Clinical Validation of InferRead Lung CT.AI

July 27, 2020 updated by: Infervision
Lung cancer is the second most common cause of cancer-related death in men and women. Early pulmonary nodule screening is an effective means to prevent lung cancer, which is no less important than the diagnosis and treatment of lung cancer. Early lung cancer screening has been investigated and applied as a medical practice. InferRead Lung CT.AI by Infervision is a dedicated post processing application that generates CADe marks as an overlay on the original CT series intended to aid the radiologist in the detection of pulmonary nodules. This study was designed to evaluate radiologists' performance in detecting actionable nodules on chest CT when aided by InferRead.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

250

Contacts and Locations

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

Study Locations

  • United States
    • Maryland
      • Baltimore, Maryland, United States, 21201
        • University of Maryland Medical Center

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

55 years to 75 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Lung cancer screening eligible patients

Description

Inclusion Criteria:

  • Lung cancer screening eligible patients

Exclusion Criteria:

-

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-Crossover
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Detection accuracy
Time Frame: 20 hours
The primary objective of this clinical study is to demonstrate that a radiologist review of a CT scan aided with InferRead Lung CT.AI significantly improves detection of actionable lung nodules. Area under the ROC curve, Sensitivity, specificity, PPV, NPV will be reported, compared between unaided and aided reads.
20 hours

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Reading time change
Time Frame: 20 hours
The secondary objective of this clinical study is to demonstrate that the radiologist's review time is not significantly increased when aided with InferRead Lung CT.AI. The reading time for each case will be recorded in both aided and unaided reads. The reading times will be compared using a paired T test.
20 hours

Collaborators and Investigators

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

Sponsor

Infervision

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 (Actual)

January 10, 2019

Primary Completion (Actual)

June 1, 2019

Study Completion (Actual)

October 30, 2019

Study Registration Dates

First Submitted

October 7, 2019

First Submitted That Met QC Criteria

October 7, 2019

First Posted (Actual)

October 9, 2019

Study Record Updates

Last Update Posted (Actual)

July 28, 2020

Last Update Submitted That Met QC Criteria

July 27, 2020

Last Verified

July 1, 2020

More Information

Terms related to this study

Other Study ID Numbers

  • InferRead01

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

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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