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Objectives: To evaluate the diagnostic performance of high-resolution magnetic resonance-vessel wall imaging (HRMR-VWI) in differentiating moyamoya disease (MMD) from atherosclerosis-associated moyamoya vasculopathy (AS-MMV) and investigate an accurate approach for the differential diagnosis. Methods: Adult patients who were diagnosed as MMD or AS-MMV and underwent HRMR-VWI were retrospectively included. The three vessel wall features (outer diameter (OD), remodeling index (RI), and pattern of vessel wall thickening) of middle cerebral artery (MCA) in identifying MMD from AS-MMV were assessed and compared. Furthermore, subgroup analysis stratified by degree of luminal stenosis was performed and the cutoff values of different vessel wall features in differentiating MMD from AS-MMV were also calculated. Results: A total of 265 patients (160 cases of MMD and 105 AS-MMV) were included. Patients with AS-MMV had greater OD and RI and were more likely to exhibit eccentric thickening of vessel wall compared to those with MMD (all p < 0.001). The ROC analysis showed that the AUC value of OD was greater than that of RI (0.912 vs. 0.889, p = 0.007) in differentiating MMD from AS-MMV, and their corresponding cutoff values were 1.77 mm and 0.27, respectively. And the AUC value of pattern of vessel wall thickening was 0.786 in non-occluded patients. With the increase of lumen stenosis, the discrimination power of the three indicators enhanced correspondingly. Conclusions: HRMR-VWI is valuable in distinguishing MMD from AS-MMV. The OD of MCA has better diagnostic performance in differentiating AS-MMV from MMD compared to RI and pattern of vessel wall thickening. Clinical relevance statement: The outer diameter of the involved artery proved to be both accurate and convenient in distinguishing atherosclerosis-associated moyamoya vasculopathy from moyamoya disease and may provide a quantitative reference for clinical diagnosis. Key Points: High-resolution magnetic resonance-vessel wall imaging is valuable in distinguishing atherosclerosis-associated moyamoya vasculopathy from moyamoya disease. Compared to remodeling index and pattern of vessel wall thickening, outer diameter is more accurate in differentiating atherosclerosis-associated moyamoya vasculopathy from moyamoya disease. With the increase of lumen stenosis, the discrimination power of outer diameter, remodeling index, and pattern of vessel wall thickening enhanced correspondingly. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to determine the association between vessel wall enhancement and progression of arterial stenosis and clinical outcomes in patients with moyamoya (MMD) using high-resolution magnetic resonance (HRMR) vessel wall imaging. Methods: Consecutive participants diagnosed with MMD were prospectively recruited and underwent HRMR at baseline and during follow-up, which had an interval period of ≥ 6 months and were clinically followed up for ≤ 24 months to record the occurrence of ischemic stroke. The relationship between vessel wall enhancement and arterial stenosis progression and stroke occurrence was evaluated. Results: HRMR vessel wall imaging was used to identify 309 stenotic lesions at the internal carotid artery (ICA) in 170 participants (mean age: 37.7 ± 11.3 years old, male: 44.1%). The baseline presence (adjusted odds ratio [aOR] = 3.57, 95% CI = 1.97–6.44, p < 0.001) and progression (aOR = 2.96, 95% CI = 1.29–6.80, p = 0.010) of vessel wall enhancement and middle cerebral artery (MCA) involvement (aOR = 4.98, 95% CI = 1.50–16.52, p = 0.009) were significantly associated with rapid progression of arterial stenosis. Furthermore, vessel wall enhancement (adjusted HR = 3.59, 95% CI = 1.33–9.70, p = 0.011) and rapid progression of arterial stenosis (adjusted HR = 4.52, 95% CI = 1.48–13.81, p = 0.008) were correlated with future stroke occurrence. Conclusion: The baseline presence of vessel wall enhancement was associated with rapid progression of arterial stenosis and increased risk for stroke in MMD patients. Our findings suggest that vessel wall enhancement may serve as a predictor of disease progression and poor outcomes in MMD. Key Points: • The baseline presence of vessel wall enhancement was significantly associated with the rapid progression of arterial stenosis. • The baseline presence of vessel wall enhancement and rapid progression of arterial stenosis were both correlated with increased risk for future occurrence of stroke. • Our findings suggest that vessel wall enhancement may serve as a predictor of rapid progression of arterial stenosis and poor outcomes in MMD patients. [ABSTRACT FROM AUTHOR]

Objective: To retrospectively analyze CT and MR imaging features of the brain in patients with hydrogen sulfide poisoning based on clinical symptom grading and to investigate their correlations with clinical symptoms and patients' prognosis.Methods: A retrospective analysis was performed of CT and MR imaging data of the brain in 40 patients with hydrogen sulfide poisoning in our hospital. There were four main imaging manifestations. Patients were clinically graded according to the central nervous system symptom scores of the Poisoning Severity Score (PSS) and staged according to the gas inhalation time segment. Based on clinical symptom grading, the frequencies and proportions of four imaging signs that occurred in each group were counted, their development trends were analyzed, and the correlations of imaging features with clinical grading and prognosis were calculated.Results: Forty patients were divided into minor, moderate and severe clinical grades and classified into four stages. In patients with minor and moderate clinical grading, only one patient suffered from generalized brain edema at stage 1, with a good prognosis. Patients with severe clinical grade showed the highest probability of presenting with the four imaging signs. The imaging signs were correlated with the severe clinical grade and a poor prognosis (P = 0.000, R = 0.828; P = 0.000, R = 0.858).Conclusion: In patients with the severe clinical grade, generalized brain edema and symmetrical hypodensity/abnormal signals in the bilateral basal ganglia and around the lateral ventricles were the main findings and were shown to persist. The presence of imaging signs can assist in the clinically effective evaluation of clinical symptom grade. [ABSTRACT FROM AUTHOR]

Background and purpose: This study aimed to investigate the enhancement characteristics of vessel wall in patients with moyamoya disease (MMD) using 3D high-resolution magnetic resonance (MR) imaging and their relationship with initial and recurrent intracranial hemorrhage. Methods: Consecutive patients with MMD were retrospectively analyzed and classified as intracranial hemorrhagic and non-hemorrhagic groups according to the CT or MR images. The clinical features and vessel wall characteristics were compared between the two groups. Logistic regression was performed to relate the vessel wall characteristics to the initial hemorrhage in MMD patients. Patients in hemorrhagic group were followed up after surgery to evaluate the relationship between vessel wall characteristics and recurrent hemorrhage. Results: A total of 507 MMD patients including 79 hemorrhagic and 428 non-hemorrhagic MMD patients were recruited in the study. We found that hemorrhagic group had more patients with vessel wall enhancements (40.5% vs. 25.7%, p = 0.009) and more eccentric enhanced lesions (17.7% vs. 6.5%, p = 0.001) compared to those in non-hemorrhage group and vessel wall enhancements were independently associated with ipsilateral initial hemorrhage after adjusted for clinical factors (OR = 1.99, CI 1.20–3.28, p = 0.007). Furthermore, three recurrent intracranial hemorrhagic episodes in the present study were all observed in MMD patients with vessel wall enhancement during the long-term follow-up after surgery. Conclusions: Wall enhancement of intracranial vessels was significantly associated with intracranial hemorrhage in MMD patients. Our findings suggest that vessel wall enhancement may serve as a marker of intracranial hemorrhage. [ABSTRACT FROM AUTHOR]

Magnetic nanoparticles(NPs) are characterized by a rich variety of properties. Because of their excellent physical and chemical properties, they have come to the fore in biomedicine and other fields. The magnetic NPs were extensively studied in magnetic separation of cells, targeted drug delivery, tumor hyperthermia, chemo-photothermal therapy, magnetic resonance imaging (MRI) and other biomedical fields. Magnetic NPs are increasingly used in magnetic resonance imaging (MRI) based on their inherent magnetic targeting, superparamagnetic enzyme-like catalytic properties and nanoscale size. Poly(lactic-co-glycolic acid) (PLGA) is a promising biodegradable material approved by FDA and EU for drug delivery. Currently, PLGA-based magnetic nano-drug delivery systems have attracted the attention of researchers. Herein, we achieved the effective encapsulation of sized-controlled polyethylene glycol-3,4-dihydroxy benzyl-amine-coated superparamagnetic iron oxide nanoparticles (SPIO NPs) and euphorbiasteroid into PLGA nanospheres via a modified multiple emulsion solvent evaporation method (W 1 /O 2 /W 2). NPs with narrow size distribution and acceptable magnetic properties were developed that are very useful for applications involving cancer therapy and MRI. Furthermore, SPIO-PLGA NPs enhanced the MRI T 2 relaxation properties of tumor sites.The prepared SPIO NPs and magnetic PLGA nanospheres can be promising magnetic drug delivery systems for tumor theranostics. This study has successfully constructed a tumor-targeting and magnetic-targeting smart nanocarrier with enhanced permeability and retention, multimodal anti-cancer therapeutics and biodegradability, which could be a hopeful candidate for anti-tumor therapy in the future. [Display omitted] • For the first time, the lipid-soluble drug EFL 1 and the water-soluble magnetic nanomaterials are co-loaded into the PLGA. • Based on the research idea of "theranostics" realize targeted treatment under the dual guidance of magnetism and biology. [ABSTRACT FROM AUTHOR]

• Propose a new end-to-end deep model called C2-Net that effectively exploits multi-view information for mammogram soft-tissue lesion detection. • Propose three specific modules to compare ipsilateral features, contrast bilateral features and fuse multi-view features respectively. • Experimental results on both the DDSM dataset and a large multi-center in-house dataset shows our model achieves state-of-the-art performance. The architecture of the proposed C2-Net. The model takes the multiview mammogram images as input and produces the enhanced representation for further detection. The major components are Spatial Context Enhancing (SCE) module, Multi-scale Kernel Pooling (MKP) module and Logic Guided Fusion (LGF) module. SCE module learns to compare corresponding regions of cross-view mammogram images, while MKP module tolerates the geometric deformation for robust contrast of asymmetry. Furthermore, LGF module distills the enhanced representation by fusing multiview features. [Display omitted] Detecting breast soft-tissue lesions including masses, structural distortions and asymmetries is of great importance due to the high risk leading to breast cancer. Most existing deep learning based approaches detect lesions with only unilateral images. However, multi-view mammogram images provide highly related and complementary information which helps to make the clinical analysis more comprehensive and reliable. In this paper, we propose a multi-view network for breast soft-tissue lesion detection called C 2 -Net (Compare and Contrast, C 2) that fuses information across different views. The proposed model contains the following three modules. The spatial context enhancing (SCE) module compares ipsilateral views and extracts complementary features to model lesion inherent 3D structure. The multi-scale kernel pooling (MKP) module contrasts contralateral views with added misalignment tolerance. Finally, the logic guided fusion (LGF) module fuses multi-view features by enhancing logic modeling capacity. Experimental results on both the public DDSM dataset and the in-house multi-center dataset demonstrate that the proposed method has achieved state-of-the-art performance. [ABSTRACT FROM AUTHOR]