COVID-19 Volumetric Quantification on Computer Tomography Using Computer Aided Diagnostics

NCT05282056 | Completed

• 1 other identifier: 282/01.02.2022
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of the study is to asses the influence of computer aided diagnostic to the process of lung affection quantification on computer tomography in COVID-19 confirmed patients.

Conditions

COVID-19

Keywords

CAD; AI; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Mean difference of lung affection quantification percentage

  The objective measurement of lung affection percentage is measured against pixel level labels. A lower difference mean better outcome.

  At CT acquisition time, up to 2 weeks

Study Arms (2)

CAD analysis

EXPERIMENTAL

The XVision COVID-19 computer aided diagnostic software is used by radiologist at CT analysis time

Diagnostic Test: CAD analysis

No CAD analysis

NO INTERVENTION

No CAD analysis is shown to radiologist.

Interventions

CAD analysis DIAGNOSTIC_TEST

CAD shows the radiologist automatically delineated areas of potential COVID-19 affection, together with an overall lung affection percentage.

CAD analysis

Eligibility Criteria

• Age: 16 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• RT-PCR confirmed patients of COVID-19

You may not qualify if:

• or lower

Sponsors & Collaborators

• Bogdan Bercean: lead
• Pius Brinzeu Timisoara County Emergency Hospital: collaborator

Study Sites (1)

Pius Brinzeu Timisoara County Emergency Hospital

Timișoara, Timiș County, Romania

Location

Related Publications (1)

• Bercean BA, Birhala A, Ardelean PG, Barbulescu I, Benta MM, Rasadean CD, Costachescu D, Avramescu C, Tenescu A, Iarca S, Buburuzan AS, Marcu M, Birsasteanu F. Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial. Sci Rep. 2023 Mar 25;13(1):4887. doi: 10.1038/s41598-023-31910-3.

  PMID: 36966179 DERIVED

MeSH Terms

Conditions

COVID-19

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: The random assignment is done automatically by the CAD system and is not visible to the patient. The radiologist obviously sees which cases have CAD analysis and which not.
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Head of Artificial Intelligence

Model Details: CAD outputs are turned off for randomly chosen 50% of patients, which represent the control group. The other 50% are analysed using CAD

Study Record Dates

• First Submitted: March 14, 2022
• First Posted: March 16, 2022
• Study Start: February 24, 2022
• Primary Completion: March 15, 2022
• Study Completion: March 15, 2022
• Last Updated: May 4, 2022

Record last verified: 2022-05

Locations

RO (1)