RecruitingOBSERVATIONAL

AI & Radiomics for Stratification of Lung Nodules After Radically Treated Cancer

This study aims to improve how doctors understand new spots (nodules) found in the lungs of people who have already been treated for a different cancer. We're using advanced computer techniques, like artificial intelligence, to look at detailed scan images. The goal is to develop a tool that can help doctors quickly identify whether a lung nodule is harmless, a spread of the previous cancer, or a completely new lung cancer. This could lead to faster diagnoses and better treatment plans for patients.

At a glance

Status

Recruiting

Sponsor

Royal Marsden NHS Foundation Trust

Enrolment target

1,000

Start

13 Oct 2021

Estimated completion

01 Nov 2026

Indeterminate Pulmonary Nodules Lung Metastases Second Primary Cancer Lung Cancer

What is this study about?

When someone has been successfully treated for cancer, new spots can sometimes appear in their lungs. Finding one of these lung spots can be worrying, and it's often difficult for doctors to immediately tell if it's harmless, a new cancer, or a sign that the previous cancer has returned or spread. This challenge is important because people who have had cancer before are at a higher risk of developing another cancer compared to the general population.

This study is looking at how clever computer programs, known as artificial intelligence (AI) and 'radiomics', can help. Radiomics involves extracting lots of detailed information from medical scans, more than the human eye can easily see. We're teaching computers to recognise patterns in these lung spots on scans from people who have previously been treated for cancer. The idea is that these patterns might show whether the spot is harmless, a new lung cancer, or cancer that has spread.

The main aim is to develop a computer tool that could help doctors make quicker, more accurate decisions about these lung spots. This might mean knowing sooner which patients need more tests, like further scans or a biopsy, and which can be simply monitored. Ultimately, this could lead to earlier diagnosis of serious conditions and better outcomes for patients.

Key takeaways

Aims to improve diagnosis of lung spots in cancer survivors.
Uses advanced computer analysis (AI) of existing scans.
Hopes to tell if a spot is harmless, new cancer, or cancer spread.
Could lead to faster diagnosis and better treatment for future patients.
No new tests or active participation required from patients.
All patient data is kept anonymous and private.

Who may be eligible?

This study is looking at information from people who have previously had a solid cancer (like breast, bowel, or prostate cancer, but not blood cancers like leukaemia) that was treated with the aim of being cured, for example, through surgery, radiotherapy, or chemotherapy. This treatment must have happened within the last 10 years.

To be included, a new spot must have been found in their lung on a CT scan, and doctors must have eventually found out what that spot was (whether it was harmless, a new cancer, or cancer spread). Also, the CT scan images of the lung spot need to be very detailed, and the spot itself must be at least 5mm in size.

People would not be included if their original cancer treatment was more than 10 years ago, if they had a blood cancer, or if their original cancer had already spread to a few places (oligometastatic disease) when it was first treated and that spread was also treated radically.

Quick self-check

Have I had a solid cancer (not blood cancer) diagnosed and treated to cure in the last 10 years?
Was my cancer treated radically (e.g., surgery, strong chemo/radiotherapy)?
Was a new spot found in my lung on a CT scan, and doctors later figured out what it was?
Was the CT scan detailed, and the lung spot at least 5mm in size?

This is a guide only — the research team will confirm whether you can take part.

What does participation involve?

This is a "non-interventional" study, which means you will not be asked to do anything differently or have any extra tests. The researchers will be looking at existing medical records and scans that have already been collected as part of your routine care. There are no study visits, no medication, and no follow-up required from you. All your personal data will be made anonymous before any analysis takes place, so your privacy is protected. Your participation simply means that your past, anonymised scan information might contribute to this important research.

Potential risks and benefits

Because this study only uses existing, anonymised medical information and does not involve any direct patient contact or new procedures, there are no physical risks to participants. The potential benefit is that the knowledge gained from this study could help develop better tools for doctors to diagnose lung spots in people who have previously had cancer, leading to earlier and more effective treatments for future patients. You have the right to withdraw your anonymised data from the study if you wish, although as the data is de-identified, it may not be possible to remove it once anonymised.

Locations (2)

The Royal Marsden NHS Foundation Trust (Chelsea Site)
London, United Kingdom· Recruiting
Royal Brompton Hospital
London, United Kingdom· Recruiting

Common questions

What is a 'lung nodule'?

A lung nodule is simply a small spot or lump found in the lung on a scan. Most are harmless, but some can be cancer.

What is 'artificial intelligence' (AI) in this study?

AI refers to computer programs that can learn from patterns in medical images (like your scans) to help doctors make decisions, similar to how facial recognition works on phones.

Will this study affect my own medical care?

No, this study only uses past information and does not involve treating patients. It aims to improve care for future patients.

Is my personal information safe?

Yes, all data used in the study is made anonymous, meaning your identity cannot be linked to the information analysed.

Who is paying for this research?

The information provided does not specify the funding source for this research.

How to find out more

Sejal Jain

sejal.jain@rmh.nhs.uk 020 7808 2603 Official trial record

Always speak to your GP or specialist before deciding to take part in a study.