Clin Transl Radiat Oncol. 2023 Jul 24;42:100666. doi: 10.1016/j.ctro.2023.100666. eCollection 2023 Sep.
We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5 T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort.
Thirty patients with HNSCC who received curative-intent RT at MD Anderson Cancer Center, were included. Baseline and weekly MRI were obtained, and various ADC parameters were extracted from the regions of interest (ROIs). Baseline and weekly ADC parameters were correlated with response during and after RT, and the recurrence using the Mann-Whitney test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) identified the optimal ΔADC threshold associated with different oncologic outcomes.
There was a significant rise in all ADC parameters at different time points of RT compared to baseline for both gross primary disease (GTV-P) and gross nodal disease volumes (GTV-N). The increased ADC values for GTV-P were statistically significant only for primary tumors achieving complete remission (CR) during RT. RPA identified GTV-P ΔADC 5th percentile > 13% at the mid-RT as the most significant parameter associated with primary tumors' CR during RT (p < 0.001). There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. A significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively).
Assessment of ADC kinetics at regular intervals throughout RT seems to be correlated with RT response. Further studies with larger cohorts and multi-institutional data are needed for validation of ΔADC as a model for prediction of response to RT.
作为一项系统性的R-IDEAL生物标志物特征研究工作的一部分，我们旨在利用在1.5T MR直线加速器上放疗（RT）期间每周获取的扩散加权成像（DWI），对目标疾病体积的系列定量表观扩散系数（ADC）变化进行特征描述，并将这些变化与头颈部鳞状细胞癌（HNSCC）患者的肿瘤反应和肿瘤学结局相关联。
纳入30例在MD安德森癌症中心接受根治性放疗的HNSCC患者。获取基线和每周的MRI，并从感兴趣区域（ROI）提取各种ADC参数。使用Mann-Whitney检验将基线和每周的ADC参数与放疗期间及放疗后的反应以及复发情况相关联。使用Wilcoxon符号秩检验比较每周的ADC与基线值。使用Spearman秩相关检验将每个ROI的每周体积变化（Δ体积）与ΔADC相关联。递归划分分析（RPA）确定了与不同肿瘤学结局相关的最佳ΔADC阈值。
与基线相比，对于大体原发性疾病（GTV-P）和大体淋巴结疾病体积（GTV-N），在放疗的不同时间点所有ADC参数均有显著升高。仅对于放疗期间实现完全缓解（CR）的原发性肿瘤，GTV-P的ADC值升高具有统计学意义。RPA确定放疗中期GTV-P ΔADC第5百分位数>13%是与放疗期间原发性肿瘤CR相关的最显著参数（p<0.001）。在整个放疗过程中，GTV-P和GTV-N的残余体积均显著减少。在放疗第3周和第4周时，检测到GTV-P的平均ΔADC与Δ体积之间存在显著负相关（分别为r = -0.39，p = 0.044和r = -0.45，p = 0.019）。
在整个放疗过程中定期评估ADC动力学似乎与放疗反应相关。需要更大队列和多机构数据的进一步研究来验证ΔADC作为预测放疗反应模型的有效性。
