Clinical trial NCT06172985: A CCTA Image Assisted Triage Software for the Assessment of Patients With Suspected Coronary Artery Disease
Official title: A CCTA Image Assisted Triage Software for the Assessment of Patients With Suspected Coronary Artery Disease: a Retrospective, Multi-center, Blind-evaluation Study
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Coronary Heart Disease
Lead sponsor: Keya Medical
Sponsor class: INDUSTRY
First posted: 2023-12-15
Enrollment: 1093
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CROSSOVER
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Suspected patients with coronary heart disease.

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.

Detailed description: The CCTA images collected by each center within a certain period of time would be screened, desensitized, and then evaluated by the software and independent expert group respectively, to evaluate the effectiveness and accuracy of the coronary CT angiography image stenosis assisted triage software developed by Koyal Medical Technology Co.

Experiment group: Evaluated by the software Independent expert group: Evaluated by experts (≥5 years of CCTA experience required)

Eligibility criteria: Inclusion Criteria:

1. 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
2. CCTA image quality score ≥ 3 (5-point Likert scale).

Exclusion Criteria:

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

Primary outcomes:
measure: Sensitivity and specificity of experiment group in triage for patients with suspected coronary artery disease
timeFrame: October 13,2022 to March 1,2023
Secondary outcomes:
measure: Diagnostic time
timeFrame: October 13,2022 to March 1,2023
measure: Patient as research unit
timeFrame: October 13,2022 to March 1,2023
measure: Blood vessels were used as the research unit
timeFrame: October 13,2022 to March 1,2023
measure: The vascular segment was used as the research unit
timeFrame: October 13,2022 to March 1,2023
measure: Gender stratified statistics, respectively, with patients and blood vessels as research units
timeFrame: October 13,2022 to March 1,2023
measure: Manufacturer stratified statistics, respectively, with patients and blood vessels as research units
timeFrame: October 13,2022 to March 1,2023
measure: Row number stratified statistics, respectively, with patients and blood vessels as research units
timeFrame: October 13,2022 to March 1,2023
measure: The stratified statistics of tube voltage were conducted with patients and blood vessels as research units
timeFrame: October 13,2022 to March 1,2023
measure: Layer thickness stratified statistics, patients and blood vessels were used as research units
timeFrame: October 13,2022 to March 1,2023
measure: The patients and blood vessels were selected as the research units
timeFrame: October 13,2022 to March 1,2023
measure: Post-processing image quality evaluation
timeFrame: October 13,2022 to March 1,2023
measure: Software performance evaluation
timeFrame: October 13,2022 to March 1,2023
Other outcomes:
measure: Device Defects
timeFrame: October 13,2022 to March 1,2023
Locations:
city: Beijing
country: China
facility: Fuwai Hospital, Chinese Academy of Medical Sciences
state: Beijing
city: Guangzhou
country: China
facility: The Pearl River Hospital of Southern Medical University
state: Guangdong
city: Zunyi
country: China
facility: Affiliated Hospital of Zunyi Medical University
state: Guizhou
city: Shijiazhuang
country: China
facility: The First Affiliated Hospital of Hebei Medical University
state: Hebei
city: Huanggang
country: China
facility: Huanggang Central Hospital
state: Hubei
Study officials:
affiliation: Chinese Academy of Medical Sciences, Fuwai Hospital
name: Bin Lu
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.