Department of Diagnostic Radiology, Ajou University School of Medicine, Yeongtong-gu, Suwon, Gyeonggi-do 442-749, Korea.
Radiology. 2010 Sep;256(3):906-15. doi: 10.1148/radiol.10091461. Epub 2010 Jul 15.
To determine whether semiquantitative histogram analysis of the normalized cerebral blood volume (CBV) for an entire contrast material-enhanced lesion could be used to predict the volume fraction of posttreatment high-grade glioma recurrence compared with posttreatment change.
The institutional review board approved this retrospective study. Informed consent was obtained. Thirty-nine patients with pathologically proved predominant tumor recurrence (tumor recurrence group, tumor fraction > or =50% [n = 14]), mixed tumor and posttreatment change (mixed group, tumor fraction > or =20% and <50% [n = 10]), and predominant posttreatment change (treatment change group, tumor fraction <20% [n = 15]) were evaluated. Histogram parameters of normalized CBV-histogram width, peak height position (PHP), and maximum value (MV)-were measured in entire contrast-enhanced lesions and used as discriminative indexes. Ordered logistic regression was used to determine independent factors for predicting the diseases of posttreatment contrast-enhanced lesions. Leave-one-out cross-validation was used to determine diagnostic accuracy.
PHP was an independent predictive factor (P = .003) for differentiating contrast-enhanced lesions in patients with posttreatment gliomas. According to receiver operating characteristic curve analyses, PHP provided sensitivity of 90.2% and specificity of 91.1% for differentiating tumor recurrence from mixed and treatment change groups at an optimum threshold of 1.7 by using leave-one-out cross-validation. MV helped distinguish treatment change group from tumor recurrence and mixed groups at an optimum threshold of 2.6 (sensitivity, 96.5%; specificity, 93.1%).
PHP can be used to predict the volume fraction of posttreatment high-grade glioma recurrence.
确定整个对比增强病变的归一化脑血容量(CBV)半定量直方图分析是否可用于预测高级别胶质瘤治疗后复发的体积分数与治疗后变化相比。
该机构审查委员会批准了这项回顾性研究。获得了知情同意。39 名经病理证实为主要肿瘤复发(肿瘤复发组,肿瘤分数≥50%[n = 14])、肿瘤和治疗后变化混合(混合组,肿瘤分数≥20%且<50%[n = 10])和主要治疗后变化(治疗变化组,肿瘤分数<20%[n = 15])的患者进行了评估。在整个对比增强病变中测量了归一化 CBV-直方图宽度、峰高位置(PHP)和最大值(MV)的直方图参数,并将其用作鉴别指数。有序逻辑回归用于确定预测治疗后对比增强病变疾病的独立因素。采用留一法交叉验证确定诊断准确性。
PHP 是区分治疗后胶质瘤患者对比增强病变的独立预测因子(P =.003)。根据接收器操作特征曲线分析,在使用留一法交叉验证时,PHP 在最佳阈值为 1.7 时,对区分肿瘤复发与混合和治疗变化组具有 90.2%的敏感性和 91.1%的特异性。MV 有助于在最佳阈值为 2.6 时区分治疗变化组与肿瘤复发和混合组(敏感性,96.5%;特异性,93.1%)。
PHP 可用于预测高级别胶质瘤治疗后复发的体积分数。