ABSTRACT
Objective.Pulmonary embolism (PE) is an acute condition that blocks the perfusion to the lungs and is a common complication of Covid-19. However, PE is often not diagnosed in time, especially in the pandemic time due to complicated diagnosis protocol. In this study, a non-invasive, fast and efficient bioimpedance method with the EIT-based reconstruction approach is proposed to assess the lung perfusion reliably.Approach.Some proposals are presented to improve the sensitivity and accuracy for the bioimpedance method: (1) a new electrode configuration and focused pattern to help study deep changes caused by PE within each lung field separately, (2) a measurement strategy to compensate the effect of different boundary shapes and varied respiratory conditions on the perfusion signals and (3) an estimator to predict the lung perfusion capacity, from which the severity of PE can be assessed. The proposals were tested on the first-time simulation of PE events at different locations and degrees from segmental blockages to massive blockages. Different object boundary shapes and varied respiratory conditions were included in the simulation to represent for different populations in real measurements.Results.The correlation between the estimator and the perfusion was very promising (R = 0.91, errors <6%). The measurement strategy with the proposed configuration and pattern has helped stabilize the estimator to non-perfusion factors such as the boundary shapes and varied respiration conditions (3%-5% errors).Significance.This promising preliminary result has demonstrated the proposed bioimpedance method's capability and feasibility, and might start a new direction for this application.