Diagnostic Imaging Challenges During Extracorporeal Membrane Oxygenation

Extracorporeal membrane oxygenation (ECMO) is a critical life support therapy for severe cardiac and respiratory failure, but it is associated with thromboembolic, hemorrhagic, and neurological complications. Diagnostic imaging is essential for early detection and management of these events; however, conventional modalities such as contrast enhanced computed tomography (CT) are often limited by the risks of transporting unstable patients and by ECMO related hemodynamic alterations that may distort contrast distribution, particularly in peripheral veno arterial (VA-ECMO).

This review aims to evaluate current diagnostic imaging strategies and emerging non invasive technologies that may improve the detection and management of ECMO related complications, with a focus on contrast enhanced CT, bedside echocardiography, and novel neuroradiological tools.

A narrative synthesis was conducted examining diagnostic approaches applicable to ECMO patients, including contrast enhanced CT, transesophageal echocardiography (TEE), low field bedside magnetic resonance imaging (MRI), and electrical impedance tomography. The review emphasizes physiological considerations, technical limitations, and potential clinical applications.

TEE enables real time assessment of cardiac-ECMO interactions and identification of the watershed zone in VA-ECMO, supporting individualized flow optimization. Low field bedside MRI reduces transport related risks and may enhance early detection of cerebral complications. Electrical impedance tomography provides dynamic, radiation free monitoring of regional ventilation in ARDS patients on veno venous VV-ECMO. Despite promising performance characteristics, these technologies remain underutilized in routine practice.

Integrating advanced bedside imaging modalities with traditional diagnostic tools may significantly improve the safety and accuracy of monitoring in ECMO patients. Broader adoption and further technological refinement could enhance early complication detection and support more personalized ECMO management.