Yang Dawei, Gu Chuanjia, Gu Ye, Zhang Xiaodong, Ge Di, Zhang Yong, Wang Ningfang, Zheng Xiaoxuan, Wang Hao, Yang Li, Chen Saihua, Xie Pengfei, Chen Deng, Yu Jinming, Sun Jiayuan, Bai Chunxue
Department of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Shanghai Respiratory Research Institution, Shanghai, China.
Front Oncol. 2022 Jul 20;12:900110. doi: 10.3389/fonc.2022.900110. eCollection 2022.
Patients with cancer have different impedances or conductances than patients with benign normal tissue; thus, we can apply electrical impedance analysis (EIA) to identify patients with cancer.
To evaluate EIA's efficacy and safety profile in diagnosing pulmonary lesions, we conducted a prospective, multicenter study among patients with pulmonary lesions recruited from 4 clinical centers (Zhongshan Hospital Ethics Committee, Approval No. 2015-16R and 2017-035(3). They underwent EIA to obtain an Algorithm Composite Score or 'Prolung Index,' PI. The classification threshold of 29 was first tested in an analytical validation set of 144 patients and independently validated in a clinical validation set of 418 patients. The subject's final diagnosis depended on histology and a 2-year follow-up.
In total, 418 patients completed the entire protocol for clinical validation, with 186 true positives, 145 true negatives, 52 false positives, and 35 false negatives. The sensitivity, specificity, and diagnostic yield were 84% (95% CI 79.3%-89.0%), 74% (95% CI 67.4%-79.8%), and 79% (95%CI 75.3%-83.1%), respectively, and did not differ according to age, sex, smoking history, body mass index, or lesion types. The sensitivity of small lesions was comparable to that of large lesions ( = 0.13). Four hundred eighty-four patients who underwent the analysis received a safety evaluation. No adverse events were considered to be related to the test.
Electrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.
癌症患者与良性正常组织患者具有不同的阻抗或电导；因此，我们可以应用电阻抗分析（EIA）来识别癌症患者。
为评估EIA在诊断肺部病变中的有效性和安全性，我们对从4个临床中心招募的肺部病变患者进行了一项前瞻性、多中心研究（中山医院伦理委员会，批准号2015 - 16R和2017 - 035(3)）。他们接受了EIA以获得算法综合评分或“肺延长指数”（PI）。首先在144例患者的分析验证集中测试了29的分类阈值，并在418例患者的临床验证集中进行了独立验证。受试者的最终诊断取决于组织学和2年的随访。
共有418例患者完成了临床验证的整个方案，其中真阳性186例，真阴性145例，假阳性52例，假阴性35例。敏感性、特异性和诊断率分别为84%（95%CI 79.3% - 89.0%）、74%（95%CI 67.4% - 79.8%）和79%（95%CI 75.3% - 83.1%），且不受年龄、性别、吸烟史、体重指数或病变类型的影响。小病变的敏感性与大病变相当（P = 0.13）。484例接受分析的患者接受了安全性评估。未发现与该检测相关的不良事件。
电阻抗分析是肺部病变风险分层的一种安全有效的工具，尤其适用于肺部病变可疑的患者。
