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Real-time instrument detection in minimally invasive surgery using radiofrequency identification technology
Michael Kranzfelder1, Armin Schneider, Adam Fiolka
1Department of Surgery, Klinikum rechts der Isar, Technische Universität München, München, Germany; Research Group, Minimally invasive Interdisciplinary Therapeutical Intervention, Klinikum rechts der Isar, Technische Universität München, München, Germany.
Background:
A key part of surgical workflow recording is recognition of the instrument in use. We present a radiofrequency identification (RFID)-based approach for real-time tracking of laparoscopic instruments.
Methods:
The system consists of RFID-tagged instruments and an antenna unit positioned on the Mayo stand. For reliability analysis, RFID tracking data were compared with the assessment of the perioperative video data of instrument changes (the reference standard for instrument application detection) in 10 laparoscopic cholecystectomies. When the tagged instrument was on the Mayo stand, it was referred to as "not in use." Once it was handed to the surgeon, it was considered to be "in use." Temporal miscounts (incorrect number of instruments "in use") were analyzed. The surgeons and scrub nurses completed a questionnaire after each operation for individual system evaluation.
Results:
A total of 110 distinct instrument applications ("in use" versus "not in use") were eligible for analysis. No RFID tag failure occurred. The RFID detection rates were consistent with the period of effective instrument application. The delay in instrument detection was 4.2 ± 1.7 s. The highest percentage of temporal miscounts occurred during phases with continuous application of coagulation current. Surgeons generally rated the system better than the scrub nurses (P = 0.54).
Conclusions:
The feasibility of RFID-based real-time instrument detection was successfully proved in our study, with reliable detection results during laparoscopic cholecystectomy. Thus, RFID technology has the potential to be a valuable additional tool for surgical workflow recognition that could enable a situation dependent assistance of the surgeon in the future.
