Unlocking the future of lung cancer screening: How DART is redefining early diagnosis
When it comes to the battle against lung cancer, early detection is the key to saving lives. But what if there were a way to transform the diagnostic process and make it more accessible? That is what we’re trying to achieve through our research programme funded by Innovate UK and Cancer Research UK (CRUK) and commercial companies GEHC, Optellum and Roche Diagnostics.
What is DART?
DART is an ambitious initiative focused on harnessing the power of artificial intelligence (AI) to transform the way we diagnose lung cancer. We collaborate with lung health checks across the UK collecting invaluable data to develop AI algorithms that will redefine early diagnosis and, ultimately, save lives.
The urgent need for early diagnosis
Lung cancer is often a silent predator, revealing its presence only when it’s reached an advanced stage. By then, treatment becomes far more challenging, and the prognosis can be bleak. The key to improved outcomes lies in diagnosing lung cancer at stage one and two when treatment options are more effective and less invasive.
The power of big data
One of DART’s distinguishing features is the scale of our data collection. While the other largest dataset in the world comprises of 28,000 CT scans, often performed on older machines, the DART dataset has already surpassed that figure. But that’s just the beginning. Our vision is to grow this dataset to a quarter of a million CT scans, making it ten times larger than the current world’s largest lung cancer screening dataset.
A collaborative approach
DART thrives on collaboration. It brings together diverse teams, combining imaging and data, to improve the decision-making process for radiologists. By analysing vast amounts of patient data, they aim to predict outcomes for different patient groups, helping medical professionals make more informed decisions.
Maintaining privacy and ethical standards
Patient privacy and data security are top priorities for us. We employ de-identification methods to protect patient information and ensure that data users don’t inadvertently access sensitive details. This approach safeguards both patients and researchers.
The future of lung cancer screening
We believe that AI will play a pivotal role in the future of lung cancer screening. With the responsibility to design lung cancer screening for the next generation, we aim to make a global impact by facilitating early diagnosis and improving patient care worldwide – which is the most extraordinary opportunity.
We hope our innovative approach to lung cancer diagnosis will change the landscape of early detection and save countless lives in the process.
Have your say
The DART project is about using data to better predict lung cancer so it can be treated earlier.
The project invites those in any way affected by lung cancer or lung cancer screening to advise us on the best ways to tell those attending lung cancer screening how their data is being used. We are planning to hold an advisory focus group by video conference on Wednesday 23rd November and invite those whose lives have been affected in any way by lung cancer to join us. Your input will make a valuable contribution to the project by ensuring we are clear about what data is collected and how it is used. If you are interested, please email DART Lung Health Project email@example.com.
The NHS Lung Health Check is a service that is running in some parts of England. It aims to help diagnose lung cancer at an earlier stage when treatment may be more successful.
People are invited for a lung health check if they:
are aged between 55 and 75
are registered with a GP
have ever smoked
live in an area where the checks are being done
Those at a higher risk of lung cancer have a CT scan. If the scan shows any abnormal areas (nodules), there may be further scans, tissue samples or surgery. This is to check if the area is cancer or not. In most cases it isn’t but in a small number of people it is.
DART researchers want to use information from scans and other test to further improve the early diagnosis and treatment of lung cancer, leading to better survival rates.
This study is collecting and using data (clinical records and copies of scans and biopsy/resection slides) from over 500,000 participants in these lung health checks. We ask you to advise us on how you feel about DART collecting data after patient treatment and without direct consent, if the documents provided to patients make it clear enough how to request not to be included in the study and how you feel about commercial companies using the data to develop methods to improve recognition of lung diseases. Copies of the documents will be circulated to those interested before the meeting.
World Lung Cancer Day 2022
On World Cancer Day 2022, read how Optellum is working to change the survival rates for lung cancer with an innovative AI platform.
DART is pleased to be partnering with Optellum and others to build and strengthen Artificial Intelligence algorithms for the early diagnosis of lung cancer and other lung conditions. Here Optellum describe their efforts to redefine early intervention of diseases like lung cancer, by enabling every clinician, in every hospital, to make the right decisions and give their patients the best chance to fight back.
Portsmouth encourages participation in Lung Health Checks
People over 55 but younger than 75 who have ever smoked are being offered a free lung health check. See a video here or read NHS news items here and here.
This is part of an expanding lung cancer screening programme.
Registration with ISRCTN
DART has been registered with ISRCTN, using ID 13720905
This includes a Plain English summary under the title “Providing data so computer systems can help with the early identification of lung diseases, leading to more rapid treatment and better survival rates”.
Registration with ISRCTN is the first step towards trial transparency and the future dissemination of health research outcomes. Its key aim is to ensure that all healthcare decisions are informed by all of the available evidence, thus, overcoming publication bias and selective reporting. Registration provides opportunities for collaboration and reduces duplication of research efforts; it also improves awareness of trials for clinicians, researchers, patients and the public.
Optellum attains CE marking in Europe
DART partner Optellum has attained CE marking in Europe.
This latest certification will allow for use in the European Union (EU) and the United Kingdom (UK), and opens the door to a European expansion for the growing company. It is the latest milestone for Optellum, which received FDA 510(k) clearance in early 2021 as the first AI-assisted diagnosis application for lung cancer. You can read the full press release online here.
In addition, researchers from the University of Oxford and Oxford University Hospitals NHS Foundation Trust (OUH) have published the results of an academic study in European Radiology which takes a closer look at the Optellum Lung Cancer Prediction (LCP) model. You can read the full story on Optellum’s website here.
Approvals and adoption
DART is very pleased that the project has been adopted onto the NIHR portfolio and is therefore deemed eligible for NIHR Clinical Research Network support. Further information about CRN support can be found on the NIHR website.
The 15 Local Clinical Research Networks (LCRN) cover the length and breadth of England and are available to coordinate and support the delivery of research across the NHS in England.
Health Research Authority HRA
DART has had confirmation that HRA and Health and Care Research Wales (HCRW) Approval has been given for the study, on the basis described in the application form, protocol, supporting documentation and clarifications requested and received.
DART has also had notification of Confidentiality Advisory Group (CAG) conditional support, as per the excerpt from their letter below.
“The role of the Confidentiality Advisory Group (CAG) is to review applications submitted under these Regulations and to provide advice to the Health Research Authority on whether application activity should be supported, and if so, any relevant conditions. This application was considered at the CAG meeting held on 10 February 2022.
Health Research Authority decision
The Health Research Authority, having considered the advice from the Confidentiality Advisory Group as set out below, has determined the following:
The application, to allow the disclosure of confidential patient information from participating trusts to the Oxford University Hospitals NHS Foundation Trust, is conditionally supported, subject to compliance with the standard and specific conditions of support.
Please note that the legal basis to allow access to the specified confidential patient information without consent is now in effect.”
The conditions of support allow for the project to proceed as planned and will be addressed by mid-May 2022. DART will comply with the HRA annual review.
CAG reference: 22/CAG/0010
IRAS project ID: 301420
REC reference: 21/WM/0278
Optellum receives FDA clearance for Virtual Nodule Clinic
DART partner Optellum receives FDA clearance for the world’s first AI-powered clinical decision support software for early lung cancer diagnosis
Virtual Nodule Clinic empowers clinicians to make optimal clinical decisions in early-stage lung cancer diagnosis and is now commercially available in the United States.
DART partner Optellum, a lung health company aiming to redefine early diagnosis and treatment of lung disease, has received clearance from the FDA for its Virtual Nodule Clinic.
This revolutionary product is an AI-powered clinical decision support software for pulmonologists and radiologists managing patients with small lesions in the lungs – nodules – that could represent early-stage lung cancer. This is the first such application of AI decision support for early lung cancer diagnosis cleared by the FDA.
Lung cancer kills more people than any other cancer. The current five-year survival rate is an abysmal 20%, primarily due to the majority of patients being diagnosed after symptoms have appeared and the disease has progressed to an advanced stage (Stage III or IV).
By comparison, the survival rate for small tumours treated at Stage IA is up to 90%.
Up to two million US patients a year are identified as having lung nodules through chest CT scans. Current guidelines mandate follow-up over one to two years to determine whether a nodule is cancerous. However, over 60% of these patients do not receive guideline-recommended follow-ups, severely limiting opportunities for early intervention and treatment. Patients who do receive recommended follow-up often require multiple imaging scans and biopsies, and sometimes unnecessary invasive procedures including surgical biopsies and lung resections, before arriving at a definite diagnosis.
Virtual Nodule Clinic
Optellum’s Virtual Nodule Clinic is designed to solve this problem by enabling pulmonologists to identify and track at-risk patients with suspicious lung nodules and make optimal clinical management decisions for those patients. The software features a clinically validated Lung Cancer Prediction (LCP) score designed to empower clinicians to more accurately and consistently evaluate lung cancer risk and make more optimal clinical decisions that could save more patient lives.
Optellum’s LCP score is powered by the world’s first FDA-cleared imaging AI/”Radiomics”-based digital biomarker for lung cancer. The score is computed from full patterns of 3D pixels in standard images captured by Computed Tomography (CT) scanners, which are already available and the standard of care in every modern hospital.
Physician use of Virtual Nodule Clinic is shown to improve diagnostic accuracy and clinical decision-making. In the clinical study which underpins the FDA clearance, all readers in the study, which included pulmonologists and radiologists of various levels of expertise, from generalists to experts, showed a statistically significant improvement in their accuracy for diagnosing lung nodules when using the Optellum software.
Optellum is a commercial-stage lung health company providing Artificial Intelligence decision support software that assists physicians in early diagnosis and optimal treatment for their patients. The company was founded so that every lung disease patient is diagnosed and treated at the earliest possible stage when chances of cure are the highest. Optellum has headquarters at the Oxford Centre for Innovation in Oxford, United Kingdom and a US office at the Texas Medical Center in Houston, TX.
The Optellum Virtual Nodule Clinic AI model is being trialled on Lung Cancer Screening (LCS) data, and an automated workflow is being developed to support implementation into clinical practice.
LCS project objectives
Model development and integration: where the existing algorithm is integrated into the LCS workflow to include automated detection and quantification.
Integration of clinical risk parameters and model calibration for UK lung screening population. The model will be extended by including the clinical risk parameters and Optellum will calibrate the resulting model for the UK LCS population to identify the threshold values entry into the various pathways.
Clinical Data Collection and Prospective Validation: the system developed earlier in the work package will be rolled out to the participating trusts and will undergo prospective clinical and health economic validation for every subsequent screening patient. Roche Diagnostics will work to ensure the enablement of the data models for point-of-care software deployment and utilization.
AI algorithm outputs are being validated using the same trial protocol currently in use for testing Optellum’s algorithm in an incidental pulmonary nodule NHS setting (IDEAL). This will lead to easy adoption into the NHS if the trials are successful.
UKRI announces £11 million funding for DART lung health project
DART (the Integration and Analysis of Data Using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases) is the latest project to join the NCIMI programme.
UK Research and Innovation, Cancer Research UK and industry are investing more than £11 million in an Oxford-led artificial intelligence (AI) research programme to improve the diagnosis of lung cancer and other thoracic diseases
Professor Fergus Gleeson at the University of Oxford will lead on a programme of research focusing on accelerating pathways for the earlier diagnosis of lung cancer. Lung cancer is the biggest cause of cancer death in the UK and worldwide, with £307 million/year cost to the NHS in England.
The earlier that lung cancer is diagnosed, the more likely that treatment will be successful but currently only 16% patients are diagnosed with the earliest stage of the disease. To address this clinical problem, NHS England is launching a £70 million lung cancer screening pilot programme at 10 sites.
To improve patient care beyond the current screening guidelines, a team of academics from Oxford University, Nottingham University, and Imperial College London; NHS clinicians from Oxford University Hospitals NHS Trust, Nottingham University Hospitals NHS Trust, the Royal Marsden Hospital, the Royal Brompton Hospital, and University College London Hospitals NHS Foundation Trust; and the Roy Castle Lung Cancer Foundation will join forces with three leading industrial partners (Roche Diagnostics, GE Healthcare, Optellum).
Working with the NHS England Lung Health Check programme, clinical, imaging and molecular data will be combined for the first time using AI algorithms with the aim of more accurately and quickly diagnosing and characterising lung cancer with fewer invasive clinical procedures. Algorithms will also be developed to better evaluate risks from comorbidities such as chronic obstructive pulmonary disease (COPD).
In addition, this programme will link to data from primary care to better assess risk in the general population to refine the right at-risk individuals to be selected for screening. It is hoped that this research will define a new set of standards for lung health and cancer screening to increase the number of lung cancers diagnosed at an earlier stage, when treatment is more likely to be successful.
DART and NCIMI
This programme builds on the National Consortium of Intelligent Medical Imaging (NCIMI) at the Big Data Institute in Oxford, one of five UK AI Centres of Excellence.
The funding, delivered through UK Research and Innovation’s (UKRI’s) Industrial Strategy Challenge Fund, is part of over £13m government investment in ‘data to early diagnosis and precision medicine’ for the research, development and evaluation of integrated diagnostic solutions. UKRI is also partnering with Cancer Research UK, which is making up to a £3m contribution to the cancer-focused projects. The Oxford-led project is one of six awarded from this competition.