Background To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS). Methods Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic (ROC) curve. Survival curves between model-defined risk groups was compared using Kaplan–Meier method. Results 24(49.0%) patients developed disease recurrence. Multivariate logistic analysis results showed elevated serum CEA level, peritumoral fatty space invasion and positive pathological vascular tumor thrombus were independent factors for disease recurrence. Odds ratios were 10.87 (95%CI, 1.14–103.66), 6.83 (95%CI, 1.08–43.08) and 42.67 (95%CI, 3.66–496.85), respectively. The constructed model showed an area under ROC of 0.912 (95%CI,0.825–0.999). The model-defined high-risk group showed poorer overall survival and recurrence-free survival than the low-risk group (both P < 0.001). Conclusions Preoperative CT appearance of peritumoral fatty space invasion, elevated serum CEA level, and pathological vascular tumor thrombus indicated poor prognosis of HAS patients.

AIM:To assess the diagnostic efficacy in response evaluation of hypopharyngeal carcinoma (HPC) using different CT measurement methods.METHODS AND MATERIALS:One hundred and three patients with locally advanced HPC receiving neoadjuvant chemotherapy (NACT) and radical radiotherapy (RT) were retrospectively enrolled. The long diameter, short diameter and largest axial area of the tumors and the largest metastatic cervical lymph node (LN) were measured before and after NACT, at the end of RT and 1 month after RT. Tumor regression ratios of the sum of the tumor's long diameter and LN's short diameter (LDTSDL), the sum of tumor and LN's short diameter (TTSDL), the sum of tumor and LN's largest axial area (AATML) were calculated. Analysis was conducted for overall survival (OS), metastasis-free survival, regional recurrence-free survival (RRFS), and local recurrence-free survival (LRFS).RESULTS:Note that 35, 28, 23, and 16 patients suffered death, local recurrence, regional recurrence and distant metastasis, respectively. TTSDL-defined effective group demonstrated better LRFS (p = .039) and RRFS (p = .047) after NACT and better OS since the end of RT (p = .037); AATML-defined effective groups demonstrated better OS, LRFS, and RRFS since the end of RT (p = .015, .008, and .005). While LDTSDL-defined groups showed differences in OS and LRFS until 1 month after RT (p = .013 and .014).CONCLUSIONS:The regression rate of TTSDL and AATML can distinguish prognosis at an earlier time and demonstrated better reliability compared with LDTSDL. They were recommended for response evaluation in HPC.

目的 探讨基于胸部增强CT影像组学特征预测免疫治疗用于难治性恶性黑色素瘤肺转移疗效的价值.方法 回顾性分析49例难治性恶性黑色素瘤肺内转移患者,均接受程序性死亡受体(PD-1)单抗免疫治疗,采用实体瘤疗效评价标准(RECIST)1.1评价疗效,并将患者分为进展组(n=17)和未进展组[n= 32,包括稳定组(n=16)及部分缓解组(n=16)].提取免疫治疗前增强CT图像中肺转移病灶信息,以3D-Slicer软件手动逐层勾画整个病灶并进行分割;采用Pyradiomics程序提取病灶形状特征、灰度一阶特征、纹理特征和小波特征,以Pearson相关性分析和递归式特征消除策略进行降维.以支持向量机(SVM)方法建立分类模型,预测病变进展的可能性.绘制受试者工作特征(ROC)曲线,评价模型预测进展组、非进展组的效能.结果 对每个靶病灶提取841个增强CT影像组学特征,最终筛选出3个影像组学纹理特征,分别为wavelet-HHH_glszm_Low Gray Level Zone Emphasis、wavelet-HHL_first order Skewness 和 wavelet-LLL_gldm_Small Dependence High Gray Level Emphasis,用于构建影像组学模型.模型预测训练组病变进展的曲线下面积(AUC)为0.913[(95％CI(0.777,1.000)],测试组为0.860[95％CI(0.643,1.000)];预测训练组病变进展的敏感度、特异度、准确率、阳性预测值和阴性预测值分别为83.3％、95.5％、91.2％、90.9％和91.3％,测试组分别为80.0％、80.0％、80.0％、66.7％和88.9％.结论 基于治疗前胸部增强CT影像组学特征建立的模型对恶性黑色素瘤肺转移免疫治疗疗效具有较好预测价值.