目的:探讨磁共振弥散峰度成像(DKI)和常规弥散加权成像(DWI)对不可切除胰腺癌一线化疗疗效的诊断价值。
方法:我们回顾性分析了21例经临床和病理证实接受姑息性化疗的未切除胰腺癌患者。在化疗前后进行包含b值为0、100、700、1400和2100s/mm2的DWI序列的三特斯拉MRI检查。参数包括表观扩散系数(ADC),平均扩散系数(MD),和平均扩散峰度(MK)。通过受试者工作特征(ROC)曲线的曲线下面积(AUC)评估DWI和DKI参数在区分化疗反应中的表现。从首次治疗日期到死亡日期或最近的随访日期计算总生存期(OS)。
结果:有反应组(PR组)的ADC变化和MDE变化明显高于无反应组(非PR组)(ADC变化:0.21±0.05vs.0.11±0.09,P=0.02;MDchange:0.37±0.24vs.0.10±0.12,P=0.002)。比较ADCpre时无统计学意义,ADCpost,MKpre,MKPost,MKchange,MDpre,PR和非PR组之间的MDpost。ROC曲线分析表明,MDchange(AUC=0.898,截止值=0.7143)在预测化疗反应方面优于ADCchange(AUC=0.806,截止值=0.1369)。
结论:在无法切除的胰腺癌中,ADCchange和MDchange显示出了评估化疗反应的强大潜力。MDchange在PR和非PR的分类中显示出比ADC更高的特异性。其他参数,包括ADCpre,ADCpost,MKpre,MKPost,MKchange,MDpre,和MDPost,不适合响应评估。与单独的DWI和DKI模型相比,组合模型SUMchange表现出卓越的性能。需要进一步的实验来评估DWI和DKI参数在预测不可切除的胰腺癌患者预后中的潜力。
OBJECTIVE: To investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer.
METHODS: We retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date.
RESULTS: The ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy.
CONCLUSIONS: The ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.