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Diogo Silva

Electrical Impedance Tomography is an imaging technique which allows a non-invasive, low-cost, real-time and point-of-care visualization of the impedance distribution of an anatomical cross-section. Through the placement of an electrode belt with injecting and measuring electrode pairs around a patient's chest, both ventilatory and cardiac information can be obtained. This makes EIT a tool especially suited for cardiorespiratory monitoring and diagnostics in the ICU.
So far, the study of the ventilation component of EIT has been a focal research point, yielding numerous methods to analyze regional lung ventilation, and unprecedented possibilities to assess lung diseases such as atelectasis, pulmonary edema, and even pneumonia. Recently, the attention has been shifting to the relatively unexplored topic of the cardiac component of the EIT signal. It is postulated that it is formed by a composition of sub-sources ranging from the movement of perfused organs to the orientation of blood cells. This project aims at developing the means to obtain: (1) this cardiac information, (2) investigate the sources that comprise it, (3) and validate its use in clinical practice:

1. Given the dominance of the ventilation component in the raw signal, algorithmic methods to separate and extract the cardiac component are being developed. These algorithms stem from different areas ranging from source-separation to machine learning.
2. Simulation-based studies are being conducted to model, isolate, and analyze the influence of individual postulated sources in the measured signal. This task includes multi-physical modelling of the cardiorespiratory system and its activity.
3. Animal trials are conducted in comparison to gold standard technology (Computerized Tomography) in order to understand what insights the measured EIT cardiac signals provide with respect central and peripheral perfusion in the lungs.

This project strives to finally achieve non-invasive complete cardiorespiratory monitoring with EIT, opening the doors to unparalleled diagnostic and monitoring indicators. One of the most promising ones, is the regional ventilation/perfusion (V/Q) ratio, which varies in the presence of a number of pathological conditions. One of the most sounding ones is, for example, COVID.

Project Goals

• Develop methodologies to obtain cardiac signals from the EIT raw signal.
• Create metrics from the cardiac signal that characterize the cardiopulmonary state of the patient.
• Understand the sources of the cardiac signal.
• Determine the cardiorespiratory monitoring and diagnostic capabilities of EIT with respect to the current gold standard.

Projektpartner

Uniklinik RWTH Aachen