Enhancing Respiratory Motion Prediction Accuracy Using Audiovisual (AV) Biofeedback
S Pollock, d lee, P Keall, T Kim,University of Sydney, Sydney, NSWWE-G-213CD-7 Wednesday 4:30:00 PM - 6:00:00 PM Room: 213CD
Purpose: Prediction of respiratory-related tumor motion is hampered by irregularities present in the patient breathing patterns. Audiovisual (AV) biofeedback reduces irregularities, thereby producing a less complex breathing pattern. The aim of this project is to improve respiratory motion prediction accuracy using an AV biofeedback system.
Methods: An AV biofeedback system combined with real-time MRI was implemented in this project (4 human subjects across 5 studies (one subject had both an initial and follow-up study)). The AV biofeedback system consists of external marker positioned on the abdomen of human subjects, being tracked using an RPM system (Real-time Position Management, Varian) to guide the subject's breathing. Acquired respiratory data has been used as input for motion prediction through a dynamic multi-leaf collimator (DMLC) simulator developed by Prof. Keall. The prediction algorithm utilized was a kernel density estimation-based real-time prediction algorithm. A variety of prediction parameters were tested to determine optimum prediction performance. Prediction parameters adjusted were the delay time (DT) and training examples (TE); the parameters tested here were: DT/TE = 2500/1500, 2500/100, 1000/250, 500/250; Given that the data sampling rate was kept at 30 Hz, the resultant prediction training window lengths were 49.5, 8.25, 3.3 and 3.3seconds respectively.
Results: The mean difference between measured and predicted data for free breathing was 1.98±2.32mm; and 0.65±0.65mm for when AV biofeedback was implemented (reduction of error of 67%). The most accurate prediction results were attained using the parameters: DT/TE = 500 ms/250.
Conclusions: This study demonstrates the improvement of respiratory motion prediction accuracy when AV biofeedback is implemented to produce a more regular breathing pattern.