10-Year lung study aims to create a 'Digital Twin' of your lungs
NCT ID NCT07517393
First seen Apr 13, 2026 · Last updated Jun 23, 2026 · Updated 8 times
Summary
This study will follow 1000 adults for up to 10 years, using a special type of CT scan (photon-counting) to look for lung nodules, tumors, and other lung conditions. Researchers will also use artificial intelligence to create a virtual copy of each person's lungs, called a 'digital twin,' to help study how lungs change over time. The goal is to better understand lung diseases and improve early detection.
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This is a summary of
the original study
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Locations
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Ospedale P. Pederzoli Casa di Cura Privata S.p.A.
RECRUITINGPeschiera del Garda, Verona, 37019, Italy
Contact Phone: •••-•••-•••• Email: •••••@•••••
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
What this could lead to
If successful, this could lead to better early detection of lung diseases and a 'digital twin' model to simulate lung behavior without invasive procedures.
What could go wrong
This is an observational study, not testing a treatment. The AI model may not be accurate enough, and results may take years to confirm.
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.