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Audiovisual Biofeedback Improves Tumor Motion Consistency for Lung Cancer Patients

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D Lee

D Lee1*, P Greer2,3 , J Arm3 , P Hunter3 , S Pollock1 , K Makhija1 , T Kim1,4 , P Keall1 , (1) The University of Sydney, Camperdown, NSW (2) The University of Newcastle, Newcastle, NSW, (3) Calvary Mater Newcastle Hospital, Newcastle, NSW, (4) University of Virginia Health System, Charlottesville, VA,


SU-E-J-29 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: To investigate whether the breathing-guidance system: audiovisual (AV) biofeedback improves tumor motion consistency for lung cancer patients. This will minimize respiratory-induced tumor motion variations across cancer imaging and radiotherapy procedues. This is the first study to investigate the impact of respiratory guidance on tumor motion.

Methods: Tumor motion consistency was investigated with five lung cancer patients (age: 55 to 64), who underwent a training session to get familiarized with AV biofeedback, followed by two MRI sessions across different dates (pre and mid treatment). During the training session in a CT room, two patient specific breathing patterns were obtained before (Breathing-Pattern-1) and after (Breathing-Pattern-2) training with AV biofeedback. In each MRI session, four MRI scans were performed to obtain 2D coronal and sagittal image datasets in free breathing (FB), and with AV biofeedback utilizing Breathing-Pattern-2. Image pixel values of 2D images after the normalization of 2D images per dataset and Gaussian filter per image were used to extract tumor motion using image pixel values. The tumor motion consistency of the superior-inferior (SI) direction was evaluated in terms of an average tumor motion range and period.

Results: Audiovisual biofeedback improved tumor motion consistency by 60% (p value = 0.019) from 1.0±0.6 mm (FB) to 0.4±0.4 mm (AV) in SI motion range, and by 86% (p value < 0.001) from 0.7±0.6 s (FB) to 0.1±0.2 s (AV) in period.

Conclusion: This study demonstrated that audiovisual biofeedback improves both breathing pattern and tumor motion consistency for lung cancer patients. These results suggest that AV biofeedback has the potential for facilitating reproducible tumor motion towards achieving more accurate medical imaging and radiation therapy procedures.

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