Clinical Validation of a Virtual Planner for Coronary Interventions Based on Coronary CT Angiography

Sonck, Jeroen; Nagumo, Sakura; Nørgaard, Bjarne Linde; Otake, Hiromasa; Ko, Brian; Zhang, Jinlong; Mizukami, Takuya; Mæng, Michael; Andreini, Daniele; Takahashi, Yu; Jensen, Jesper Møller; Ihdayhid, Abdul Rahman; Heggermont, Ward; Barbato, Emanuele; Mileva, Niya; Munhoz, Daniel; Bartúnek, Jozef; Updegrove, Adam; Collinsworth, Amy; Pěnička, Martin; Hoe, Lieven Van; Leipsic, Jonathon; Koo, Bwon-Kon; Bruyne, Bernard De; Collet, Carlos

doi:10.1016/j.jcmg.2022.02.003

Cited by 58 publications

(32 citation statements)

References 24 publications

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“…The latter is a novel interactive tool for the prediction of post-PCI FFR through the virtual stenting of coronary stenoses. Recent data from the P3 (Precise Percutaneous Coronary Intervention Plan) study supports the high accuracy and precision of the FFR CT Planner for predicting invasive post-PCI FFR values 83 . These results were independent of CAD complexity (i.e., diffuse lesions, high calcium burden) and image quality.…”

Section: Post-pci Ffr As Predicted From Ffr Ct : the "Ffr Ct Planner"mentioning

confidence: 89%

Computed tomographic angiography in coronary artery disease

Serruys¹,

Kotoku²,

Nørgaard³

et al. 2023

EuroIntervention

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Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFR CT ), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

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Section: Post-pci Ffr As Predicted From Ffr Ct : the "Ffr Ct Planner"mentioning

confidence: 89%

Computed tomographic angiography in coronary artery disease

Serruys¹,

Kotoku²,

Nørgaard³

et al. 2023

EuroIntervention

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“…This substudy is a predefined analysis of the P3 (Precise PCI Plan), which study design and main results have been reported elsewhere. 10 , 11 Briefly, the P3 study was a prospective, investigator‐initiated, multicenter study of patients with stable CAD referred for PCI. Patients with a significant epicardial lesion based on an FFR ≤0.80 were considered for inclusion.…”

Section: Methodsmentioning

confidence: 99%

Procedural Outcomes After Percutaneous Coronary Interventions in Focal and Diffuse Coronary Artery Disease

Mizukami

Sonck

Sakai

et al. 2022

JAHA

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Background Coronary artery disease (CAD) patterns play an essential role in the decision‐making process about revascularization. The pullback pressure gradient (PPG) quantifies CAD patterns as either focal or diffuse based on fractional flow reserve (FFR) pullbacks. The objective of this study was to evaluate the impact of CAD patterns on acute percutaneous coronary intervention (PCI) results considered surrogates of clinical outcomes. Methods and Results This was a prospective, multicenter study of patients with hemodynamically significant CAD undergoing PCI. Motorized FFR pullbacks and optical coherence tomography (OCT) were performed before and after PCI. Post‐PCI FFR >0.90 was considered an optimal result. Focal disease was defined as PPG >0.73 (highest PPG tertile). Overall, 113 patients (116 vessels) were included. Patients with focal disease were younger than those with diffuse CAD (61.4±9.9 versus 65.1±8.7 years, P =0.042). PCI in vessels with high PPG (focal CAD) resulted in higher post‐PCI FFR (0.91±0.07 in the focal group versus 0.86±0.05 in the diffuse group, P <0.001) and larger minimal stent area (6.3±2.3 mm 2 in focal versus 5.3±1.8 mm 2 in diffuse CAD, P =0.015) compared withvessels with low PPG (diffuse CAD). The PPG was associated with the change in FFR after PCI ( R 2 =0.51, P <0.001). The PPG significantly improved the capacity to predict optimal PCI results compared with an angiographic assessment of CAD patterns (area under the curve PPG 0.81 [95% CI, 0.73–0.88] versus area under the curve angio 0.51 [95% CI, 0.42–0.60]; P <0.001). Conclusions PCI in vessels with focal disease defined by the PPG resulted in greater improvement in epicardial conductance and larger minimal stent area compared with diffuse disease. PPG, but not angiographically defined CAD patterns, distinguished patients attaining superior procedural outcomes. Registration URL: https://clinicaltrials.gov/ct2/show/NCT03782688

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“…Finally, there is a growing interest in the use of CCTA and AI to guide clinical response following treatment such as PCI for significant lesions. The FFR-CT Planner [ 40 ] is a new tool that recomputes FFR-CT values after coronary angioplasty, which it achieves by combining the results of multiple simulations and reduced order modelling to calculate instantaneous FFR-CT values in a particular coronary lumen. It enables pre-procedural planning with regards to virtual stenting of coronary lesions and prediction of FFR following PCI [ 41 ].…”

Section: Coronary Ctmentioning

confidence: 99%

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease

et al. 2023

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Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide, and it is associated with considerable economic burden. In an ageing, multimorbid population, it has become increasingly important to develop reliable, consistent, low-risk, non-invasive means of diagnosing CAD. The evolution of multiple cardiac modalities in this field has addressed this dilemma to a large extent, not only in providing information regarding anatomical disease, as is the case with coronary computed tomography angiography (CCTA), but also in contributing critical details about functional assessment, for instance, using stress cardiac magnetic resonance (S-CMR). The field of artificial intelligence (AI) is developing at an astounding pace, especially in healthcare. In healthcare, key milestones have been achieved using AI and machine learning (ML) in various clinical settings, from smartwatches detecting arrhythmias to retinal image analysis and skin cancer prediction. In recent times, we have seen an emerging interest in developing AI-based technology in the field of cardiovascular imaging, as it is felt that ML methods have potential to overcome some limitations of current risk models by applying computer algorithms to large databases with multidimensional variables, thus enabling the inclusion of complex relationships to predict outcomes. In this paper, we review the current literature on the various applications of AI in the assessment of CAD, with a focus on multimodality imaging, followed by a discussion on future perspectives and critical challenges that this field is likely to encounter as it continues to evolve in cardiology.

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Clinical Validation of a Virtual Planner for Coronary Interventions Based on Coronary CT Angiography

Cited by 58 publications

References 24 publications

Computed tomographic angiography in coronary artery disease

Computed tomographic angiography in coronary artery disease

Procedural Outcomes After Percutaneous Coronary Interventions in Focal and Diffuse Coronary Artery Disease

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease

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