Electrical Impedance Analysis for Lung Cancer: A Prospective, Multicenter, Blind Validation Study

Dawei Yang; Chuanjia Gu; Ye Gu; Xiaodong Zhang; Di Ge; Yong Zhang; Ningfang Wang; Xiaoxuan Zheng; Hao Wang; Li Yang; Saihua Chen; Pengfei Xie; Deng Chen; Jinming Yu; Jiayuan Sun; Chunxue Bai

doi:10.3389/fonc.2022.900110

Electrical Impedance Analysis for Lung Cancer: A Prospective, Multicenter, Blind Validation Study

Front Oncol. 2022 Jul 20:12:900110. doi: 10.3389/fonc.2022.900110. eCollection 2022.

Authors

Dawei Yang^{1

2

3

4}, Chuanjia Gu^{5

6}, Ye Gu⁷, Xiaodong Zhang⁸, Di Ge⁹, Yong Zhang¹, Ningfang Wang¹, Xiaoxuan Zheng^{5

6}, Hao Wang⁷, Li Yang⁷, Saihua Chen⁸, Pengfei Xie⁸, Deng Chen¹⁰, Jinming Yu¹⁰, Jiayuan Sun^{5

6

11}, Chunxue Bai^{1

2

3

4}

Affiliations

¹ Department of Pulmonary Medicine and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
² Shanghai Respiratory Research Institution, Shanghai, China.
³ Chinese Alliance Against Lung Cancer, Shanghai, China.
⁴ Shanghai Engineer & Technology Research Center of Internet of Things for Respiratory Medicine, Shanghai, China.
⁵ Department of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
⁶ Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
⁷ Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
⁸ Department of Pulmonary Medicine, Nantong Tumor Hospital, Nantong, China.
⁹ Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
¹⁰ Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
¹¹ Shanghai Engineering Research Center of Respiratory Endoscopy, Shanghai, China.

Abstract

Hypothesis: 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.

Method: 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.

Results: 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 (p = 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.

Conclusion: Electrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.

Keywords: diagnosis; electrical impedance; lung cancer; prospective; pulmonary nodules.