动态增强成像影像组学分析鉴别良恶性腮腺病变的价值研究  

Value of dynamic enhanced imaging radiomics in differentiating benign and malignant parotid gland neoplastic lesions

作　　者：王艳[1] 曲源[1] 陈杰[1] 田慧[1] 尚雨蓉 WANG Yan;QU Yuan;CHEN Jie;TIAN Hui;SHANG Yurong(Department of Radiology and Medical Imaging,People's Hospital of Xinjiang Uygur Autonomous Region,Urumqi,Xinjiang 830001,China;不详)

机构地区：[1]新疆维吾尔自治区人民医院放射影像中心,新疆乌鲁木齐830001 [2]University College London,England WC1E6BT

出　　处：《中华全科医学》2023年第3期463-468,共6页Chinese Journal of General Practice

基　　金：新疆维吾尔自治区自然科学基金项目(2019D01C114)。

摘　　要：目的腮腺肿瘤类型复杂,动态增强扫描定性分析鉴别腮腺肿瘤的良恶性较为困难,本研究利用腮腺动态增强的定量参数图像进行影像组学分析,判断动态增强成像在鉴别腮腺肿瘤良恶性中的价值。方法回顾性分析新疆维吾尔自治区人民医院2019年1月—2022年4月病理证实的51例腮腺占位性病灶磁共振图像,共54个病灶,其中多形性腺瘤12个,Warthin瘤19个,恶性肿瘤8个,其余非肿瘤病变15个。腮腺动态增强图像生成转运常数(K_(trans))、血管外细胞外容积分数(V_(e))、血浆容积分数(V_(p))、回流常数(K_(ep))定量位图,通过FAE软件提取影像学特征,建立鉴别腮腺病变良恶性诊断的影像组学模型,并用AUC、敏感性、特异性、准确度等指标对影像组学模型进行评价,判断腮腺良恶性肿瘤样病变鉴别的效能。同时,将多形性腺瘤、腺淋巴瘤和非肿瘤性病变分别与恶性腮腺瘤进行影像组学比较分析。结果腮腺动态增强定量图像通过特征提取进行影像组学分析,判断腮腺肿块良恶性的AUC、准确度、敏感性、特异度分别为0.612、0.844、0.500、0.875。多形性腺瘤、腺淋巴瘤和非肿瘤性病变分别与恶性腮腺肿瘤对照进行影像组学分析时,AUC、准确度、敏感性、特异性分别为0.736、0.781、0.909、0.714,0.886、0.880、0.933、0.857,0.805、0.781、0.700、0.818。结论利用动态增强功能定量图像进行影像组学分析能够初步判断腮腺肿瘤的良恶性,而在区分不同病理亚型的良性腮腺瘤、非肿瘤性病变与恶性腮腺肿瘤中,影像组学的评估效能更好。Objective The classification of parotid gland tumors is complex,qualitative analysis of dynamic enhancement scan is difficult to distinguish benign and malignant parotid tumors.To determine the clinical value of dynamic enhanced imaging in distinguishing the benign and malignant parotid gland mass through radiomics analysis of quantitative parameter images.Methods Magnetic resonance images of 51 cases of parotid gland mass confirmed by pathology in People's Hospital of Xinjiang Uygur Autonomous Region from January 2019 to April 2022 were retrospectively analyzed,including 12 pleomorphic adenomas,19 Warthin tumors,8 malignant tumors,and 15 non-neoplastic lesions.Quantitative parametric maps of transfer constant(K_(trans)),extracellular volume fraction(V_(e)),plasma volume fraction(V_(p)),and outflow rate constant(K_(ep))were generated from dynamic enhancement images of parotid gland,and the imaging features were extracted by FAE software to establish a radiomics model for the diagnosis of benign and malignant parotid lesions.The area under the receiver operating characteristic curve(AUC),sensitivity,specificity,and accuracy were used to evaluate the radiomics model and assess the efficacy of distinguishing benign and malignant parotid gland lesions.At the same time,pleomorphic adenoma,Warthin tumors and non-neoplastic lesions were separately compared with malignant parotid adenoma in terms of radiomics.Results Feature extraction and radiomics analysis of dynamic enhanced images were performed to determine the efficacy of benign and malignant parotid gland mass.The AUC,accuracy,sensitivity,and specificity were 0.612,0.844,0.500 and 0.875,respectively.When pleomorphic adenoma,Warthin's tumor and non-neoplastic lesions were separately compared with malignant parotid tumors,the AUC,accuracy,sensitivity,and specificity were 0.736,0.781,0.909,0.714,and 0.886,0.880,0.933,0.857,and 0.805,0.781,0.700,0.818.Conclusion Radiomics analysis using dynamic enhanced quantitative images can preliminarily determine the benign and ma

关 键 词：磁共振成像 头颈部 腮腺瘤 影像组学 动态增强 

分 类 号：R730.44[医药卫生—肿瘤] R445.2[医药卫生—临床医学]