Computational tools for Impedance Imaging

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Electrical Impedance Tomography (EIT) investigates the electrical properties of tissue with body-surface electrodes. The applicant is an internationally recognized expert in EIT image reconstruction and analysis algorithms. In the past grant period, contributions have been disseminated by editing of the main textbook and leading consensus projects on algorithms and data analysis, an open-source software tool which has become the most widely used in the field, in the scientific literature (47 journal papers), and supervising 16 graduate students, 4 PDFs and 60 undergraduate students. Software developed by the research team is a core component of three companies' products. This grant will focus on two specific EIT applications: non-invasive measurement of pulmonary arterial pressure (PAP) for monitoring of heart-failure; and sensitive measures of bronchoconstriction to monitor obstructive lung disease. These conditions affect very large populations, and early results are promising. Heart failure (HF) affects a large fraction of the elderly popultion, and occurs when the valves degrade or the heart becomes too weak to pump blood adequately. When the right heart compensates for HF, PAP increases, and the high blood pressure squeezes fluid into the airspaces leading tolung edema, congestion and shortness of breath. An exacerbation of heart failure requires admission to urgent care; however, the increases in PAP which lead to these exacerbations are detectable days or weeks before symptoms, and interventions during this window dramatically improve patient outcomes. Development will focus on recent work showing PAP can be measured non-invasively with EIT. HR-synchronized filtered data are reconstructed and the EIT signal in the lung region extracted. Two improvements to this algorithm will be researched: calcultion of millisecond-accuracy images, and error-tolerant algorithms. Diseases such as asthma and chronic obstructive lung disease, result from lung inflammation due to exposure to irritants and particularly smoke, and result in cough, mucus production and wheezing. With proper care and monitoring most patients can control symptoms and improve their quality of life. Monitoring of obstructive lung disease is inconvenient, and also gives only a global picture of the highly-heterogeneous lung. Recent work suggests that EIT can detect airflow limitation in a more sensitive way by analyzing the regional distribution of flow-volume parameters. Within this grant, we will research optimized electrode locations, robust 3D imaging, and regional flow-volume parameters. Results will be translated to Canadian partner companies. While working on specific technology applications, this grant will also further develop robust algorithms and computational tools useful to improve the accuracy and sensitivity of EIT, and make these contributions available through open-source software.