NCT04955704

Brief Summary

A retrospective, blineded, multicenter study of the InferRead CT Pneumonia.AI to evaluate the performance in identifying non-contrast chest CT scans containing pneumonia findings.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
423

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Sep 2021

Shorter than P25 for all trials

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

June 22, 2021

Completed
17 days until next milestone

First Posted

Study publicly available on registry

July 9, 2021

Completed
2 months until next milestone

Study Start

First participant enrolled

September 1, 2021

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

January 31, 2022

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

January 31, 2022

Completed
Last Updated

July 9, 2021

Status Verified

June 1, 2021

Enrollment Period

5 months

First QC Date

June 22, 2021

Last Update Submit

June 29, 2021

Conditions

Pneumonia

Outcome Measures

Primary Outcomes (1)

  • Primary Endpoint

    1. The Sensitivity (SE) of InferRead CT Pneumonia.AI is higher than 0.80. H0: YSE ≤ 0.80 HA: YSE \> 0.80 2. The Specificity (SP) of InferRead CT Pneumonia.AI is higher than 0.80. H0: YSP ≤ 0.80 HA: YSP \> 0.80

    1/1/2022 - 2/28/2022

Secondary Outcomes (1)

  • Secondary Endpoint

    1/1/2022 - 2/28/2022

Interventions

InferRead CT Pneumonia.AIDEVICE

InferRead CT Pneumonia.AI reads chest CT DICOM images from medical imaging storage devices and triages cases by detecting pneumonia lesions and then flagging suspected cases in the study list. InferRead CT Pneumonia.AI is a tool to assist clinicians and it does not replace the interpretation and diagnosis by clinicians.

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

This retrospective study will be used to assess the performance of the subject device. The principal investigator will collect DICOM data and relevant clinical information based on the selection criteria. DICOM will be de-identified of PHI and stored in a secure location. The validation dataset will contain non-contrast chest CT scans from patients in the United States that are either negative or have confirmed pneumonia (viral or bacterial). Data will come from at least 3 hospitals and cover a variety of data attributes.

You may qualify if:

  • Non-contrast chest CT DICOM scans
  • Contains both lung lobes
  • Slice thickness is less than 3 mm.

You may not qualify if:

  • Incomplete scan or corrupted scan
  • Irregular scanning, increased intrapulmonary density due to insufficient inspiration, and respiratory artifacts affecting the physician's judgment.
  • Altered or absent lung morphology in the postoperative patient.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Pneumonia

Condition Hierarchy (Ancestors)

Respiratory Tract InfectionsInfectionsLung DiseasesRespiratory Tract Diseases

Central Study Contacts

Frank Wu

CONTACT

8579981888frank.wu@infervision.ai

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
RETROSPECTIVE
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 22, 2021

First Posted

July 9, 2021

Study Start

September 1, 2021

Primary Completion

January 31, 2022

Study Completion

January 31, 2022

Last Updated

July 9, 2021

Record last verified: 2021-06