Safer, Faster, Clearer Imaging.

There are numerous limitations and trade-offs in medical imaging that affect the quality of the images doctors can use for diagnosis and treatment:

Up until now, the solution has been to keep the patient as still as possible during imaging. Even then, the lungs breathe, and the heart beats, remaining constantly in motion. Hundreds of images might be gathered, with only a few being usable.

  • Limits to the amount of radiation a patient can safely be exposed to during scans.
  • The amount of time it takes to capture a usable image.
  • The blurring and artefacts caused by patient motion.

In conventional imaging, images are constantly acquired throughout the scan. After the competition of the scan, the acquired images are sorted retrospectively with the patients recorded ECG. Only a subset of the images acquired are used to construct the final image. However, the patient has received the radiation dose for every single image that was acquired during the scan.

Our Solution: ACROBEAT

What if we adapted the imaging equipment to the moving patient, rather than making the patient conform to the limitations of the equipment? Acquiring images only when the heart and lungs are in perfect position would result in clearer images, and no unnecessary radiation dose to the patient.

We’re creating imaging protocol software that connects the imaging equipment to motion signals taken from the patient (e.g. breathing and the heart beating). By syncing the machine to the patient, we can ensure images are taken at the exact moments when there will be minimal potential for blurring or artefacts.

In Patient Connected Imaging, the patient’s ECG signal is utilized by our software to control the scanner, only collecting images at precise points in the ECG. All images collected are used, significantly reducing the imaging radiation dose.

Left:Comparison: (Left) Example of conventional robotic C-arm retrospective ECG gated acquisition (right) ACROBEAT acquisition.

The potential applications for this technology inform the main branches of our research:

-Cardiac imaging during interventional cardiology
-Motion Imaging: Adapting to more general motion of a patient for diagnostic imaging, eg joint movement.
-Cardiac motion in radiotherapy

How does PCI Work?

Patient Connected Imaging is a type of ‘imaging protocol’. Medical imaging systems have multiple protocols, – each for use in different scenarios. A helpful analogy is a Digital SLR Camera, with its different settings (protocols) for photographing portraits, landscapes, macro, indoor or outdoor scenes. Where a Digital SLR camera’s protocols have different aperture and white balance settings, the protocols for medical imaging might include the strength of the x-ray, the rotation speed of the gantry, the duration of the scan etc.

PCI utilizes two additional elements not currently used in conventional image acquisition protocols: the velocity of the gantry that rotates around the patient, and the time interval between each image (projection) being taken. These are the elements that are adapted by the patient’s respiratory trace, ECG or both in real-time.

Respiratory and cardiac signals (red & blue) inform when the projections (yellow) are taken.

Dr Tess Reynolds conducting image acquisition in the Hybrid Theatre, Charles Perkins Centre.

Current Status

Comprehensive theoretical in-silico studies have been completed and will be published before the end of 2018.

Experimental phantom studies in both imaging configurations (linac and robotic C-arm) are about to get underway. Here, a programmable dynamic phantom will be used to simulate the motion of a patient’s heart.


Research is taking place at our newest research node, the Charles Perkins Centre Hybrid Theatre. Opened in 2017 as part of the University’s Sydney Imaging facilities, the Hybrid Theatre contains our most recent major equipment acquisition, the Siemens Artis Pheno.

In the media

Physics World – a feature article about AAPM 2018 conference, highlighting ‘ACROBEAT’- one of our Patient Connected Imaging projects.



A/Prof Ricy O’Brien

Dr Tess Reynolds