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Introduction: Papillary meningioma is a rare subtype of malignant meningiomas. The aim of this retrospective study was to investigate the clinical, radiological, histopathological features and prognosis for papillary meningioma at our institutions. Materials and methods: Ten patients with clinically, radiologically and histopathologically confirmed papillary meningiomas were treated at our hospitals. The clinical data, imaging characteristics, histopathological features, surgical treatment and postoperative follow-up, were analyzed retrospectively. Results: The patients with a mean age of 36.9 years at the time of their initial operations. The papillary meningiomas were predominantly located in the convexity (n = 6). At their initial operation, six patients underwent gross total resection and four patients underwent subtotal resection. The mean post-operative follow-up period was 42.6 months (range: 12–90 months). Six patients underwent multiple surgical resections. The mean time to first recurrence was 21.5 months. On magnetic resonance imaging scan, marked enhancements and dural tail signs were displayed in all lesions. All lesions showed peritumoral edema. Cysts were seen in four lesions. Bone hyperostosis or destruction was seen in six lesions. Cerebrospinal fluid dissemination was seen in three lesions. Incomplete surgical resection was associated with recurrence. MIB-1 labeling index was associated with progression-free survival for patients (p = 0.0442). Conclusions: Papillary meningioma has a tendency to present in middle-aged patients, and it has specific clinical and histopathological characteristics. MIB-1 labeling index and the extent of resection might predict the recurrence. Cystic formation, peritumoral edema, osseous change and CSF dissemination might be neuroimaging characteristics of papillary meningioma, especially in recurrence papillary meningioma. [ABSTRACT FROM AUTHOR]

Gliomas are the most dominant and lethal type of brain tumors. Growth prediction is significant to quantify tumor aggressiveness, improve therapy planning, and estimate patients' survival time. This is commonly addressed in literature using mathematical models guided by multi-time point scans of multi/single-modal data for the same subject. However, these models are mechanism-based and heavily rely on complicated mathematical formulations of partial differential equations with few parameters that are insufficient to capture different patterns and other characteristics of gliomas. In this paper, we propose a 3D generative adversarial networks (GANs) for glioma growth prediction. Specifically, we stack 2 GANs with conditional initialization of segmented feature maps. Furthermore, we employ Dice loss in our objective function and devised 3D U-Net architecture for better image generation. The proposed method is trained and validated using 3D patch-based strategy on real magnetic resonance images of 9 subjects with 3 time points. Experimental results show that the proposed method can be successfully used for glioma growth prediction with satisfactory performance.

Tumor growth modeling at macroscopic level from multimodal images can help in predicting the future evolution of tumor and the treatment planning. This can be achieved using mathematical models where multi time-point images are available. In this paper, we propose a coupled modified reaction diffusion model that measures tumor invasion and infiltration with biomechanical model to consider tumor mass effect. In addition, our model considers treatment effects from radiotherapy and/or chemotherapy if any. The chemotherapy effect is included via a modified log-kill method to consider tissue heterogeneity while radiotherapy effect is considered using the linear quadratic model. We test the proposed model on both synthetic and 6 real datasets of low grade glioma cases with and without treatments. Experimental results of the proposed model on the clinical magnetic resonance images show that our model can simulate the tumor growth with good accuracy and effectively include the treatment effects.

In order to accurately localize the image coordinates and serial numbers of intraoperative subdural matrix electrodes, a matrix electrode localization algorithm for image processing is proposed in this paper. Firstly, by using point-by-point extended electrode location algorithm, the electrode is expanded point-by-point vertically and horizontally, and the initial coordinates and serial numbers of each electrode are determined. Secondly, the single electrode coordinate region extraction algorithm is used to determine the best coordinates of each electrode, so that the image coordinates and serial numbers of all electrodes are determined point-by-point. The results show that the positioning accuracy of electrode serial number is 100%, and the electrode coordinate positioning error is less than 2 mm. The algorithms in this paper can accurately localize the image coordinates and the serial numbers of a matrix electrode arranged in an arc, which could aid drawing of cortical function mapping, and achieve precise positioning of brain functional areas, so that it can be widely used in neuroscience research and clinical application based on electrocorticogram analysis.

Objective: To investigate the effects of recombinant human bone morphogenic protein-2 (rhBMP-2) and hyaluronic acid (HA) on the invasion and metastasis of rat brain glioma in vivo., Methods: C6 rat glioma cells were transfected with the plasmid vector named pEGFP-N3 which contained an enhanced green fluorescent protein (EGFP) gene. The stable cell clones which expressed EGFP protein were stereotactically injected into the brain parenchyma of SD rats in order to establish a xenotransplanted tumor model. After rhBMP-2 and HA were administered in the xenotransplanted tumor model at different dosages, their effects on glioma invasion and metastasis were observed by pathology, flow cytometry fluoresclnec, and electronmicvoscopy., Results: EGFP-transfected C6 glioma cells gave off green fluorescence in vivo and in vitro. Area with tumor and area without tumor could be easily distinguished by fluorescence microscopy. Even distant micrometastasis and invasion at single-cell level could be detected. 10 microliter rhBMP-2 of the concentration of 5 microgram/ml inhibited C6 tumor invasion, while 10 microliter hyaluronic acid of the concentration of 100 microgram/ml evidently promoted the tumor invasion., Conclusion: EGFP-transfected C6 cells can be transplanted into rats' brain so as to establish an excellent experimental animal model in the research on invasion and metastasis of brain glioma in vivo. RhBMP-2 inhibits tumor invasion, while HA evidently promotes its invasion.