Abstract

Purpose: To test the hypothesis that audiovisual biofeedback (AV) respiratory training improves 4D‐PET image quality. Methods: In an IRB‐approved study, two 4D‐PET scans, with AV and free breathing, were acquired sequentially for 10 lung cancer patients. AV was performed by guiding a patient to follow a waveform with period and displacement determined by averaging the respiratory cycles of the patient. The acquisition time for the second scan was increased to compensate for activity decaying. 4D‐PET images were created by phase‐based gating with six bins. The 4D‐PET images with AV were compared to those with free breathing by quantifying (1) SUVmax and (2) tumor motion range. The motion range was quantified through the center of mass of a segmented tumor volume at each phase. To investigate the correlation of respiratory regularity and SUVmax, we separated tumors into two groups: (1) tumors with large motion (>5 mm, spatial resolution) and (2) the others. We tested the hypothesis using the two‐tailed paired t‐test. Results: For tumors with large motion, the average SUVmax with AV and free breathing was 11.5 and 10.8, respectively (p = 0.03); for the other tumors, the average SUVmax with AV and free breathing was 14.4 and 12.4, respectively (p < 0.001). For tumors with large motion, the average motion range with AV and free breathing was 9.1 and 7.4 mm (p = 0.36) in the superior‐inferior direction, respectively. However, the results were patient‐specific. In the 7 tumors with large motion, SUVmax with AV was improved for 3 tumors, worsen for 2 tumors, not correlated with respiratory regularity for 2 tumors. Conclusion: A 10‐patients study demonstrated statistically significant improvement of SUVmax with AV for tumors with large motion. Futures studies will focus on optimizing the interface for improved compliance and recruiting patients who have tumors with large motion.Research supported by the Kwanjeong Education Foundation in Korea, NIH/NCI 2 R01 CA 093626, and Stanford BioX Interdisciplinary Initiatives

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