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Abstract：
BACKGROUND: Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions.
OBJECTIVE: To develop a 2D-SWE-based predictive model for preoperative identification of HCC.
METHODS: A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms.
RESULTS: In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003).
CONCLUSIONS: 2D-SWE\'s hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.
OBJECTIVE: To develop a 2D-SWE-based predictive model for preoperative identification of HCC.
METHODS: A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms.
RESULTS: In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003).
CONCLUSIONS: 2D-SWE\'s hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.
摘要：
背景：将常规超声特征与2D剪切波弹性成像（2D-SWE）相结合可以潜在地增强术前肝细胞癌（HCC）的预测。
目的：开发一种基于2D-SWE的预测模型，用于肝癌的术前识别。
方法：回顾性分析2021年2月至2023年8月在东方肝胆外科医院接受肝切除和病理评估的884例患者。将患者分为模型组(n=720)和对照组(n=164)。这项研究包括常规超声，2D-SWE,和术前实验室检查。采用多因素logistic回归分析确定肝脏恶性病变的独立预测因素,然后被描绘成列线图。
结果：在建模组分析中，肿瘤及其外周的最大弹性（Emax），血小板计数,肝硬化,和血流是恶性肿瘤的独立危险指标。这些因素产生的曲线下面积为0.77（95％置信区间：0.73-0.81），灵敏度为84％，特异性为61％。该模型在构建和验证队列中均表现出良好的校准，如校准图和Hosmer-Lemeshow检验所示（分别为P=0.683和P=0.658）。此外,在肝脏恶性肿瘤中,肿瘤周边的平均弹性(Emean)是微血管侵犯(MVI)的危险因素(P=0.003).接受抗病毒治疗的患者在血小板计数上有显著差异（P=0.002），肿瘤Emax(P=0.033),肿瘤的Emean（P=0.042），肿瘤周边Emax（P<0.001），和Emean在肿瘤周围（P=0.003）。
结论：2D-SWE的硬度值可作为提高肝脏恶性病变的术前诊断的有价值的指标，与MVI和抗病毒治疗疗效显着相关。
目的：开发一种基于2D-SWE的预测模型，用于肝癌的术前识别。
方法：回顾性分析2021年2月至2023年8月在东方肝胆外科医院接受肝切除和病理评估的884例患者。将患者分为模型组(n=720)和对照组(n=164)。这项研究包括常规超声，2D-SWE,和术前实验室检查。采用多因素logistic回归分析确定肝脏恶性病变的独立预测因素,然后被描绘成列线图。
结果：在建模组分析中，肿瘤及其外周的最大弹性（Emax），血小板计数,肝硬化,和血流是恶性肿瘤的独立危险指标。这些因素产生的曲线下面积为0.77（95％置信区间：0.73-0.81），灵敏度为84％，特异性为61％。该模型在构建和验证队列中均表现出良好的校准，如校准图和Hosmer-Lemeshow检验所示（分别为P=0.683和P=0.658）。此外,在肝脏恶性肿瘤中,肿瘤周边的平均弹性(Emean)是微血管侵犯(MVI)的危险因素(P=0.003).接受抗病毒治疗的患者在血小板计数上有显著差异（P=0.002），肿瘤Emax(P=0.033),肿瘤的Emean（P=0.042），肿瘤周边Emax（P<0.001），和Emean在肿瘤周围（P=0.003）。
结论：2D-SWE的硬度值可作为提高肝脏恶性病变的术前诊断的有价值的指标，与MVI和抗病毒治疗疗效显着相关。
