NCT06281015

Artificial Intelligence and Bone Tomoscintigraphies Achieved With CZT Camera

Ultra-Fast Whole-Body Bone Tomoscintigraphies Achieved With a High-Sensitivity 360° CZT Camera and a Dedicated Deep Learning Noise Reduction Algorithm

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 19 (actual)
• Sponsor: Central Hospital, Nancy, France · Academic / Other
• Sex: All
• Age: 18 Years – 95 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Bone Lesion

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasis	Cancer patients referred to fast whole-body bone for detection or follow-up of bone metastasis were retrospectively included in this study.

Timeline

• Start date: 2023-08-30
• Primary completion: 2023-09-10
• Completion: 2023-10-30
• First posted: 2024-02-28
• Last updated: 2024-02-28

Locations

1 site across 1 country: France