MRI动态对比增强成像及DWI联合应用对进展期食管癌同步放化疗早期疗效评估的价值

Predictive value of DWI-MRI combined with DCE-MRI on the early efficacy of concurrent chemoradiotherapy in locally advanced esophageal carcinoma

    摘要
  • 摘要:
    目的 探讨MRI动态对比增强成像（DCE-MRI）联合磁共振弥散加权成像（DWI-MRI）在进展期食管癌同步放化疗患者早期疗效评价中的应用价值。
    方法 回顾性分析2018年2月至2021年6月于江苏省肿瘤医院确诊的48例进展期食管癌患者放化疗治疗前、治疗第2~3周（治疗中）DWI-MRI和DCE-MRI的影像学及临床资料，其中男性24例、女性24 例，年龄（67.1±7.7）岁。根据实体瘤疗效评价标准（RESIST）（1.1版）将患者分为治疗有效组和无效组。采用配对样本t检验、Wilcoxon秩和检验比较容量转移常数（Ktrans）、速率常数（Kep）、血管外细胞外间隙容积比（Ve）、表观扩散系数（ADC）、Ktrans的差值（ΔKtrans）、Kep的差值（ΔKep）、Ve的差值（ΔVe）、ADC差值（ΔADC）在治疗前、治疗中的差异；采用独立样本t检验、Mann-Whitney U 检验比较Ktrans、Kep、Ve、ADC、ΔKtrans、ΔKep、ΔVe、ΔADC在治疗有效组、无效组之间的差异；计数资料的比较采用χ2检验或Kruskal-Wallis检验；采用单因素Logistic回归分析预测疗效的相关因素；采用多因素Logistic回归分析筛选出独立影响因素并建立疗效的预测模型，利用受试者工作特征（ROC）曲线评估模型的预测效能。
    结果 48例患者中，治疗有效组32例、无效组16例。治疗有效组治疗前Ktrans高于无效组0.42（0.33，0.55） min−1对0.29（0.25，0.42） min−1，差异有统计学意义（Z=−2.909，P=0.007）；治疗有效组治疗前ADC高于无效组（1.42±0.38）×10−3 mm2/s对（1.14±0.21）×10−3 mm2/s）、治疗中ADC高于无效组（2.30±0.43）×10−3 mm2/s对（1.63±0.44）×10−3 mm2/s、ΔADC高于无效组（0.86±0.39）×10−3 mm2/s对（0.45±0.49）×10−3 mm2/s，且差异均有统计学意义（t=−3.244、 −5.013、−3.068，均P<0.05）。单因素Logistic回归分析结果显示，治疗前Ktrans（OR=1.093，95%CI：1.021~1.171）、ΔKtrans（OR=0.968，95%CI：0.939~0.997）、治疗前ADC（OR=18.304，95%CI：1.606~208.659）、治疗中ADC（OR=22.678，95%CI：3.920~131.211）、ΔADC（OR=9.996，95%CI：1.802~55.440）是同步放化疗疗效的影响因素（均P<0.05）；多因素二元Logistic回归分析结果显示，治疗中ADC是影响疗效的独立预测因素（95%CI：1.331~81.220，AUC=0.892，P=0.026）。
    结论 DCE-MRI联合DWI-MRI参数预测模型可对进展期食管癌同步放化疗治疗效果进行早期评价。

     

    Abstract:
    Objective To investigate the potential application of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with diffusion-weighted imaging (DWI) in evaluating response to concurrent chemoradiotherapy (CCRT) in locally advanced esophageal carcinoma (EC).
    Methods The clinical data of 48 patients with locally advanced EC who were treated with CCRT at Jiangsu Cancer Hospital from February 2018 to June 2021 were retrospectively analyzed, including 24 males and 24 females, with an average age of (67.1±7.7) years. DCE-MRI and DWI-MRI were performed before and during CCRT (2–3 weeks). Patients were categorized into two groups, namely, the response group and non-response group, after 3 months of treatment in accordance with the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. The quantitative parameters of DCE-MRI (Ktrans, Kep, and Ve) and the changes in parameters (ΔKtrans, ΔKep, and ΔVe), as well as the quantitative parameter of DWI-MRI (apparent diffusion coefficient (ADC)) and the changes in ADC (ΔADC), were calculated and compared by using the paired sample t-test and Wilcoxon rank sum test before and during CCRT of the two groups, respectively. The independent sample t-test and Mann-Whitney U test were used to evaluate the differences between the response group and non-response group. Moreover, univariate and multivariate Logistic regression analysis were used to analyze the potential prognostic factors. Receiver operating characteristic curve was used to evaluate the efficiency of the prediction model.
    Results A total of 48 patients were divided into two groups: 32 in the response group and 16 in the non-response group. Ktrans before the start of CCRT in the response group was significantly higher than that in the non-response group (0.42(0.33, 0.55) min−1 vs. 0.29(0.25, 0.42) min−1, Z=−2.909, P=0.007), whereas ADC before the start of CCRT ((1.42±0.38)×10−3 mm2/s vs. (1.14±0.21)×10−3 mm2/s), ADC during CCRT ((2.30±0.43)×10−3 mm2/s vs. (1.63±0.44)×10−3 mm2/s), and ΔADC ((0.86±0.39)×10−3 mm2/s vs. (0.45±0.49)×10−3 mm2/s) also showed a remarkable difference between the two groups (t=−3.244, −5.013, −3.068; all P<0.05). Univariate Logistic regression analysis showed that Ktrans before the start of CCRT (OR=1.093, 95%CI: 1.021–1.171), ΔKtrans (OR=0.968, 95%CI: 0.939–0.997), ADC before the start of CCRT (OR=18.304, 95%CI: 1.606–208.659), ADC during CCRT (OR=22.678, 95%CI: 3.920–131.211), and ΔADC (OR=9.996, 95%CI: 1.802–55.440) were the potential prognostic factors for effective early treatment. Multivariable Logistic regression analysis showed that ADC during CCRT could be the best parameter to evaluate treatment performance (95%CI: 1.331–81.220, AUC=0.892, P=0.026).
    Conclusion The combination of DCE-MRI and DWI-MRI can be used in predicting response to CCRT in locally advanced EC.

     

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