AI-Powered Ultra-Low radiation CT could revolutionize kidney stone diagnosis

NCT ID NCT04490343

Completed Diagnosis Sponsor: Centre Hospitalier Universitaire, Amiens Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tested whether an ultra-low-dose CT scan, combined with a deep-learning AI reconstruction, can accurately detect urinary tract stones. 62 adults with known or suspected kidney stones received both a standard low-dose CT and an additional ultra-low-dose scan (less than 1 mSv). The goal was to see if the AI-enhanced ultra-low-dose method matches the standard scan's accuracy while exposing patients to much less radiation.

What this could mean

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

Active substance: ultra-low dose CT with deep-learning image reconstruction
What this could lead to: If successful, this approach could allow doctors to diagnose kidney stones using much less radiation than standard CT scans.
What could go wrong: This is a small, completed study (62 people) testing a new imaging technique. The AI method may not work as well in all patients or settings, and further validation is needed.

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

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Conditions

The condition(s) this trial relates to.

Renal Colic Urinary Calculi urolithiasis

As listed by the trial registrant

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

DEEP LEARNING RECONSTRUCTION RENAL COLIC URINARY TRACT STONES UROLITHIASIS

Contacts and locations

Locations

CHU Amiens

Amiens, 80480, France

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