Yuan Zheng, Niu Xiao-Min, Liu Xue-Mei, Fu Hong-Chao, Xue Ting-Jia, Koo Chi Wan, Okuda Katsuhiro, Yao Feng, Ye Xiao-Dan
Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China.
Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Transl Lung Cancer Res. 2021 Aug;10(8):3671-3681. doi: 10.21037/tlcr-21-610.
The intravoxel incoherent motion (IVIM) method of magnetic resonance imaging (MRI) analysis can provide information regarding many physiological and pathological processes. This study aimed to investigate whether IVIM-derived parameters and the apparent diffusion coefficient (ADC) can act as imaging biomarkers for predicting non-small cell lung cancer (NSCLC) response to anti-tumor therapy and compare their performances.
This prospective study included 45 patients with NSCLC treated with chemotherapy (29 men and 16 women, mean age 57.9±9.7 years). Diffusion-weighted imaging was performed with 13 b-values before and 2-4 weeks after treatment. The IVIM parameter pseudo-diffusion coefficient (D*), perfusion fraction (f), diffusion coefficient (D), and ADC from a mono-exponential model were obtained. Responses 2 months after chemotherapy were assessed. The diagnostic performance was evaluated, and optimal cut-off values were determined by receiver operating characteristic (ROC) curve analysis, and the differences of progression-free survival (PFS) in groups of responders and non-responders were tested by Cox regression and Kaplan-Meier survival analyses.
Of 45 patients, 30 (66.7%) were categorized as responders, and 15 as non-responders. Differences in the diffusion coefficient D and ADC between responders and non-responders were statistically significant (all P<0.05). Conversely, differences in f and D* between responders and non-responders were both not statistically significance (all P>0.05). The ROC analyses showed the change in D value (ΔD) was the best predictor of early response to anti-tumor therapy [area under the ROC curve (AUC), 0.764]. The Cox-regression model showed that all ADC and D parameters were independent predictors of PFS, with a range of reduction in risk from 56.2% to 82.7%, and ΔD criteria responders had the highest reduction (82.7%).
ADC and D derived from IVIM are potentially useful for the prediction of NSCLC treatment response to anti-tumor therapy. Although ΔD is best at predicting response to treatment, ΔADC measurement may simplify manual efforts and reduce the workload.
磁共振成像（MRI）分析中的体素内不相干运动（IVIM）方法能够提供有关多种生理和病理过程的信息。本研究旨在探究IVIM衍生参数和表观扩散系数（ADC）是否可作为预测非小细胞肺癌（NSCLC）抗肿瘤治疗反应的影像生物标志物，并比较它们的性能。
本前瞻性研究纳入了45例接受化疗的NSCLC患者（男性29例，女性16例，平均年龄57.9±9.7岁）。在治疗前及治疗后2 - 4周采用13个b值进行扩散加权成像。获取IVIM参数伪扩散系数（D*）、灌注分数（f）、扩散系数（D）以及单指数模型的ADC。评估化疗2个月后的反应。评估诊断性能，通过受试者操作特征（ROC）曲线分析确定最佳截断值，并通过Cox回归和Kaplan - Meier生存分析检验反应者和无反应者组无进展生存期（PFS）的差异。
45例患者中，30例（66.7%）被归类为反应者，15例为无反应者。反应者和无反应者之间的扩散系数D和ADC差异具有统计学意义（均P<0.05）。相反，反应者和无反应者之间的f和D*差异均无统计学意义（均P>0.05）。ROC分析显示，D值变化（ΔD）是抗肿瘤治疗早期反应的最佳预测指标[ROC曲线下面积（AUC），0.764]。Cox回归模型显示，所有ADC和D参数都是PFS的独立预测指标，风险降低范围为56.2%至82.7%，且ΔD标准反应者的风险降低幅度最大（82.7%）。
IVIM衍生的ADC和D可能有助于预测NSCLC对抗肿瘤治疗的反应。虽然ΔD在预测治疗反应方面最佳，但ΔADC测量可能会简化人工操作并减少工作量。
