(Sunday, 7/14/2019) 1:00 PM - 2:00 PM
Room: 221AB
Purpose: The purpose of this work is evaluation of a novel capacitive-sensing technology for continuous detection of respiratory motion during radiation therapy. This modular system provides real-time motion monitoring without any contact with the patient, ionizing radiation or surrogates such as reflective markers on the skin.
Methods: In this work we describe a novel system featuring an array of capacitive detectors that are sensitive to the position of the body and capable of high temporal frequency readout. Performance of this system in the context of respiratory motion detection was investigated in comparison to the RPM infrared monitoring system (Varian Medical Systems). This novel system includes three capacitive copper sensors, each 5cm by 10cm in size, located at a distance of 8 to 10 cm from the volunteer. Capacitive measurements were acquired for three locations during chest free-breathing: Xiphoid process, two inches lateral to the xiphoid on either side. Additional measurements were acquired during abdominal breathing at locations 10 cm inferior to those mentioned above. RPM IR data were acquired with the reflector block at corresponding positions. The system was also tested during deep inspiration and expiration breath-hold maneuvers. Measurements were repeated with bare skin and with clothing.
Results: CMS data demonstrate close agreement with the RPM status quo at all locations examined. Cross-correlation analysis on RPM and CMS data showed an average absolute lag of 0.08s (range: 0.033-0.23s) for DIBH and DEBH data and 0.13s (range: 0-0.43s) for free breathing. The capacitive system performance was not affected when the subject was clothed.
Conclusion: This novel technology permits sensing of both free-breathing and breath-hold respiratory motion. It provides data comparable to the RPM system but without the need for IR tracking camera in the treatment room or use of reflective markers on the patient.
Funding Support, Disclosures, and Conflict of Interest: The authors acknowledge financial support from the Atlantic Canada Opportunities Agency (ACOA), Atlantic Innovation Fund (AIF), and Brainlab AG.
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