RESUMO
OBJECTIVE: Prosthetic grafts used for lower extremity revascularization and dialysis access fail because of hyperplastic stenosis and thrombosis. Graft surveillance is advocated to monitor function; however, graft failure can occur between episodic examinations. An innovative sensor with wireless, microchip technology allows automated surveillance with assessment of graft function using a "cloud"-based algorithm. We performed proof-of-concept experiments with in vitro and in vivo models to assess the feasibility such a real-time graft surveillance system. METHODS: A self-monitoring graft system was evaluated consisting of a prosthetic conduit of expanded polytetrafluoroethylene and a sensor unit, and a microsensor, microelectronics, battery, and remote processor with a monitor. The sensor unit was integrated on the extraluminal surface of expanded polytetrafluoroethylene grafts without compromise to the lumen of the conduit. The grafts were tested in vitro in a pulsatile, recirculating flow system under physiologic flow parameters. The hemodynamic parameters were varied to assess the ability to obtain wireless signal acquisition reflecting real-time flow properties in vitro. Segments of custom tubing with reduced diameters were inserted into the model to mimic stenosis proximal and distal to the grafts. After characterization of the initial data, the self-monitoring grafts were implanted in an ovine carotid model to assess proof of concept in vivo with 30-day follow-up of signal acquisition as well as arteriographic and histologic analysis. RESULTS: In vitro flow data demonstrated the device was able to determine factors related to prosthetic graft function under varied hemodynamic flow conditions. Wireless signal acquisition using Bluetooth technology (Bluetooth SIG, Inc, Kirkland, Wash) allowed remote data analysis reflecting graft flow parameters through changes in microsensor voltage and frequency. Waveform analysis was applied to construct an algorithm using proprietary software and determine a parameter for graft flow characteristics. This algorithm allowed determination of the degree of stenosis and location of stenosis location (proximal or distal) for display on a remote monitor in real time. Subsequent in vivo experiments confirmed the ability of the system to generate signal acquisition through skin and soft tissue under biologic conditions with no arteriographic stenosis and a favorable healing response at 30-day harvest. CONCLUSIONS: Initial in vitro and in vivo experiments demonstrate the ability for a self-monitoring graft system to remotely monitor hemodynamic parameters reflecting graft function using wireless data transmission. This automated system shows promise to deliver real-time data that can be analyzed by cloud-based algorithms alerting the clinician of a change in graft function or development of stenosis for further diagnostic study or intervention before graft failure.