DOLCE: Determining the Impact of Optellum's Lung Cancer Prediction Solution
Launched by NOTTINGHAM UNIVERSITY HOSPITALS NHS TRUST · May 20, 2022
Trial Information
Current as of July 25, 2025
Recruiting
Keywords
ClinConnect Summary
The DOLCE trial is studying how an artificial intelligence (AI) tool, called the Lung Cancer Prediction (LCP) solution, can help doctors make better decisions for patients with small lung nodules found during routine chest scans. These nodules can be solid or part-solid and measure between 5 and 30 millimeters. The goal is to see if using this AI tool provides better clinical outcomes and economic benefits compared to the usual care that patients currently receive.
To participate in this study, you need to be at least 35 years old and have a specific type of pulmonary nodule detected on a CT scan. However, if you have had a cancer diagnosis in the last five years, more than five nodules, or certain other conditions, you may not be eligible. If you join the study, you will be monitored to see how the AI tool influences your treatment decisions and outcomes. This trial is currently recruiting participants, and all genders are welcome to apply.
Gender
ALL
Eligibility criteria
- Inclusion Criteria:
- Patients are eligible for the study if all of the following apply:
- • Are aged 35 years or above
- * Have baseline CT study with at least one incidentally detected solid or part-solid (must have a solid component \>=80%) pulmonary nodule that:
- • is not fully calcified
- • Is 5-30mm inclusive in maximum axial diameter for the whole lesion measured using manual electronic callipers
- * Have baseline CT study that includes at least one series that meets all of the following (training for this will be provided):
- • Is of a type that meets VNC instructions for use
- • Comprises at least one full-inspiration breath-hold scans without a high degree of contrast media and does not exhibit quality issues (e.g., motion artefacts)
- Exclusion Criteria:
- Patients will be excluded from the study if any of the following apply:
- • Have received a diagnosis for cancer in the last 5 years
- • Have thoracic implants that impact the image appearance of the nodule
- • Have more than five reported pulmonary nodules of any size or type excluding fully calcified nodules (this criterion is used as a proxy due to the risk of being an infection or metastasis)
- * Have one or more additional nodules where any of the following applies:
- • Are already undergoing follow-up according to pulmonary nodule management standard care
- • Pure ground glass opacity (GGO) of \>=5mm in maximum axial diameter for the whole lesion measured using manual electronic callipers
- • \>30mm in maximum axial diameter for the whole lesion measured using manual electronic callipers
About Nottingham University Hospitals Nhs Trust
Nottingham University Hospitals NHS Trust is a leading healthcare provider in the UK, dedicated to delivering high-quality patient care and advancing medical research. Comprising two major hospitals, Queen's Medical Centre and Nottingham City Hospital, the Trust is at the forefront of clinical innovation and education. With a strong emphasis on translational research, Nottingham University Hospitals NHS Trust actively sponsors clinical trials aimed at improving treatment outcomes and understanding various health conditions. The Trust collaborates with academic institutions, healthcare professionals, and industry partners to foster a robust research environment that enhances clinical practice and contributes to evidence-based medicine.
Contacts
Jennifer Cobb
Immunology at National Institute of Allergy and Infectious Diseases (NIAID)
Locations
London, , United Kingdom
Leicester, , United Kingdom
Leeds, , United Kingdom
London, , United Kingdom
London, , United Kingdom
Nottingham, , United Kingdom
London, , United Kingdom
Oxford, , United Kingdom
Bangor, , United Kingdom
Derby, , United Kingdom
London, , United Kingdom
Frimley, , United Kingdom
Patients applied
Timeline
First submit
Trial launched
Trial updated
Estimated completion
Not reported
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