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| Name | Class |
|---|---|
| National Health and Medical Research Council, Australia | OTHER |
| Northern Sydney and Central Coast Area Health Service | OTHER |
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The goal of this observational validation study is to determine the best implementation of fluoroscopic and CT ventilation imaging in patients having non-stereotactic ablative body radiotherapy (non-SABR) radiotherapy for stages II-IV lung cancer. The main questions it aims to answer are:
Participants will:
Prior to radiation therapy treatment, patients will undergo:
Galligas PET ventilation images (control) are compared with ventilation images derived from additional scans (comparator) for each participant. Tc-99m MAA SPECT perfusion images (control) are compared with perfusion images derived from BHCT scans (comparator) for each patient.
There will be no change to patient treatment and patients will be treated using a standard of care anatomical based treatment plan. The pre-treatment 4DCBCT scan is part of standard of care.
Lung cancer is the leading cause of cancer mortality worldwide with non-small cell lung cancers (NSCLC) accounting for approximately 85% of all lung cancers diagnosed. Surgery, immunotherapy, chemotherapy, targeted therapy, and radiation therapy may be used alone or in combination for lung cancer treatment depending on the cancer staging. Radiation therapy is a primary component of lung cancer treatment with 77% of lung cancer patients having evidence-based indication for external beam radiotherapy at some point through their treatment journey.
Radiotherapy is associated with radiation-induced toxicities such as radiation pneumonitis and fibrosis that adversely impacts a patient's quality of life and limits the dose that can be safely delivered. Radiation pneumonitis is the inflammation of lung tissue with symptoms such shortness of breath, cough, and fever, manifesting 4 to 12 weeks following the completion of a radiotherapy course. Symptomatic pneumonitis, defined as grade 2 or higher, has an overall incidence of 29.8% with conventional radiotherapy.
Current radiotherapy treatment planning assumes that lung function is homogeneous throughout the organ and does not account for regional differences in lung function. These regional differences may arise from the cancer growth itself via tumour compression of lung structures, or from pre-existing, often smoking-induced factors which can also impact the lung health of cancer patients. Pre-existing conditions that can impact lung health include chronic obstructive pulmonary disease (COPD), fibrosis and thickening of the lymphatics in the lung, emphysema, asbestosis and partial lung collapse or side effects from previous cancer treatment such as fluid in the lungs, inflammation and pneumonitis, or even partial lung removal. In order to give patients the best quality of life after radiotherapy, it is crucial to preserve as much healthy lung as possible during the course of treatment.
Functional lung avoidance treatment planning for radiotherapy has the potential to reduce pulmonary toxicity by minimising irradiation of healthy lung tissue based on functional maps of the lung. Nuclear medicine functional lung images have been previously incorporated into radiotherapy treatment planning for the purposes of reducing mean doses to functional lung and hence radiation-induced toxicity. Normal tissue complication probability (NTCP) models have also predicted an overall reduction of 6% and 3% for grade 2+ and 3+ radiation pneumonitis, respectively, with functional planning while honouring dose constraints to the target and organs at risk.
Nuclear medicine scans are expensive, time consuming and not available in all institutions. CT ventilation imaging has been developed as a cheaper and more accessible alternative to nuclear medicine for mapping the healthy areas of the lung as part of routine pre-treatment CT acquisition.
The key steps in CT ventilation imaging are:
The resulting ventilation image is superimposed directly onto the anatomic image, providing an added dimension of functional information which is easy to understand and can be of direct benefit to radiotherapy treatment planning.
There are existing commercial products, CT Lung Ventilation Analysis Software and XV Technology Lung Ventilation Analysis Software (4DMedical Limited, Melbourne), for producing ventilation maps from CT scans and fluoroscopy imaging sequences. Unlike CT which produces one or more 3D images, fluoroscopy produces a fast sequence of 2D X-ray images. These images are usually acquired by dedicated C-arm scanners in radiology departments or surgical theatres and has not previously been assessed with relation to radiotherapy. Cine-fluoroscope sequences capturing at least one complete, continuous breath are acquired at five distinct angles across the chest during spontaneous breathing and a lung motion field is reconstructed to produce a ventilation map. As Therapeutic Goods Administration (TGA)-approved modalities of lung ventilation assessment, comparison of these techniques offers valuable insights into their robustness.
Functional lung avoidance treatment planning based on pre-treatment ventilation images can be compromised by interfraction (week-to-week) ventilation changes during treatment, such as those resulting from tumour regression. 4DCBCT allows convenient acquisition of anatomical images on the radiotherapy system to ensure accurate patient positioning prior to treatment delivery. Existing techniques developed for computed tomography ventilation imaging (CTVI) can be applied to 4DCBCT images to produce ventilation images that can be used to adapt treatment planning and minimise irradiation of healthy lung. However, 4DCBCT suffers from poor image quality and the physiological accuracy of 4DCBCT-based ventilation images remains to be assessed.
Previous studies have validated the physiological accuracy of CT ventilation imaging against the existing clinical gold standard Galligas PET ventilation imaging. These studies found strong correlation at the lobar level (several cm) and moderate positive correlations at the regional level (2 to 5 mm).
Clinical evidence for efficacy of the functional lung avoidance technique using CT ventilation images is beginning to be gathered. Vinogradskiy et al. performed a Phase II clinical trial, comparing radiation pneumonitis rates in a cohort treated with functional lung avoidance against historic controls. The authors found the rate of grade ≥2 radiation pneumonitis to be 14.9% of patients in the functional lung avoidance cohort, compared to an historical rate of 25%, reporting a positive trial outcome with a power of 80% and significance of 0.05. Using Xenon-enhanced CT ventilation, Huang et al performed a Phase II study comparing functional lung avoidance to historic controls. With a 17% rate of grade ≥2 radiation pneumonitis compared to the historical control of 30%, the authors also concluded a positive trial outcome with a power of 80% and significance of 0.05.
Despite this encouraging clinical evidence, there are still gaps in knowledge on assessing the best technical implementation of CT ventilation imaging, quality assurance of the process and the clinically acceptable threshold of accuracy required. To this end, the focus of our proposed clinical trial is to determine the best implementation of fluoroscopic and CT ventilation imaging. To achieve this, we will assess the physiological accuracy of different CT and fluoroscopy-based ventilation imaging techniques, using Galligas as a ground truth for true ventilation. Secondary aims of our study are to assess the dosimetric variation in functional avoidance radiotherapy plans produced using these ventilation imaging techniques, establish a quality assurance procedure for functional lung avoidance RT and to evaluate the clinical acceptable thresholds for accuracy of the method.
To compare the impact of functional lung avoidance planning on the radiation therapy treatment workflow, functional avoidance radiation therapy treatment plans will be created in addition to standard of care treatment plans and the difference in planning time quantified. The predicted reduction in radiation pneumonitis rates will be quantified using the method of Faught et al. and the predicted reduction in number of hospitalisations and medical costs will be calculated.
CT perfusion imaging methods have been recently developed to allow the computation of perfusion information from non-contrast inhale/exhale CT image pairs. CTPI is based on the principle that there is a mass change within the lung during the respiratory cycle due to changes in blood volume. Perfusion is derived from this mass change which is calculated at the voxel resolution using intensity-based material density estimates and spatial mapping between different CT images. Computed tomography perfusion imaging (CTPI) is a nascent technology that requires further validation of its accuracy. However, there is currently a lack of paired BHCT-perfusion datasets for validation. To date, the only validation study conducted by Castillo et al. reported a median correlation of 0.57 between CTPI and SPECT perfusion imaging.
The University of Sydney and Northern Sydney Local Health District have recently installed a new Total Body PET scanner at the Royal North Shore Hospital which can acquire scans in a single bed position with higher sensitivity, faster acquisition time, and longer scan length. The higher sensitivity of this new device allows faster imaging, including 4D (time series) images, giving more detailed ventilation information. To support this, an additional low-dose 4DCT scan, across the lungs only rather than the full scan length, will be acquired in pre-treatment imaging for the purpose of investigating 4D attenuation correction.
Choice of comparators Control
Comparators
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| Measure | Description | Time Frame |
|---|---|---|
| Physiological accuracy of X-ray-based ventilation imaging (BHCT, fluoroscopy, 4DCBCT, 4DCT) | Voxel-based Spearman correlation between X-ray-based ventilation imaging and nuclear medicine ventilation images (Galligas PET) | 1 week |
| Measure | Description | Time Frame |
|---|---|---|
| Difference in mean dose to high functioning lung structures between avoidance treatment plans and standard of care anatomical based treatment plans. | Difference in mean dose delivered to high functioning lung structures | 1 week |
| Difference in percentage volume of high functioning lung structures receiving 20 Gray (20Gy) or more between functional lung avoidance treatment plans and standard of care anatomical based treatment plans. |
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Inclusion Criteria:
Exclusion Criteria:
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Patients having non-SABR radiotherapy for stage II-IV lung cancer at Northern Sydney Cancer Centre, Sydney Australia.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Clinical Trial Coordinator | Contact | +61 2 8627 1185 | Shona.Silvester@sydney.edu.au |
| Name | Affiliation | Role |
|---|---|---|
| Ricky O'Brien | University of Sydney | Study Chair |
| Dasantha Jayamanne | Northern Sydney Local Health District | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Royal North Shore Hospital | Recruiting | St Leonards | New South Wales | 2065 | Australia |
After study completion, to maximise the scientific and clinical use of individual participant data (IPD) they will be made available to researchers for further scientific research. It will be stored at the University of Sydney and is likely to also be stored at an external research data repository archive or register, e.g. The Cancer Imaging Archive, and made publicly available. They may also be used in imaging scientific challenges, similar to previously scientific grand challenges we have led such as the SPARE and MATCH challenges.
After study completion and results published, IPD will be available indefinitely.
IPD stored at the university: To download / decompress IPD, participating researchers will agree to the terms of use for the data, including that the data are not to be published or otherwise redistributed without the express consent of the original investigator(s).
IPD stored at an external repository: IPD will be stored at and managed by the external repository. IPD will only be shared with repositories whose function has been reviewed and approved by an accredited Research Integrity/Ethics Committee/Board.
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| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| D011658 | Pulmonary Fibrosis |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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Difference in percentage volume of high functioning lung structures receiving 20Gy or more. |
| 1 week |
| Reduction in predicted risk of grade 2+ radiation pneumonitis (CTCAE v5) in functional lung avoidance treatment plans compared to standard of care anatomical based treatment plans. | Reduction in grade 2+ radiation pneumonitis rates quantified using Normal Tissue Complication Probability (NTCP) models. | 1 week |
| Increased burden in the radiotherapy workflow involved with creating functional lung avoidance treatment plans. | Time required to conduct the additional imaging, produce the ventilation image, and creating the functional treatment plan. | 2 weeks |
| Change in ventilation from lung radiation therapy. | Voxel-based Spearman correlation. Pre- and post-treatment X-ray-based ventilation images will be compared to pre- and post-treatment Galligas PET ventilation scans. | 8 weeks |
| Physiological accuracy of CT perfusion imaging | Voxel-based Spearman correlation between CT perfusion imaging and nuclear medicine perfusion images (Tc-99m MAA) | 1 week |
| Improvement in 4D PET image reconstruction using 4D attenuation CT | Quantification of PET signal within the lung | 1 week |
| D008171 |
| Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D017563 | Lung Diseases, Interstitial |
| D005355 | Fibrosis |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |