High-risk Features of Coronary Lesions in CTA and OCT

NCT ID: NCT06089343

Last Updated: 2023-10-18

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-10-01

Study Completion Date

2024-10-31

Brief Summary

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This study is a multicenter and retrospective study. ACS patients who underwent CCTA or OCT from 1 months to 3 years prior to the event will be retrospectively identified. Plaques in the non-culprit vessels will be regarded as a primary control group.

Detailed Description

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The high-risk features of plaque rupture and subsequent acute coronary syndrome (ACS) are not fully identified. Plaque features, hemodynamic forces, and the interaction between these factors may cause plaque instability and subsequent clinical events. A previous study showed that the addition of hemodynamic parameters calculated noninvasively from coronary computed tomography (CCTA) using computational fluid dynamics (such as wall shear stress and axial plaque stress) improved the ability to predict the risk of ACS compared with conventional approaches based on anatomical stenosis severity and adverse plaque characteristics. Wall shear stress and axial plaque stress derived from CT were highly correlated to those derived from optical coherence tomography (OCT). In addition, other hemodynamic parameters, such as oscillatory shear index, endothelial shear stress (ESS), and spatial ESS gradient have also been demonstrated to be associated with unstable plaque. In this regard, we designed this study to find the best hemodynamic and plaque features derived from CTA and verified by OCT to predict ACS, and to investigate whether a comprehensive risk prediction model with them has an incremental value in a larger population.

Conditions

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Acute Coronary Syndromes

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Culprit

Plaques which is related with acute coronary syndrome

Coronary CT angiography

Intervention Type DIAGNOSTIC_TEST

Comprehensive hemodynamic and plaque features derived from CTA and verified by OCT of all culprit and non-culprit lesions to predict ACS.

Non-culprit

Plaques which is not related with acute coronary syndrome

Coronary CT angiography

Intervention Type DIAGNOSTIC_TEST

Comprehensive hemodynamic and plaque features derived from CTA and verified by OCT of all culprit and non-culprit lesions to predict ACS.

Interventions

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Coronary CT angiography

Comprehensive hemodynamic and plaque features derived from CTA and verified by OCT of all culprit and non-culprit lesions to predict ACS.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Patients who presented with ACS and underwent invasive coronary angiography or OCT
2. The patients who underwent coronary CT angiography, regardless of the reason (for example, routine healthcare check-up, or evaluation for stable angina or atypical chest pain) prior to the acute event.
3. Time limit of CCTA: 1 months \~ 3 years prior to the event.

Exclusion Criteria

Patients with stents in two or more vessel territories prior to CCTA Poor quality of CCTA which is unsuitable for plaque and CFD analysis Patients with ACS culprit lesion in a stented segment Patients with previous history of coronary artery bypass graft surgery Patients with revascularization after CCTA and before ACS event Secondary ACS due to other general medical conditions, such as sepsis, arrhythmia, bleeding, etc.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Shanghai Zhongshan Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Zhongshan Hospital Fudan University

Shanghai, Shanghai Municipality, China

Site Status

Countries

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China

Other Identifiers

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ACS-CTA&OCT

Identifier Type: -

Identifier Source: org_study_id

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