Quantitative Features From CHO PET Distinguish the WHO Grades of Primary Diffuse Glioma

医学 接收机工作特性 胶质瘤 威尔科克森符号秩检验 核医学 胶质母细胞瘤 曲线下面积 放射科 曼惠特尼U检验 内科学 癌症研究
作者
Ziren Kong,Chendan Jiang,Delin Liu,Wenlin Chen,Wenbin Ma,Xin Cheng,Yu Wang
出处
期刊:Clinical Nuclear Medicine [Lippincott Williams & Wilkins]
卷期号:46 (2): 103-110 被引量:12
标识
DOI:10.1097/rlu.0000000000003406
摘要

The aim of this study was to investigate the quantitative 18F-fluoroethylcholine (CHO) PET characteristics for differentiating lower-grade glioma (LGG) from glioblastoma (GBM).Thirty-nine patients who underwent CHO PET with histopathologically confirmed primary diffuse glioma were prospectively enrolled. The 3-dimensional region of interest was semiautomatically defined based on the SUV threshold, and a total of 74 quantitative features, including 13 shape features, 31 SUV-based features, and 30 normalized SUV-based features, were calculated. Wilcoxon rank sum test, receiver operating characteristic curve, and correlation coefficient analyses were applied to select independent representative features, and patient prognosis was stratified by the World Health Organization (WHO) grade and CHO features.A total of 89.2% of the quantitative features were significantly different between LGG and GBM, and the SUV-based features displayed higher area under the receiver operating characteristic curve (AUC) values than the other feature groups. Among the 5 traditional features, the SUVmax and the total lesion CHO uptake were the most distinguishing, with AUCs of 0.880 and 0.860 (0.938 and 0.927 after reclassification of 2 outliers), respectively, both of which could also stratify patient prognosis better than WHO grade. Five alternative features, including 2 shape features and 3 SUV-based features, were considered representative, with AUCs ranging from 0.754 to 0.854.Quantitative features from CHO PET are reliable in determining the WHO grade of primary diffuse gliomas. Our findings suggest that GBM has a larger volume, a more spherical shape, higher choline activity in most interval segments, and a more symmetrical distribution than LGG.
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