AI cuts radiation in lung scans by 83% in new study

NCT ID NCT07035977

Completed Diagnosis Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Source: ClinicalTrials.gov ↗

First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tested an AI system called DeepPriorCBCT that reconstructs lung CT images from very low radiation scans (one-sixth the usual dose). 138 participants each received both a low-dose and a conventional-dose scan. The goal was to see if the AI could produce images good enough for doctors to diagnose lung nodules. The study is complete, and results will show whether the AI can reduce radiation exposure without sacrificing image quality.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: DeepPriorCBCT model (AI software for image reconstruction)
What this could lead to: If successful, this AI could allow lung scans with much less radiation, making repeated imaging safer for patients.
What could go wrong: This is an early-stage validation study with 138 participants. The AI may not perform as well in real-world settings or with different equipment.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

LUNG NODULES

Contacts and locations

Locations

The First Affiliated Hospital East Campus of Zhengzhou University

Zhengzhou, Henan, China
The First Affiliated Hospital of Zhengzhou University

Zhengzhou, Henan, China
Wuhan Union Hospital

Wuhan, Hubei, 430022, China
Wuhan Union Jinyin Lake Hospital

Wuhan, Hubei, 430022, China
Wuhan Union West Hospital

Wuhan, Hubei, 430022, China

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