Artificial Intelligence and Bone Tomoscintigraphies Achieved With CZT Camera

Completed

• Conditions: Bone Lesion

• Registration Number: NCT06281015
• Lead Sponsor: Central Hospital, Nancy, France

Brief Summary

This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 minutes, routinely provided by a high-sensitivity 360 degrees cadmium and zinc telluride (CZT) camera, can be further reduced by a deep learning noise reduction (DLNR) algorithm.

Detailed Description

This study aimed to determine the extent to which fast whole-body bone-SPECT recording times, routinely obtained with a high-sensitivity 360 degrees CZT-camera and rather low injected activities, can be further reduced using the DLNR algorithm.

Study Timeline

• Study Start: 2023-08-30
• Primary Completion: 2023-09-10
• Study Completion: 2023-10-30
• Status Verified: 2024-02
• Study First Submitted: 2024-02-20
• Study First Submitted QC: 2024-02-20
• Last Update Submitted: 2024-02-20
• Study First Posted: 2024-02-28
• Last Update Posted: 2024-02-28

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 19

Inclusion Criteria

• patients referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis

Exclusion Criteria

Not provided

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Assess a dedicated deep learning noise reduction algorithm	one day	A deep learning noise reduction algorithm was applied on whole-body images recorded

Trial Locations

Locations (1)

CHRU Nancy; 🇫🇷 Vandoeuvre les Nancy cedex, France