Artificial Intelligence and Bone Tomoscintigraphies Achie... | NCT06281015

Studies
Artificial Intelligence and Bone Tomoscintigraphies Achieved With CZT Camera

NCT06281015

Sponsor

Central Hospital, Nancy, France

Status

Completed

Last Update Posted

Feb 28, 2024Actual

Enrollment

19Actual

Phase

Not provided

Conditions

Bone Lesion

Interventions

Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasis

Countries

France

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Feb 2024

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Aug 30, 2023Actual

Primary Completion Date

Sep 10, 2023Actual

Completion Date

Oct 30, 2023Actual

First Submitted Date

Feb 20, 2024

First Submission Date that Met QC Criteria

Feb 20, 2024

First Posted Date

Feb 28, 2024Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Feb 20, 2024

Last Update Posted Date

Feb 28, 2024Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Achraf BAHLOUL, Principal investigator, Central Hospital, Nancy, FrancePrincipal Investigator

Lead Sponsor

Central Hospital, Nancy, FranceOTHER

Collaborators

Not provided

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

19Actual

Arms/Interventions Module

Arm Groups

Not provided

Interventions

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

Outcomes Module

Primary Outcomes

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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

95 Years

Standard Ages

AdultOlder Adult

Study Population

Nineteen cancer patients (8 women, 11 men) referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis were retrospectively included in this study.

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Not provided

Locations

Facility	Status	City	State	ZIP	Country	Contacts
CHRU Nancy		Vandœuvre-lès-Nancy		54511	France

Intervention Browse Module

MeSH Terms

ID	Term
D015899	Tomography, Emission-Computed, Single-Photon

Ancestor Terms

ID	Term
D014055	Tomography, Emission-Computed
D007090	Image Interpretation, Computer-Assisted
D003952	Diagnostic Imaging
D019937	Diagnostic Techniques and Procedures

Browse Leaves

Not provided

Browse Branches

Not provided