Different approaches for quantifying ventilation distribution and lung tissue properties by functional EIT

Physiological Measurement
G HahnG Hellige

Abstract

We investigated five different methods which can be applied to quantitatively construct functional tomograms of the lungs. The focus was on the sensitivity of functional tomograms to errors in acquired data. To quantify this sensitivity, theoretical, error-free data sets of well-known properties were artificially generated based on a 'living thorax model'. Physiological time courses and a typical distribution of errors caused by a typical Goe-MF II EIT system were used for the calculations which encompassed a range up to 50 times greater than the initial error level (4 microV(rms max)-400 microV(rms max)). Additionally, low-pass filtering and principal component analysis (PCA) were used to quantify the effect of preprocessing the raw data. The results demonstrate that all methods based on fitting the local to the global time course were superior to the common functional tomograms utilizing standard deviation or maximum and minimum detection. Ventilation distribution was best quantified by the so-called VT methods. Filling capacity--a lung tissue property--was least dependent on increasing error levels. The errors introduced by filtering are significant with respect to a quantitative analysis of ventilation distribution. A prepr...Continue Reading

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Citations

Jan 26, 2011·Respirology : Official Journal of the Asian Pacific Society of Respirology·Florian ReifferscheidInéz Frerichs
Jan 18, 2012·IEEE Transactions on Medical Imaging·Camille Gómez-LabergeGerhard K Wolf
Oct 18, 2016·Pediatric Pulmonology·Sylvia LehmannKlaus Tenbrock
Sep 14, 2016·Clinical Physiology and Functional Imaging·B CambiaghiG Hahn
Nov 4, 2011·Physiological Measurement·Satoru NebuyaBrian H Brown
Dec 30, 2015·Physiological Measurement·T D AmbriskoY P S Moens
Apr 12, 2011·Current Opinion in Critical Care·Onnen MoererMichael Quintel
Oct 1, 2011·Journal of Applied Physiology·João Batista BorgesMarcelo Amato
Jul 13, 2017·Critical Care : the Official Journal of the Critical Care Forum·Johannes BickenbachMichael Dreher
Dec 2, 2017·Physiological Measurement·Zhanqi ZhaoKnut Möller

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