Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr;10(8):471.
doi: 10.21037/atm-22-1366.

Diagnostic test of bioimpedance-based neural network algorithm in early cervical cancer

Ling Mei #  1   2 , Jian Meng #  1   2 , Dongmei Wei  1   2 , Qian Hu  2 , Yueyue Chen  1   2 , Tao Cui  1   2 , Yueting Zhang  1   2 , Qiao Li  1   2 , Xiaoli Zhang  2 , Yuqing Liu  2 , Qian Wang  2 , Lisha Ding  2 , Tao Wang  2 , Yukuan Feng  1 , Wei Lei  1 , Yanhui Deng  3 , Xiaoyun Gong  4 , Jingchun Ling  5 , Xiaoyu Niu  1   2
Affiliations

Diagnostic test of bioimpedance-based neural network algorithm in early cervical cancer

Ling Mei et al. Ann Transl Med. 2022 Apr.

Abstract

Background: Colposcopy is a critical component of cervical cancer screening services, but the accuracy of colposcopy varies greatly due to the lack of standardized training for colposcopists and pathologists. Thus, to improve the accuracy of colposcopy in the detection of cervical lesions intelligently is urgent. Here, we explored the sensitivity and specificity of a bioimpedance-based neural network algorithm in distinguishing normal and precancerous cervical tissues.

Methods: Bioimpedance data were collected using a bioimpedance analyzer (Mscan1.0B, Sealand Technology, Chengdu, China) from the cervices of 102 female patients with abnormal cervical cytology (≥atypical squamous cells of undetermined significance) who required further colposcopy. Finally, the data of 106 samples from 37 patients were included, among which 85were used as the training set and 21 as the validation set. Using the biopsy pathology at each locus as the gold standard, the sensitivity, specificity, predictive value, likelihood ratio, and false positive and false negative rates of the bioimpedance-based neural network in identifying the normal and precancerous cervical tissues were calculated.

Results: The bioimpedance method had a sensitivity of 0.90 [95% confidence interval (CI): 0.54 to 0.99], specificity of 0.82 (95% CI: 0.48 to 0.97), positive predictive value of 0.82 (95% CI: 0.48 to 0.97), and a negative predictive value of 0.90 (95% CI: 0.54 to 0.99) in distinguishing normal and precancerous cervical tissues. The Kappa value was 0.72.

Conclusions: The bioimpedance method was an intelligent method with relative good sensitivity and specificity in distinguishing benign cervical tissue and precancerous lesions and can therefore be used as an adjunctive test to colposcopy to improve the detection of cervical lesions.

Keywords: Bioimpedance; cervical cancer; cervical precancerous lesion; neural network algorithm.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-1366/coif). YD is an employee of Sealand Technology (Chengdu) Ltd. JL reports funds from HINER CLIENT Technology (Chengdu) Ltd.; employment contract with HINER CLIENT Technology (Chengdu) Ltd.; patents planned, issued or pending of HINER CLIENT Technology (Chengdu) Ltd. XN reports that this study was supported by National Key Research and Development Program of China (Nos. 2021YFC2009100; 2021YFC2009105). The other authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Schematic diagram of bioimpedance. (A) 3-element model of the biological tissue. The cell membrane is regarded as capacitor C1 and the extracellular fluid and intracellular fluid as R1 and R2. (B) Low-frequency electrical signal cannot penetrate the cell membrane and just flows through the extracellular gap; the high-frequency electrical signal can penetrate the cell membrane and flows through the cells. HF, high-frequency electrical signal; LF, low-frequency electrical signal.
Figure 2
Figure 2
Schematic diagram of the histological changes in cervical epithelium at different disease status. CIN, cervical intraepithelial neoplasia.
Figure 3
Figure 3
Bioimpedance analyzer. (A) The disposable pen; (B) the console.
Figure 4
Figure 4
Schematic diagram of cervical directions.
Figure 5
Figure 5
Data screening and inclusion process.
See this image and copyright information in PMC

Comment in

References

    1. World Health Organization. Cervical cancer;(cited 2021 Dec 23). Available online: https://www.who.int/health-topics/cervical-cancer#tab=tab_1
    1. Zhou PR, Zhou WH, Xia L, et al. Research progress of early screening methods for cervical cancer. Journal of Hubei University (Medical Edition) 2020;37:48-51.
    1. Redman CWE, Kesic V, Cruickshank ME, et al. European consensus statement on essential colposcopy. Eur J Obstet Gynecol Reprod Biol 2021;256:57-62. 10.1016/j.ejogrb.2020.06.029 - DOI - PubMed
    1. Baasland I, Hagen B, Vogt C, et al. Colposcopy and additive diagnostic value of biopsies from colposcopy-negative areas to detect cervical dysplasia. Acta Obstet Gynecol Scand 2016;95:1258-63. 10.1111/aogs.13009 - DOI - PMC - PubMed
    1. Brown BH, Tidy JA, Boston K, et al. Relation between tissue structure and imposed electrical current flow in cervical neoplasia. Lancet 2000;355:892-5. 10.1016/S0140-6736(99)09095-9 - DOI - PubMed