磁共振弥散成像
医学
部分各向异性
脑积水
接收机工作特性
白质
外科
核医学
放射科
磁共振成像
内科学
作者
Cailei Zhao,Yiping Ouyang,Gong‐Wei Zhang,Dongdong Zang,Jun Xia,Guohua Liang,Miaoting Ye,Wang Jingsheng,Yungen Gan,Yangyang Zhou,Jian Yang,Xianjun Li
标识
DOI:10.1227/neu.0000000000003050
摘要
BACKGROUND AND OBJECTIVES: Assessment of postoperative outcomes on pediatric hydrocephalus is critical for adjusting treatment strategies. The aim of this work was to investigate the ability of MRI metrics to predict postoperative outcomes. METHODS: A total of 55 children with hydrocephalus who underwent MRI and ventriculoperitoneal shunt surgery were prospectively enrolled. MRI was also performed at 6 months postoperatively in 33 of the 55 children. A total of 92 controls matched for age and sex were enrolled and divided into preoperative and postoperative control groups. We calculated the diffusion tensor imaging along the perivascular space (DTI-ALPS) index, Evans index, and diffusion tensor imaging metrics. The ability of various metrics to predict postoperative outcomes was assessed using receiver operating characteristic curve analysis. RESULTS: The DTI-ALPS index was significantly lower in patients with hydrocephalus than in controls. The abnormal DTI-ALPS index trended toward the normal range after surgery. Patients with lower preoperative DTI-ALPS index, lower fractional anisotropy (FA), and higher radial diffusivity in association fibers had less favorable short-term outcomes. Patients with worse long-term outcomes had lower postoperative DTI-ALPS index, higher postoperative Evans index, and lower FA and higher radial diffusivity in association fibers. Predictive performance was better when the DTI-ALPS index and FA in association fibers were used in combination than when either of these metrics was used alone. CONCLUSION: The DTI-ALPS index and FA in association fibers provided complementary information for prognostic assessment after the ventriculoperitoneal shunt surgery on pediatric hydrocephalus. A combination of DTI-ALPS index and FA would improve our ability to predict postoperative outcomes in these patients.
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