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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2022

Standalone electrical impedance tomography predicts spirometry indicators and enables regional lung assessment.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Zouari Fedi, Oon Wei Yi, Modak Dipyaman, Kwok Wang Chun, Cao Peng, Lee Wei-Ning, Tam Terence Chi Chun, Wong Eddie C, Chan Russell W

Аннотация

Electrical impedance tomography (EIT) is a bio-medical imaging modality that has several clinical applications namely for human lungs. Yet, its relationship with gold standard lung diagnostic tools including spirometry is not available. In this study, simultaneous EIT and spirometry measurements were collected for 14 healthy subjects who performed forced breathing paradigms of different efforts simulating a wide range of spirometry indicators. It is demonstrated that EIT can predict standard spirometry indicators over a wide dynamic range, with a potential sensitivity and specificity of 98% and 100%, respectively, in detecting obstructive patterns. It is also shown that EIT can provide a regional mapping of the spirometry indicator which are shown to be consistent with their corresponding global indicators. Overall, EIT can predict spirometry indicators and can assess regional lung health through parametric mapping. Clinical Relevance- This study shows that EIT can infer standard spirometry indicators and potentially assess regional lung health. Therefore, EIT can be used for screening, diagnosis, and monitoring of obstructive and resistive lung diseases.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты