NCT06172985

Brief Summary

The goal of this clinical trail is to evaluate the effectiveness and accuracy of the CCTA image assisted triage software(DeepVessel® Cardisight, Keya Medical.) for the triage of patients with suspected coronary artery disease.

Trial Health

43
At Risk

Trial Health Score

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

Trial has exceeded expected completion date
Enrollment
1,093

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started May 2023

Shorter than P25 for all trials

Geographic Reach
1 country

5 active sites

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

Study Start

First participant enrolled

May 9, 2023

Completed
1 month until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 8, 2023

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

August 17, 2023

Completed
4 months until next milestone

First Posted

Study publicly available on registry

December 15, 2023

Completed
3 months until next milestone

Study Completion

Last participant's last visit for all outcomes

February 29, 2024

Completed
Last Updated

December 15, 2023

Status Verified

August 1, 2023

Enrollment Period

1 month

First QC Date

August 17, 2023

Last Update Submit

December 7, 2023

Conditions

Coronary Heart Disease

Outcome Measures

Primary Outcomes (1)

  • Sensitivity and specificity of experiment group in triage for patients with suspected coronary artery disease

    Based on the results of the independent expert group, uses stenosis degree≥50% as the boundary for triage indication on a per-patient basis.

    October 13,2022 to March 1,2023

Secondary Outcomes (12)

  • Diagnostic time

    October 13,2022 to March 1,2023

  • Patient as research unit

    October 13,2022 to March 1,2023

  • Blood vessels were used as the research unit

    October 13,2022 to March 1,2023

  • The vascular segment was used as the research unit

    October 13,2022 to March 1,2023

  • Gender stratified statistics, respectively, with patients and blood vessels as research units

    October 13,2022 to March 1,2023

  • +7 more secondary outcomes

Other Outcomes (1)

  • Device Defects

    October 13,2022 to March 1,2023

Study Arms (1)

Suspected patients with coronary heart disease.

The coronary CT angiography (CCTA) images collected by each center within a certain period of time will be desensitized after the screening is successful. The final CCTA images were sent to an independent judgment expert group for diagnosis, the results of the test group and the independent judgment expert group were compared, and the clinical application of the coronary artery CT angiography image vascular stenosis auxiliary triage software developed by Keya Medical Technology Co., Ltd. was evaluated. Validity and Accuracy

Other: No intervention

Interventions

No interventionOTHER

Due to observational study

Suspected patients with coronary heart disease.

Eligibility Criteria

Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Suspected patients with coronary heart disease.

You may qualify if:

  • CCTA images acquired by CT detectors need to meet the following requirements:
  • Check Modal = CT
  • Number of detector rows ≥ 64 rows
  • Layer thickness ≤1mm
  • Layer spacing ≤1mm
  • Pixel pitch ≤ 0.5mm
  • Ball tube voltage ≥ 70kV
  • Number of layers ≥ 100 layers
  • CCTA image quality score ≥ 3 (5-point Likert scale).

You may not qualify if:

  • Severe coronary artery calcification, which in the judgment of readers affects the stenosis adjudicator;
  • Previous percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG);
  • Congenital anomalies of coronary artery origin or other malformations;
  • Coronary artery occlusive lesions;
  • Implantation of the pacemaker, internal defibrillator electrode, or prosthetic heart valve.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (5)

Fuwai Hospital, Chinese Academy of Medical Sciences

Beijing, Beijing Municipality, China

Location

The Pearl River Hospital of Southern Medical University

Guangzhou, Guangdong, China

Location

Affiliated Hospital of Zunyi Medical University

Zunyi, Guizhou, China

Location

The First Affiliated Hospital of Hebei Medical University

Shijiazhuang, Hebei, China

Location

Huanggang Central Hospital

Huanggang, Hubei, China

Location

Related Publications (6)

  • Meijboom WB, Meijs MF, Schuijf JD, Cramer MJ, Mollet NR, van Mieghem CA, Nieman K, van Werkhoven JM, Pundziute G, Weustink AC, de Vos AM, Pugliese F, Rensing B, Jukema JW, Bax JJ, Prokop M, Doevendans PA, Hunink MG, Krestin GP, de Feyter PJ. Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol. 2008 Dec 16;52(25):2135-44. doi: 10.1016/j.jacc.2008.08.058.

    PMID: 19095130RESULT

  • Lucke C, Foldyna B, Andres C, Boehmer-Lasthaus S, Grothoff M, Nitzsche S, Gutberlet M, Lehmkuhl L. Post-processing in cardiovascular computed tomography: performance of a client server solution versus a stand-alone solution. Rofo. 2014 Dec;186(12):1111-21. doi: 10.1055/s-0034-1366726. Epub 2014 Aug 14.

    PMID: 25122171RESULT

  • Choi AD, Marques H, Kumar V, Griffin WF, Rahban H, Karlsberg RP, Zeman RK, Katz RJ, Earls JP. CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study. J Cardiovasc Comput Tomogr. 2021 Nov-Dec;15(6):470-476. doi: 10.1016/j.jcct.2021.05.004. Epub 2021 Jun 12.

    PMID: 34127407RESULT

  • Paul JF, Rohnean A, Giroussens H, Pressat-Laffouilhere T, Wong T. Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection. Diagn Interv Imaging. 2022 Jun;103(6):316-323. doi: 10.1016/j.diii.2022.01.004. Epub 2022 Jan 26.

    PMID: 35090845RESULT

  • Meyer M, Schoepf UJ, Fink C, Goldenberg R, Apfaltrer P, Gruettner J, Vajcs D, Schoenberg SO, Henzler T. Diagnostic performance evaluation of a computer-aided simple triage system for coronary CT angiography in patients with intermediate risk for acute coronary syndrome. Acad Radiol. 2013 Aug;20(8):980-6. doi: 10.1016/j.acra.2013.02.014. Epub 2013 Jun 2.

    PMID: 23735619RESULT

  • Chen Y, Yu H, Fan B, Wang Y, Wen Z, Hou Z, Yu J, Wang H, Tang Z, Li N, Jiang P, Wang Y, Yin W, Lu B. Diagnostic performance of deep learning-based coronary computed tomography angiography in detecting coronary artery stenosis. Int J Cardiovasc Imaging. 2025 May;41(5):979-989. doi: 10.1007/s10554-025-03383-0. Epub 2025 Mar 29.

    PMID: 40156689DERIVED

Related Links

MeSH Terms

Conditions

Coronary Disease

Condition Hierarchy (Ancestors)

Myocardial IschemiaHeart DiseasesCardiovascular DiseasesVascular Diseases

Study Officials

  • Bin Lu

    Chinese Academy of Medical Sciences, Fuwai Hospital

    PRINCIPAL INVESTIGATOR

Study Design

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

Study Record Dates

First Submitted

August 17, 2023

First Posted

December 15, 2023

Study Start

May 9, 2023

Primary Completion

June 8, 2023

Study Completion

February 29, 2024

Last Updated

December 15, 2023

Record last verified: 2023-08

Data Sharing

IPD Sharing
Will not share

Locations

CN(5)