Room: Room 202
Purpose: In the absence of motion management, respiratory tumor motion and the presence of cycle-to-cycle variations greatly degrades the accuracy of radiation targeting. By measuring the volumetric tidal flow, spirometry has been shown to be an accurate surrogate for internal displacement. However, spirometers are prone to drift. We investigate the performance in estimating volumetric tidal flow when integrating higher order information associated with monitoring the entire thoraco-abdominal surface rather than the commonly used technique of monitoring a single patch/point.
Methods: Breathing patterns of five healthy volunteers was recorded simultaneously using two common, non-invasive breathing
methods: volumetric tidal flow using spirometry (SDX, Dynâ€™R, France), and abdominal height displacement with Real Time Position Management (RPM, Varian Medical Systems, USA). Simultaneous to the two measurements, a prototype, research version, optical surface imaging system (AlignRT, Vision RT, UK), was used to capture a dense point-cloud of the thoraco-abdominal surface with a rate of 15fps and reconstructed as a watertight surface on a rectangular grid to perform a principal component (PC) analysis. The RPM signal, and the first three components of the surface were normalized. The first ten seconds of the measurement was used to train a principal least square model to estimate volumetric tidal flow for the remaining 100 seconds.
Results: Both surface surrogates (RPM and VisionRT) showed a high degree of correlation with tidal flow. In comparison to the RPM, a three PC surface model leads to a reduction in estimated tidal flow RMSE by as much as one order of magnitude. One volunteer exhibited a one dimensional breathing pattern with the first surface PC correlated with tidal flow correlated (RMSE=0.001).
Conclusion: Our study suggest that monitoring the entire surface rather than a single point can lead to improvements when estimating tidal flow, and hence represents a more accurate breathing metric.