XneXt: Next generation X-ray digital imaging modules for healthcare: high resolution and sensitivity detection of dynamic scenes

Lead Research Organisation: University College London
Department Name: Medical Physics and Biomedical Eng

Abstract

The potential for rapid, computer assisted diagnostics and high precision, automated treatments, coupled with ever increasing patient numbers imposes big demands on healthcare technology. Image directed healthcare is a key component; the challenge is to develop faster, better, smarter technologies leading to optimised and application-specific information, rapid and reliable decision making and automated operation. X-ray imaging technology is widely used and heavily relied upon in many diagnostic and therapy departments to make major decisions. Yet the commercially available technology is basic and has limited capability; indirect phosphor plates and amorphous silicon imagers form the vast majority of commercial, clinical systems. CMOS technology is starting to come through but again with very basic capability and offer little more than film except digital convenience, often at lower image quality. This proposal aims to exploit the latest advances in smart CMOS imaging technology developed at the STFC Rutherford Appleton lab to make component sensors for next generation imaging directed healthcare. The developed technology is a high resolution, high speed, adaptive, radiation hard, x-ray imaging sensor for the clinic.
An x-ray imaging sensor capable of producing high frame rate, high quality images with a radiation hard technology has application in a variety of clinical applications. Such technology could potentially replace digital radiographic panels in radiology (amorphous silicon and phosphor plate), flat plane imagers in radiotherapy and image intensifiers in x-ray fluoroscopy. In each case end-users would benefit from a step change in both image quality (resulting from reduced noise, smaller pixels and higher dynamic range) and dynamic imaging capability (resulting from far superior read out / frame rates) as well as added capability and integration (resulting from Active Pixel Sensor technology and on-line processing). In the field of cancer management these properties lead to superior tumour delineation, increased 4D image quality for managing organ motion and real-time integration between the imager and the linac to enable genuine adaptive therapies.
University College London and the National Physical Laboratory will evaluate and exploit the benefits of the Rutherford Appleton Lab technology in three important yet diverse areas of medical imaging: cone beat CT imaging in the radiotherapy treatment room, managing organ motion during a radiotherapy lung cancer treatment and dual energy x-ray CT. The latter is in collaboration with National Physical Laboratory.

Planned Impact

Societal impact
The purpose of this project is to introduce a new technology to healthcare, in particular the management of cancer. In the UK approximately 1 in 3 people will receive treatment for cancer at some stage of their lives and in the vast majority of cases some x-ray imaging technology will be employed. In terms of patient numbers the impact of an advanced x-ray imaging technology is huge. The new x-ray imaging sensor can potentially form the basis of technology to replace any digital x-ray imaging sensor, of which there are a wide range of applications: from conventional x-ray imaging (the 'digital film') to x-ray fluoroscopy for live x-ray imaging to patient planning, positioning and verification during radiotherapy treatments. This project will focus on the latter to test and to demonstrate the capabilities of the technology.
Within radiotherapy, in-room x-ray CT imaging (cone beam CT) is important for checking that the patient is in the correct position and for verifying that the treatment that will be delivered is optimally planned; patients gradually change during their course of treatment and so the carefully planned radiation dose map may no longer closely match the tumour volume. This proposal aims to replace the current sensor technology within the cone beam CT system in order to improve image quality, achieve better dosimetric accuracy and enable a significant improvement in dynamic imaging. This can lead to a number of endpoints, such as 1. the introduction of genuine adaptive therapy, which is the imaging technology providing a real time feedback to the treatment delivery system to deliver the best possible treatment, 2. the ability to track tumour motion (e.g. lung tumours), and 3. an immediate and accurate decision on the need to replay the radiotherapy treatment. These endpoints will lead to increased dose conformability, i.e. better matching of the delivered dose map to the tumour volume, which in turn leads to greater confidence in the treatment delivery, the opportunity to introduce more radical treatment regimes and ultimately the chance to reduce secondary effects, such as induced secondary cancers.

Economic impact
Two primary economic factors apply: i. improved efficiency of a radiotherapy department, and ii. commercial sales of the sensors.
In the first case an increase in efficiency, caused by the introduction of automated technology, translates directly to an increase in patient throughput. Typically a cancer patient is in a radiotherapy treatment room for about 40 minutes. Of that time irradiating the patient with the treatment beam accounts for less than 10 minutes, the remainder is imaging and positioning the patient. Automating this process, which is feasible with Active Pixel Sensor CMOS imaging technology, can potentially halve the time per patient.
In the second case, sales of such technology could be significant. International guidelines recommend a minimum of 3 radiotherapy treatment machines per million of population. Large growth over the coming decade for radiation oncology is necessary and predicted, with new emerging markets gradually increasing the percentage of sales (from 30% to 40% in the last 5 years). The UK Department of Health recommends a growth from the 265 machines in 2011 to 459 by 2020 (Department of Health, Radiotherapy Services in England, 2012). On-board imaging capability in radiotherapy is now an acceptable standard, meaning that all current machines must be gradually upgraded for imaging technology. Our project partner, Elekta Oncology Systems, has ~32% of the global market share for linear accelerator sales with annual growth of 14%. Consequently, there is a significant market opportunity for sensor technology within this space.

Publications

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Ricketts K (2016) Clinical Experience and Evaluation of Patient Treatment Verification With a Transit Dosimeter. in International journal of radiation oncology, biology, physics

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Ricketts K (2016) Implementation and evaluation of a transit dosimetry system for treatment verification. in Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

 
Description We discovered that novel sensor technology can improve the ability to evaluate and verify the quality of a radiotherapy treatment delivered to a patient. Current technologies exist but the one developed during this grant has superior performance.
Exploitation Route We are currently taking the project forward in collaboration with the original project team and with clinical partners. We are working towards translating this technology to the clinic.
Sectors Healthcare

 
Description We are working towards implementing our findings in clinical radiotherapy.
First Year Of Impact 2019
Sector Healthcare
Impact Types Societal

 
Title Fast Monte Carlo modelling 
Description A novel way to calculate very fast simulations of radiation dose within the patient during a radiotherapy treatment. 
Type Of Material Model of mechanisms or symptoms - human 
Provided To Others? No  
Impact Still under development. Likely impact is near-real time estiamte of dose to the patient during radiotherapy delivery. This will provide better verification of the treatment quality. 
 
Description This project is done in collaboration with STFC Rutherford Appleton Laboratory. 
Organisation Elekta Inc
Country Sweden 
Sector Private 
PI Contribution We specified the clinical design criteria for medical imaging sensors designed and produced by Rutherford Appleton Laboratory, Subsequently we have tested their performance characterstics and benchmarked against competing technologies. In addition we have researched applications for these sensors in radiotherapy.
Collaborator Contribution Rutherford Appleton Lab have designed and fabricated novel CMOS imaging sensors. Elekta provides commercial guidance on the direction of the product.
Impact The work is undergoing. To date the sensors have been designed, fabricated and partially tested. Currently second level testing is on-going and new applications are being developed.
Start Year 2015
 
Description This project is done in collaboration with STFC Rutherford Appleton Laboratory. 
Organisation Rutherford Appleton Laboratory
Country United Kingdom 
Sector Academic/University 
PI Contribution We specified the clinical design criteria for medical imaging sensors designed and produced by Rutherford Appleton Laboratory, Subsequently we have tested their performance characterstics and benchmarked against competing technologies. In addition we have researched applications for these sensors in radiotherapy.
Collaborator Contribution Rutherford Appleton Lab have designed and fabricated novel CMOS imaging sensors. Elekta provides commercial guidance on the direction of the product.
Impact The work is undergoing. To date the sensors have been designed, fabricated and partially tested. Currently second level testing is on-going and new applications are being developed.
Start Year 2015
 
Title Fast dose reconstruction 
Description A software to simulate the radiation transport through the patient during a radiotherapy treatment, The software uses a new approach based upon novel optical transport methods. 
Type Of Technology Software 
Year Produced 2017 
Impact Still on-going. The software is at the testing stage. Once successfully validated we expect that we can deliver accurate dose estimates whilst the patient is on the couch to quality assess radiotherapy treatments.