From the Departments of Radiology (J.M.H., Y.Z., L.S.H.).
Departments of Pathology (J.M.E.).
AJNR Am J Neuroradiol. 2020 Mar;41(3):408-415. doi: 10.3174/ajnr.A6486. Epub 2020 Mar 12.
Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects.
We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (), against histologic tumor content (0%-100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor).
Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%-100%) for normalized ( = 0.63, < .001) and standardized ( = 0.66, < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor.
Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology.
灌注 MR 成像测量相对 CBV 可区分高级别胶质瘤中的复发性肿瘤与治疗后放射性效应。目前，相对 CBV 测量需要基于用户定义的参考组织进行归一化。最近提出的一种相对 CBV 标准化方法消除了对用户输入的需求。本研究比较了相对 CBV 标准化与相对 CBV 归一化在量化高级别胶质瘤中新出现的增强病变中相对于治疗后放射性效应的复发性肿瘤负担方面的预测性能。
我们招募了 38 名先前接受过治疗的高级别胶质瘤（世界卫生组织 3 级或 4 级）患者，他们因新出现的增强病变而再次接受手术切除，这些病变考虑为复发性肿瘤或治疗后放射性效应。我们回收了 112 个图像定位活检，并对每个样本的组织学肿瘤含量与治疗后放射性效应进行了量化。我们测量了每个活检的空间匹配的归一化和标准化相对 CBV 指标（平均值、中位数）和分数肿瘤负担。我们比较了相对 CBV 性能以预测肿瘤含量，包括与组织学肿瘤含量（0%-100%）的 Pearson 相关系数（），以及使用二元组织学截止值（≥50%；≥80%肿瘤）预测高-低肿瘤含量的受试者工作特征曲线下面积。
在相对 CBV 指标中，分数肿瘤负担与归一化（ = 0.63，<.001）和标准化（ = 0.66，<.001）值的肿瘤含量（0%-100%）具有最高相关性。使用二元截止值（即，≥50%；≥80%肿瘤），标准化和归一化指标以及相对 CBV 指标的预测准确性相似。中位数相对 CBV 预测≥50%肿瘤的曲线下面积最高（归一化=0.87，标准化=0.86），而分数肿瘤负担预测≥80%肿瘤的曲线下面积最高（归一化=0.77，标准化=0.80）。
相对 CBV 的标准化与相对 CBV 的归一化具有相似的性能，为工作流程优化和共识方法提供了重要步骤。
