Coronary Intervention Solution

CN EN

Product Introduction

CtaPlus provides non-invasive coronary anatomical and physiological assessment from CCTA using computational physiology algorithms derived from μFR, supporting clinical decision-making from non-invasive evaluation to PCI planning.

Key Features

CT-μFR Physiological Assessment

On-site, non-invasive FFR derived from CCTA; high diagnostic accuracy; guides revascularization decisions.
Comprehensive Plaque Analysis

Qualitative and quantitative assessment of plaque burden, composition (lipid, fibrous, calcified), and high-risk features.
Virtual Stent Planning

Simulates PCI strategies and predicts post-PCI residual ischemia to optimize stent selection and landing zone.
CT-Angiography Co-registration

Automatic co-registration of CCTA with angiography for intra-procedural navigation and complex lesion planning.
Automated Structured Reporting

One-click generation of structured reports integrating anatomical and functional results.

Clinical Benefits

01

Automatic CT-μFR calculation.Fast, precise, and non-invasive ischemia assessment.
02

Automatic stenosis quantification. Precise lesion quantification.Reduce calcium-related overestimation.
03

Simulate stent implantation before PCI. Optimize stent size and landing zones.Optimize PCI strategy.
04

Automatic CT–DSA registration and fusion. Connect preprocedural planning with procedural guidance. Enable precise intervention for complex lesions.

CT-μFR Clinical Evidence

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Artificial intelligence-powered automatic coronary computed tomography angiography plaque quantification: comparison against optical coherence tomography

Li G, Yu W, Wang Z, et al. Eur Heart J Digit Health. 2026;7:ztag024. doi:10.1093/ehjdh/ztag024

A novel AI method enables fully automated CCTA plaque quantification, showing good correlation with co-registered OCT plaque identification (plaque volume r=0.84).

Diagnostic performance of fully automatic coronary CT angiography-based quantitative flow ratio

Li G, Weng T, Sun P, et al. J Cardiovasc Comput Tomogr. 2025;19:40-47. doi:10.1016/j.jcct.2024.10.001

Fully automated CT-μFR demonstrates high feasibility and good diagnostic performance, identifying hemodynamically non-significant coronary stenoses and reducing unnecessary invasive catheterization.

GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration

Chen Y, Li G, Li C, et al. IEEE Trans Med Imaging. 2025;44(6):2617-2629. doi:10.1109/TMI.2025.3540906

GVM-Net, a graph neural network-based vessel matching network, achieves accurate 2D/3D coronary registration even with discontinuous segmentation, outperforming existing CCTA-to-angiography registration methods.

Diagnostic Performance of Angiography-Derived Quantitative Flow Ratio in Complex Coronary Lesions

Wu X, Wang K, Li G, et al. Circ Cardiovasc Imaging. 2024;17:e016046. doi:10.1161/CIRCIMAGING.123.016046

Both CT-μFR and μFR demonstrate significant diagnostic performance in complex coronary lesions (accuracy 92%/94%), playing a key role in CAD management.

Accuracy of coronary computed tomography angiography-derived quantitative flow ratio for onsite assessment of coronary lesions

Weng T, Ding D, Li G, et al. EuroIntervention. 2024;20:e1288-e1297. doi:10.4244/EIJ-D-24-00336

The CAREER prospective trial confirmed an onsite diagnostic accuracy of 89.6% for CT-μFR, meeting the primary endpoint. In vessels without significant calcification, its diagnostic performance was non-inferior to angiography-based μFR.

Prognostic Value of Coronary CT Angiography–Derived Quantitative Flow Ratio in Suspected Coronary Artery Disease

Li Z, Tu S, Matheson MB, et al. Radiology. 2024;313(2):e240299. doi:10.1148/radiol.240299

CT-μFR is an independent predictor of MACE during 5-year follow-up in suspected CAD patients, with long-term prognostic value comparable to ICA/SPECT.

Comparison of coronary CT angiography-based and invasive coronary angiography-based quantitative flow ratio for functional assessment of coronary stenosis: A multicenter retrospective analysis

Li Z, Li G, Chen L, et al. J Cardiovasc Comput Tomogr. 2022;16(6):509-516. doi:10.1016/j.jcct.2022.06.002

A multicenter study shows CT-μFR diagnostic performance is slightly lower than μFR but without statistical difference, and significantly outperforms CTA diameter stenosis. Extensive calcification reduces its accuracy.

Feasibility and Diagnostic Accuracy of CT Angiography–Based Quantitative Flow Ratio

Li Z, Chang Y, Yu M, et al. JACC Cardiovasc Imaging. 2020;13(1):172-175. doi:10.1016/j.jcmg.2019.07.017

The first CT-μFR validation study shows good correlation with invasive FFR (r=0.79) and vessel-level diagnostic accuracy of 87.2%, confirming the feasibility of non-invasive physiological assessment.

CtaPlus®CCTA-Based Physiology Analysis System