Jia Fei, Wu Baolin, Yan Ruifang, Li Lei, Wang Kaiyu, Han Dongming
Department of MR, First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China.
J Magn Reson Imaging. 2020 Dec;52(6):1657-1667. doi: 10.1002/jmri.27189. Epub 2020 May 19.
The outcome of intermediate-stage hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) is greatly heterogeneous. Current means for predicting HCC response to TACE are lacking.
To investigate whether the combination of parameters derived from amide proton transfer (APT) and intravoxel incoherent motion (IVIM) imaging, and morphological characteristics of tumor can establish a better prediction model than the univariant model for HCC response to TACE.
Prospective.
56 patients with intermediate-stage HCC (50 males and six females).
FIELD STRENGTH/SEQUENCES: 3.0T; T -weighted-fast spin echo, 3D liver acquisition with volume flex, single-shot fast spin echo-planar imaging (EPI), spin echo-EPI.
Pretreatment APT signal intensities (SIs), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) for tumor, peritumoral, and normal tissues were measured. Follow-up MRI scanning was performed, and the patients were classified as responders or nonresponders based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria.
The imaging parameters were compared among the three tissues and between the two groups using analysis of variance (ANOVA) or two-sample t-test. The prediction model's variables were derived from univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.
Based on the logistic regression analysis results, we established a prediction model that integrated the APT SI and D values in the tumor tissue and the tumor size. ROC analyses revealed that the model was better able to predict tumor response to TACE (area under the ROC curve = 0.851) than the individual parameters on their own.
A prediction model incorporating pretreatment APT SI, D in the tumor tissue and tumor size may be useful for predicting the response of intermediate-stage HCC to TACE.
1 TECHNICAL EFFICACY: Stage 1 J. MAGN. RESON. IMAGING 2020;52:1657-1667.
经动脉化疗栓塞术(TACE)治疗中期肝细胞癌(HCC)的疗效差异很大。目前缺乏预测HCC对TACE反应的方法。
研究酰胺质子转移(APT)和体素内不相干运动(IVIM)成像得出的参数与肿瘤形态特征的组合,是否能比单变量模型更好地建立预测HCC对TACE反应的模型。
前瞻性研究。
56例中期HCC患者(50例男性,6例女性)。
场强/序列:3.0T;T加权快速自旋回波、容积式肝脏三维采集、单次激发快速自旋回波平面成像(EPI)、自旋回波-EPI。
测量肿瘤、瘤周和正常组织的治疗前APT信号强度(SI)、表观扩散系数(ADC)、真实分子扩散系数(D)、假扩散系数(D*)和灌注分数(f)。进行随访MRI扫描,并根据改良的实体瘤疗效评价标准(mRECIST)将患者分为反应者或无反应者。
使用方差分析(ANOVA)或两样本t检验比较三种组织之间以及两组之间的成像参数。预测模型的变量来自单变量和多变量逻辑回归分析。采用受试者操作特征(ROC)曲线分析来探索预测性能。
基于逻辑回归分析结果,我们建立了一个整合肿瘤组织中APT SI和D值以及肿瘤大小的预测模型。ROC分析显示,该模型比单独的个体参数更能预测肿瘤对TACE的反应(ROC曲线下面积=0.851)。
结合治疗前APT SI、肿瘤组织中的D和肿瘤大小的预测模型可能有助于预测中期HCC对TACE的反应。
1 技术疗效:1级 《磁共振成像杂志》2020年;52:1657 - 1667。