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Baseline apparent diffusion coefficients: Validation study of new predictor of survival in patients with unresectable hepatocellular carcinoma following chemoembolization
Journal of X-Ray Science and Technology ( IF 1.7 ) Pub Date : 2021-03-26 , DOI: 10.3233/xst-200827
Lichao Xu 1 , Shiqin Wang 2 , Shengping Wang 3 , Ying Wang 1 , Wentao Li 1 , Guangwu Lin 2 , Zheng Yuan 2, 4
Affiliation  

OBJECTIVES:To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS:Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan–Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and non-responders. RESULTS:The difference is statistically significant in the baseline ADC between the responders and non-responders (P < 0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10–3 mm2/s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. CONCLUSION:An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients.

中文翻译:

基线表观扩散系数:化疗栓塞后不可切除的肝细胞癌患者生存的新预测因子的验证研究

目的:研究基线表观扩散系数(ADC)是否可以预测接受化疗栓塞的肝细胞癌(HCC)患者的生存率。材料与方法:在化疗栓塞前 2 周内对 HCC 患者进行弥散加权 MR 成像。记录最大指标病变的ADC。在第二个化疗栓塞疗程开始后,mRECIST 评估反应。进行受试者工作特征 (ROC) 曲线分析以评估诊断性能并确定最佳临界值。Cox 回归和 Kaplan-Meier 生存分析用于探索响应者和非响应者之间总生存 (OS) 的差异。结果:响应者和非响应者之间的基线 ADC 差异具有统计学意义(P < 0.001)。ROC 分析表明,基线 ADC 值是治疗反应的良好预测指标,ROC 曲线下面积 (AUC) 为 0.744,最佳临界值为 1.22×10–3 mm2/s。Cox 回归模型显示基线 ADC 是 OS 的独立预测因子,风险降低 57.2%。结论:最佳基线 ADC 值是一种功能性成像反应生物标志物,在预测 HCC 患者化疗栓塞后的肿瘤反应和延长生存期方面具有更高的辨别力。Cox 回归模型显示基线 ADC 是 OS 的独立预测因子,风险降低 57.2%。结论:最佳基线 ADC 值是一种功能性成像反应生物标志物,它在预测 HCC 患者化疗栓塞后的肿瘤反应和延长生存期方面具有更高的辨别力。Cox 回归模型显示基线 ADC 是 OS 的独立预测因子,风险降低 57.2%。结论:最佳基线 ADC 值是一种功能性成像反应生物标志物,在预测 HCC 患者化疗栓塞后的肿瘤反应和延长生存期方面具有更高的辨别力。
更新日期:2021-03-30
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