van den Elshout Rik, Herings Siem D A, Mannil Manoj, Gijtenbeek Anja M M, Ter Laan Mark, Smeenk Robert J, Meijer Frederick J A, Scheenen Tom W J, Henssen Dylan J H A
Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands.
Radiologie Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands.
Cancers (Basel). 2023 Oct 14;15(20):4990. doi: 10.3390/cancers15204990.
Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10 mm/s; SD = 0.31 × 10 mm/s) were significantly different compared to TRA (mean = 1.53 × 10 mm/s; SD = 0.28 × 10 mm/s) ( = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10 mm/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.
在胶质母细胞瘤患者中，由于传统磁共振成像序列形态相同，区分与治疗相关的异常（TRA）和肿瘤进展（TP）是一项诊断成像挑战。扩散加权成像（DWI）及其表观扩散系数（ADC）衍生图像已被建议作为解决此问题的诊断工具。本研究的目的是确定不同ADC截止值区分TP和TRA的诊断准确性。总共选择了76例治疗后出现新的对比增强病变的胶质母细胞瘤患者。使用T1加权对比增强扫描对病变进行分割。比较TRA组和TP组分割区域的平均ADC值。通过曲线下面积（AUC）以及截止点得出的敏感性和特异性值比较诊断准确性。尽管TP组的ADC值（平均值 = 1.32×10⁻³mm²/s；标准差 = 0.31×10⁻³mm²/s）与TRA组（平均值 = 1.53×10⁻³mm²/s；标准差 = 0.28×10⁻³mm²/s）相比有显著差异（P = 0.003），但其分布存在相当大的重叠。区分TP和TRA的ADC值的AUC为0.71，在ADC值为1.47×10⁻³mm²/s时，敏感性和特异性分别为65%和70%。因此，这些发现表明，在没有时间演变信息的情况下，在某个时间点，ADC图不应被用于区分TP和TRA。
