Reimer Caroline, Deike Katerina, Graf Markus, Reimer Peter, Wiestler Benedikt, Floca Ralf Omar, Kickingereder Philipp, Schlemmer Heinz-Peter, Wick Wolfgang, Bendszus Martin, Radbruch Alexander
Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany.
Department of Radiology, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany.
PLoS One. 2017 Apr 6;12(4):e0174620. doi: 10.1371/journal.pone.0174620. eCollection 2017.
The purpose of this study was to investigate whether a voxel-wise analysis of apparent diffusion coefficient (ADC) values may differentiate between progressive disease (PD) and pseudoprogression (PsP) in patients with high-grade glioma using the parametric response map, a newly introduced postprocessing tool.
Twenty-eight patients with proven PD and seven patients with PsP were identified in this retrospective feasibility study. For all patients ADC baseline and follow-up maps on four subsequent MRIs were available. ADC maps were coregistered on contrast enhanced T1-weighted follow-up images. Subsequently, enhancement in the follow-up contrast enhanced T1-weighted image was manually delineated and a reference region of interest (ROI) was drawn in the contralateral white matter. Both ROIs were transferred to the ADC images. Relative ADC (rADC) (baseline)/reference ROI values and rADC (follow up)/reference ROI values were calculated for each voxel within the ROI. The corresponding voxels of rADC (follow up) and rADC (baseline) were subtracted and the percentage of all voxels within the ROI that exceeded the threshold of 0.25 was quantified.
rADC voxels showed a decrease of 59.2% (1st quartile (Q1) 36.7; 3rd quartile (Q3) 78.6) above 0.25 in patients with PD and 18.6% (Q1 3.04; Q3 26.5) in patients with PsP (p = 0.005). Receiver operating characteristic curve analysis showed the optimal decreasing rADC cut-off value for identifying PD of > 27.05% (area under the curve 0.844±0.065, sensitivity 0.86, specificity 0.86, p = 0.014).
This feasibility study shows that the assessment of rADC using parametric response maps might be a promising approach to contribute to the differentiation between PD and PsP. Further research in larger patient cohorts is necessary to finally determine its clinical utility.
本研究旨在探讨使用一种新引入的后处理工具——参数反应映射，对高级别胶质瘤患者表观扩散系数（ADC）值进行体素分析，是否能够区分疾病进展（PD）和假性进展（PsP）。
在这项回顾性可行性研究中，确定了28例经证实为PD的患者和7例PsP患者。所有患者均有后续4次MRI检查的ADC基线图和随访图。将ADC图与增强T1加权随访图像进行配准。随后，手动勾勒出随访增强T1加权图像中的强化区域，并在对侧白质中绘制一个感兴趣参考区域（ROI）。将两个ROI都转移到ADC图像上。计算ROI内每个体素的相对ADC（rADC）（基线）/参考ROI值和rADC（随访）/参考ROI值。将rADC（随访）和rADC（基线）的相应体素相减，并对ROI内超过0.25阈值的所有体素的百分比进行量化。
PD患者中，rADC体素在0.25以上下降了59.2%（第一四分位数（Q1）36.7；第三四分位数（Q3）78.6），PsP患者中下降了18.6%（Q1 3.04；Q3 26.5）（p = 0.005）。受试者操作特征曲线分析显示，识别PD的最佳rADC下降临界值>27.05%（曲线下面积0.844±0.065，敏感性0.86，特异性0.86，p = 0.014）。
这项可行性研究表明，使用参数反应映射评估rADC可能是一种有助于区分PD和PsP的有前景方法。需要在更大患者队列中进行进一步研究，以最终确定其临床实用性。
