, end-of-treatment tumor regression is a reliable indicator of treatment sensitivity. This study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters could predict sensitivity to neck-lymph node radiotherapy in patients with NPC. METHODS: Overall, 388 lymph nodes were collected from 98 patients with NPC who underwent pretreatment DECT. The patients were divided into complete response (CR) and partial response (PR) groups. Clinical characteristics and quantitative DECT parameters were compared between the groups, and the optimal predictive ability of each parameter was determined using receiver operating characteristic (ROC) analysis. A nomogram prediction model was constructed and validated using univariate and binary logistic regression. RESULTS: DECT parameters were higher in the CR group than in the PR group. The iodine concentration (IC), normalized IC, Mix-0.6, spectral Hounsfield unit curve slope, effective atomic number, and virtual monoenergetic images were significantly different between the groups. The area under the ROC curve of the DECT parameters was 0.73-0.77. Based on the binary logistic regression, a column chart was constructed using 10 predictive factors, including age, sex, N stage, maximum lymph node diameter, arterial phase NIC, venous phase NIC, λHU and spectral Hounsfield units at 70 keV. The area under the ROC curve value of the constructed model was 0.813, with a sensitivity and specificity of 85.6% and 81.3%, respectively. CONCLUSION: Quantitative DECT parameters could effectively predict the sensitivity of NPC to radiotherapy. Therefore, DECT parameters and NPC clinical features can be combined to construct a nomogram with high predictive power and used as a clinical analytical tool.

Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation.

Background: Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI. Methods: Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling. Results: The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model. Conclusions: The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.

Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.

Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major adverse cardiac events (MACE) in patients with coronary artery disease (CAD). We conducted a retrospective cohort study involving patients diagnosed with CAD who underwent coronary computed tomography angiography (CCTA). Participants were classified into MACE and non-MACE groups based on their clinical outcomes. Clinical characteristics and AI-assisted measurements of CCTA parameters, including CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI), were collected. Both univariate and multivariable logistic regression analyses were performed to identify independent predictors of MACE, which were used to build predictive models. Statistical analyses revealed three independent predictors of MACE: severe stenosis, CT-FFR ≤ 0.8, and mean FAI (P < 0.05). Seven predictive models incorporating various combinations of these predictors were developed. The model combining all three predictors demonstrated superior performance, as evidenced by the receiver operating characteristic (ROC) curve, with an area under the curve (AUC) of 0.811 (95% CI 0.774 - 0.847), a sensitivity of 0.776, and a specificity of 0.726. Our findings suggest that AI-assisted CCTA analysis, particularly using FFR and FAI, could significantly improve the prediction of MACE in CAD patients, thereby potentially aiding clinical decision-making.

Nomogram incorporating preoperative MRI-VASARI features for differentiating intracranial extraventricular ependymoma from glioblastoma.

Background: Intracranial extraventricular ependymoma (IEE) and glioblastoma (GBM) may have similar imaging findings but different prognosis. This study aimed to develop and validate a nomogram based on magnetic resonance imaging (MRI) Visually AcceSAble Rembrandt Images (VASARI) features for preoperatively differentiating IEE from GBM. Methods: The clinical data and the MRI-VASARI features of patients with confirmed IEE (n=114) and confirmed GBM (n=258) in a multicenter cohort were retrospectively analyzed. Predictive models for differentiating IEE from GBM were built using a multivariate logistic regression method. A nomogram was generated and the performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Results: The predictors identified in this study consisted of six VASARI features and four clinical features. Compared with the individual models, the combined model incorporating clinical and VASARI features had the highest area under the curve (AUC) value [training set: 0.99, 95% confidence interval (CI): 0.98-1.00; validation set: 0.97, 95% CI: 0.94-1.00] in comparison to the clinical model. The nomogram was well calibrated with significant clinical benefit according to the calibration curve and decision curve analyses. Conclusions: The nomogram combining clinical and MRI-VASARI characteristics was robust for differentiating IEE from GBM preoperatively and may potentially assist in diagnosis and treatment of brain tumors.

Neuroimaging features of primary central nervous system post-transplantation lymphoproliferative disorder following hematopoietic stem cell transplant in patients with ß-thalassemia: a case series and review of literature.

PURPOSE: Primary central nervous system post-transplantation lymphoproliferative disorder (PCNS-PTLD) is a rare but serious complication of hematopoietic stem cell transplantation (HSCT) in patients with severe ß-thalassemia. This study aimed to assess the clinical presentation, pathological characteristics, neuroimaging findings, and treatment strategies in patients with ß-thalassemia who developed PCNS-PTLD and to compare a case series from our transplant center to reported cases from literature. METHODS: We retrospectively reviewed our hospital database and identified four cases of pathologically confirmed PCNS-PTLD without a history of systemic PTLD in patients with severe ß-thalassemia after HSCT. We also performed a relevant literature review on PCNS-PTLD. RESULTS: The median time from transplantation to diagnosis of PCNS-PTLD was 5.5 months. Intracerebral lesions were usually multiple involving both supratentorial and infratentorial regions with homogeneous or rim enhancement. All patients had pathologically confirmed PCNS-PTLD with three patients having diffuse large B-cell lymphoma and the fourth patient having plasmacytic hyperplasia. There was low response to treatment with a median survival of 83 days. CONCLUSION: PCNS-PTLD should be considered in the differential diagnosis of patients with ß-thalassemia who had an intracranial lesion on neuroimaging after HSCT. CRITICAL RELEVANCE STATEMENT: This case series with a comprehensive review of neuroimaging and clinical characteristics of children with primary central nervous system post-transplantation lymphoproliferative disorder should advance our understanding and improve management of this rare yet severe complication following transplant for ß-thalassemia. KEY POINTS: • We assessed clinical presentation, treatment strategies, and neuroimaging characteristics of PCNS-PTLD in patients with ß-thalassemia after transplantation. • Patients with ß-thalassemia may have post-transplantation lymphoproliferative disorder presenting as brain lesions on neuroimaging. • Neuroimaging findings of the brain lesions are helpful for prompt diagnosis and proper management.

Spatiotemporal dedifferentiation of the global brain signal topography along the adult lifespan.

Age-related variations in many regions and/or networks of the human brain have been uncovered using resting-state functional magnetic resonance imaging. However, these findings did not account for the dynamical effect the brain's global activity (global signal [GS]) causes on local characteristics, which is measured by GS topography. To address this gap, we tested GS topography including its correlation with age using a large-scale cross-sectional adult lifespan dataset (n = 492). Both GS topography and its variation with age showed frequency-specific patterns, reflecting the spatiotemporal characteristics of the dynamic change of GS topography with age. A general trend toward dedifferentiation of GS topography with age was observed in both spatial (i.e., less differences of GS between different regions) and temporal (i.e., less differences of GS between different frequencies) dimensions. Further, methodological control analyses suggested that although most age-related dedifferentiation effects remained across different preprocessing strategies, some were triggered by neuro-vascular coupling and physiological noises. Together, these results provide the first evidence for age-related effects on global brain activity and its topographic-dynamic representation in terms of spatiotemporal dedifferentiation.

Magnetic resonance imaging findings of intracranial extraventricular ependymoma: A retrospective multi-center cohort study of 114 cases.

BACKGROUND: Intracranial extraventricular ependymoma (IEE) is an ependymoma located in the brain parenchyma outside the ventricles. IEE has overlapping clinical and imaging characteristics with glioblastoma multiforme (GBM) but different treatment strategy and prognosis. Therefore, an accurate preoperative diagnosis is necessary for optimizing therapy for IEE. METHODS: A retrospective multicenter cohort of IEE and GBM was identified. MR imaging characteristics assessed with the Visually Accessible Rembrandt Images (VASARI) feature set and clinicopathological findings were recorded. Independent predictors for IEE were identified using multivariate logistic regression, which was used to construct a diagnostic score for differentiating IEE from GBM. RESULTS: Compared to GBM, IEE tended to occur in younger patients. Multivariate logistic regression analysis identified seven independent predictors for IEE. Among them, 3 predictors including tumor necrosis rate (F7), age, and tumor-enhancing margin thickness (F11), demonstrated higher diagnostic performance with an Area Under Curve (AUC) of more than 70% in distinguishing IEE from GBM. The AUC was 0.85, 0.78, and 0.70, with sensitivity of 92.98%, 72.81%, and 96.49%, and specificity of 65.50%, 73.64%, and 43.41%, for F7, age, and F11, respectively. CONCLUSION: We identified specific MR imaging features such as tumor necrosis and thickness of enhancing tumor margins that could help to differentiate IEE from GBM. Our study results should be helpful to assist in diagnosis and clinical management of this rare brain tumor.

Brain iron content and cognitive function in patients with ß-thalassemia.

Patients with ß-thalassemia (ß-TM) may have brain iron overload from long-term blood transfusions, ineffective erythropoiesis, and increased intestinal iron absorption, leading to cognitive impairment. Brain magnetic resonance imaging (MRI) methods such as the transverse relaxation rate, susceptibility-weighted imaging, and quantitative susceptibility mapping can provide quantitative, in vivo measurements of brain iron. This review assessed these MRI methods for brain iron quantification and the measurements for cognitive function in patients with ß-TM. We aimed to identify the neural correlates of cognitive impairment, which should help to evaluate therapies for improving cognition and quality of life in patients with ß-TM.

MRI-based radiomics models for the early prediction of radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

Objective: This study was conducted to develop and validate a radiomics-clinics combined model-based magnetic resonance imaging (MRI) radiomics and clinical features for the early prediction of radiation-induced temporal lobe injury (RTLI) in patients with nasopharyngeal carcinoma (NPC). Methods: This retrospective study was conducted using data from 130 patients with NPC (80 patients with and 50 patients without RTLI) who received radiotherapy. Cases were assigned randomly to training (n = 91) and testing (n = 39) datasets. Data on 168 medial temporal lobe texture features were extracted from T1WI, T2WI, and T1WI-CE MRI sequences obtained at the end of radiotherapy courses. Clinics, radiomics, and radiomics-clinics combined models (based on selected radiomics signatures and clinical factors) were constructed using machine learning software. Univariate logistic regression analysis was performed to identify independent clinical factors. The area under the ROC curve (AUC) was performed to evaluate the performance of three models. A nomogram, decision curves, and calibration curves were used to assess the performance of the combined model. Results: Six texture features and three independent clinical factors associated significantly with RTLI were used to build the combined model. The AUCs for the combined and radiomics models were 0.962 [95% confidence interval (CI), 0.9306-0.9939] and 0.904 (95% CI, 0.8431-0.9651), respectively, for the training cohort and 0.947 (95% CI, 0.8841-1.0000) and 0.891 (95% CI, 0.7903-0.9930), respectively, for the testing cohort. All of these values exceeded those for the clinics model (AUC = 0.809 and 0.713 for the training and testing cohorts, respectively). Decision curve analysis showed that the combined model had a good corrective effect. Conclusion: The radiomics-clinics combined model developed in this study showed good performance for predicting RTLI in patients with NPC.

Performance of Pretreatment MRI-Based Radiomics in Recombinant Human Endostatin Plus Concurrent Chemoradiotherapy Response Prediction in Nasopharyngeal Carcinoma: A Retrospective Study.

PURPOSE: To investigate the capability of an Magnetic resonance imaging (MRI) radiomics model based on pretreatment texture features in predicting the short-term efficacy of recombinant human endostatin (RHES) plus concurrent chemoradiotherapy (CCRT) for nasopharyngeal carcinoma (NPC). METHODS: We retrospectively enrolled 65 patients newly diagnosed as having NPC and treated with RHES + CCRT. A total of 144 texture features were extracted from the MRI before RHES + CCRT treatment of all the NPC patients. The maximum relevance minimum redundancy (mRMR) method was used to remove redundant, irrelevant texture features, and calculate the Rad score of the primary tumor. Multivariable logistic regression was used to select the most predictive features subset, and prediction models were constructed. The performance of the 3 models in predicting the early response of RHES + CCRT for NPC was explored. RESULTS: The diagnostic efficiency of combined model and radiomics model in distinguishing between the effective and the ineffective groups of patients was found to be moderate. The area under the ROC curve (AUC) of the combined model and radiomics model was 0.74 (95% confidence interval [CI]: 0.62-0.86) and 0.71 (95% CI: 0.58-0.84), respectively, with both being higher than the AUC of the clinics model (0.63, 95% CI: 0.49-0.78). Compared with the radiomics model, the combined model showed marginally improved diagnostic performance in predicting RHES + CCRT treatment response. The accuracy of combined model and radiomics model for RHES + CCRT response assessment in NPC were higher than those of the clinics model (0.723, 0.723 vs 0.677). CONCLUSION: The pretreatment MRI-based radiomics may be a noninvasive and effective method for the prediction of RHES + CCRT early response in patients with NPC.

Frequency-dependent effective connections between local signals and the global brain signal during resting-state.

The psychological and physiological meanings of resting-state global brain signal (GS) and GS topography have been well confirmed. However, the causal relationship between GS and local signals was largely unknown. Based on the Human Connectome Project dataset, we investigated the effective GS topography using the Granger causality (GC) method. In consistent with GS topography, both effective GS topographies from GS to local signals and from local signals to GS showed greater GC values in sensory and motor regions in most frequency bands, suggesting that the unimodal superiority is an intrinsic architecture of GS topography. However, the significant frequency effect for GC values from GS to local signals was primarily located in unimodal regions and dominated at slow 4 frequency band whereas that from local signals to GS was mainly located in transmodal regions and dominated at slow 6 frequency band, consisting with the opinion that the more integrated the function, the lower the frequency. These findings provided valuable insight for the frequency-dependent effective GS topography, improving the understanding of the underlying mechanism of GS topography. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09831-0.

Spirometra mansoni sparganosis identified by metagenomic next-generation sequencing: a case report.

A 30-year-old male patient had a cyst on the left hip and progressive enlargement for more than 2 months. Combined blood tests, magnetic resonance imaging, and pathology findings, cysticercosis infection was suspected. However, the treatment for cysticercosis was ineffective. We conducted a metagenomic next-generation sequencing (mNGS) analysis on the formalin-fixed, paraffin-embedded specimen of the patient's surgically excised tissue, and the results suggested Spirometra mansoni, mNGS was further confirmed by polymerase chain reaction and phylogenetic analysis of cytochrome c oxidase subunit 1 (cox1) gene. Based on these results, we found that mNGS provided a better method of diagnosing parasitic infections.

Auditory brainstem response after electrolytic lesions in the unilateral medial geniculate body of tree shrews.

OBJECTIVES: This study aimed to assess the processing of clicks and tone pips in the auditory brainstem of tree shrews and analyze the long-term evolution of postlesion plasticity in the auditory system and its ability to self-repair. METHODS: The auditory brainstem response (ABR) was measured in the normal control group (n=10) and the electrolytic damage group (n=10) before and 0 h, 24 h, 48 h, 72 h, and 25 d after electrolytic damage. Recordings were performed under closed-field conditions using clicks and tone pips, followed by statistical analysis of the ABR threshold, amplitude and latency. RESULTS: The results were as follows: (1) After electrolytic damage to the tree shrew medial geniculate body (MGB), the latency and amplitude of ABR waveforms from the left ear changed from 0 h to 25 d. All parameters were lower at 25 d than they were preoperatively. The amplitude of ABR wave VI (using click sound stimulation) decreased or disappeared in both ears. (2) The ABR threshold was significantly different in both ears at 72 h postoperatively compared with preoperatively (0 h) (P < 0.05) but recovered by 25 d. CONCLUSION: Based on these results, we conclude the following: (1) The origin of wave VI in tree shrews may be associated with the MGB. After electrolytic damage to the MGB, the changes in the ABR waveforms at different frequencies indicated that the MGB nucleus had a certain characteristic frequency. (2) Unilateral injury to the MGB can lead to similar levels of hearing impairment in both ears.

Intelligent Diagnosis and Analysis of Brain Lymphoma Based on DSC Imaging Features.

Currently, DSC has been extensively studied in the diagnosis, differential diagnosis, and prognosis evaluation of brain lymphoma, but it has not obtained a uniform standard. By combining DSC imaging features, this study investigated the imaging features and diagnostic value of several types of tumors such as primary brain lymphoma. At the same time, this study obtained data from brain lymphoma patients by data collection and set up different groups to conduct experimental studies to explore the correlation between IVIMMRI perfusion parameters and DSC perfusion parameters in brain lymphoma. Through experimental research, it can be seen that the combination of two perfusion imaging techniques can more fully reflect the blood flow properties of the lesion, which is beneficial to determine the nature of the lesion.

Clinical application of MIIRMR as a salvage method in gadolinium-enhanced MRI after intra-tympanic injection.

BACKGROUND: Three-dimensional fluid-attenuated inversion-recovery (3 D-FLAIR) and real inversion-recovery (3 D-real IR) sequences are used to detect endolymphatic hydrops (EH), but medium inversion-time inversion-recovery imaging with magnitude reconstruction (MIIRMR) may be more sensitive. AIMS: We investigated the inner-ear visualisation success rate and EH detection rates of 3 D-FLAIR and 3 D-real IR, and whether salvage MIIRMR could improve EH detection. MATERIALS AND METHODS: Fifty-one patients (102 ears) with episodic or chronic vestibular syndrome were injected intra-tympanically with 8-fold diluted gadolinium, and 3 D-FLAIR and 3 D-real IR images obtained 24-h post-injection. If 3 D-FLAIR inner-ear visualisation failed, additional MIIRMR was performed. The success and EH detection rate increase by MIIRMR was calculated. The diagnostic performance of combined MIIRMR + 3D-FLAIR + 3D-real IR for Meniere's disease (MD) was evaluated. RESULTS: The success rates of 3 D-FLAIR and 3 D-real IR were 88.90% and 72.55%, respectively. MIIRMR increased the success and EH detection rates by 11.10% and 6.86%, respectively. In MD, MIIRMR increased these rates by 10.53% and 10.53%, respectively. 3 D-FLAIR + 3D-real IR + MIIRMR had 92.11% sensitivity, 79.68% specificity, 72.92% positive-predictive value, and 94.44% negative-predictive value for MD diagnosis. CONCLUSION AND SIGNIFICANCE: MIIRMR can improve success and EH detection rates when 3 D-FLAIR fails. Combined MIIRMR + 3D-FLAIR + 3D-real IR is more valuable for diagnosing MD than conventional sequences.

Disrupted resting-state interhemispheric functional connectivity in systemic lupus erythematosus patients with and without neuropsychiatric lupus.

PURPOSE: The aim of the study is to explore interhemispheric homotopic functional connectivity alterations in systemic lupus erythematosus (SLE) patients with and without neuropsychiatric lupus (NPSLE and non-NPSLE, respectively) and their potential correlations with clinical characteristics and neuropsychological performance. METHODS: Based on resting-state functional MRI (rs-fMRI) data collected from SLE patients and matched healthy controls (HCs), the voxel-mirrored homotopic connectivity (VMHC) analysis was conducted to measure functional homotopy. Subsequently, correlations between altered functional homotopy and clinical/neuropsychological data were analyzed. RESULTS: Compared with the HC group, both NPSLE and non-NPSLE groups showed attenuated homotopic connectivity in middle temporal gyrus (MTG), cuneus (CUN), middle occipital gyrus (MOG), angular gyrus (ANG), and postcentral gyrus (PoCG). NPSLE patients also exhibited decreased homotopic connectivity in inferior parietal gyrus (IPG) and middle frontal gyrus (MFG). Compared with non-NPSLE patients, NPSLE patients showed weaker interhemispheric homotopic functional connectivity in MOG. Decreased homotopic functional connectivity in PoCG, IPG, and MOG were associated with the anxiety state of SLE patients. CONCLUSIONS: Our findings revealed attenuated functional homotopy in both NPSLE and non-NPSLE groups compared to the HC group, which appeared to be more severe in patients with comorbid neuropsychiatric lupus. Interhemispheric homotopy dysconnectivity may participate in the neuropathology of anxiety symptoms in SLE.

Alterations of Regional Homogeneity in Children With Congenital Sensorineural Hearing Loss: A Resting-State fMRI Study.

Background: Brain functional alterations have been observed in children with congenital sensorineural hearing loss (CSNHL). The purpose of this study was to assess the alterations of regional homogeneity in children with CSNHL. Methods: Forty-five children with CSNHL and 20 healthy controls were enrolled into this study. Brain resting-state functional MRI (rs-fMRI) for regional homogeneity including the Kendall coefficient consistency (KCC-ReHo) and the coherence-based parameter (Cohe-ReHo) was analyzed and compared between the two groups, i.e., the CSNHL group and the healthy control group. Results: Compared to the healthy controls, children with CSNHL showed increased Cohe-ReHo values in left calcarine and decreased values in bilateral ventrolateral prefrontal cortex (VLPFC) and right dorsolateral prefrontal cortex (DLPFC). Children with CSNHL also had increased KCC-ReHo values in the left calcarine, cuneus, precentral gyrus, and right superior parietal lobule (SPL) and decreased values in the left VLPFC and right DLPFC. Correlations were detected between the ReHo values and age of the children with CSNHL. There were positive correlations between ReHo values in the pre-cuneus/pre-frontal cortex and age (p < 0.05). There were negative correlations between ReHo values in bilateral temporal lobes, fusiform gyrus, parahippocampal gyrus and precentral gyrus, and age (p < 0.05). Conclusion: Children with CSNHL had RoHo alterations in the auditory, visual, motor, and other related brain cortices as compared to the healthy controls with normal hearing. There were significant correlations between ReHo values and age in brain regions involved in information integration and processing. Our study showed promising data using rs-fMRI ReHo parameters to assess brain functional alterations in children with CSNHL.

Altered Functional Brain Network in Systemic Lupus Erythematosus Patients Without Overt Neuropsychiatric Symptoms Based on Resting-State Functional Magnetic Resonance Imaging and Multivariate Pattern Analysis.

Objective: This study aims to investigate the alterations in functional brain network in systemic lupus erythematosus patients without overt neuropsychiatric symptoms [neuropsychiatric systemic lupus erythematosus (non-NPSLE)] from the perspective of degree centrality (DC) and functional connectivity (FC) using resting-state functional magnetic resonance imaging (MRI) and multivariate pattern analysis (MVPA) approach. Methods: DC analysis was performed based on the resting-state functional MRI data derived from 47 non-NPSLE patients and 47 healthy controls (HCs). Nodes with abnormal DC were utilized as seeds for further FC analysis. The correlation between MRI variables and clinical or neuropsychological data was analyzed using Pearson correlation analysis. Finally, MVPA classification based on DC was performed. Results: When compared with the HCs, the non-NPSLE patients exhibited remarkably higher DC in the bilateral hippocampus (HIP), right insula (INS), and lower DC in the left superior parietal gyrus. Furthermore, the patients displayed significantly higher FC between the left HIP and the left INS/left dorsolateral middle frontal gyrus/left supramarginal gyrus and higher FC between the right HIP and the right middle temporal gyrus/right dorsolateral middle frontal gyrus/right dorsolateral inferior frontal gyrus/right supramarginal gyrus (all imaging variables mentioned earlier underwent cluster-level false discovery rate corrections, the voxel threshold was p < 0.001, cluster threshold was p < 0.05). Correlation analysis revealed significantly negative correlations between DC values of the right INS and disease activity and the DC values of the right HIP and the Montreal Cognitive Assessment scores. The accuracy, sensitivity, and specificity of MVPA classification based on DC were 72.34, 63.83, and 80.85%, respectively. The most discriminative power brain regions were chiefly located within the temporal, parietal, and frontal regions. Conclusion: Patients with non-NPSLE exhibited abnormal DC and FC in the brain network. MVPA based on DC possessed commendable classification ability. Our study may provide a novel perspective on the neuropathological mechanisms underlying subclinical brain damage in non-NPSLE.

Assessing Cerebral White Matter Microstructure in Children With Congenital Sensorineural Hearing Loss: A Tract-Based Spatial Statistics Study.

OBJECTIVES: To assess the microstructural properties of cerebral white matter in children with congenital sensorineural hearing loss (CSNHL). METHODS: Children (>4 years of age) with profound CSNHL and healthy controls with normal hearing (the control group) were enrolled and underwent brain magnetic resonance imaging (MRI) scans with diffusion tensor imaging (DTI). DTI parameters including fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were obtained from a whole-brain tract-based spatial statistics analysis and were compared between the two groups. In addition, a region of interest (ROI) approach focusing on auditory cortex, i.e., Heschl's gyrus, using visual cortex, i.e., forceps major as an internal control, was performed. Correlations between mean DTI values and age were obtained with the ROI method. RESULTS: The study cohort consisted of 23 children with CSHNL (11 boys and 12 girls; mean age ± SD: 7.21 ± 2.67 years; range: 4.1-13.5 years) and 18 children in the control group (11 boys and 7 girls; mean age ± SD: 10.86 ± 3.56 years; range: 4.5-15.3 years). We found the axial diffusivity values being significantly greater in the left anterior thalamic radiation, right corticospinal tract, and corpus callosum in the CSHNL group than in the control group (p < 0.05). Significantly higher radial diffusivity values in the white matter tracts were noted in the CSHNL group as compared to the control group (p < 0.05). The fractional anisotropy values in the Heschl's gyrus in the CSNHL group were lower compared to the control group (p = 0.0015). There was significant negative correlation between the mean fractional anisotropy values in Heschl's gyrus and age in the CSNHL group < 7 years of age (r = -0.59, p = 0.004). CONCLUSION: Our study showed higher axial and radial diffusivities in the children affected by CNHNL as compared to the hearing children. We also found lower fractional anisotropy values in the Heschl's gyrus in the CSNHL group. Furthermore, we identified negative correlation between the fractional anisotropy values and age up to 7 years in the children born deaf. Our study findings suggest that myelination and axonal structure may be affected due to acoustic deprivation. This information may help to monitor hearing rehabilitation in the deaf children.

Imaging characteristics of cerebral extraventricular neurocytoma with pathological correlation.

PURPOSE: Extraventricular neurocytoma (EVN) is an exceedingly rare tumor. In this study, we sought to characterize the imaging and pathological features of this uncommon tumor. METHODS: Retrospective review of 18 patients (9 male; 9 female) with pathologically confirmed EVN treated at a single center between 2005 and 2017. RESULTS: All patients had a solitary lesion. Sixteen lesions were found in hemispheres. The greatest tumor diameter ranged from 2.6 to 8 cm. The lesions were generally solid with cystic components; the solid portion appeared isodense or hyperdense on CT, isointense to hypointense on T1WI, and slightly hyperintense on T2WI. Heterogeneous hyperintensity interspersed with isointense or hypointense areas suggestive of hemorrhage, calcification or vascular flow voids were seen on T2WI. Heterogeneous enhancement was noted in 17 lesions; no enhancement was observed in one lesion. Cystic components were observed in 13 lesions; 9 of these showed characteristic perilesional cysts (9/13). Mild to moderate peritumoral edema (15/18), calcification (4/16), intratumoral hemorrhage (11/18) and vascular flow voids (10/16) were observed in some lesions. Pathologically, tumor cells showed round nucleus and fine neuropil matrix. Foci of calcification in the solid portion of the tumor were seen in five cases. Microcystic changes were observed in almost all cases. Some lesions exhibited positive staining for synaptophysin (Syn) (15/16) and neuronal nuclei (NeuN) (7/8). MIB-1 was determined for 10 patients; seven of these had an MIB-1 ≥ 3. These six patients experienced recurrence; four of them relapsed twice. CONCLUSIONS: EVNs occur as single intracranial solid mass with cystic components (especially peripherally located cysts); solid portion exhibits slight hyperintensity or heterogeneous signal intensity. Mild to moderate peritumoral edema, calcification, intratumoral hemorrhage and vascular flow voids were characteristic features of extraventricular neurocytoma. Positive staining for synaptophysin and neuronal nuclei confirmed the diagnosis. A combination of atypical pathologic features and atypical radiologic features should be considered for prognostic assessment.