Making cone beam CT imaging fit for aggressive targeting & adaptive re-planning of photon and proton radiotherapy

Radiotherapy is an important cancer treatment given to about 125,000 patients each year. It is typically delivered in daily doses (fractions) over a period of several weeks using multiple high energy X-ray (and now proton) "beams". The beams are individually shaped for each patient and designed to overlap at the precise location of the target disease. The intention is to give maximum dose to the cancer cells while minimising dose to nearby healthy tissues. Usual practice is to plan the arrangement and shape of these treatment beams based on CT images taken before treatment begins.

Ensuring that the patient and their tumour target are in the correct position for treatment on each day of their therapy is challenging. Small changes (more than a few millimetres) could invalidate the pre-treatment planning leading to the target receiving too low a dose of radiation (and hence reduced chance of cure) or healthy tissues receiving too high a dose of radiation (and hence increased chance of side effects).

The use of cone-beam CT (CBCT) imaging within the treatment room to check patient position, pose, and anatomy just before the radiation beams are switched on has recently become widespread. However, changes in patient shape can be complex, making it difficult to calculate whether the resulting change in radiation dose received will be significant - that is, will it be necessary to alter the pre-planned treatment to take account of the change?

Our aim is to simplify this decision process. We will develop a computerised method that uses a patient's CBCT image to calculate changes from their prescribed and planned dose. Currently this is not possible because calculation of radiation dose requires accurate data on tissue density within the patient, in order to determine how X-rays (or protons) will interact with their anatomy. Unlike CT images, which are used to generate the initial treatment plan, CBCT images do not give accurate information on tissue density.

This project will develop a method to "correct" the CBCT images so that the tissue density information that they contain can be used to directly compute delivered doses. This will be of significant benefit to radiotherapy patients since staff we be able to quickly check that the correct dose will be delivered, or if it is necessary to take action to avoid incorrect doses. Currently this process is very time consuming - tissue boundaries have to be manually drawn onto CBCT images and assumed density values assigned to each region. The technology we propose to develop will accelerate such assessments, estimated to be necessary for about one fifth of CBCT images. A further benefit is that our correction method not only restores accurate CBCT density values, but also markedly improves visual image quality. This makes images easier to interpret and more suitable for automatic analysis, with potential for further time savings.

The project builds on our previous work, where we have developed a correction method that appears to be effective for pelvic or head and neck images. We have acquired a UK patent for this invention, ensuring that benefits and value to the NHS can be maximised. In this project we propose to extend our method for use in lung images. This site is challenging due to the large differences in tissue densities present (lung, soft-tissue, bone), and the inherent respiratory motion. We will additionally investigate the suitability of corrected CBCT images for the planning of proton radiotherapy, a looming challenge as we move towards the opening of the first high-energy proton therapy centres in the UK.

In-treatment cone-beam CT (CBCT) imaging is widely used in radiotherapy (RT) to provide 3D anatomical data for patient positioning and tumour targeting. However, because of X-ray scatter, non-ideal detectors and large regions of interest, CBCT cannot be used for essential re-calculation of delivered X-ray or proton dose when anatomical changes are observed following pre-treatment planning and during daily delivery.

The proposers have previously developed and patented a software post-processing method to restore accurate tissue attenuation values in CBCT images by generation of an adaptive filter based on prior imaging. The method has proved successful for pelvic and head and neck images, which show marked improvements in visual image quality and numerical integrity for photon dose calculation. However this has not yet been achieved for thorax images, where it is particularly important to correctly account for differences in tissue attenuation due to the presence of highly variable tissue densities and of course physiological motion, primarily respiratory effects.

First we will consolidate these advances, specifically by developing streamlined software tools that make the method suitable for implementation in the clinical environment and subsequent commercialization. Then we will perform Monte Carlo modelling of patient and imaging processes to advance our methodology, particularly for challenging lung imaging. Finally, we will pilot the use of corrected in-room images to address the pressing but unmet need for in-treatment proton therapy monitoring and re-planning.

The resulting tools for correction of CBCT images will significantly reduce the time required to investigate the clinical impact of anatomical changes observed with CBCT (currently consuming a large amount of RT physics staff resource), and will pave the way for CBCT based adaptive photon and proton RT, where treatments are individually optimized mid-course based on imaging acquired on-treatment.

Beneficiaries:
Direct Immediate - radiotherapy departments, where CBCT imaging is used to verify accurate patient location for curative/radical treatment delivery e.g. ~60 radiotherapy centres in England, with around 300 radiotherapy linear accelerators, delivering external beam radiotherapy to 125,000 patients annually. It is estimated that 50% of machines used to deliver radiotherapy have capability for 3D on-treatment imaging (CBCT), although this proportion has increased rapidly since the technology was introduced in the mid 2000's, and is likely to continue increasing over the coming years.

Direct Medium/Long Term - the bulk of routine radiotherapy care is palliative and by comparison to radical treatments is relatively unsophisticated - rarely deemed worthy of full image guidance. Were corrected CBCT to become available at the treatment console it is likely that this will be used for more rigorously delivered irradiations that would be checked for dosimetric sparing of healthy tissues, thus providing a higher quality of remaining life.

Indirect - Restored/corrected wide angle CBCT has the potential to influence diagnostic radiology e.g. open access, single-arc scanning systems supplementing if not actually replacing the fan-beam CT scanner 'doughnuts' now seen in hospitals. Certainly our technology could be applied to the C-arm CBCT scanners that currently find limited bed-side use. Similarly, there is potential for use of our approach in dental scanning, where CBCT systems are replacing orthopantomographs.

The Benefits & Potential Contribution to the Nation's health:
Image guided adaptive radiation therapy (IGART) is recommended to be the future standard of care in the NHS. CBCT scans are the primary core technology upon which this ambition is founded, and so they must be developed to directly support accurate geometric targeting of and dose delivery to disease. Changes in patient external and internal geometry are observed both within a single treatment day and as treatment progresses. Indeed, a complete re-assessment of an individual's treatment plan is estimated to be necessary in about 1/5th of cases. At present this cannot be done on the CBCT images themselves. Our proposal aims to rectify this situation by making them 'fit for purpose', and in particular focuses on the large number of lung cancer cases where the dynamics of respiration are a particular challenge. The potential rewards are significant:

Accessibility to advanced healthcare: the reality is that the UK's recent and costly investment in modern photon therapy technology with CBCT image guidance, will serve our NHS hospitals for decades. The project will support the clinical 'pull' towards the new image guided treatment paradigms of (a) 'living with cancer', where we hunt down and precisely define/segment disease repeatedly whenever it recurs/metastases and (b) 'hitting hard & hitting fast' in the right place at the right dose to achieve cures with aggressive, individualised treatments.

Safer cancer treatment: The effective roll out of new and more sophisticated treatment paradigms are key to improved healthcare. Current treatments are assumed to be delivered to a pre-treatment, image-based plan. However, such an assumption for lung disease afflicted by motion right from the primary imaging stage through to repeated treatment delivery is highly questionable. At the moment generous 'tolerance' margins are required which can and do result in the expected therapeutic gains being diminished, lost, or worse patient damage.

Individualised therapy: Treatment pre-planning and the setup of multiple radiation beam aiming are undermined by almost total ignorance of patient dynamics during subsequent irradiation and the impact on carefully sequenced dose delivery, which is ubiquitously performed by the intricate superposition of multiple beamlets. Such precisely targeted therapy urgently needs live impact assessment of quantified delivered dose.