Correlation and variation of a multi-modal sensor setup for respiratory motion prediction and correlation

Type of publication:  Artikel in einem Konferenzbericht
Buchtitel: 55th Annual Meeting & Exhibition of AAPM
Serie: Medical Physics
Band: 40
Nummer: 6
Jahr: 2013
Monat: August
Seiten: 186
Ort: Indianapolis, USA
Organisation: American Association of Physicists in Medicine (AAPM)
Notiz: Motion Compensation in Radiosurgery
Querverweis: AAPM13
DOI: 10.1118/1.4814365
Abriss: Purpose: In robotic radiosurgery, tumor movements are compensated by tracking external optical surrogates. These surrogates are used to compensate for time delays (prediction) and to calculate the internal fiducial position (correlation). We aim to increase the accuracy and robustness by using a multi-modal sensor approach including different physiological sensors. We evaluate the correlation coefficient of a strain belt, acceleration and air flow sensor with respect to external standard optical sensors and an internal landmark in the liver tracked using 3D ultrasound and evaluate the variance for a measurement over 20 minutes. Methods: We recorded sensor data from 6 subjects (5 male/1 female). All sensors have been synchronized and downsampled to the optical sampling rate (fs = 47 Hz) or in case of internal correlation to the ultrasound sampling rate (fs = 17 Hz). Pearson’s correlation coefficient r was calculated for each minute, discarding the first and last minute. Results: The mean (standard deviation) external correlation coefficients over all subjects and time periods were obtained as: 0.88 (0.036) for strain, 0.75 (0.024) for flow and 0.73 (0.052) for acceleration with respect to an optical marker on the chest. The mean (standard deviation) internal correlation coefficients are: 0.81 (0.045) for strain, 0.76 (0.041) for flow, 0.58 (0.088) for acceleration and 0.80 (0.057) for the optical marker on the chest with respect to the internal landmark. Conclusion: This study indicates that apart from the optical markers, strain and flow data show the best correlation to external and internal motion and seem to be promising for increasing the prediction and correlation accuracy as well as robustness. Among the investigated sensors, the strain data have the lowest standard deviation for internal and external correlation, being even lower than the standard deviation of the optical chest marker.
Schlagworte:
Autoren: Dürichen, Robert
Bruder, Ralf
Davenport, Lucas
Wissel, Tobias
Ernst, Floris
Schweikard, Achim
Anhänge
  • 2013 - AAPM - Dürichen - Corr...
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