Grading Astrocytic Tumors by Using Apparent Diffusion Coefficient Parameters: Superiority of a One- versus Two-Parameter Pilot Method
Grading Astrocytic Tumors by Using Apparent Diffusion Coefficient Parameters: Superiority of a One- versus Two-Parameter Pilot Method
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DOI：
10.1148/radiol.2513080899
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发表时间：
2009-06-01
期刊：
影响因子：
19.7
通讯作者：
Yamashita, Yasuyuki
中科院分区：
文献类型：
--
作者：
Murakami, Ryuji;Hirai, Toshinori;Yamashita, Yasuyuki
目的：为了评估最小表观扩散系数（ADC）和ADC差值的效用分级星形细胞肿瘤在磁共振imaging.Materials and Methods：医院的机构审查委员会批准了这项回顾性研究，并放弃知情同意。对50例新诊断的星形细胞肿瘤患者（23例男性患者，27例女性患者;中位年龄53岁）进行了评价。两名对临床信息不知情的观察者通过在实体瘤内手动放置三到五个感兴趣区域（40-60 mm（2））（有或没有造影剂增强成分）独立测量ADC，并计算平均ADC。选择最小和最大ADC，并将它们之间的差值记录为ADC差值。结果：采用Kruskal-Wallis检验和受试者工作特征（ROC）曲线分析，ADC值越小，ROC曲线下面积越大。最小ADC最佳地帮助区分1级和较高级别的肿瘤，其临界值为1.47 x 10（-3）mm（2）/sec，4级和较低级别的肿瘤，其临界值为1.01 x 10（-3）mm（2）/sec（两者均P <0.001）。ADC差值有助于区分2级和3级肿瘤，临界值为0.31 x 10 - 3 mm 2/sec（P <0.001）。当使用上述最小ADC值和ADC差值截止值对肿瘤进行分级时，（双参数法），获得以下阳性预测值：1级肿瘤，73%，（8/11）; 2级肿瘤，100%（5/5）; 3级肿瘤，67%结论：结合最小ADC值和ADC差值（双参数法）有助于星形细胞肿瘤的准确分级。(C)RSNA，2009年
Purpose: To assess the utility of both minimum apparent diffusion coefficients (ADCs) and ADC difference values for grading astrocytic tumors at magnetic resonance imaging.Materials and Methods: The hospital's institutional review board approved this retrospective study and waived informed consent. Fifty patients (23 male patients, 27 female patients; median age, 53 years) with newly diagnosed astrocytic tumors were evaluated. Two observers blinded to clinical information independently measured the ADCs by manually placing three to five regions of interest (40-60 mm(2)) within the solid tumor either with or without contrast material-enhanced components and calculated the average ADC. Minimum and maximum ADCs were selected, and the difference between them was recorded as the ADC difference value. These ADC values were used as the parameters for tumor grading and were compared by using the Kruskal-Wallis test and receiver operating characteristic (ROC) curve analysis.Results: According to ROC analyses for distinguishing tumor grade, minimum ADCs showed the largest areas under the ROC curve. Minimum ADCs optimally helped distinguish grade 1 from higher-grade tumors at a cutoff value of 1.47 x 10(-3) mm(2)/sec and grade 4 from lower-grade tumors at a cutoff value of 1.01 x 10(-3) mm(2)/sec (P < .001 for both). ADC difference values helped distinguish grade 2 from grade 3 tumors at a cutoff value of 0.31 x 10(-3) mm(2)/sec (P < .001). When tumors were graded by using the combined minimum ADC and ADC difference cutoff values mentioned above (the two-parameter method), the following positive predictive values were obtained: grade 1 tumors, 73% (eight of 11); grade 2 tumors, 100% (five of five); grade 3 tumors, 67% (eight of 12); and grade 4 tumors, 91% (20 of 22).Conclusion: Using a combination of minimum ADCs and ADC difference values (the two-parameter method) facilitates the accurate grading of astrocytic tumors. (C) RSNA, 2009