AI cuts radiation in lung scans while keeping image quality
NCT ID NCT07035977
First seen Jan 06, 2026 · Last updated Jun 20, 2026 · Updated 28 times
Summary
This study tested a deep-learning system called DeepPriorCBCT that aims to produce high-quality lung CT images using only one-sixth of the usual radiation dose. 138 adults getting a lung biopsy under CT guidance received both a standard-dose scan and a low-dose scan, and radiologists compared the image quality. The goal is to see if the AI can safely reduce radiation exposure without compromising the ability to spot lung nodules.
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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.
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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The First Affiliated Hospital East Campus of Zhengzhou University
Zhengzhou, Henan, China
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The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China
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Wuhan Union Hospital
Wuhan, Hubei, 430022, China
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Wuhan Union Jinyin Lake Hospital
Wuhan, Hubei, 430022, China
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Wuhan Union West Hospital
Wuhan, Hubei, 430022, China
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
DeepPriorCBCT deep-learning model for low-dose CBCT image reconstruction
What this could lead to
If successful, this could lead to safer, lower-radiation CT scans for diagnosing lung nodules without losing image quality.
What could go wrong
This is an early-stage validation study with 138 participants, so results may not apply to all patients or settings. The model may not match standard image quality in practice.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.