AV biofeedback is a simple, personalised and interactive respiratory guide designed to facilitate regular patient breathing. The AV biofeedback system is shown in figure 1.

Figure 1.

AV biofeedback system. Display screen and marker block on the abdomen shown. The visual display (centre) as seen by the subject (sans arrows) of the AV biofeedback system shows the guiding wave (white curve) and a marker position (marker block) in real time. The AV biofeedback system is compatible for both imaging (left) and treatment (right) environments.

The problem that AV biofeedback is addressing is that should a patient’s breathing be irregular (see Figure 2a), it can result in incorrect information presented in medical imaging (see Figure 2b). Such irregularities and image artefacts can lead to incorrect tumour targeting in radiotherapy (see Figure 2c) or an increase in the radiation target volume resulting in an increase in radiation dose delivered to healthy tissue. This may damage the healthy surrounding organs leading to loss of function and even cancer reoccurrence. This problem affects the 44% of the 10,200 lung cancer patients treated with radiotherapy in Australia, and up to 71% of the 1.2 million lung cancer patients treated with radiotherapy in the world each year.

Figure 2a.

Figure 3.

Comparison of free breathing and AV biofeedback breathing signals (top) and image quality for 4D-CT (middle) and gated-MRI (bottom). Arrows point out image artefacts due to irregular breathing.

A number of studies have already been performed demonstrating the effectiveness of AV biofeedback in reducing breathing irregularities in addition to improving image quality, demonstrated in Figure 3.

AV biofeedback is now at a crucial stage towards commercialisation. This will be achieved through comprehensive clinical evaluations and technology assessments of the AV biofeedback device in prospective, randomised multi-institutional clinical trials, involving both lung and liver cancer patients across a range of imaging modalities; these will be the most thorough and significant studies of their kind to date.
Such audiovisual biofeedback studies include:

Research Opportunities

For more information and enquiries contact Professor Paul Keall.


  • Pollock S, Tse R, Martin D, McLean L, Pham M, Tait D, Estoesta R, Whittington G, Turley J, Kearney C, Cho G, Hill R, Pickard S, Aston P, Makhija K, O’Brien R, Keall P. Impact of audiovisual biofeedback on interfraction respiratory motion reproducibility in liver cancer stereotactic body radiotherapy. J Med Imaging Radiat Oncol. 2018 Feb;62(1):133-139. [More Information]
  • Lee, D., Greer, P., Lapuz, C., Ludbrook, J., Hunter, P., Arm, J., Pollock, S., Makhija, K., O’Brien, R., Kim, T., Keall, P. (2017). Audiovisual biofeedback guided breath-hold improves lung tumor position reproducibility and volume consistency. Advances in Radiation Oncology, In Press, 1-9.
  • Lee, D., Greer, P., Ludbrook, J., Arm, J., Hunter, P., Pollock, S., Makhija, K., O’Brien, R., Kim, T., Keall, P. (2016). Audiovisual Biofeedback Improves Cine-Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency. International Journal of Radiation Oncology: Biology Physics, 94(3), 628-636. [More Information]
  • Yang, J., Yamamoto, T., Pollock, S., Berger, J., Diehn, M., Graves, E., Loo Jr, B., Keall, P. (2016). The impact of audiovisual biofeedback on 4D functional and anatomic imaging: Results of a lung cancer pilot study. Radiotherapy and Oncology, 120(2), 267-272. [More Information]
  • Pollock, S., Tse, R., Martin, D., McLean, L., Cho, G., Hill, R., Pickard, S., Aston, P., Huang, C., Makhija, K., O’Brien, R., Keall, P. (2015). First clinical implementation of audiovisual biofeedback in liver cancer stereotactic body radiation therapy. Journal of Medical Imaging and Radiation Oncology, 59(5), 654-656. [More Information]
  • Lee, D., Greer, P., Arm, J., Keall, P., Kim, T. (2014). Audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI. Journal of Physics: Conference Series, 489(1), 1-4. [More Information]
  • Pollock, S., Lee, D., Keall, P., Kim, T. (2013). Audiovisual biofeedback improves motion prediction accuracy. Medical Physics, 40(4), 041705-1-041705-9. [More Information]
  • Kim, T., Pollock, S., Lee, D., O’Brien, R., Keall, P. (2012). Audiovisual biofeedback improves diaphragm motion reproducibility in MRI. Medical Physics, 39(11), 6921-6928. [More Information]
  • Yang, J., Yamamoto, T., Cho, B., Seo, Y., Keall, P. (2012). The impact of audio-visual biofeedback on 4D PET images: Results of a phantom study. Medical Physics, 39(2), 1046-1057. [More Information]