Free flap perfusion prediction by laser doppler flowmetry based time series analysis

Flap ischemia and consecutive flap loss is an innate complication in reconstructive free flap surgery. With the development of machine learning, time series analysis based flap failure prediction has become possible. With the laser doppler flowmetry pocket device (PocketLDF®) by JMS it has become possible to measure skin perfusion every second. In this trial skin perfusion in addition to blood pressure, pulse and respiratory rate were measured in 3 patients and flap failure prediction based on the Auto-Regressive Moving Average (ARMA) model and the Long Short Term Memory (LSTM) network was conducted. Accurate perfusion prediction with the ARMA model for stationary processes and with the LSTM network for non-stationary processes was possible. In comparison with real time observation by the attending doctor, the ARMA model was able to predict flap ischemia ahead of time. © 2021, Japan Soc. of Med. Electronics and Biol. Engineering. All rights reserved.