Lung function assessment by electrical impedance tomography among obese patients

Obesity is a growing problem worldwide. It is well reported that obesity is associated with various degrees of respiratory function compromise, which could be contributed by mechanical factors as well as co-morbid diseases such as asthma. While spirometry is the gold standard for lung function measurement, it does have the drawback of only being able to measure the global function of the lungs and is uncomfortable for those with difficulty using a large degree of effort. A prospective cross-sectional study was conducted in Queen Mary Hospital, Hong Kong to recruit Chinese obese and non-obese subjects, to compare and correlate the lung function parameters measured by electrical impedance tomography (EIT) and spirometry. Obesity was diagnosed based on the local definition of body mass index of 25 kg/m<sup>2</sup> or above, using the cut-off value for Asian population. A total of 42 obese subjects and 35 non-obese subjects were included in this study. The spirometric values (Litres) measured by spirometry and EIT demonstrated good correlation among obese and non-obese subjects, with Pearson correlation coefficient of 0.705 and 0.673 for FEV<sub>1</sub> among obese and non-obese subjects, p-value < 0.01. The Pearson correlation coefficients were 0.568 and 0.541 for FVC among obese and non-obese subjects respectively, p-value < 0.01. EIT technology has comparable performance in lung function measurement among obese and non-obese subjects. It can suggest that EIT is a potential tool for lung function measurement in obese subjects as in non-obese subjects.

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Publication Details

Journal
Scientific Reports
Published
2025-11-25
DOI
https://doi.org/10.1038/s41598-025-29559-1
Citations
1
Primary Topic
Body Composition Measurement Techniques
Type
article
Field-Weighted Citation Impact
1.16
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article

Lung function assessment by electrical impedance tomography among obese patients

Venkateshwarlu Sarangi, Adrien Touboul, Justin Chan, Michele Mae Ann Yuen et al.
1 citations
Scientific Reports
Body Composition Measurement Techniques
1.16
article

Lung function assessment by electrical impedance tomography among obese patients

Venkateshwarlu Sarangi, Adrien Touboul, Justin Chan, Michele Mae Ann Yuen, Wang Chun Kwok, Wing Chow
article en
1 citations

Abstract

Obesity is a growing problem worldwide. It is well reported that obesity is associated with various degrees of respiratory function compromise, which could be contributed by mechanical factors as well as co-morbid diseases such as asthma. While spirometry is the gold standard for lung function measurement, it does have the drawback of only being able to measure the global function of the lungs and is uncomfortable for those with difficulty using a large degree of effort. A prospective cross-sectional study was conducted in Queen Mary Hospital, Hong Kong to recruit Chinese obese and non-obese subjects, to compare and correlate the lung function parameters measured by electrical impedance tomography (EIT) and spirometry. Obesity was diagnosed based on the local definition of body mass index of 25 kg/m<sup>2</sup> or above, using the cut-off value for Asian population. A total of 42 obese subjects and 35 non-obese subjects were included in this study. The spirometric values (Litres) measured by spirometry and EIT demonstrated good correlation among obese and non-obese subjects, with Pearson correlation coefficient of 0.705 and 0.673 for FEV<sub>1</sub> among obese and non-obese subjects, p-value < 0.01. The Pearson correlation coefficients were 0.568 and 0.541 for FVC among obese and non-obese subjects respectively, p-value < 0.01. EIT technology has comparable performance in lung function measurement among obese and non-obese subjects. It can suggest that EIT is a potential tool for lung function measurement in obese subjects as in non-obese subjects.

Scientific ReportsVol. 15(1)
Chinese University of Hong Kong (HK), Queen Mary Hospital (CN), University of Hong Kong (HK)
Openalex Percentile: Top 16%
Body Composition Measurement Techniques
1.16
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