Charles Sturt University: A Method and System for Automating Radiation Dose Parameters

Main content area
Publication Date: 
July 2017
Case study from: National Survey of Research Commercialisation

Description and benefits

The initiative is an algorithm that reduces patient exposure to radiation in a CT scan while maintaining image quality.

Medical X-ray computed tomography system (CT) imaging results in a high radiation dose to patients. Given concerns about potential health impacts of accumulated X-ray exposure, it is important that radiation dose to patients be minimised whilst maintaining an image quality that allows for patient diagnosis.

CT image quality is currently radiation dose dependent. A higher image quality generally means a higher radiation dose to patients. In CT scanners, both the image quality and dose to patients are dependent on a number of image acquisition parameters such as peak voltage, kVp, and exposure (mAs, or milliampere x second).

In general, the thicker the patient body, the less photons reach the photon detector (attenuation). The quantity of photons received by the photon detector impacts image “noise” (which by current international standards is an index for image quality). High numbers of photons received by the photon detector generate high quality images (i.e. low noise) whilst low numbers of photons received by the photon detector generate low quality images (i.e. high noise).

In prior art imaging devices, the exposure (photon flux) is increased or decreased during the CT scan in order to maintain the same noise level (i.e. the number of photons received by the detector is kept constant by varying exposure). Thus, prior art methods propose an automatic control of exposure in order to keep a constant noise level.

This invention proposes a novel method for automating the calculation of radiation parameters based on specific patient measurements rather than “noise”. The invention has the potential to fundamentally change the current approach to X-ray imaging.

The University is currently engaged in initial discussion with a major international manufacturer of CT scanners with a view to obtaining their support to conduct further research work and initial implementation of the invention. This research work may or may not be conducted in association with CSU, but in either case there would be an obligation for the company to provide full details of the research and the results. At the conclusion of the research, the company will be offered an option to license the invention.

Outcomes for the organisation, researchers, students and industry partners

The University will need to collaborate with an industry partners to commercialise this innovation. If successful, the University would obtain a commercial return from the innovation by way of licence fees paid by the licensee. A significant proportion of any commercial gain of this nature would be directed into funding for research and research infrastructure to allow other researchers and students to explore and develop their own novel ideas.

The researcher who developed this initiative would also receive a commercial benefit, in the form of share of the net commercial benefit received by the University as a result of commercialisation. The researcher has already published the findings in a well-respected journal and the success of this research will assist with the researcher’s standing, both within the University and as part of the scientific research community more broadly.

The industry partner will receive a commercial benefit from sales of the invention to end users. In addition, they will gain reputational benefits from the fact that the invention that is directed at improving patient welfare through reduced exposure to radiation.

It is also hoped that longer terms benefits to both the University and the industry partner would be generated by establishing a relationship and a dialogue that could form the basis for future collaborations.

Funding sources

To date the initiative and the associated investment in patent protection have been wholly funded by the University. Further research and development of the innovation will require industry partner funding. The relevant discipline areas are Medical Physics and Diagnostic Methods.

Significant milestones

Patent filed 27 July 2016