Development of a multi-phase CT-based radiomics model to differentiate heterotopic pancreas from gastrointestinal stromal tumor.

BACKGROUND: To investigate whether CT-based radiomics can effectively differentiate between heterotopic pancreas (HP) and gastrointestinal stromal tumor (GIST), and whether different resampling methods can affect the model's performance. METHODS: Multi-phase CT radiological data were retrospectively collected from 94 patients. Of these, 40 with HP and 54 with GISTs were enrolled between April 2017 and November 2021. One experienced radiologist manually delineated the volume of interest and then resampled the voxel size of the images to 0.5 × 0.5 × 0.5 mm3, 1 × 1 × 1 mm3, and 2 × 2 × 2 mm3, respectively. Radiomics features were extracted using PyRadiomics, resulting in 1218 features from each phase image. The datasets were randomly divided into training set (n = 66) and validation set (n = 28) at a 7:3 ratio. After applying multiple feature selection methods, the optimal features were screened. Radial basis kernel function-based support vector machine (RBF-SVM) was used as the classifier, and model performance was evaluated using the area under the receiver operating curve (AUC) analysis, as well as accuracy, sensitivity, and specificity. RESULTS: The combined phase model performed better than the other phase models, and the resampling method of 0.5 × 0.5 × 0.5 mm3 achieved the highest performance with an AUC of 0.953 (0.881-1), accuracy of 0.929, sensitivity of 0.938, and specificity of 0.917 in the validation set. The Delong test showed no significant difference in AUCs among the three resampling methods, with p > 0.05. CONCLUSIONS: Radiomics can effectively differentiate between HP and GISTs on CT images, and the diagnostic performance of radiomics is minimally affected by different resampling methods.

Cognition and motion dysfunction-associated brain functional network disruption in diabetic peripheral neuropathy.

Neuroimaging studies have demonstrated extensive brain functional alterations in cognitive and motor functional areas in Type 2 diabetes mellitus (T2DM) with diabetic peripheral neuropathy (DPN), suggesting potential alterations in large-scale brain networks related to DPN and associated cognition and motor dysfunction. In this study, using resting-state functional connectivity (FC) and graph theory computational approaches, we investigated the topological disruptions of brain functional networks in 28 DPN, 43 T2DM without DPN (NDPN), and 32 healthy controls (HCs) and examined the correlations between altered network topological metrics and cognitive/motor function parameters in T2DM. For global topology, NDPN exhibited a significantly decreased shortest path length compared with HCs, suggesting increased efficient global integration. For regional topology, DPN and NDPN had separated topological reorganization of functional hubs compared with HCs. In addition, DPN showed significantly decreased nodal efficiency (Enodal ), mainly in the bilateral superior occipital gyrus (SOG), right cuneus, middle temporal gyrus (MTG), and left inferior parietal gyrus (IPL), compared with NDPN, whereas NDPN showed significantly increased Enodal compared with HCs. Intriguingly, in T2DM patients, the Enodal of the right SOG was significantly negatively correlated with Toronto Clinical Scoring System scores, while the Enodal of the right postcentral gyrus (PoCG) and MTG were significantly positively correlated with Montreal Cognitive Assessment scores. Conclusively, DPN and NDPN patients had segregated disruptions in the brain functional network, which were related to cognition and motion dysfunctions. Our findings provide a theoretical basis for understanding the neurophysiological mechanism of DPN and its effective prevention and treatment in T2DM.

Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds.

Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.

Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens.

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Quantitative information from gadobenate dimeglumine-enhanced MRI can predict proliferative subtype of solitary hepatocellular carcinoma: a multicenter retrospective study.

OBJECTIVES: To investigate the value of quantitative parameters derived from gadobenate dimeglumine-enhanced magnetic resonance imaging (MRI) for predicting molecular subtype of hepatocellular carcinoma (HCC) and overall survival. METHODS: This multicenter retrospective study included 218 solitary HCC patients who underwent gadobenate dimeglumine-enhanced MRI. All HCC lesions were resected and pathologically confirmed. The lesion-to-liver contrast enhancement ratio (LLCER) and lesion-to-liver contrast (LLC) were measured in the hepatobiliary phase. Potential risk factors for proliferative HCC were assessed by logistic regression. The ability of LLCER and LLC to predict proliferative HCC was assessed by the receiver operating characteristic (ROC) curve. Prognostic factors were evaluated using the Cox proportional hazards regression model for survival outcomes. RESULTS: LLCER was an independent predictor of proliferative HCC (odds ratio, 0.015; 95% confidence interval [CI], 0.008-0.022; p < 0.001). The area under the ROC curve was 0.812 (95% CI, 0.748-0.877), higher than that of LLC, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement (all p ≤ 0.001). HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%. During the follow-up period, LLCER was an independent predictor of overall survival (hazard ratio, 0.070; 95% CI, 0.015-0.324; p = 0.001) in HCC patients. CONCLUSIONS: Gadobenate dimeglumine-enhanced quantitative parameter in the hepatobiliary phase can predict the proliferative subtype of solitary HCC with a moderately high accuracy. CLINICAL RELEVANCE STATEMENT: Quantitative information from gadobenate dimeglumine-enhanced MRI can provide crucial information on hepatocellular carcinoma subtypes. It might be valuable to design novel therapeutic strategies, such as targeted therapies or immunotherapy. KEY POINTS: • The lesion-to-liver contrast enhancement ratio (LLCER) is an independent predictor of proliferative hepatocellular carcinoma (HCC). • The ability of LLCER to predict proliferative HCC outperformed lesion-to-liver contrast, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement. • HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%.

Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease.

This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (Eglob/Eloc) and decreased shortest path lengths (Lp), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (Eglob, Eloc, and Lp) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.

The tumor or inflammation? a case report on primary pulmonary choriocarcinoma.

Choriocarcinoma is a rare malignant germ cell neoplasm with high invasiveness, the majority of which are pregnancy-related, and the female genital tract is the most prevalent site of the disease. Although early-stage choriocarcinoma typically metastasizes to the lungs, primary pulmonary choriocarcinoma is extremely rare. Primary pulmonary choriocarcinoma is difficult to diagnose, and it progresses rapidly. Combined with the difficulty of treatment, the prognosis of patients is generally poor. In this article, we retrospectively analyzed a case of female primary pulmonary choriocarcinoma, combined with a review of literature, to understand and describe the diagnostic and treatment progress of PPC.

Abnormal whole-brain voxelwise structure-function coupling and its association with cognitive dysfunction in patients with different cerebral small vessel disease burdens.

Cerebral small vessel disease (CSVD) is a universal neurological disorder in older adults that occurs in connection with cognitive dysfunction and is a chief risk factor for dementia and stroke. While whole-brain voxelwise structural and functional abnormalities in CSVD have been heavily explored, the degree of structure-function coupling abnormality possible in patients with different CSVD burdens remains largely unknown. This study included 53 patients with severe CSVD burden (CSVD-s), 108 patients with mild CSVD burden (CSVD-m) and 76 healthy controls. A voxelwise coupling metric of low frequency fluctuations (ALFF) and voxel-based morphometry (VBM) was used to research the important differences in whole-brain structure-function coupling among groups. The correlations between ALFF/VBM decoupling and cognitive parameters in CSVD patients were then investigated. We found that compared with healthy controls, CSVD-s patients presented notably decreased ALFF/VBM coupling in the bilateral caudate nuclei and increased coupling in the right inferior temporal gyrus (ITG). In addition, compared with the CSVD-m group, the CSVD-s group demonstrated significantly decreased coupling in the bilateral caudate nuclei, right putamen and inferior frontal gyrus (IFG) and increased coupling in the left middle frontal gyrus and medial superior frontal gyrus. Notably, the ALFF/VBM decoupling values in the caudate, IFG and ITG not only showed significant correlations with attention and executive functions in CSVD patients but also prominently distinguished CSVD-s patients from CSVD-m patients and healthy controls in receiver operating characteristic curve research. Our discoveries demonstrated that decreased ALFF/VBM coupling in the basal ganglia and increased coupling in the frontotemporal lobes were connected with more severe burden and worse cognitive decline in CSVD patients. ALFF/VBM coupling might serve as a novel effective neuroimaging biomarker of CSVD burden and provide new insights into the pathophysiological mechanisms of the clinical development of CSVD.

Brain structure-function coupling associated with cognitive impairment in cerebral small vessel disease.

Cerebral small vessel disease (CSVD) is a common chronic and progressive disease that can lead to mental and cognitive impairment. Damage to brain structure and function may play an important role in the neuropsychiatric disorders of patients with CSVD. Increasing evidence suggests that functional changes are accompanied by structural changes in corresponding brain regions. Thus, normal structure-function coupling is essential for optimal brain performance, and disrupted structure-function coupling can be found in many neurological and psychiatric disorders. To date, most studies on patients with CSVD have focused on separate structures or functions, including reductions in white matter volume and blood flow, which lead to cognitive dysfunction. However, there are few studies on brain structure-function coupling in patients with CSVD. In recent years, with the rapid development of multilevel (voxel-wise, neurovascular, regional level, and network level) brain structure-functional coupling analysis methods based on multimodal magnetic resonance imaging (MRI), new evidence has been provided to reveal the correlation between brain function and structural abnormalities and cognitive impairment. Therefore, studying brain structure-function coupling has a potential significance in the exploration and elucidation of the neurobiological mechanism of cognitive impairment in patients with CSVD. This article mainly describes the currently popular brain structure-function coupling analysis technology based on multimodal MRI and the important research progress of these coupling technologies on CSVD and cognitive impairment to provide a perspective for the study of the pathogenesis and early diagnosis of CSVD.

Voxel-based morphometry reveals the correlation between gray matter volume and serum P-tau-181 in type 2 diabetes mellitus patients with different HbA1c levels.

Introduction: Emerging evidence suggested widespread decreased gray matter volume (GMV) and tau hyperphosphorylation were associated with type 2 diabetes mellitus (T2DM). Insulin resistance is one of the mechanisms of neuron degeneration in T2DM; it can decrease the activity of protein kinase B and increase the activity of glycogen synthesis kinase-3ß, thus promoting the hyperphosphorylation of tau protein and finally leading to neuronal degeneration. However, the association between GMV and serum tau protein phosphorylated at threonine 181 (P-tau-181) in T2DM patients lacks neuroimaging evidence. We aimed to investigate the difference in brain GMV between T2DM patients with different glycated hemoglobin A1c (HbA1c) levels and healthy control (HC) subjects and the correlation between serum P-tau-181 and GMV in T2DM patients. Methods: Clinical parameters, biochemical indicators, and MRI data were collected for 41 T2DM patients with high glycosylated hemoglobin level (HGL), 17 T2DM patients with normal glycosylated hemoglobin level (NGL), and 42 HC subjects. Voxel-based morphometry (VBM) method was applied to investigate GMV differences among groups, and multiple regression analysis was used to examine the correlation between serum P-tau-181 and GMV. Results: Compared with HC subjects, the T2DM patients with HGL or NGL all showed significantly decreased GMV. Briefly, the GMV decreased in T2DM patients with HGL was mainly in the bilateral parahippocampal gyrus (PHG), right middle temporal gyrus (MTG), temporal pole (TPOmid), hippocampus (HIP), and left lingual gyrus. The GMV reduction in T2DM patients with NGL was in the right superior temporal gyrus (STG), and there was no significant difference in GMV between the two diabetic groups. The GMV values of bilateral PHG, right MTG, TPOmid, HIP, and STG can significantly (p < 0.0001) distinguish T2DM patients from HC subjects in ROC curve analysis. In addition, we found that serum P-tau-181 levels were positively correlated with GMV in the right superior and middle occipital gyrus and cuneus, and negatively correlated with GMV in the right inferior temporal gyrus in T2DM patients. Conclusion: Our study shows that GMV atrophy can be used as a potential biological indicator of T2DM and also emphasizes the important role of P-tau-181 in diabetic brain injury, providing new insights into the neuropathological mechanism of diabetic encephalopathy.

Diagnosis of cervical lymph node metastasis with thyroid carcinoma by deep learning application to CT images.

Introduction: The incidence of thyroid diseases has increased in recent years, and cervical lymph node metastasis (LNM) is considered an important risk factor for locoregional recurrence. This study aims to develop a deep learning-based computer-aided diagnosis (CAD) method to diagnose cervical LNM with thyroid carcinoma on computed tomography (CT) images. Methods: A new deep learning framework guided by the analysis of CT data for automated detection and classification of LNs on CT images is proposed. The presented CAD system consists of two stages. First, an improved region-based detection network is designed to learn pyramidal features for detecting small nodes at different feature scales. The region proposals are constrained by the prior knowledge of the size and shape distributions of real nodes. Then, a residual network with an attention module is proposed to perform the classification of LNs. The attention module helps to classify LNs in the fine-grained domain, improving the whole classification network performance. Results: A total of 574 axial CT images (including 676 lymph nodes: 103 benign and 573 malignant lymph nodes) were retrieved from 196 patients who underwent CT for surgical planning. For detection, the data set was randomly subdivided into a training set (70%) and a testing set (30%), where each CT image was expanded to 20 images by rotation, mirror image, changing brightness, and Gaussian noise. The extended data set included 11,480 CT images. The proposed detection method outperformed three other detection architectures (average precision of 80.3%). For classification, ROI of lymph node metastasis labeled by radiologists were used to train the classification network. The 676 lymph nodes were randomly divided into 70% of the training set (73 benign and 401 malignant lymph nodes) and 30% of the test set (30 benign and 172 malignant lymph nodes). The classification method showed superior performance over other state-of-the-art methods with an accuracy of 96%, true positive and negative rates of 98.8 and 80%, respectively. It outperformed radiologists with an area under the curve of 0.894. Discussion: The extensive experiments verify the high efficiency of the proposed method. It is considered instrumental in a clinical setting to diagnose cervical LNM with thyroid carcinoma using preoperative CT images. The future research can consider adding radiologists' experience and domain knowledge into the deep-learning based CAD method to make it more clinically significant. Conclusion: The extensive experiments verify the high efficiency of the proposed method. It is considered instrumental in a clinical setting to diagnose cervical LNM with thyroid carcinoma using preoperative CT images.

Characterization of white matter microstructural abnormalities associated with cognitive dysfunction in cerebral small vessel disease with cerebral microbleeds.

BACKGROUND: Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore white matter (WM) microstructural alterations. Cerebral small vessel disease (CSVD) may be accompanied by extensive WM microstructural deterioration, while cerebral microbleeds (CMBs) are an important factor affecting CSVD. METHODS: Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups. RESULTS: Compared with the CSVD-n and control groups, the CSVD-c group showed a significant FA decrease and AD, RD and MD increases mainly in the cognitive and sensorimotor-related WM tracts. There was no significant difference in any diffusion metric between the CSVD-n and control groups. Furthermore, the widespread regional diffusion alterations among groups were significantly correlated with cognitive parameters in both the CSVD-c and CSVD-n groups. Notably, we applied the multiple kernel learning technique in multivariate pattern analysis to combine multiregion and multiparameter diffusion features, yielding an average accuracy >77 % for three binary classifications, which showed a considerable improvement over the single modality approach. LIMITATIONS: We only grouped the study according to the presence or absence of CMBs. CONCLUSIONS: CSVD patients with CMBs have extensive WM microstructural deterioration. Combining DTI-derived diffusivity and anisotropy metrics can provide complementary information for assessing WM alterations associated with cognitive dysfunction and serve as a potential discriminative pattern to detect CSVD at the individual level.

Altered Intrinsic Brain Activity Related to Neurologic and Motor Dysfunction in Diabetic Peripheral Neuropathy Patients.

CONTEXT: Brain functional alterations in type 2 diabetes with diabetic peripheral neuropathy (DPN) related to motor dysfunction remain largely unknown. OBJECTIVE: We aimed to explore intrinsic resting brain activity in DPN. METHODS: A total of 28 patients with DPN, 43 patients with diabetes and without DPN (NDPN), and 32 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging. We calculated the amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo). One-way analysis of covariance was applied to evaluate the above indicators among the 3 groups, and the mean ALFF/fALFF/ReHo values of altered brain regions were then correlated with clinical features of patients. RESULTS: Compared with the NDPN group, the DPN group showed significantly decreased ALFF values in the right orbital superior frontal gyrus (ORBsup) and medial superior frontal gyrus (SFGmed), and increased ALFF values in the left inferior temporal gyrus (ITG) and decreased fALFF values in the right SFGmed. Compared with HCs, the NDPN group showed increased ALFF values in the right ORBsup, middle frontal gyrus, and left orbital middle frontal gyrus, and decreased fALFF values in the right middle temporal gyrus. Notably, the mean ALFF values of the right ORBsup were significantly negatively correlated with Toronto Clinical Scoring System scores and gait speed in diabetics. The mean ALFF/fALFF values of right SFGmed and the mean ALFF values of left ITG and right ORBsup were significantly differentiated between DPN and patients witht NDPN in receiver operating characteristic curve analysis. CONCLUSION: Patients with DPN have abnormal brain activity in sensorimotor and cognitive brain areas, which may implicate the underlying neurophysiological mechanisms in intrinsic brain activity.

The value of gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase for predicting post-hepatectomy liver failure in HCC patients.

OBJECTIVES: To determine the value of gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). METHODS: Patients with HCC who underwent gadobenate dimeglumine-enhanced hepatobiliary magnetic resonance imaging prior to hepatectomy were collected in two centers. The relative enhancement ratio of the biliary system (REB) and the liver to muscle ratio (LMR) were measured at the hepatobiliary phase. Potential risk factors for PHLF were analyzed by logistic regression. The capacity of the REB and LMR to predict PHLF was analyzed via receiver operating characteristic curve. RESULTS: Of the 221 patients, post-hepatectomy liver failure occurred in 60 patients (27.1%). The REB was an independent risk factor for PHLF (odds ratio [OR] = 0.127 [0.047-0.348], p < 0.001). Although the LMR tended to be associated with PHLF (p = 0.063), it was not an independent risk factor in the multivariable analysis (OR = 0.624 [0.023-16.709], p = 0.779). Moreover, the area under the receiver operating characteristic curve of the REB and LMR was 0.87 and 0.60. The most appropriate cutoff value for the REB was 2.21. The HCC patients with the REB ≤ 2.21 had a higher incidence of post-hepatectomy liver failure than those with the REB > 2.21 (60.0% versus 8.5%, p < 0.001). CONCLUSIONS: Gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase was valuable in predicting post-hepatectomy liver failure in HCC patients. KEY POINTS: • The relative enhancement ratio of the biliary system (REB) was an independent risk factor for post-hepatectomy liver failure in HCC patients. • HCC patients with the REB ≤ 2.21 had significantly higher incidence of post-hepatectomy liver failure than those with the REB > 2.21 (60.0% versus 8.5%).

Disrupted topological organization of resting-state functional brain networks in cerebral small vessel disease.

We aimed to investigate alterations in functional brain networks and assess the relationship between functional impairment and topological network changes in cerebral small vessel disease (CSVD) patients with and without cerebral microbleeds (CMBs). We constructed individual whole-brain, region of interest (ROI) level functional connectivity (FC) networks for 24 CSVD patients with CMBs (CSVD-c), 42 CSVD patients without CMBs (CSVD-n), and 36 healthy controls (HCs). Then, we used graph theory analysis to investigate the global and nodal topological disruptions between groups and relate network topological alterations to clinical parameters. We found that both the CSVD and control groups showed efficient small-world organization in FC networks. However, compared to CSVD-n patients and controls, CSVD-c patients exhibited a significantly decreased clustering coefficient, global efficiency, and local efficiency and an increased shortest path length, indicating a disrupted balance between local specialization and global integration in FC networks. Although both the CSVD and control groups showed highly similar hub distributions, the CSVD-c group exhibited significantly altered nodal betweenness centrality (BC), mainly distributed in the default mode network (DMN), attention, and visual functional areas. There were almost no global or regional alterations between CSVD-n patients and controls. Furthermore, the altered nodal BC of the right anterior/posterior cingulate gyrus and left cuneus were significantly correlated with cognitive parameters in CSVD patients. These results suggest that CSVD patients with and without CMBs had segregated disruptions in the topological organization of the intrinsic functional brain network. This study advances our current understanding of the pathophysiological mechanisms underlying CSVD.

White matter changes, duration of hypertension, and age are associated with cerebral microbleeds in patients with different stages of hypertension.

BACKGROUND: We aimed to investigate risk factors for the presence and number of cerebral microbleeds (CMBs) in patients with different stages of hypertension stages, with an emphasis on the relationship between white matter changes (WMCs) and CMBs. METHODS: Since 2016, participants aged 40 years or more have been evaluated for the presence of CMBs using enhanced 3D multiecho GE T2*-weighted angiography (ESWAN) sequences. The Mann-Whitney U test and Pearson χ2 test were used to compare the clinical characteristics between the CMB and no-CMB patient groups. Furthermore, we used Spearman's rank correlation analysis to examine the associations between the degree of CMB severity and other important factors. RESULTS: CMBs were detected in 110 (36.7%) of 300 participants. Among patients with stage 2 hypertension, the majority also had CMBs (61.8%, 68/110). CMBs were positively correlated with age, hypertension stage, duration of hypertension, WMCs, and silent cerebral infarction. Patients with grade 3 WMCs were significantly more likely to have CMBs than those without WMCs; this association was true for both patients with stage 1 and those with stage 2 hypertension. In patients with stage 1 or stage 2 hypertension lasting longer than 20 years, the majority had CMBs (69.0%, 29/42; 69.1%, 47/68). The results of binary logistic regression indicated that a more severe hypertension stage, longer duration of hypertension, aging, having silent cerebral infarction and higher values of WMC increase the likelihood of the occurrence of CMBs. CONCLUSIONS: CMBs detected in hypertensive patients were more likely to occur in deep structures, and the grade of WMCs and duration of hypertension were more closely associated with the CMB degree than with age.

Altered Spontaneous Brain Activity Related to Neurologic Dysfunction in Patients With Cerebral Small Vessel Disease.

Cerebral small vessel disease (CSVD) encompasses several diseases affecting the small arteries, arterioles, venules, and capillaries of the brain and refers to several pathological processes and etiologies. Neuroimaging is considered the gold standard for detecting CSVD, which can present diverse features on MRI. Cerebral microbleeds (CMBs) in CSVD have been demonstrated to play a synergistic role in both cerebrovascular and neurodegenerative pathology. Considering previous studies on brain structural abnormalities in CSVD, in the present study, we aimed to explore altered spontaneous brain activity among CSVD patients using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) methods based on resting-state functional MRI. In this study, we recruited 24 CSVD patients with CMBs (CSVD-c), 42 CSVD patients without CMBs (CSVD-n) and 36 healthy controls from outpatient clinics in Shandong Provincial Hospital affiliated to Shandong First Medical University between September 2018 and June 2019. All subjects underwent 3-T MRI, including blood oxygen level-dependent (BOLD) and susceptibility-weighted imaging (SWI). Anatomic structures were segmented, ALFF/fALFF values were calculated, and ReHo maps were generated. Further statistical analysis was applied to study the difference in ALFF/fALFF/ReHo among the three groups and the association between ALFF/fALFF/ReHo changes in different brain regions and clinical characteristics. Twenty-four CSVD-c patients (age: 67.54 ± 6.00 years, 10 females), 42 CSVD-n patients (age: 66.33 ± 5.25 years, 22 females) and 36 healthy subjects (age: 64.14 ± 8.57 years, 19 females) were evaluated. Compared with controls, the CSVD-c group showed significantly increased ALFF values in the right insula, putamen and left precuneus; decreased fALFF values in the right precentral gyrus and postcentral gyrus; and increased ReHo values in the left precuneus, fusiform gyrus, right supplementary motor area (SMA), and superior frontal gyrus. Notably, the mean ALFF values of the right insula and putamen were not only significantly related to all clinical parameters but also demonstrated the best performance in Receiver Operating Characteristic (ROC) curve analysis. These findings reveal CSVD-c patients have dysfunctions in the default mode network, sensorimotor network and frontoparietal network, which may implicate the underlying neurophysiological mechanisms of intrinsic brain activity. The correlation between altered spontaneous neuronal activity and clinical parameters provides early useful diagnostic biomarkers for CSVD.

Coronary artery fistulas detected with coronary CT angiography: a pictorial review of 73 cases.

Coronary artery fistulas (CAFs) are abnormal connections of the coronary arteries that bypass the myocardial capillary bed and terminate into chambers of the heart or major blood vessels. CAFs are rare, and most of them are congenital. Because CAFs can be asymptomatic and detected incidentally, the true incidence is difficult to evaluate. CAFs usually have various and complicated image features, and the clinical symptoms mainly depend on the size, origin and drainage site of the fistulas. Thus, accurate imaging assessment of these characteristics is crucial for therapeutic planning and post-operative evaluation. Due to the high temporal and spatial resolution, coronary CT angiography has recently become more widely used in cardiovascular disease diagnosis, and more asymptomatic CAFs are accidentally found. Furthermore, with multiplanar reconstruction images, some complicated and subtle structures can be displayed more accurately. In this article, we reviewed the imaging features of CAFs on coronary CT angiography, mainly focusing on the pre- and post-operative anatomy displaying of these abnormalities.

Rhabdoid Meningioma Arising Concurrent in Pulmonary and Intracranial with a Rare Malignant Clinical Progression: Case Report and Literature Review.

BACKGROUND: Rhabdoid meningioma (RM) is an unusual variant of meningioma, classified as World Health Organization grade III. Although its recurrence is common, extracranial metastasis is rare and usually misdiagnosed. The transfer mechanism and pathway are ambiguous; once the metastasis occurs, the prognosis is poor, and there is no effective management. The present case is the first report of concurrent intracranial and pulmonary RM with rapid and widespread metastasis. We hope this report can serve as a helpful reference for clinicians and radiologists. CASE DESCRIPTION: A 39-year-old woman presented to our hospital complaining of headache and memory disturbances. Magnetic resonance imaging (MRI) of the brain revealed a well-defined, inhomogeneous signal tumor with intense enhancement and severe peritumoral edema. Postoperatively, RM (grade III) was confirmed by histopathology. A chest CT performed 2 weeks later revealed an isolated lung mass, which was confirmed as RM on subsequent surgery. Three months after the first radiotherapy, the cancer had progressed uncommonly rapidly with widespread metastasis to the cerebellum, lung, kidney, and thigh. Gamma knife radiosurgery, chemotherapy, and molecular-targeted therapy were performed; however, the patient's condition continued to worsen, and she died 1 year after the initial operation. CONCLUSIONS: Intracranial RM is a relatively rare tumor with the potential for wide intracranial and extracranial transfer. Cystic components and necrosis can be seen in this type of meningioma. Metastatic meningioma should be kept in mind when dealing with isolated lung lesions. This case report may serve as a helpful reference for clinicians and radiologists.