44
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Electrical Impedance Tomography: Tissue Properties to Image Measures.

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Electrical impedance tomography (EIT) uses electrical stimulation and measurement at the body surface to image the electrical properties of internal tissues. It has the advantage of noninvasiveness and high temporal resolution but suffers from poor spatial resolution and sensitivity to electrode movement and contact quality. EIT can be useful to applications, where there are conductive contrasts between tissues, fluids, or gasses, such as imaging of cancerous or ischemic tissue or functional monitoring of breathing, blood flow, gastric motility, and neural activity. The past decade has seen clinical application and commercial activity using EIT for ventilation monitoring. Interpretation of EIT-based measures is complex, and this review paper focuses on describing the image interpretation "pathway." We review this pathway, from Tissue Electrical Properties, EIT Electrodes & Hardware, Sensitivity, Image Reconstruction, Image Processing to EIT Measures. The relationship is discussed between the clinically relevant parameters and the reconstructed properties. An overview is given of areas of EIT application and of our perspectives for research and development.Electrical impedance tomography (EIT) uses electrical stimulation and measurement at the body surface to image the electrical properties of internal tissues. It has the advantage of noninvasiveness and high temporal resolution but suffers from poor spatial resolution and sensitivity to electrode movement and contact quality. EIT can be useful to applications, where there are conductive contrasts between tissues, fluids, or gasses, such as imaging of cancerous or ischemic tissue or functional monitoring of breathing, blood flow, gastric motility, and neural activity. The past decade has seen clinical application and commercial activity using EIT for ventilation monitoring. Interpretation of EIT-based measures is complex, and this review paper focuses on describing the image interpretation "pathway." We review this pathway, from Tissue Electrical Properties, EIT Electrodes & Hardware, Sensitivity, Image Reconstruction, Image Processing to EIT Measures. The relationship is discussed between the clinically relevant parameters and the reconstructed properties. An overview is given of areas of EIT application and of our perspectives for research and development.

          Related collections

          Most cited references85

          • Record: found
          • Abstract: found
          • Article: not found

          Electrical conductivity of tissue at frequencies below 1 MHz.

          A two-pronged approach, review and measurement, has been adopted to characterize the conductivity of tissues at frequencies below 1 MHz. The review covers data published in the last decade and earlier data not included in recent reviews. The measurements were carried out on pig tissue, in vivo, and pig body fluids in vitro. Conductivity data have been obtained for skeletal and myocardial muscle, liver, skull, fat, lung and body fluids (blood, bile, CSF and urine). A critical analysis of the data highlights their usefulness and limitations and enables suggestions to be made for measuring the electrical properties of tissues.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Electrical impedance tomography

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              GREIT: a unified approach to 2D linear EIT reconstruction of lung images.

              Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.
                Bookmark

                Author and article information

                Journal
                IEEE Trans Biomed Eng
                IEEE transactions on bio-medical engineering
                Institute of Electrical and Electronics Engineers (IEEE)
                1558-2531
                0018-9294
                November 2017
                : 64
                : 11
                Affiliations
                [1 ] Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.
                Article
                7982758
                10.1109/TBME.2017.2728323
                28715324
                4cec0a28-4d61-4597-9539-e18ae2843d5e
                History

                Conductivity,Tomography,Biomedical measurement,Blood,Electrodes,Monitoring

                Comments

                Comment on this article