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Ziedses des Plantes AC, Scoccia A, Gijsen F, van Soest G, Daemen J. Intravascular Imaging-Derived Physiology-Basic Principles and Clinical Application. Cardiol Clin 2024; 42:89-100. [PMID: 37949542 DOI: 10.1016/j.ccl.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Intravascular imaging-derived physiology is emerging as a promising tool allowing simultaneous anatomic and functional lesion assessment. Recently, several optical coherence tomography-based and intravascular ultrasound-based fractional flow reserve (FFR) indices have been developed that compute FFR through computational fluid dynamics, fluid dynamics equations, or machine-learning methods. This review aims to provide an overview of the currently available intravascular imaging-based physiologic indices, their diagnostic performance, and clinical application.
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Affiliation(s)
- Annemieke C Ziedses des Plantes
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Alessandra Scoccia
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Frank Gijsen
- Department of Biomedical Engineering, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Gijs van Soest
- Department of Biomedical Engineering, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Joost Daemen
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands.
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Huang J, Yang X, Hu Y, Li H, Leng X, Xiang J, Wei W. Intravascular Ultrasound-Based Fractional Flow Reserve for Predicting Prognosis after Percutaneous Coronary Intervention. J Cardiovasc Transl Res 2023; 16:1417-1424. [PMID: 37440164 DOI: 10.1007/s12265-023-10409-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 06/26/2023] [Indexed: 07/14/2023]
Abstract
AccuFFRivus is an alternative to fractional flow reserve (FFR) based on intravascular ultrasound (IVUS) images for functional assessment of coronary stenosis. However, its prognostic impact in patients undergoing percutaneous coronary intervention (PCI) is still unclear. This retrospective study aimed to investigate the capability of AccuFFRivus in predicting prognosis. AccuFFRivus was calculated based on postoperative angiographic and IVUS images. Vessel-oriented clinical events (VOCE) at 2 years were recorded and analyzed. A total of 131 participants with 131 vessels were included in the study. VOCE occurred in 15 patients during 2-year follow-up. AccuFFRivus after PCI (post-AccuFFRivus) was significantly higher in the non-VOCE group than in the VOCE group (0.95 ± 0.03 vs. 0.91 ± 0.02, p < 0.001). Multivariate Cox regression showed that AccuFFRivus ≤ 0.94 was a strong independent predictor of VOCE during 2-year follow-up (hazard ratio 23.76, 95% confidence interval: 3.04-185.81, p < 0.001). The left panel displays the Receiver operating characteristics (ROC) curves of postoperative parameters (post-AccuFFRivus and post-MLA) versus vessel-oriented clinical events (VOCE) occurrence within 2-year follow-up. The right panel demonstrates Kaplan-Meier curves of VOCE stratified by the optimal cut-off of post-AccuFFRivus.
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Affiliation(s)
- Jianzhen Huang
- Department of Cardiology, The First People's Hospital of Xiaoshan District, Hangzhou, China
| | - Xinyi Yang
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Yumeng Hu
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Huibin Li
- Department of Cardiology, The First People's Hospital of Xiaoshan District, Hangzhou, China
| | | | | | - Wenjuan Wei
- Department of Cardiology, The First People's Hospital of Xiaoshan District, Hangzhou, China.
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Pan W, Wei W, Hu Y, Feng L, Ren Y, Li X, Li C, Jiang J, Xiang J, Leng X, Yin D. Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance. Cardiol J 2023; 31:381-389. [PMID: 37964647 PMCID: PMC11229798 DOI: 10.5603/cj.90744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 03/18/2023] [Accepted: 10/15/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function. METHODS The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson's correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of -0.037 (limits of agreement: -0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78). CONCLUSIONS This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis.
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Affiliation(s)
- Weili Pan
- Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Wenjuan Wei
- Department of Cardiology, The First People’s Hospital of Xiaoshan District, Hangzhou, China
| | - Yumeng Hu
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Li Feng
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Yongkui Ren
- Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xinsheng Li
- Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Changling Li
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jun Jiang
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | | | | | - Da Yin
- Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Cardiology, Shenzhen Cardiovascular Minimally Invasive Medical Engineering Technology Research and Development Center, Shenzhen People’s Hospital, Shenzhen, China
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Iyer K, Nallamothu BK, Figueroa CA, Nadakuditi RR. A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images. Sci Rep 2023; 13:17603. [PMID: 37845232 PMCID: PMC10579444 DOI: 10.1038/s41598-023-44633-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023] Open
Abstract
We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from uncalibrated 2D X-ray angiography images. This method uses several binarized images from different angles to reconstruct a 3D coronary tree without any knowledge of image acquisition parameters. The method consists of a single backbone network and separate stages for vessel centerline and radius reconstruction. The output is an analytical matrix representation of the coronary tree suitable for downstream applications such as hemodynamic modeling of local vessel narrowing (i.e., stenosis). The network was trained using a dataset of synthetic coronary trees from a vessel generator informed by both clinical image data and literature values on coronary anatomy. Our multi-stage network achieved sub-pixel accuracy in reconstructing vessel radius (RMSE = 0.16 ± 0.07 mm) and stenosis radius (MAE = 0.27 ± 0.18 mm), the most important feature used to inform diagnostic decisions. The network also led to 52% and 38% reduction in vessel centerline reconstruction errors compared to a single-stage network and projective geometry-based methods, respectively. Our method demonstrated robustness to overcome challenges such as vessel foreshortening or overlap in the input images. This work is an important step towards automated analysis of anatomic and functional disease severity in the coronary arteries.
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Affiliation(s)
- Kritika Iyer
- University of Michigan, 2800 Plymouth Road Building 20-210W, Ann Arbor, MI, 48109, USA.
| | | | - C Alberto Figueroa
- University of Michigan, 2800 Plymouth Road Building 20-210W, Ann Arbor, MI, 48109, USA
| | - Raj R Nadakuditi
- University of Michigan, 2800 Plymouth Road Building 20-210W, Ann Arbor, MI, 48109, USA
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Wu W, Oguz UM, Banga A, Zhao S, Thota AK, Gadamidi VK, Vasa CH, Harmouch KM, Naser A, Tieliwaerdi X, Chatzizisis YS. 3D reconstruction of coronary artery bifurcations from intravascular ultrasound and angiography. Sci Rep 2023; 13:13031. [PMID: 37563354 PMCID: PMC10415353 DOI: 10.1038/s41598-023-40257-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023] Open
Abstract
Coronary bifurcation lesions represent a challenging anatomical subset, and the understanding of their 3D anatomy and plaque composition appears to play a key role in devising the optimal stenting strategy. This study proposes a new approach for the 3D reconstruction of coronary bifurcations and plaque materials by combining intravascular ultrasound (IVUS) and angiography. Three patient-specific silicone bifurcation models were 3D reconstructed and compared to micro-computed tomography (µCT) as the gold standard to test the accuracy and reproducibility of the proposed methodology. The clinical feasibility of the method was investigated in three diseased patient-specific bifurcations of varying anatomical complexity. The IVUS-based 3D reconstructed bifurcation models showed high agreement with the µCT reference models, with r2 values ranging from 0.88 to 0.99. The methodology successfully 3D reconstructed all the patient bifurcations, including plaque materials, in less than 60 min. Our proposed method is a simple, time-efficient, and user-friendly tool for accurate 3D reconstruction of coronary artery bifurcations. It can provide valuable information about bifurcation anatomy and plaque burden in the clinical setting, assisting in bifurcation stent planning and education.
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Affiliation(s)
- Wei Wu
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Usama M Oguz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Akshat Banga
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Shijia Zhao
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Anjani Kumar Thota
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Vinay Kumar Gadamidi
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Charu Hasini Vasa
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Khaled M Harmouch
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Abdallah Naser
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Xiarepati Tieliwaerdi
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Yiannis S Chatzizisis
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA.
- Division of Cardiovascular Medicine, Leonard M. Miller School of Medicine, University of Miami Health System, University of Miami, 1120 NW 14th Street, Suite 1124, Miami, FL, 33136, USA.
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Huang W, Zhang J, Yang L, Hu Y, Leng X, Liu Y, Jin H, Tang Y, Wang J, Liu X, Guo Y, Ye C, Feng Y, Xiang J, Tang L, Du C. Accuracy of intravascular ultrasound-derived virtual fractional flow reserve (FFR) and FFR derived from computed tomography for functional assessment of coronary artery disease. Biomed Eng Online 2023; 22:64. [PMID: 37370077 DOI: 10.1186/s12938-023-01122-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 05/28/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND Coronary computed tomography-derived fractional flow reserve (CT-FFR) and intravascular ultrasound-derived fractional flow reserve (IVUS-FFR) are two functional assessment methods for coronary stenoses. However, the calculation algorithms for these methods differ significantly. This study aimed to compare the diagnostic performance of CT-FFR and IVUS-FFR using invasive fractional flow reserve (FFR) as the reference standard. METHODS Six hundred and seventy patients (698 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2020 and July 2021. A total of 40 patients (41 lesions) underwent intravascular ultrasound (IVUS) and FFR evaluations within six months after completing coronary CT angiography were included. Two novel CFD-based models (AccuFFRct and AccuFFRivus) were used to compute the CT-FFR and IVUS-FFR values, respectively. The invasive FFR ≤ 0.80 was used as the reference standard for evaluating the diagnostic performance of CT-FFR and IVUS-FFR. RESULTS Both AccuFFRivus and AccuFFRct demonstrated a strong correlation with invasive FFR (R = 0.7913, P < 0.0001; and R = 0.6296, P < 0.0001), and both methods showed good agreement with FFR. The area under the receiver operating characteristic curve was 0.960 (P < 0.001) for AccuFFRivus and 0.897 (P < 0.001) for AccuFFRct in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (96.6%), specificity (85.7%), and the Youden index (0.823) using the same cutoff value of 0.80 for AccuFFRivus. A good diagnostic performance (sensitivity 89.7%, specificity 85.7%, and Youden index 0.754) was also demonstrated by AccuFFRct. CONCLUSIONS AccuFFRivus, computed from IVUS images, exhibited a high diagnostic performance for detecting myocardial ischemia. It demonstrated better diagnostic power than AccuFFRct, and could serve as an accurate computational tool for ischemia diagnosis and assist in clinical decision-making.
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Affiliation(s)
- Wenhao Huang
- Department of Medicine, The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jingyuan Zhang
- Department of Medicine, The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Lin Yang
- Department of Geriatrics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yumeng Hu
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | | | - Yajun Liu
- Department of Medicine, The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Hongfeng Jin
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Yiming Tang
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Jiangting Wang
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Xiaowei Liu
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Yitao Guo
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Chen Ye
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Yue Feng
- Department of Radiology, Zhejiang Hospital, Hangzhou, China
| | | | - Lijiang Tang
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China.
| | - Changqing Du
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China.
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Yong D, Minjie C, Yujie Z, Jianli W, Ze L, Pengfei L, Xiangling L, Xiujian L, Javier DS. Diagnostic performance of IVUS-FFR analysis based on generative adversarial network and bifurcation fractal law for assessing myocardial ischemia. Front Cardiovasc Med 2023; 10:1155969. [PMID: 37020517 PMCID: PMC10067879 DOI: 10.3389/fcvm.2023.1155969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 02/20/2023] [Indexed: 03/22/2023] Open
Abstract
BackgroundIVUS-based virtual FFR (IVUS-FFR) can provide additional functional assessment information to IVUS imaging for the diagnosis of coronary stenosis. IVUS image segmentation and side branch blood flow can affect the accuracy of virtual FFR. The purpose of this study was to evaluate the diagnostic performance of an IVUS-FFR analysis based on generative adversarial networks and bifurcation fractal law, using invasive FFR as a reference.MethodIn this study, a total of 108 vessels were retrospectively collected from 87 patients who underwent IVUS and invasive FFR. IVUS-FFR was performed by analysts who were blinded to invasive FFR. We evaluated the diagnostic performance and computation time of IVUS-FFR, and compared it with that of the FFR-branch (considering side branch blood flow by manually extending the side branch from the bifurcation ostia). We also compared the effects of three bifurcation fractal laws on the accuracy of IVUS-FFR.ResultThe diagnostic accuracy, sensitivity, and specificity for IVUS-FFR to identify invasive FFR≤0.80 were 90.7% (95% CI, 83.6–95.5), 89.7% (95% CI, 78.8–96.1), 92.0% (95% CI, 80.8–97.8), respectively. A good correlation and agreement between IVUS-FFR and invasive FFR were observed. And the average computation time of IVUS-FFR was shorter than that of FFR-branch. In addition to this, we also observe that the HK model is the most accurate among the three bifurcation fractal laws.ConclusionOur proposed IVUS-FFR analysis correlates and agrees well with invasive FFR and shows good diagnostic performance. Compared with FFR-branch, IVUS-FFR has the same level of diagnostic performance with significantly lower computation time.
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Affiliation(s)
- Dong Yong
- Department of Cardiology, the 7th People’s Hospital of Zhengzhou, Zhengzhou, China
| | - Chen Minjie
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China
| | - Zhao Yujie
- Department of Cardiology, the 7th People’s Hospital of Zhengzhou, Zhengzhou, China
| | - Wang Jianli
- Department of Cardiology, the 7th People’s Hospital of Zhengzhou, Zhengzhou, China
| | - Liu Ze
- Department of Cardiology, the 7th People’s Hospital of Zhengzhou, Zhengzhou, China
| | - Li Pengfei
- Department of Cardiology, the 7th People’s Hospital of Zhengzhou, Zhengzhou, China
| | - Lai Xiangling
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China
| | - Liu Xiujian
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China
- Correspondence: Xiujian Liu
| | - Del Ser Javier
- TECNALIA, Basque Research & Technology Alliance (BRTA), Derio, Spain
- University of the Basque Country (UPV/EHU), Bilbao, Spain
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Ziedses des Plantes AC, Scoccia A, Gijsen F, van Soest G, Daemen J. Intravascular Imaging-Derived Physiology-Basic Principles and Clinical Application. Interv Cardiol Clin 2023; 12:83-94. [PMID: 36372464 DOI: 10.1016/j.iccl.2022.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Intravascular imaging-derived physiology is emerging as a promising tool allowing simultaneous anatomic and functional lesion assessment. Recently, several optical coherence tomography-based and intravascular ultrasound-based fractional flow reserve (FFR) indices have been developed that compute FFR through computational fluid dynamics, fluid dynamics equations, or machine-learning methods. This review aims to provide an overview of the currently available intravascular imaging-based physiologic indices, their diagnostic performance, and clinical application.
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Affiliation(s)
- Annemieke C Ziedses des Plantes
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Alessandra Scoccia
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Frank Gijsen
- Department of Biomedical Engineering, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Gijs van Soest
- Department of Biomedical Engineering, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Joost Daemen
- Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, the Netherlands.
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Samady H, Jaber W. Harnessing Vascular Biology and Fluid Dynamics to Risk Stratify Patients With Acute Coronary Syndromes. JACC Cardiovasc Interv 2022; 15:2049-2051. [DOI: 10.1016/j.jcin.2022.08.046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 08/29/2022] [Indexed: 11/25/2022]
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Takahashi T, Shin D, Kuno T, Lee JM, Latib A, Fearon WF, Maehara A, Kobayashi Y. Diagnostic performance of fractional flow reserve derived from coronary angiography, intravascular ultrasound, and optical coherence tomography; a meta-analysis. J Cardiol 2022; 80:1-8. [DOI: 10.1016/j.jjcc.2022.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 02/06/2022] [Accepted: 02/17/2022] [Indexed: 10/18/2022]
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Jiang J, Tang L, Du C, Leng X, He J, Hu Y, Dong L, Sun Y, Li C, Xiang J, Wang J. Diagnostic performance of AccuFFRangio in the functional assessment of coronary stenosis compared with pressure wire-derived fractional flow reserve. Quant Imaging Med Surg 2022; 12:949-958. [PMID: 35111596 DOI: 10.21037/qims-21-463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 08/26/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Non-invasive fractional flow reserve (FFR) has been increasingly used in the clinical workflow to assist clinical decision-making for percutaneous coronary intervention (PCI). This clinical study evaluates the diagnostic accuracy of coronary stenosis assessed by a non-invasive FFR analysis method (termed AccuFFRangio) based on invasive coronary angiography (ICA). It is a blinded, self-controlled, retrospective, and dual-center clinical investigation study. METHODS Coronary angiography data and the related information of 320 patients with 320 vessels were collected, and AccuFFRangio was used to assess the FFR for these patients. Compared with the wire-measured FFR values, we evaluated AccuFFRangio performance by its accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS The diagnostic accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRangio in identifying hemodynamically significant coronary stenosis were 93.3%, 92.6%, 93.5%, 84.3%, and 97.1%, respectively. The direct correlation between computed AccuFFRangio and measured FFR was 0.812 (P<0.001), and the area under the receiver operating characteristic curve (AUC) value of AccuFFRangio was 0.96. CONCLUSIONS This clinical study demonstrates the efficiency and accuracy of AccuFFRangio for clinical implementation when using invasive wire-measured FFR as a reference. Further validation is required in a large prospective multicenter study.
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Affiliation(s)
- Jun Jiang
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lijiang Tang
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | - Changqing Du
- Department of Cardiology, Zhejiang Hospital, Hangzhou, China
| | | | - Jingsong He
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Yumeng Hu
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Liang Dong
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yong Sun
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Changling Li
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | | | - Jian'an Wang
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Li C, Leng X, He J, Xia Y, Jiang W, Pan Y, Dong L, Sun Y, Hu X, Wang J, Xiang J, Jiang J. Diagnostic Performance of Angiography-Based Fractional Flow Reserve for Functional Evaluation of Coronary Artery Stenosis. Front Cardiovasc Med 2021; 8:714077. [PMID: 34712703 PMCID: PMC8546292 DOI: 10.3389/fcvm.2021.714077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 09/15/2021] [Indexed: 11/13/2022] Open
Abstract
Background: A new method for calculating fraction flow reserve (FFR) without pressure-wire (angiography-derived FFR) based on invasive coronary angiography (ICA) images can be used to evaluate the functional problems of coronary stenosis. Objective: The aim of this study was to assess the diagnostic performance of a novel method of calculating the FFR compared to wire-based FFR using retrospectively collected data from patients with stable angina. Methods: Three hundred patients with stable angina pectoris who underwent ICA and FFR measurement were included in this study. Two ICA images with projections >25° apart at the end-diastolic frame were selected for 3D reconstruction. Then, the contrast frame count was performed in an angiographic run to calculate the flow velocity. Based on the segmented vessel, calculated velocity, and aortic pressure, AccuFFRangio distribution was calculated through the pressure drop equation. Results: Using FFR ≤ 0.8 as a reference, we evaluated AccuFFRangio performance for 300 patients with its accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Comparison of AccuFFRangio with wire-measured FFR resulted in an area under the curve (AUC) of 0.954 (per-vessel, p < 0.0001). Accuracy for AccuFFRangio was 93.7% for Pa set from measurement and 87% for Pa = 100 mmHg in this clinical study. Overall sensitivity, specificity, PPV, and NPV for per-vessel were 90, 95, 86.7, 96.3, and 57.5, 97.7, 90.2, 86.3%, respectively. Overall accuracy, sensitivity, specificity, PPV, and NPV for 2-dimensional (2D) quantitative coronary angiography (QCA) were 63.3, 42.5, 70.9, 34.7, and 77.2%, respectively. The average processing time of AccuFFRangio was 4.30 ± 1.87 min. Conclusions: AccuFFRangio computed from coronary ICA images can be an accurate and time-efficient computational tool for detecting lesion-specific ischemia of coronary artery stenosis.
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Affiliation(s)
- Changling Li
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | | | - Jingsong He
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Yongqing Xia
- ArteryFlow Technology Co., Ltd., Hangzhou, China
| | - Wenbing Jiang
- Department of Cardiology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, China
| | - Yibin Pan
- Department of Cardiology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, China
| | - Liang Dong
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yong Sun
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyang Hu
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jian'an Wang
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | | | - Jun Jiang
- Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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