Literature DB >> 9863674

Ventilation and perfusion imaging by electrical impedance tomography: a comparison with radionuclide scanning.

P W Kunst1, A Vonk Noordegraaf, O S Hoekstra, P E Postmus, P M de Vries.   

Abstract

Electrical impedance tomography (EIT) is a technique that makes it possible to measure ventilation and pulmonary perfusion in a volume that approximates to a 2D plane. The possibility of using EIT for measuring the left-right division of ventilation and perfusion was compared with that of radionuclide imaging. Following routine ventilation (81mKr) and perfusion scanning (99mTc-MAA), EIT measurements were performed at the third and the sixth intercostal level in 14 patients with lung cancer. A correlation (r = 0.98, p < 0.005) between the left-right division for the ventilation measured with EIT and that with 81mKr was found. For the left-right division of pulmonary perfusion a correlation of 0.95 (p < 0.005) was found between the two methods. The reliability coefficient (RC) was calculated for estimating the left-right division with EIT. The RC for the ventilation measurements was 94% and 96% for the perfusion measurements. The correlation analysis for reproducibility of the EIT measurements was 0.95 (p < 0.001) for the ventilation and 0.93 (p < 0.001) for the perfusion measurements. In conclusion, EIT can be regarded as a promising technique to estimate the left-right division of pulmonary perfusion and ventilation.

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Year:  1998        PMID: 9863674     DOI: 10.1088/0967-3334/19/4/003

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  24 in total

1.  Determinants of pulmonary perfusion measured by electrical impedance tomography.

Authors:  Henk J Smit; Anton Vonk Noordegraaf; J Tim Marcus; Anco Boonstra; Peter M de Vries; Pieter E Postmus
Journal:  Eur J Appl Physiol       Date:  2004-02-21       Impact factor: 3.078

2.  Impact of model shape mismatch on reconstruction quality in electrical impedance tomography.

Authors:  Bartłomiej Grychtol; William R B Lionheart; Marc Bodenstein; Gerhard K Wolf; Andy Adler
Journal:  IEEE Trans Med Imaging       Date:  2012-05-22       Impact factor: 10.048

3.  Body and head position effects on regional lung ventilation in infants: An electrical impedance tomography study.

Authors:  Sina Heinrich; Holger Schiffmann; Alexander Frerichs; Adelbert Klockgether-Radke; Inéz Frerichs
Journal:  Intensive Care Med       Date:  2006-06-24       Impact factor: 17.440

Review 4.  [Electrical impedance tomography: ready for routine clinical use for mechanically ventilated patients?].

Authors:  J Hinz; G Hahn; M Quintel
Journal:  Anaesthesist       Date:  2008-01       Impact factor: 1.041

5.  Electrical impedance tomography: changes in distribution of pulmonary ventilation during laparoscopic surgery in a porcine model.

Authors:  T Meier; T Leibecke; C Eckmann; U W Gosch; M Grossherr; H P Bruch; H Gehring; S Leonhardt
Journal:  Langenbecks Arch Surg       Date:  2006-03-24       Impact factor: 3.445

6.  The complete electrode model for EIT in a mammography geometry.

Authors:  Bong Seok Kim; Gregory Boverman; Jonathan C Newell; Gary J Saulnier; David Isaacson
Journal:  Physiol Meas       Date:  2007-06-26       Impact factor: 2.833

7.  Reconstructions of conductive and insulating targets using the D-bar method on an elliptical domain.

Authors:  E K Murphy; J L Mueller; J C Newell
Journal:  Physiol Meas       Date:  2007-06-26       Impact factor: 2.833

8.  A Real-time D-bar Algorithm for 2-D Electrical Impedance Tomography Data.

Authors:  Melody Dodd; Jennifer L Mueller
Journal:  Inverse Probl Imaging (Springfield)       Date:  2014-11-01       Impact factor: 1.639

9.  Estimating a regional ventilation-perfusion index.

Authors:  P A Muller; T Li; D Isaacson; J C Newell; G J Saulnier; Tzu-Jen Kao; Jeffrey Ashe
Journal:  Physiol Meas       Date:  2015-05-26       Impact factor: 2.833

10.  Electrical impedance tomography applied to assess matching of pulmonary ventilation and perfusion in a porcine experimental model.

Authors:  Anneli Fagerberg; Ola Stenqvist; Anders Aneman
Journal:  Crit Care       Date:  2009-03-05       Impact factor: 9.097

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