Performance Study for InferRead CT Pneumonia.AI

NCT04955704 | Unknown FDA Device

• 1 other identifier: PNEUMONIA06142021
• Study Type: observational
• Target: 423
• Locations: 0 countries
• Sites: N/A

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.

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.AI DEVICE

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

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability 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.

Sponsors & Collaborators

• Infervision: lead
• University of Maryland, College Park: collaborator

MeSH Terms

Conditions

Pneumonia

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Lung Diseases; Respiratory Tract Diseases

Central Study Contacts

Frank Wu

CONTACT

8579981888; frank.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