Artificial Intelligence and Bone Tomoscintigraphies Achieved With CZT Camera

NCT ID: NCT06281015

Last Updated: 2024-02-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

19 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-08-30

Study Completion Date

2023-10-30

Brief Summary

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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

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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

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Bone Lesion

Study Design

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Observational Model Type

OTHER

Study Time Perspective

RETROSPECTIVE

Interventions

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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.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* patients referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis
Minimum Eligible Age

18 Years

Maximum Eligible Age

95 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Central Hospital, Nancy, France

OTHER

Sponsor Role lead

Responsible Party

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Achraf BAHLOUL

Principal investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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CHRU Nancy

Vandœuvre-lès-Nancy, , France

Site Status

Countries

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France

Other Identifiers

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2023PI095-407

Identifier Type: -

Identifier Source: org_study_id

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