Mediation of White Matter Alterations in the Association Between Ventricular Dilation and Cognitive Decline in Hydrocephalus Patients: An MRI Study.

BACKGROUND: Cognitive impairment is commonly observed in hydrocephalus patients. Ventricular enlargement compresses brain parenchyma, especially the white matter (WM). PURPOSE: To investigate whether the relationship between ventricular dilation and cognitive decline in hydrocephalus patients is mediated by WM alterations. STUDY TYPE: Retrospective. POPULATION: 51 communicating hydrocephalus patients (median age, 54 years), 50 obstructive hydrocephalus patients (median age, 49 years), and 53 control subjects (median age, 50 years). FIELD STRENGTH/SEQUENCE: Diffusion tensors imaging, 3D T1 BRAVO, 3D FIESTA, CUBE T2, and FLAIR sequences at 3T. ASSESSMENT: DTI parameters (skeletonized fractional anisotropy (FA), skeletonized mean diffusivity (MD), and peak width of skeletonized mean diffusivity p(PSMD)) were extracted using FSL software. Global, periventricular, and deep white matter hyperintensity (WMH) volumes, degree of ventricular enlargement (Evans index), and other conventional imaging markers (number of lacunes and perivascular spaces, intracranial and brain volume) were extracted using united imaging intelligence. Cognitive tests included Montreal cognitive assessment (MoCA), clock drawing test (CDT), and vocabulary fluency test (VFT). STATISTICAL TESTS: Multivariable linear regression analysis, mediation analyses, and dominance analysis. P-value <0.05 was considered significant. RESULTS: The degree of ventricular dilation, DTI parameters, and cognitive function scores were interrelated. The skeletonized FA values (ß = -0.0917, 95% confidence interval (CI): -0.205, -0.024) and normalized global WMH volume (ß = -0.0635, 95% CI: -0.13, -0.0005) together mediated 37.2% of the association between Evans index and MoCA. A comparable causal pathway was found for periventricular WMHs but not for deep WMHs. Dominance analysis indicated skeletonized FA values had a greater impact on cognition than WMH volume. The skeletonized FA values also mediated the association between Evans index and CDT (ß = -0.0897, 95% CI: -0.165, -0.026) and VFT (ß = -0.1589, 95% CI: -0.27, -0.083). CONCLUSION: WM alterations were causal mediators between ventricular dilation and cognitive decline in hydrocephalus patients. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 3.

A radiomics nomogram based on multiparametric MRI for diagnosing focal cortical dysplasia and initially identifying laterality.

BACKGROUND: Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance imaging (MRI) to diagnose FCD and identify laterality early. METHODS: Forty-three patients treated between July 2017 and May 2022 with histopathologically confirmed FCD were retrospectively enrolled. The contralateral unaffected hemispheres were included as the control group. Therefore, 86 ROIs were finally included. Using January 2021 as the time cutoff, those admitted after January 2021 were included in the hold-out set (n = 20). The remaining patients were separated randomly (8:2 ratio) into training (n = 55) and validation (n = 11) sets. All preoperative and postoperative MR images, including T1-weighted (T1w), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR), and combined (T1w + T2w + FLAIR) images, were included. The least absolute shrinkage and selection operator (LASSO) was used to select features. Multivariable logistic regression analysis was used to develop the diagnosis model. The performance of the radiomic nomogram was evaluated with an area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration and clinical utility. RESULTS: The model-based radiomics features that were selected from combined sequences (T1w + T2w + FLAIR) had the highest performances in all models and showed better diagnostic performance than inexperienced radiologists in the training (AUCs: 0.847 VS. 0.664, p = 0.008), validation (AUC: 0.857 VS. 0.521, p = 0.155), and hold-out sets (AUCs: 0.828 VS. 0.571, p = 0.080). The positive values of NRI (0.402, 0.607, 0.424) and IDI (0.158, 0.264, 0.264) in the three sets indicated that the diagnostic performance of Model-Combined improved significantly. The radiomics nomogram fit well in calibration curves (p > 0.05), and decision curve analysis further confirmed the clinical usefulness of the nomogram. Additionally, the contrast (the radiomics feature) of the FCD lesions not only played a crucial role in the classifier but also had a significant correlation (r = -0.319, p < 0.05) with the duration of FCD. CONCLUSION: The radiomics nomogram generated by logistic regression model-based multiparametric MRI represents an important advancement in FCD diagnosis and treatment.

Radiomics features based on T2-weighted fluid-attenuated inversion recovery MRI predict the expression levels of CD44 and CD133 in lower grade gliomas.

Objective: To verify the association between CD44 and CD133 expression levels and the prognosis of patients with lower grade gliomas (LGGs) and constructing radiomic models to predict those two genes' expression levels before surgery. Materials & methods: Genomic data of patients with LGG and the corresponding T2-weighted fluid-attenuated inversion recovery images were downloaded from The Cancer Genome Atlas and The Cancer Imaging Archive, which were utilized for prognosis analysis, radiomic feature extraction and model construction, respectively. Results & conclusion: CD44 and CD133 expression levels in LGG can significantly affect the prognosis of patients with LGG. Based on the T2-weighted fluid-attenuated inversion recovery images, the radiomic features can effectively predict the expression levels of CD44 and CD133 before surgery.

Preclinical evaluation of severely defective manganese-based nanocrystal as a liver-specific contrast media for MR imaging: comparison with Gd-EOB-DTPA and MnDPDP.

Manganese-based (chemically formulated of KMnF3) nanocrystal was evaluated as a liver-specific contrast agent for MR imaging and its imaging performance was also compared with those of two commercial hepatobiliary contrast media (Gd-EOB-DTPA and MnDPDP). KMnF3 nanocrystal was post-treated using a plasma technique to cause severe defects, leading to appropriate water dispersibility and high relaxivity. Severely defective KMnF3 nanocrystal (SD-KMnF3) has characteristic high tolerance, as evidenced by cytotoxicity on the macrophage cell, and acute and subchronic toxicity on the healthy mouse. SD-KMnF3 showed better hepatic MR imaging as the T 1 relaxation time of the liver decreased to only 17% of the control group, compared to 22% of the control group for Gd-EOB-DTPA (P < 0.01) and 42% of the control group for MnDPDP (P < 0.001). As applied to MR imaging of the allograft orthotopic model of liver cancer, statistical studies demonstrated that SD-KMnF3 significantly improved the tumor's contrast-to-noise ratio, compared with Gd-EOB-DTPA (P < 0.01) and MnDPDP (P < 0.01) by spin-echo pulse sequence, and even better performance (P < 0.001) by gradient-echo sequence. Our findings indicate that SD-KMnF3 could serve as a hepatic contrast agent for imaging liver cancer such as hepatocarcinoma or metastatic lesions.

Downregulation of USP18 inhibits growth and induces apoptosis in hepatitis B virus-related hepatocellular carcinoma cells by suppressing BCL2L1.

Ubiquitin-specific peptidase 18 (USP18) is closely related with hepatitis B virus (HBV), which has been involved in tumourigenesis. However, there has been little research into the role of USP18 on the progression of hepatocellular carcinoma (HCC), especially in HBV-related HCC. In present study, we found that USP18 expression was aberrantly elevated in HCC tissues than adjacent non-tumour tissues. Importantly, USP18 expression was higher in HBV-related HCC cell lines (HepG2.2.15 and Hep3B) than HBV-unrelated HCC cell lines. Furthermore, knockdown of USP18 significantly suppressed tumour cell proliferation in vitro and tumour growth in vivo, whereas overexpression of USP18 promoted HCC cells growth. Moreover, our experimental data revealed that USP18 silencing obviously blocked cell cycle at G1 phase and increased cell apoptosis. Finally, BCL2L1, a member of BCL2 family protein, was identified as a downstream gene of USP18. Mechanistically, we found that USP18 directly bind to BCL2L1 and positively regulated its expression in HCC cells. Overall, our results suggested that USP18 has a crucial role in regulating diverse aspects of the pathogenesis of HCC, indicating that it might be a potential therapeutic target.

Is arterial spin labelling necessarily low perfusion for cavernous sinus venous malformation? A case of hyperperfusion cavernous sinus venous malformation.

Generally, due to the complexity of the skull base structures, it is difficult to differentiate cavernous vascular malformation and meningioma in the cavernous sinus area using conventional imaging studies. Cavernous sinus venous malformation are characterized by increased capillary masses without a direct arterial supply, typically leading to low perfusion. On the other hand, meningiomas receive arterial blood supply to the tumour and often exhibit high perfusion. So, arterial spin labelling (ASL) can be helpful in distinguishing between the 2 tumour types. However, in our specific case of a cavernous sinus venous malformation, the ASL imaging showed hyperperfusion. Further analysis revealed that this hyperperfusion on ASL can occur when cavernous sinus venous malformation is associated with arteriovenous fistula malformation.

Three-dimensional pseudocontinuous arterial spin labeling with dual postlabeling delay for reflecting cerebral blood flow regulation in patients with hydrocephalus: a retrospective cross-sectional study.

Background: Three-dimensional pseudo-continuous arterial spin-labeling (3D pCASL) with dual postlabeling delay (PLD) captures both early and delayed cerebral blood flow (CBF), yet its potential in reflecting blood flow regulation in hydrocephalus patients remains uncertain. This study investigated the hemodynamic characteristics in patients with hydrocephalus and whether the difference in cerebral blood flow using short and long PLDs (ΔCBF = CBFPLD =2.5 s - CBFPLD =1.5 s) could reflect cerebral regulation and further aimed to demonstrate the associations between regional ΔCBF and the degree of ventricular dilatation. Methods: This retrospective study included consecutive patients with hydrocephalus and control participants attending The Second Affiliated Hospital of Nanchang University from December 2017 to December 2022. The CBF in 18 brain regions was manually delineated by two radiologists. Regional CBF and ΔCBF were compared via covariance analyses. The associations between ΔCBF and the degree of ventricular dilatation were investigated using linear regression analyses and interaction analysis. Results: In total, 58 patients with communicating hydrocephalus, 57 patients with obstructive hydrocephalus, and 52 controls were analyzed. CBF of the hydrocephalus groups was lower than that of the control group at the shorter PLD. CBF was higher at a longer PLD, with no difference between the hydrocephalus groups and the control group in some regions. The hydrocephalus groups showed a higher ΔCBF compared to the control group. Furthermore, in the left medial watershed (10.6±5.66 vs. 7.01±5.88 mL/100 g/min; P=0.038), communicating hydrocephalus exhibited greater ΔCBF than did obstructive hydrocephalus. ΔCBF of the right posterior external watershed [adjusted ß: 0.276; 95% confidence interval (CI): 0.047-0.505; P=0.019] and right parietal cortex (adjusted ß: 0.277; 95% CI: 0.056-0.498; P=0.015) in the obstructive hydrocephalus group and ΔCBF of the left internal watershed (adjusted ß: 0.274; 95% CI: 0.013-0.536; P=0.040) in the communicating hydrocephalus group were associated with the degree of ventricular dilatation, respectively. Conclusions: Patients with hydrocephalus showed cerebral regulation in maintaining adequate CBF, resulting in longer arterial transit times. The ability to regulate CBF in brain regions represented by the watershed was associated with the degree of ventricular dilation.

The use of multi b values diffusion-weighted imaging in patients with acute stroke.

INTRODUCTION: The purpose of this paper is to study the mechanism of apparent diffusion coefficient reduction after stroke by using multi b value diffusion-weighted imaging. METHODS: Ten healthy people and 25 patients with acute stroke were enrolled. In healthy volunteers, region of interests were put in the semioval center and in the precentral gyrus. In patients with acute stroke, region of interests were put in lesions and contralateral normal brain regions. ADC(fast) and ADC(slow) are thought of as a fast and a slow apparent diffusion coefficient, which result from the extracellular and intracellular compartments, respectively. p (fast) and p (slow) are regarded as the percentage of signal intensities deriving from water diffusion of the extracellular and intracellular compartments, separately. All data were analyzed using paired, two-tailed t tests. Statistical analyses were performed using SPSS 15.0. RESULTS: In patients with acute stroke, p (fast) in lesions (0.54 ± 0.11) is lower than that in normal regions (0.75 ± 0.09), while p (slow) is on the contrary. ADC(fast) and ADC(slow) values in lesions are less than those in normal areas. Compared with those in normal regions, p (fast) of lesions decreases by 28 %, and ADC(fast) and ADC(slow) of lesions went down by 27 and 36 %, respectively. There are statistically significant differences (P < 0.05) in ADC(fast), ADC(slow), and p (fast) between lesions and normal regions. CONCLUSION: The increase in the volume of extracellular space and the decrease in ADC(slow) are the primary reasons that lead to the decrease in apparent diffusion coefficient of lesions after stroke.

[Effect of lead exposure on brain iron in aged rats based on the MRI].

OBJECTIVE: To explore the effect of long-term lead exposure on brain iron in aged rats. METHODS: SPF female and male Sprague-Dawley rats were respectively randomly divided into three groups: control, low lead-exposed, high lead-exposed. Lead-exposed female rats drank 0.8g/L or 1.5g/L lead acetate solutions through pregnancy until weaning and then the pups received 0.3g/L or 0.9g/L lead acetate solution depending on their group. Control group rats drank deionized water throughout the experiment. At the postnatal 18 months, one pup for per group was given an ultra structural detection of hippocampus, and the other male pups were measured the lead and iron concentration of blood and brain by GE MR 3.0T MR scanner and ICP-AES. RESULTS: In comparing with control group, the lead concentrations of blood and brain in lead-exposed groups were significantly higher, and the iron contents of brain and cortex, hippocampus, thalamus were significantly higher in 0.9g/L lead-exposed group. Also, it was highly positively correlated between blood lead and iron of blood, cortex, hippocampus, thalamus, respectively. With the dose of lead-exposed increased, cytoplasm, nucleus, mitochondrial structure and synaptic structure had suffered vary degrees of damage from ultra structural detection of hippocampus, it could be observed early neuronal apoptosis. CONCLUSION: Lead induced neurodegenerative diseases might be related to iron overload which caused by lead exposure.

Combined Cerebrospinal Fluid Hydrodynamics and Fourth Ventricle Outlet Morphology to Improve Predictive Efficiency of Prognosis for Chiari Malformation Type I Decompression.

OBJECTIVE: To identify the morphological characteristics together with cerebrospinal fluid (CSF) hydrodynamics on preoperative magnetic resonance imaging that improve the prediction of foramen magnum decompression (FMD) treatment outcome for Chiari malformations type I (CM-I) patients compared with the CSF hydrodynamics-based model. METHODS: This retrospective study included CM-I patients who underwent FMD, phase-contrast cine magnetic resonance, and static MR between January 2018 and March 2022. The relationships of the preoperative CSF hydrodynamic quantifications derived from phase-contrast cine magnetic resonance and morphological measurements from static magnetic resonance imaging, clinical indicators with different outcomes, were analyzed with logistic regression analysis. The outcomes were determined using the Chicago Chiari Outcome Scale. The predictive performance was evaluated with receiver operating characteristic, calibration, decision curves and area under the receiver operating characteristic curve, net reclassification index, and integrated discrimination improvement and was compared with CSF hydrodynamics-based model. RESULTS: A total of 27 patients were included. 17 (63%) had improved outcomes and 10 (37%) had poor outcomes. The peak diastolic velocity of the aqueduct midportion (odd ratio, 5.17; 95% confidence interval: 1.08, 24.70; P = 0.039) and the fourth ventricle outlet diameter (odd ratio, 7.17; 95% confidence interval: 1.07, 48.16; P = 0.043) were predictors of different prognoses. The predictive performance improved significantly than the CSF hydrodynamics-based model. CONCLUSIONS: Combined CSF hydrodynamic and static morphologic MR measurements can better predict the response to FMD. A higher peak diastolic velocity of the aqueduct midportion and broader fourth ventricle outlet were associated with satisfying outcomes after decompression in CM-I patients.

Does Regular Physical Activity Improve Personal Income? Empirical Evidence from China.

A lack of adequate exercise threatens human health, weakening human capital accumulation. The relationship between exercise and income has become the focus of attention in health economics. In terms of reducing body weight and improving physical fitness, diet and physical exercise are intertwined and become effective ways to shape a healthy state. Based on individual-level survey data from China, this study quantified the economic returns of habitual exercise behavior by using an endogenous switching regression model (ESRM) to eliminate selection bias. The study shows that (1) participants in the group with regular exercise behavior increased their income by 3.79% compared with those not exercising regularly; (2) for the group with no regular exercise behavior, regular exercise increased their income by 13.36% compared with those not exercising regularly. Additionally, empirical evidence shows that both drinking and smoking can significantly increase individual income, despite unhealthy habits. These results suggest that the habit of regular physical activity plays a vital role in increasing individual income and improving overall national health, and the effect of individual behavior on income is affected by national culture. The outcomes are empirical evidence for the Chinese government to promote Healthy China Action and support developing countries worldwide to enable habitual exercise, stimulating a policy of exercise behavior.

A Radiomics Model for Predicting Early Recurrence in Grade II Gliomas Based on Preoperative Multiparametric Magnetic Resonance Imaging.

OBJECTIVE: This study aimed to develop a radiomics model to predict early recurrence (<1 year) in grade II glioma after the first resection. METHODS: The pathological, clinical, and magnetic resonance imaging (MRI) data of patients diagnosed with grade II glioma who underwent surgery and had a recurrence between 2017 and 2020 in our hospital were retrospectively analyzed. After a rigorous selection, 64 patients were eligible and enrolled in the study. Twenty-two cases had a pathologically confirmed recurrent glioma. The cases were randomly assigned using a ratio of 7:3 to either the training set or validation set. T1-weighted image (T1WI), T2-weighted image (T2WI), and contrast-enhanced T1-weighted image (T1CE) were acquired. The minimum-redundancy-maximum-relevancy (mRMR) method alone or in combination with univariate logistic analysis were used to identify the most optimal predictive feature from the three image sequences. Multivariate logistic regression analysis was then used to develop a predictive model using the screened features. The performance of each model in both training and validation datasets was assessed using a receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: A total of 396 radiomics features were initially extracted from each image sequence. After running the mRMR and univariate logistic analysis, nine predictive features were identified and used to build the multiparametric radiomics model. The model had a higher AUC when compared with the univariate models in both training and validation data sets with an AUC of 0.966 (95% confidence interval: 0.949-0.99) and 0.930 (95% confidence interval: 0.905-0.973), respectively. The calibration curves indicated a good agreement between the predictable and the actual probability of developing recurrence. The DCA demonstrated that the predictive value of the model improved when combining the three MRI sequences. CONCLUSION: Our multiparametric radiomics model could be used as an efficient and accurate tool for predicting the recurrence of grade II glioma.

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI.

Glioma characterized by high morbidity and mortality, is one of the most common brain tumors. The application of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in differentiating glioma grading and IDH1 mutation status were poorly investigated. 78 glioma patients confirmed by pathological and imaging methods were enrolled. Glioma patients were measured using IVIM-DWI, then related parameters such as cerebral blood flow (CBF), perfusion fraction (f), pseudo diffusivity (D*), and true diffusivity (D), were derived. Receiver operating characteristic (ROC) curves were made to calculate specificity and sensitivity. The values of CBF1, CBF3, D*1, rCBF1-2, rCBF3-2, and age in group high-grade gliomas (HGG) were significantly higher than that of in group low-grade gliomas (LGG). The values of CBF1, CBF3, rCBF1-2, rCBF3-2, D*1, and age in group IDH1mut were significantly lower than that of in group IDH1wt. The levels of D1 and f1 were remarkably higher in the group IDH1mut than group IDH1wt. rCBF1-2 had a remarkably positive correlation with CBF1 (r=0.852, p<0.001). f1 showed a markedly negative correlation with CBF1 (r= -0.306, p=0.007). IVIM-DWI presented efficacy in differentiating glioma grading and IDH1 mutation status.

Multiparametric MRI Radiomics for the Early Prediction of Response to Chemoradiotherapy in Patients With Postoperative Residual Gliomas: An Initial Study.

PURPOSE: To evaluate whether multiparametric magnetic resonance imaging (MRI)-based logistic regression models can facilitate the early prediction of chemoradiotherapy response in patients with residual brain gliomas after surgery. PATIENTS AND METHODS: A total of 84 patients with residual gliomas after surgery from January 2015 to September 2020 who were treated with chemoradiotherapy were retrospectively enrolled and classified as treatment-sensitive or treatment-insensitive. These patients were divided into a training group (from institution 1, 57 patients) and a validation group (from institutions 2 and 3, 27 patients). All preoperative and postoperative MR images were obtained, including T1-weighted (T1-w), T2-weighted (T2-w), and contrast-enhanced T1-weighted (CET1-w) images. A total of 851 radiomics features were extracted from every imaging series. Feature selection was performed with univariate analysis or in combination with multivariate analysis. Then, four multivariable logistic regression models derived from T1-w, T2-w, CET1-w and Joint series (T1+T2+CET1-w) were constructed to predict the response of postoperative residual gliomas to chemoradiotherapy (sensitive or insensitive). These models were validated in the validation group. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were applied to compare the predictive performances of these models. RESULTS: Four models were created and showed the following areas under the ROC curves (AUCs) in the training and validation groups: Model-Joint series (AUC, 0.923 and 0.852), Model-T1 (AUC, 0.835 and 0.809), Model-T2 (AUC, 0.784 and 0.605), and Model-CET1 (AUC, 0.805 and 0.537). These results indicated that the Model-Joint series had the best performance in the validation group, followed by Model-T1, Model-T2 and finally Model-CET1. The calibration curves indicated good agreement between the Model-Joint series predictions and actual probabilities. Additionally, the DCA curves demonstrated that the Model-Joint series was clinically useful. CONCLUSION: Multiparametric MRI-based radiomics models can potentially predict tumor response after chemoradiotherapy in patients with postoperative residual gliomas, which may aid clinical decision making, especially to help patients initially predicted to be treatment-insensitive avoid the toxicity of chemoradiotherapy.

A Clinical-Radiomic Nomogram Based on Unenhanced Computed Tomography for Predicting the Risk of Aldosterone-Producing Adenoma.

PURPOSE: To develop and validate a clinical-radiomic nomogram for the preoperative prediction of the aldosterone-producing adenoma (APA) risk in patients with unilateral adrenal adenoma. PATIENTS AND METHODS: Ninety consecutive primary aldosteronism (PA) patients with unilateral adrenal adenoma who underwent adrenal venous sampling (AVS) were randomly separated into training (n = 62) and validation cohorts (n = 28) (7:3 ratio) by a computer algorithm. Data were collected from October 2017 to June 2020. The prediction model was developed in the training cohort. Radiomic features were extracted from unenhanced computed tomography (CT) images of unilateral adrenal adenoma. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensions, select features, and establish a radiomic signature. Multivariable logistic regression analysis was used for the predictive model development, the radiomic signature and clinical risk factors integration, and the model was displayed as a clinical-radiomic nomogram. The nomogram performance was evaluated by its calibration, discrimination, and clinical practicability. Internal validation was performed. RESULTS: Six potential predictors were selected from 358 texture features by using the LASSO regression model. These features were included in the Radscore. The predictors included in the individualized prediction nomogram were the Radscore, age, sex, serum potassium level, and aldosterone-to-renin ratio (ARR). The model showed good discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.900 [95% confidence interval (CI), 0.807 to 0.993], and good calibration. The nomogram still showed good discrimination [AUC, 0.912 (95% CI, 0.761 to 1.000)] and good calibration in the validation cohort. Decision curve analysis presented that the nomogram was useful in clinical practice. CONCLUSIONS: A clinical-radiomic nomogram was constructed by integrating a radiomic signature and clinical factors. The nomogram facilitated accurate prediction of the probability of APA in patients with unilateral adrenal nodules and could be helpful for clinical decision making.

Reduced structural covariance connectivity of defaut mode network and salience network in MRI-normal focal epilepsy.

Neuroimaging studies have found altered functional connectivity of default mode network (DMN) and salience network (SN) in patients with focal epilepsy (FE). However, the structural basis underlying the functional connectivity disturbance in the patients is still unclear. Sixteen MRI-normal FE and 22 healthy controls were included in the current study. The T1 structural image of each participant was obtained. Seed-based structural covariance connectivity was employed to investigate changes of structural covariance connectivity of DMN and SN in FE patients. We further evaluated gray matter volume changes of brain areas showing altered structural connectivity in the patients. We found that patients with FE showed reduced connectivity of posterior cingulate cortex and left medial prefrontal cortex, hippocampus and orbitofrontal cortex, and reduced connectivity of right fronto-insula cortex with left insula, orbitofrontal cortex, opercum part of inferior frontal cortex and right medial prefrontal cortex compared with healthy controls. Moreover, those brain areas showing significant reduced structural covariance connectivity in patients with FE also had a loss of gray matter volume, indicating that reduced structural connectivity of DMN and SN might be associated with gray matter atrophy in the patients. Those results highlight the crucial role of DMN and SN in the pathology of patients with FE, and provided structural basis for the functional disturbance of the two networks in this disease.

An Assessment of the Relationship between Structural and Functional Imaging of Cerebrovascular Disease and Cognition-Related Fibers.

In order to assess the relationship between structural and functional imaging of cerebrovascular disease and cognition-related fibers, this paper chooses a total of 120 patients who underwent cerebral small vessel disease (CSVD) treatment at a designated hospital by this study from June 2013 to June 2018 and divides them into 3 groups according to the random number table method: vascular dementia (VaD) group, vascular cognitive impairment no dementia (VCIND) group, and noncognition impairment (NCI) group with 40 cases of patients in each group. Cognitive function measurement and imaging examination were performed for these 3 groups of patients, and the observation indicators of cognitive state examination (CSE), mental assessment scale (MAS), clock drawing test (CDT), adult intelligence scale (AIS), frontal assessment battery (FAB), verbal fluency test (VFT), trail making test (TMT), cognitive index (CI), white matter lesions (WML), third ventricle width (TVW), and frontal horn index (FHI) were tested, respectively. The results shows that the average scores of CSE, MAS, AIS, and VFT in the VaD and VCIND group are lower than those of the NCI group and the differences are statistically significant (P < 0.05); the average scores of FAB, TMT, and CI in the VaD group are higher than those of the VCIND group and the differences are also statistically significant (P < 0.05); the average scores of FHI and TVW in the VaD group are lower than those of the VCIND and NCI group with statistically significant differences (P < 0.05); the average scores of WML, CDT, and AIS in the VaD group are higher than those of the VCIND and NCI group with statistically significant differences (P < 0.05). Therefore, it is believed that the structural and functional imaging features of cerebrovascular disease are closely related to cognition-related fibers, and the incidence of white matter lesions is closely related to the degree of lesions and cognitive dysfunction of cerebral small vessel disease, in which a major risk factor for cognitive dysfunction in patients with small blood vessels is the severity of white matter lesions; brain imaging and neuropsychiatric function assessment can better understand the relationship between cerebrovascular disease and cognitive impairment. The results of this study provide a reference for the further research studies on the relationship between structural and functional imaging of cerebrovascular disease and cognition-related fibers.

Diagnostic value of whole body diffusion weighted imaging for screening primary tumors of patients with metastases.

OBJECTIVE: To evaluate the values of whole body diffusion weighted imaging (DWI) in screening primary unknown tumor in patients with metastases. METHODS: Totally, 34 patients with metastases of primary unknown tumors were scanned with whole body DWI, and conventional magnetic resonance (MR) imaging was performed if suspected lesions were detected. All the metastases including 27 cases of osseous metastases, 2 brain metastases, 2 liver metastases, 1 pulmonary multiple metastasis, 1 neck metastasis and 1 malignant ascites, were diagnosed by computed tomography, single photon emission computed tomography, or MR imaging. For the proven primary tumors diagnosed by biopsy or pathology of surgical specimens, apparent diffusion coefficient (ADC) values of the primary and metastatic lesions were measured respectively. The sensitivity and specificity of this technique for screening primary tumors were evaluated. RESULTS: We found 24 cases with suspected primary lesions, in which 23 lesions were proved to be primary tumors, and 1 was proved to be benign lesion. And no definite primary lesion was found in 10 cases on whole body DWI, but in which 1 case was diagnosed with primary tumor by biopsy later, and the other 9 cases remained unknown within follow-up of over half a year. The difference was not significant in ADC values between primary and metastatic lesions (P>0.05). The sensitivity and specificity of whole body DWI for searching primary tumors was 95.8% and 90.0%, respectively. CONCLUSION: Combined with conventional MR scanning, whole body DWI can help to search primary lesions of patients with metastases.