Literature DB >> 26006107

Feasibility of using 'lung density' values estimated from EIT images for clinical diagnosis of lung abnormalities in mechanically ventilated ICU patients.

Satoru Nebuya1, Tomotaka Koike, Hiroshi Imai, Yoshiaki Iwashita, Brian H Brown, Kazui Soma.   

Abstract

This paper reports on the results of a study which compares lung density values obtained from electrical impedance tomography (EIT), clinical diagnosis and CT values (HU) within a region of interest in the lung. The purpose was to assess the clinical use of lung density estimation using EIT data. In 11 patients supported by a mechanical ventilator, the consistency of regional lung density measurements as estimated by EIT was validated to assess the feasibility of its use in intensive care medicine. There were significant differences in regional lung densities recorded in the supine position between normal lungs and diseased lungs associated with pneumonia, atelectasis and pleural effusion (normal; 240 ± 71.7 kg m(-3), pneumonia; 306 ± 38.6 kg m(-3), atelectasis; 497 ± 130 kg m(-3), pleural effusion; 467 ± 113 kg m(-3): Steel-Dwass test, p < 0.05). In addition, in order to compare lung density with CT image pixels, the image resolution of CT images, which was originally 512 × 512 pixels, was changed to 16 × 16 pixels to match that of the EIT images. The results of CT and EIT images from five patients in an intensive care unit showed a correlation coefficient of 0.66 ± 0.13 between the CT values (HU) and the lung density values (kg m(-3)) obtained from EIT. These results indicate that it may be possible to obtain a quantitative value for regional lung density using EIT.

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Year:  2015        PMID: 26006107     DOI: 10.1088/0967-3334/36/6/1261

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


  1 in total

1.  An innovative design for cardiopulmonary resuscitation manikins based on a human-like thorax and embedded flow sensors.

Authors:  Mark Thielen; Rohan Joshi; Frank Delbressine; Sidarto Bambang Oetomo; Loe Feijs
Journal:  Proc Inst Mech Eng H       Date:  2017-02-13       Impact factor: 1.617

  1 in total

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