In Vivo Depiction Of Bone Vascularization With UHR-CT CT And Deep Learning Algorithm Reconstruction: A Preliminary Study

November 23, 2022 updated by: GILLET Romain, Central Hospital, Nancy, France
To evaluate the image quality and ability to depict in vivo bone vascularization with an ultra-high-resolution computed tomography (UHR-CT) scanner using a deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) algorithms, compared to simulated conventional CT, using osteoid osteoma (OO) as a model.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Anticipated)

20

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 70 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

retrospective inclusion of all histologically proven Osteoid Osteoma referred to our department for CT imaging

Description

Inclusion Criteria:

  • Proven osteoid osteoma
  • Ultra High Resolution CT

Exclusion Criteria:

  • None

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Case-Only
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of cortical vessels
Time Frame: Retrospective review of all ultra high resolution CT of the precedent 2 years
Number
Retrospective review of all ultra high resolution CT of the precedent 2 years
Number of nidus vessels
Time Frame: Retrospective review of all ultra high resolution CT of the precedent 2 years
Number
Retrospective review of all ultra high resolution CT of the precedent 2 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Confidence Score
Time Frame: Retrospective review of all ultra high resolution CT of the precedent 2 years
1 (weak) to 5 (strong)
Retrospective review of all ultra high resolution CT of the precedent 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Central Hospital, Nancy, France

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

December 20, 2022

Primary Completion (Anticipated)

January 31, 2023

Study Completion (Anticipated)

March 31, 2023

Study Registration Dates

First Submitted

October 28, 2022

First Submitted That Met QC Criteria

November 23, 2022

First Posted (Actual)

November 29, 2022

Study Record Updates

Last Update Posted (Actual)

November 29, 2022

Last Update Submitted That Met QC Criteria

November 23, 2022

Last Verified

November 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • N°2-RCB/EUDRACT

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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