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NCT06782438: IATOS2

Evaluation of an Artificial Intelligence Algorithm Reducing Noise on Fast Whole-body Bone Tomoscintigraphy Acquisitions Recorded by a 360 Degree Cadmium-Zinc-Tellurid Camera

Recruiting now Last updated 4 March 2025
What this trial tests

trial testing artificial intelligence algorithm in Bone Scan in 20 participants. Currently enrolling.

Timeline
27 February 2025
Primary endpoint
15 March 2025
30 March 2025

Quick facts

Lead sponsorCentral Hospital, Nancy, France
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment20
Start date27 February 2025
Primary completion15 March 2025
Estimated completion30 March 2025
Sites1 location across France

Drugs / interventions tested

Conditions studied

Sponsor

Central Hospital, Nancy, France

Who can join

Adults 18 to 99, any sex, with Bone Scan. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Recently, artificial intelligence algorithms reducing noise by deep learning have been developed with application to SPECT and PET images. Many studies have reported the possibility of reducing the recording time in bone scintigraphy by applying artificial intelligence algorithms reducing noise

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360° CZT-camera.
    Bahloul A, Rajadhas F, Doyen M, Lamash Y, et al · · 2025 · PMID 41474536 · DOI 10.1186/s13550-025-01344-1

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Other Central Hospital, Nancy, France trials

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Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06782438.

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