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Nijiati Kudulaiti,Tianming Qiu,Junfeng Lu,Huiwei Zhang,Zhengwei Zhang,Yihui Guan,Dongxiao Zhuang,Jinsong Wu 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.6
Objective: To evaluate whether the combination of magnetic resonance spectroscopy (MRS) and 11C-methionine positron emission tomography (11C-MET PET) could increase accurate diagnostic sensitivity for non-enhancing supratentorial gliomas. Materials and Methods: Between February 2012 and December 2017, 109 patients with non-enhanced supratentorial lesions on contrast-enhanced MRI were enrolled. Each patient underwent MRS and 11C-MET PET before treatment. A lesion was considered to be a glioma when either the MRS or 11C-MET PET results reached the diagnostic threshold. The radiological diagnosis was compared with the pathological diagnosis or medical diagnostic criteria. Results: The sensitivity and specificity were 60.0% and 50.0% for MRS and 75.8% and 50.0% for 11C-MET PET, respectively. Upon combining the two modalities, the sensitivity and specificity of the imaging-based diagnosis prior to surgery reached 89.5% and 42.9%, respectively. Statistically significant differences in the sensitivities were observed between the combined and individual approaches (MRS alone, 89.5% vs. 60.0%, p < 0.001; 11C-MET PET alone, 89.5% vs. 75.8%, p = 0.001). However, no significant differences in specificity were observed between the combined and individual modalities. Conclusion: The combination of MRS and 11C-MET PET findings significantly increases accurate diagnostic sensitivity for nonenhancing supratentorial gliomas without significantly lowering the specificity. This finding suggests the potential of the combined MRS and 11C-MET PET approach in clinical applications.
Surface Mesh Generation in Parametric Space Using a Riemannian Surface Definition
Cui Dai,Zhaoxue Wang,Liang Dong,Yiping Chen,Junfeng Qiu 한국유체기계학회 2020 International journal of fluid machinery and syste Vol.13 No.2
In order to solve the problem of generating distortion elements in the mapping from parameter space to real space, and the boundary coincidence of the mesh generated by the software quality, an approach for parametric surface mesh generation based on Riemannian metric, combined with Delaunay triangulation and AFT is proposed. In our algorithm, the boundary curves are discretized based on the proximity and curvature of the curves in the model after derivation the correlation of curve length between parametric space and real space. Background meshes of parametric space were generated by using improved AFT, and could improve the efficient of the algorithm and control element sizing and metric values. When background mesh of parametric space were refined, to counteract mapping distortion, the traditional Delaunay incremental insertion kernel is replaced by inserting the center of triangle circumscribed ellipse, and the algorithm for locating ellipse center and judging whether nodes within ellipse. In this paper, the details of the surface mesh generated by the algorithm are introduced in detail. The algorithm proposed in this paper has the characteristics of reliable algorithm, high mesh generation efficiency and mesh quality. Finally, the reliability of the proposed algorithm is verified by an example of surface mesh generation.