AI Performance for the Detection of Bone Fractures in Chi... | NCT05538403

Studies
AI Performance for the Detection of Bone Fractures in Children

NCT05538403

Sponsor

University Hospital, Montpellier

Status

Unknown status

Last Update Posted

Sep 13, 2022Actual

Enrollment

210Estimated

Phase

Not provided

Conditions

Fracture

Interventions

Not provided

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

Sep 2022

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

May 1, 2022Actual

Primary Completion Date

Nov 1, 2022Estimated

Completion Date

Dec 30, 2022Estimated

First Submitted Date

Sep 9, 2022

First Submission Date that Met QC Criteria

Sep 9, 2022

First Posted Date

Sep 13, 2022Actual

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

Sep 9, 2022

Last Update Posted Date

Sep 13, 2022Actual

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

The artificial intelligence (AI) software BoneView (GLEAMER Company, Paris, France) has been designed, tested and validated to detect and locate recent or semi-recent fractures on standard radiographs.

The objective will be to assess the AI performance for the detection of bone fractures in children aged less than 2 years old in suspected child abuse setting.

These patients benefit from a whole body radiography with a double blind reading by a "generalist" radiologist and a radiologist with expertise in child abuse. This readings will be compared with the AI results.

Hypothesis is that AI is effective for child fractures detection and could be of help especially for radiologists who are not experts in child abuse.

Detailed Description

Not provided

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

210Estimated

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Percentage of fracture detected by AI on radiographs	Percentage of fracture detected by AI on radiographs	1 day

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion criteria:

aged less than 2 years old
whole body radiography performed for suspected child abuse setting
report available with a double blind reading (generalist radiologist and radiologist with expertise in child abuse)

Exclusion criteria:

Radiograph not interpretable ( poor quality)
AI not applicable

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

0 Years

Maximum Age

2 Years

Standard Ages

Child

Study Population

Children aged less than 2 years old in suspected child abuse setting

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Ingrid Millet, PUPH	Contact	678887174	33	i-millet@chu-montpellier.fr

Overall Officials

Name	Affiliation	Role
Ingrid Millet, PUPH	University Hospital, Montpellier	Study Director

Locations

Facility	Status	City	State	ZIP	Country	Contacts
University hospital	Recruiting	Montpellier		34295	France

IPD Sharing Statement Module

Plan to Share IPD

Undecided

Description

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D050723	Fractures, Bone

Ancestor Terms

ID	Term
D014947	Wounds and Injuries

Browse Leaves

Not provided

Browse Branches

Not provided