NCT05992324

Brief Summary

The purpose of this study is to assess the efficacy of Caption LungAI.

Trial Health

57
Monitor

Trial Health Score

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

Trial has exceeded expected completion date
Enrollment
220

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Jul 2023

Geographic Reach
1 country

4 active sites

Status
recruiting

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

Study Start

First participant enrolled

July 17, 2023

Completed
14 days until next milestone

First Submitted

Initial submission to the registry

July 31, 2023

Completed
15 days until next milestone

First Posted

Study publicly available on registry

August 15, 2023

Completed
1.4 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2024

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

March 1, 2025

Completed
Last Updated

November 26, 2024

Status Verified

November 1, 2024

Enrollment Period

1.5 years

First QC Date

July 31, 2023

Last Update Submit

November 22, 2024

Conditions

Shortness of Breath

Keywords

Lung UltrasoundB-LinesPOCUS by non-expert user

Outcome Measures

Primary Outcomes (4)

  • Diagnostic Image Quality (Trained Healthcare Professional)

    Evaluate the product's ability to assist the user to capture a LUS image with diagnostic quality. Percentage of zones with diagnostic image quality \> 0.80

    Up to 24 weeks from completion of the study.

  • B-Lines Detection

    Evaluate the product's ability to retrospectively detect present B-lines on images acquired by a local expert with no Caption Lung AI assistance. AUROC \> 0.80; Sensitivity (Se) \> 0.80; Specificity (Sp) \> 0.75

    Up to 24 weeks from completion of the study.

  • B-Line Significance

    Evaluate the product's ability to retrospectively detect B-lines of significant severity on images acquired by a local expert with no Caption Lung AI assistance. AUROC \> 0.80; Sensitivity (Se) \> 0.80; Specificity (Sp) \> 0.75

    Up to 24 weeks from completion of the study.

  • Remote Reader Performance

    Evaluate the product's impact on a remote expert reader's ability to interpret LUS images. Difference Between Aided \& Unaided Groups: AUROC \> 0.00; Sensitivity (Se) \> 0.00; Specificity (Sp) \> 0.00

    Up to 24 weeks from completion of the study.

Secondary Outcomes (1)

  • Sub-group Analyses

    Up to 24 weeks from completion of the study.

Study Arms (1)

Patients presenting with clinical suspicion of B-Lines

EXPERIMENTAL

Patients will undergo two 8-zone protocol lung ultrasound exams. One exam will be conducted by an expert lung ultrasound user without Caption LungAI and will last approximately 5-10 minutes. The second exam will be conducted by a healthcare professional with Caption LungAI and will last approximately 15-20 minutes.

Device: Caption LungAI

Interventions

Caption LungAIDEVICE

Caption LungAI is a software that is designed to help non-expert healthcare professionals acquire diagnostic quality images on an 8-zone lung protocol for both healthy patients and patients presenting with pathology such as B-Lines.

Patients presenting with clinical suspicion of B-Lines

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Patients over the age of 18
  • Patients presenting to the hospital or outpatient setting with shortness of breath and suspected B-lines.

You may not qualify if:

  • Patients in extremis/in whom a research lung ultrasound would not normally be performed due to other priorities

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (4)

Yale New Haven Hospital

New Haven, Connecticut, 06510, United States

RECRUITING

Northwestern University

Chicago, Illinois, 60611, United States

COMPLETED

Rush University Medical Center

Chicago, Illinois, 60612, United States

COMPLETED

The Moses H. Cone Memorial Hospital

Greensboro, North Carolina, 27401, United States

COMPLETED

Related Publications (1)

  • Baloescu C, Bailitz J, Cheema B, Agarwala R, Jankowski M, Eke O, Liu R, Nomura J, Stolz L, Gargani L, Alkan E, Wellman T, Parajuli N, Marra A, Thomas Y, Patel D, Schraft E, O'Brien J, Moore CL, Gottlieb M. Artificial Intelligence-Guided Lung Ultrasound by Nonexperts. JAMA Cardiol. 2025 Mar 1;10(3):245-253. doi: 10.1001/jamacardio.2024.4991.

    PMID: 39813064DERIVED

MeSH Terms

Conditions

Dyspnea

Condition Hierarchy (Ancestors)

Respiration DisordersRespiratory Tract DiseasesSigns and Symptoms, RespiratorySigns and SymptomsPathological Conditions, Signs and Symptoms

Central Study Contacts

Angeline Trinidad

CONTACT

619-322-0727angeline.trinidad@gehealthcare.com

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
SINGLE GROUP
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

July 31, 2023

First Posted

August 15, 2023

Study Start

July 17, 2023

Primary Completion

December 31, 2024

Study Completion

March 1, 2025

Last Updated

November 26, 2024

Record last verified: 2024-11

Data Sharing

IPD Sharing
Will not share

Locations

US(4)