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Zsarnoczay E, Pinos D, Schoepf UJ, Fink N, O'Doherty J, Gnasso C, Griffith J, Vecsey-Nagy M, Suranyi P, Maurovich-Horvat P, Emrich T, Varga-Szemes A. Intra-individual comparison of coronary CT angiography-based FFR between energy-integrating and photon-counting detector CT systems. Int J Cardiol 2024; 399:131684. [PMID: 38151162 DOI: 10.1016/j.ijcard.2023.131684] [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: 10/06/2023] [Revised: 12/12/2023] [Accepted: 12/22/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Coronary computed tomography angiography (CCTA)-based fractional flow reserve (CT-FFR) allows for noninvasive determination of the functional severity of anatomic lesions in patients with coronary artery disease. The aim of this study was to intra-individually compare CT-FFR between photon-counting detector (PCD) and conventional energy-integrating detector (EID) CT systems. METHODS In this single-center prospective study, subjects who underwent clinically indicated CCTA on an EID-CT system were recruited for a research CCTA on PCD-CT within 30 days. Image reconstruction settings were matched as closely as possible between EID-CT (Bv36 kernel, iterative reconstruction strength level 3, slice thickness 0.5 mm) and PCD-CT (Bv36 kernel, quantum iterative reconstruction level 3, virtual monoenergetic level 55 keV, slice thickness 0.6 mm). CT-FFR was measured semi-automatically using a prototype on-site machine learning algorithm by two readers. CT-FFR analysis was performed per-patient and per-vessel, and a CT-FFR ≤ 0.75 was considered hemodynamically significant. RESULTS A total of 22 patients (63.3 ± 9.2 years; 7 women) were included. Median time between EID-CT and PCD-CT was 5.5 days. Comparison of CT-FFR values showed no significant difference and strong agreement between EID-CT and PCD-CT in the per-vessel analysis (0.88 [0.74-0.94] vs. 0.87 [0.76-0.93], P = 0.096, mean bias 0.02, limits of agreement [LoA] -0.14/0.19, r = 0.83, ICC = 0.92), and in the per-patient analysis (0.81 [0.60-0.86] vs. 0.76 [0.64-0.86], P = 0.768, mean bias 0.02, LoA -0.15/0.19, r = 0.90, ICC = 0.93). All included patients were classified into the same category (CT-FFR > 0.75 vs ≤0.75) with both CT systems. CONCLUSIONS CT-FFR evaluation is feasible with PCD-CT and it shows a strong agreement with EID-CT-based evaluation when images are similarly reconstructed.
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Affiliation(s)
- Emese Zsarnoczay
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; MTA-SE Cardiovascular Imaging Research Group, Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Daniel Pinos
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA
| | - Nicola Fink
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Jim O'Doherty
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Siemens Medical Solutions USA Inc, Malvern, USA
| | - Chiara Gnasso
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Joseph Griffith
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA
| | - Milán Vecsey-Nagy
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Pal Suranyi
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany.
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA
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Zhang H, Song X, Wu R, Li N, Hou Q, Xie J, Hou Y, Qiao A. A novel method for noninvasive quantification of fractional flow reserve based on the custom function. Front Bioeng Biotechnol 2023; 11:1207300. [PMID: 37711442 PMCID: PMC10498765 DOI: 10.3389/fbioe.2023.1207300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 08/21/2023] [Indexed: 09/16/2023] Open
Abstract
Boundary condition settings are key risk factors for the accuracy of noninvasive quantification of fractional flow reserve (FFR) based on computed tomography angiography (i.e., FFRCT). However, transient numerical simulation-based FFRCT often ignores the three-dimensional (3D) model of coronary artery and clinical statistics of hyperemia state set by boundary conditions, resulting in insufficient computational accuracy and high computational cost. Therefore, it is necessary to develop the custom function that combines the 3D model of the coronary artery and clinical statistics of hyperemia state for boundary condition setting, to accurately and quickly quantify FFRCT under steady-state numerical simulations. The 3D model of the coronary artery was reconstructed by patient computed tomography angiography (CTA), and coronary resting flow was determined from the volume and diameter of the 3D model. Then, we developed the custom function that took into account the interaction of stenotic resistance, microcirculation resistance, inlet aortic pressure, and clinical statistics of resting to hyperemia state due to the effect of adenosine on boundary condition settings, to accurately and rapidly identify coronary blood flow for quantification of FFRCT calculation (FFRU). We tested the diagnostic accuracy of FFRU calculation by comparing it with the existing methods (CTA, coronary angiography (QCA), and diameter-flow method for calculating FFR (FFRD)) based on invasive FFR of 86 vessels in 73 patients. The average computational time for FFRU calculation was greatly reduced from 1-4 h for transient numerical simulations to 5 min per simulation, which was 2-fold less than the FFRD method. According to the results of the Bland-Altman analysis, the consistency between FFRU and invasive FFR of 86 vessels was better than that of FFRD. The area under the receiver operating characteristic curve (AUC) for CTA, QCA, FFRD and FFRU at the lesion level were 0.62 (95% CI: 0.51-0.74), 0.67 (95% CI: 0.56-0.79), 0.85 (95% CI: 0.76-0.94), and 0.93 (95% CI: 0.87-0.98), respectively. At the patient level, the AUC was 0.61 (95% CI: 0.48-0.74) for CTA, 0.65 (95% CI: 0.53-0.77) for QCA, 0.83 (95% CI: 0.74-0.92) for FFRD, and 0.92 (95% CI: 0.89-0.96) for FFRU. The proposed novel method might accurately and rapidly identify coronary blood flow, significantly improve the accuracy of FFRCT calculation, and support its wide application as a diagnostic indicator in clinical practice.
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Affiliation(s)
- Honghui Zhang
- Key Laboratory of Intelligent Manufacturing Technology, College of Engineering, Inner Mongolia Minzu University, Tongliao, China
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Xiaorui Song
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an, China
| | - Rile Wu
- Department of Neurology, Tong Liao City Hospital, Tongliao, China
| | - Na Li
- School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an, China
| | - Qianwen Hou
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Jinjie Xie
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Department of Echocardiography, Jiahui International Hospital, Shanghai, China
| | - Yang Hou
- Shengjing Hospital, China Medical University, Shenyang, China
| | - Aike Qiao
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
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Hu X, Liu X, Wang H, Xu L, Wu P, Zhang W, Niu Z, Zhang L, Gao Q. A novel physics-based model for fast computation of blood flow in coronary arteries. Biomed Eng Online 2023; 22:56. [PMID: 37303051 DOI: 10.1186/s12938-023-01121-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/28/2023] [Indexed: 06/13/2023] Open
Abstract
Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to the simulation of virtual interventional treatment. The purpose of this study is to propose a fast novel physics-based model, called FAST, for the prediction of blood flow and pressure. More specifically, blood flow in a vessel is discretized into a number of micro-flow elements along the centerline of the artery, so that when using the equation of viscous fluid motion, the complex blood flow in the artery is simplified into a one-dimensional (1D) steady-state flow. We demonstrate that this method can compute the fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA). 345 patients with 402 lesions are used to evaluate the feasibility of the FAST simulation through a comparison with three-dimensional (3D) computational fluid dynamics (CFD) simulation. Invasive FFR is also introduced to validate the diagnostic performance of the FAST method as a reference standard. The performance of the FAST method is comparable with the 3D CFD method. Compared with invasive FFR, the accuracy, sensitivity and specificity of FAST is 88.6%, 83.2% and 91.3%, respectively. The AUC of FFRFAST is 0.906. This demonstrates that the FAST algorithm and 3D CFD method show high consistency in predicting steady-state blood flow and pressure. Meanwhile, the FAST method also shows the potential in detecting lesion-specific ischemia.
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Affiliation(s)
- Xiuhua Hu
- Department of Radiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xingli Liu
- Hangzhou Shengshi Science and Technology Co., Ltd., Hangzhou, China
| | - Hongping Wang
- The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing, China
| | - Lei Xu
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Peng Wu
- Biomanufacturing Research Centre, School of Mechanical and Electric Engineering, Soochow University, Suzhou, Jiangsu, China
| | - Wenbing Zhang
- Department of Cardiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Zhaozhuo Niu
- Department of Cardiac Surgery, Qingdao Municipal Hospital, Qingdao, China
| | - Longjiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
| | - Qi Gao
- Institute of Fluid Engineering, School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, China.
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Arvidsson I, Davidsson A, Overgaard NC, Pagonis C, Åström K, Good E, Frias-Rose J, Heyden A, Ochoa-Figueroa M. Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera. J Nucl Cardiol 2023; 30:116-126. [PMID: 35610536 DOI: 10.1007/s12350-022-02995-6] [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: 06/28/2021] [Accepted: 03/15/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning. METHODS 546 patients (67% men) undergoing stress 99mTc-tetrofosmin MPI in a CZT camera in the upright and supine position were included (1092 MPIs). Patients were divided into two groups: ICA group included 271 patients who performed an ICA within 6 months of MPI and a control group with 275 patients with low pre-test probability for CAD and a normal MPI. QCA analyses were performed using radiologic software and verified by an expert reader. Left ventricular myocardium was segmented using clinical nuclear cardiology software and verified by an expert reader. A deep learning model was trained using a double cross-validation scheme such that all data could be used as test data as well. RESULTS Area under the receiver-operating characteristic curve for the prediction of QCA, with > 50% narrowing of the artery, by deep learning for the external test cohort: per patient 85% [95% confidence interval (CI) 84%-87%] and per vessel; LAD 74% (CI 72%-76%), RCA 85% (CI 83%-86%), LCx 81% (CI 78%-84%), and average 80% (CI 77%-83%). CONCLUSION Deep learning can predict the presence of different QCA percentages of coronary artery stenosis from MPIs.
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Affiliation(s)
- Ida Arvidsson
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Anette Davidsson
- Department of Clinical Physiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85, Linköping, Sweden
| | | | - Christos Pagonis
- Department of Cardiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Kalle Åström
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Elin Good
- Department of Cardiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Jeronimo Frias-Rose
- Department of Pathology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Anders Heyden
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Miguel Ochoa-Figueroa
- Department of Clinical Physiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85, Linköping, Sweden.
- Department of Radiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
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Rajiah P, Cummings KW, Williamson E, Young PM. CT Fractional Flow Reserve: A Practical Guide to Application, Interpretation, and Problem Solving. Radiographics 2022; 42:340-358. [PMID: 35119968 DOI: 10.1148/rg.210097] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
CT fractional flow reserve (FFRCT) is a physiologic simulation technique that models coronary flow from routine coronary CT angiography (CTA). To evaluate lesion-specific ischemia, FFRCT is measured 2 cm distal to a stenotic lesion. FFRCT greater than 0.8 is normal, 0.76-0.8 is borderline, and 0.75 or less is abnormal. FFRCT should always be interpreted in correlation with clinical and anatomic coronary CTA findings. FFRCT increases the specificity of coronary CTA in the evaluation of coronary artery disease, decreases the prevalence of nonobstructive disease in invasive coronary angiography (ICA), and helps with revascularization decisions and planning. Patients with intermediate-risk coronary anatomy at CTA and abnormal FFRCT can undergo ICA and revascularization, whereas those with normal FFRCT can be safely deferred from ICA. In borderline FFRCT values, management is decided in the context of the clinical scenario, but many cases could be safely managed with medical treatment. There are some limitations and pitfalls of FFRCT. Abnormal FFRCT values can be seen in mild stenosis, and normal FFRCTvalues can be seen in severe stenosis. Gradually decreasing or abnormal low FFRCT values at the distal vessel without a proximal focal lesion could be due to diffuse atherosclerosis. Coronary stents, bypass grafts, coronary anomalies, coronary dissection, transcatheter aortic valve replacement, unstable angina, and acute or recent myocardial infarction are situations in which FFRCT has not been validated and should not be used at this time. The authors provide a practical guide to the applications and interpretation of FFRCT, focusing on common pitfalls and challenges. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Prabhakar Rajiah
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905 (P.R., E.W., P.M.Y.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (K.W.C.)
| | - Kristopher W Cummings
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905 (P.R., E.W., P.M.Y.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (K.W.C.)
| | - Eric Williamson
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905 (P.R., E.W., P.M.Y.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (K.W.C.)
| | - Phillip M Young
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905 (P.R., E.W., P.M.Y.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (K.W.C.)
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Peper J, Schaap J, Rensing BJWM, Kelder JC, Swaans MJ. Diagnostic accuracy of on-site coronary computed tomography-derived fractional flow reserve in the diagnosis of stable coronary artery disease. Neth Heart J 2021; 30:160-171. [PMID: 34910279 PMCID: PMC8881589 DOI: 10.1007/s12471-021-01647-7] [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] [Accepted: 10/01/2021] [Indexed: 10/30/2022] Open
Abstract
PURPOSE Invasive fractional flow reserve (FFR), the reference standard for identifying significant coronary artery disease (CAD), can be estimated non-invasively by computed tomography-derived fractional flow reserve (CT-FFR). Commercially available off-site CT-FFR showed improved diagnostic accuracy compared to coronary computed tomography angiography (CCTA) alone. However, the diagnostic performance of this lumped-parameter on-site method is unknown. The aim of this cross-sectional study was to determine the diagnostic accuracy of on-site CT-FFR in patients with suspected CAD. METHODS A total of 61 patients underwent CCTA and invasive coronary angiography with FFR measured in 88 vessels. Significant CAD was defined as FFR and CT-FFR below 0.80. CCTA with stenosis above 50% was regarded as significant CAD. The diagnostic performance of both CT-FFR and CCTA was assessed using invasive FFR as the reference standard. RESULTS Of the 88 vessels included in the analysis, 34 had an FFR of ≤ 0.80. On a per-vessel basis, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 91.2%, 81.4%, 93.6%, 75.6% and 85.2% for CT-FFR and were 94.1%, 68.5%, 94.9%, 65.3% and 78.4% for CCTA. The area under the receiver operating characteristic curve was 0.91 and 0.85 for CT-FFR and CCTA, respectively, on a per-vessel basis. CONCLUSION On-site non-invasive FFR derived from CCTA improves diagnostic accuracy compared to CCTA without additional testing and has the potential to be integrated in the current clinical work-up for diagnosing stable CAD.
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Affiliation(s)
- J Peper
- Department of Cardiology, St. Antonius Hospital, Nieuwegein, The Netherlands. .,Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands.
| | - J Schaap
- Department of Cardiology, Amphia Hospital, Breda, The Netherlands
| | - B J W M Rensing
- Department of Cardiology, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - J C Kelder
- Department of Cardiology, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - M J Swaans
- Department of Cardiology, St. Antonius Hospital, Nieuwegein, The Netherlands
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Kamo Y, Fujimoto S, Nozaki YO, Aoshima C, Kawaguchi YO, Dohi T, Kudo A, Takahashi D, Takamura K, Hiki M, Okai I, Okazaki S, Tomizawa N, Kumamaru KK, Aoki S, Minamino T. Incremental Diagnostic Value of CT Fractional Flow Reserve Using Subtraction Method in Patients with Severe Calcification: A Pilot Study. J Clin Med 2021; 10:jcm10194398. [PMID: 34640414 PMCID: PMC8509262 DOI: 10.3390/jcm10194398] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 12/30/2022] Open
Abstract
Although on-site workstation-based CT fractional flow reserve (CT-FFR) is an emerging method for assessing vessel-specific ischemia in coronary artery disease, severe calcification is a significant factor affecting CT-FFR’s diagnostic performance. The subtraction method significantly improves the diagnostic value with respect to anatomic stenosis for patients with severe calcification in coronary CT angiography (CCTA). We evaluated the diagnostic capability of CT-FFR using the subtraction method (subtraction CT-FFR) in patients with severe calcification. This study included 32 patients with 45 lesions with severe calcification (Agatston score >400) who underwent both CCTA and subtraction CCTA using 320-row area detector CT and also received invasive FFR within 90 days. The diagnostic capabilities of CT-FFR and subtraction CT-FFR were compared. The sensitivities, specificities, positive predictive values (PPVs), and negative predictive values (NPVs) of CT-FFR vs. subtraction CT-FFR for detecting hemodynamically significant stenosis, defined as FFR ≤ 0.8, were 84.6% vs. 92.3%, 59.4% vs. 75.0%, 45.8% vs. 60.0%, and 90.5% vs. 96.0%, respectively. The area under the curve for subtraction CT-FFR was significantly higher than for CT-FFR (0.84 vs. 0.70) (p = 0.04). The inter-observer and intra-observer variabilities of subtraction CT-FFR were 0.76 and 0.75, respectively. In patients with severe calcification, subtraction CT-FFR had an incremental diagnostic value over CT-FFR, increasing the specificity and PPV while maintaining the sensitivity and NPV with high reproducibility.
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Affiliation(s)
- Yuki Kamo
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Shinichiro Fujimoto
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
- Correspondence: ; Tel.: +81-3-5802-1056
| | - Yui O. Nozaki
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Chihiro Aoshima
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Yuko O. Kawaguchi
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Tomotaka Dohi
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Ayako Kudo
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Daigo Takahashi
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Kazuhisa Takamura
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Makoto Hiki
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Iwao Okai
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Shinya Okazaki
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
| | - Nobuo Tomizawa
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (N.T.); (K.K.K.); (S.A.)
| | - Kanako K. Kumamaru
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (N.T.); (K.K.K.); (S.A.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (N.T.); (K.K.K.); (S.A.)
| | - Tohru Minamino
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (Y.K.); (Y.O.N.); (C.A.); (Y.O.K.); (T.D.); (A.K.); (D.T.); (K.T.); (M.H.); (I.O.); (S.O.); (T.M.)
- Japan Agency for Medical Research and Development-Core Research for Evolutionary Medical Science and Technology (AMED-CREST), Japan Agency for Medical Research and Development, Tokyo 100-0004, Japan
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Hsieh YF, Lee CK, Wang W, Huang YC, Lee WJ, Wang TD, Chou CY. Coronary CT angiography-based estimation of myocardial perfusion territories for coronary artery FFR and wall shear stress simulation. Sci Rep 2021; 11:13855. [PMID: 34226598 PMCID: PMC8257574 DOI: 10.1038/s41598-021-93237-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/21/2021] [Indexed: 11/30/2022] Open
Abstract
This study aims to apply a CCTA-derived territory-based patient-specific estimation of boundary conditions for coronary artery fractional flow reserve (FFR) and wall shear stress (WSS) simulation. The non-invasive simulation can help diagnose the significance of coronary stenosis and the likelihood of myocardial ischemia. FFR is often regarded as the gold standard to evaluate the functional significance of stenosis in coronary arteries. In another aspect, proximal wall shear stress (\documentclass[12pt]{minimal}
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\begin{document}$$\mathrm{{WSS}_{prox}}$$\end{document}WSSprox) can also be an indicator of plaque vulnerability. During the simulation process, the mass flow rate of the blood in coronary arteries is one of the most important boundary conditions. This study utilized the myocardium territory to estimate and allocate the mass flow rate. 20 patients are included in this study. From the knowledge of anatomical information of coronary arteries and the myocardium, the territory-based FFR and the \documentclass[12pt]{minimal}
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\begin{document}$$\mathrm{{WSS}_{prox}}$$\end{document}WSSprox can both be derived from fluid dynamics simulations. Applying the threshold of distinguishing between significant and non-significant stenosis, the territory-based method can reach the accuracy, sensitivity, and specificity of 0.88, 0.90, and 0.80, respectively. For significantly stenotic cases (\documentclass[12pt]{minimal}
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\begin{document}$$\mathrm{FFR}_{m}$$\end{document}FFRm\documentclass[12pt]{minimal}
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\begin{document}$$\le$$\end{document}≤ 0.80), the vessels usually have higher wall shear stress in the proximal region of the lesion.
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Affiliation(s)
- Yu-Fang Hsieh
- Department of Biomechatronics Engineering, National Taiwan University, Taipei, 106, Taiwan
| | - Chih-Kuo Lee
- Department of Internal Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, 300, Taiwan
| | - Weichung Wang
- Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, 106, Taiwan
| | - Yu-Cheng Huang
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, 100, Taiwan
| | - Wen-Jeng Lee
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, 100, Taiwan
| | - Tzung-Dau Wang
- Cardiovascular Center and Divisions of Cardiology and Hospital Medicine, Department of Internal Medicine, National Taiwan University Hospital, Taipei, 100, Taiwan
| | - Cheng-Ying Chou
- Department of Biomechatronics Engineering, National Taiwan University, Taipei, 106, Taiwan.
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Luo Y, Mao M, Xiang R, Han B, Chang J, Zuo Z, Wu F, Ma K. Diagnostic performance of computed tomography-based fraction flow reserve in identifying myocardial ischemia caused by coronary artery stenosis: A meta-analysis. Hellenic J Cardiol 2021; 63:1-7. [PMID: 34107338 DOI: 10.1016/j.hjc.2021.05.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 05/14/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND As a new noninvasive diagnostic technique, computed tomography (CT)-based fraction flow reserve (FFR) has been used to identify hemodynamically significant coronary artery stenosis. This meta-analysis used invasive FFR as the standard to evaluate the diagnostic performance of FFRCT. METHODS We searched the PubMed, Cochrane library, and EMBASE for articles published between January 2009 and January 2021. The synthesized sensitivity and specificity of invasive FFR and FFRCT were analyzed at both the patient and vessel levels. We generated a summary receiver operating characteristic curve (SROC) and then calculated the area under the curve (AUC). RESULTS We included a total of 23 studies, including 2,178 patients and 3,029 vessels or lesions. Analysis at each patient level demonstrated a synthesized sensitivity of 88%, specificity of 79%, LR+ of 4.16, LR-of 0.15, and AUC of 0.89 for FFRCT. Analysis at the level of each vessel or lesion showed a synthesized sensitivity of 85%, specificity of 81%, LR+ of 4.44, LR-of 0.19, and AUC of 0.87 for FFRCT. CONCLUSION Our research reveals that FFRCT has high diagnostic performance in patients with coronary artery stenosis, regardless of whether it is at the patient level or the vessel level.
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Affiliation(s)
- Yue Luo
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Min Mao
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Rui Xiang
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Baoru Han
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jing Chang
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zhong Zuo
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Fan Wu
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Kanghua Ma
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Clinical application of computed tomography angiography and fractional flow reserve computed tomography in patients with coronary artery disease: A meta-analysis based on pre- and post-test probability. Eur J Radiol 2021; 139:109712. [PMID: 33865062 DOI: 10.1016/j.ejrad.2021.109712] [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: 01/13/2021] [Revised: 03/22/2021] [Accepted: 04/06/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE To assess the diagnostic role of coronary computed tomography angiography (CCTA) and fractional flow reserve computed tomography (FFRCT) in confirming or excluding ischemic coronary artery disease (CAD) and to provide a rational use of CCTA and FFRCT in different pre-test probability (PTP) of CAD. METHODS We searched the electronic databases from the earliest relevant literature to July 2020 comparing FFRCT or CCTA with FFR. The bivariate random-effects models and Bayes' theorem were used to investigate the diagnostic performance of CCTA and FFRCT with the sensitivity, specificity, pre- and post-test probability. RESULTS Fifty-three articles with 4817 patients and 7026 vessels finally met our inclusion criteria. At the patient level, the sensitivity and specificity of CCTA were (0.94, 0.89-0.97), and (0.50, 0.43-0.58), respectively. For FFRCT, the sensitivity and specificity were (0.90, 0.87-0.93) and (0.81, 0.73-0.87). CCTA or FFRCT could increase the post-test probability to >85 % in patients with a PTP > 74.9 % or 54.5 %; CCTA or FFRCT could decrease the post-test probability to <15 % in patients with a pre-test probability <61.3 % or 59.3 %. CONCLUSIONS In patients with low to intermediate PTP, CCTA is suggested to exclude CAD, while the time-consuming calculation of FFRCT may be unnecessary. If CCTA detects significant or uncertain stenosis with intermediate to high PTP of CAD, further FFRCT is suggested. The advantages of FFRCT for guiding CAD treatment have sufficiently been demonstrated.
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11
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Asher A, Wragg A, Davies C. Review: FFRCT Changing the Face of Cardiac CT. CURRENT CARDIOVASCULAR IMAGING REPORTS 2020. [DOI: 10.1007/s12410-020-09548-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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12
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Peper J, Suchá D, Swaans M, Leiner T. Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning. Br J Radiol 2020; 93:20200349. [PMID: 32783626 DOI: 10.1259/bjr.20200349] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR, CT-myocardial perfusion and how developments in machine learning can supplement these techniques.
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Affiliation(s)
- Joyce Peper
- Department of Cardiology, St. Antonius Hospital Koekoekslaan 1, Nieuwegein, the Netherlands.,Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands
| | - Dominika Suchá
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands
| | - Martin Swaans
- Department of Cardiology, St. Antonius Hospital Koekoekslaan 1, Nieuwegein, the Netherlands
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands
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Tian XW, Ma AL, Zhou RB, Jiang LJ, Hao Y, Zou XG. Advances in Cardiac Computed Tomography Functional Imaging Technology. Cardiology 2020; 145:615-622. [PMID: 32829331 DOI: 10.1159/000505317] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 12/09/2019] [Indexed: 11/19/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death among patients in China, and cardiac computed tomography (CT) is one of the most commonly used examination methods for CVD. Coronary artery CT angiography can be used for the morphologic evaluation of the coronary artery. At present, cardiac CT functional imaging has become an important direction of development of CT. At present, common CT functional imaging technologies include transluminal attenuation gradient, stress dynamic CT myocardial perfusion imaging, and CT-fractional flow reserve. These three imaging modes are introduced and analyzed in this review.
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Affiliation(s)
- Xu-Wei Tian
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China
| | - Ai-Lin Ma
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China
| | - Ren-Bing Zhou
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China
| | - Liu-Jiang Jiang
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China
| | - Yue Hao
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China
| | - Xiao-Guang Zou
- Department of Radiology, Department of Medical Imaging, The First People's Hospital Kashgar Region, Kashgar, China,
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14
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Tanabe Y, Kurata A, Matsuda T, Yoshida K, Baruah D, Kido T, Mochizuki T, Rajiah P. Computed tomographic evaluation of myocardial ischemia. Jpn J Radiol 2020; 38:411-433. [PMID: 32026226 PMCID: PMC7186254 DOI: 10.1007/s11604-020-00922-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 01/20/2020] [Indexed: 01/02/2023]
Abstract
Myocardial ischemia is caused by a mismatch between myocardial oxygen consumption and oxygen delivery in coronary artery disease (CAD). Stratification and decision-making based on ischemia improves the prognosis in patients with CAD. Non-invasive tests used to evaluate myocardial ischemia include stress electrocardiography, echocardiography, single-photon emission computed tomography, and magnetic resonance imaging. Invasive fractional flow reserve is considered the reference standard for assessment of the hemodynamic significance of CAD. Computed tomography (CT) angiography has emerged as a first-line imaging modality for evaluation of CAD, particularly in the population at low to intermediate risk, because of its high negative predictive value; however, CT angiography does not provide information on the hemodynamic significance of stenosis, which lowers its specificity. Emerging techniques, e.g., CT perfusion and CT-fractional flow reserve, help to address this limitation of CT, by determining the hemodynamic significance of coronary artery stenosis. CT perfusion involves acquisition during the first pass of contrast medium through the myocardium following pharmacological stress. CT-fractional flow reserve uses computational fluid dynamics to model coronary flow, pressure, and resistance. In this article, we review these two functional CT techniques in the evaluation of myocardial ischemia, including their principles, technology, advantages, limitations, pitfalls, and the current evidence.
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Affiliation(s)
- Yuki Tanabe
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Akira Kurata
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Takuya Matsuda
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Kazuki Yoshida
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Dhiraj Baruah
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Teruhito Kido
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan.
| | - Teruhito Mochizuki
- Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan
- Department of Radiology, I.M. Sechenov First Moscow State Medical University, Bol'shaya Pirogovskaya Ulitsa, Moscow, Russia
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von Spiczak J, Mannil M, Model H, Schwemmer C, Kozerke S, Ruschitzka F, Alkadhi H, Manka R. Multimodal Multiparametric Three-dimensional Image Fusion in Coronary Artery Disease: Combining the Best of Two Worlds. Radiol Cardiothorac Imaging 2020; 2:e190116. [PMID: 33778554 PMCID: PMC7977970 DOI: 10.1148/ryct.2020190116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 09/19/2019] [Accepted: 09/26/2019] [Indexed: 11/11/2022]
Abstract
PURPOSE To allow for comprehensive noninvasive diagnostics of coronary artery disease (CAD) by using three-dimensional (3D) image fusion of CT coronary angiography, CT-derived fractional flow reserve (CT FFR), whole-heart dynamic 3D cardiac MRI perfusion, and 3D cardiac MRI late gadolinium enhancement (LGE). MATERIALS AND METHODS Seventeen patients (54 years ± 10 [standard deviation], one female) who underwent cardiac CT and cardiac MRI were included (combined subcohort of three prospective trials). Software facilitating multimodal 3D image fusion was developed. Postprocessing of CT data included segmentation of the coronary tree and heart contours, calculation of CT FFR values, and color coding of the coronary tree according to CT FFR. Postprocessing of cardiac MRI data included segmentation of the left ventricle (LV) in cardiac MRI perfusion and cardiac MRI LGE, co-registration of cardiac MRI to CT data, and projection of cardiac MRI perfusion and LGE values onto the high spatial resolution LV from CT. RESULTS Image quality was rated as good to excellent (scores: 2.5-2.6; 3 = excellent). CT coronary angiography revealed significant stenoses in seven of 17 cases (41%). CT FFR was possible in 16 of 17 cases (94%) and showed pathologic flow in seven of 17 cases (41%), six of which coincided with cases revealing significant stenoses at CT coronary angiography. Cardiac MRI perfusion identified eight of 17 patients (47%) with hypoperfusion (ischemic burden of 17% ± 5). Cardiac MRI LGE showed myocardial scar in three of 17 cases (18%, scar burden of 7% ± 4). Conventional two-dimensional readout of CT coronary angiography and cardiac MRI resulted in eight of 17 cases (47%) with uncertain findings. Most of these divergent findings could be solved when adding information from CT FFR and 3D image fusion (six of eight, 75%). CONCLUSION Multimodal 3D cardiac image fusion is feasible and may help with comprehensive noninvasive CAD diagnostics.Supplemental material is available for this article.© RSNA, 2020.
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Affiliation(s)
- Jochen von Spiczak
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Manoj Mannil
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Hanna Model
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Chris Schwemmer
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Sebastian Kozerke
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Frank Ruschitzka
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Hatem Alkadhi
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
| | - Robert Manka
- From the Institute of Diagnostic and Interventional Radiology (J.v.S., M.M., H.M., H.A., R.M.) and Department of Cardiology, University Heart Center (F.R., R.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; Siemens Healthineers, Forchheim, Germany (C.S.); and Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland (J.v.S., S.K., R.M.)
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van Hamersvelt RW, Voskuil M, de Jong PA, Willemink MJ, Išgum I, Leiner T. Diagnostic Performance of On-Site Coronary CT Angiography-derived Fractional Flow Reserve Based on Patient-specific Lumped Parameter Models. Radiol Cardiothorac Imaging 2019; 1:e190036. [PMID: 33778519 DOI: 10.1148/ryct.2019190036] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 06/14/2019] [Accepted: 06/20/2019] [Indexed: 11/11/2022]
Abstract
Purpose To evaluate the diagnostic performance of a prototype on-site coronary CT angiography-derived fractional flow reserve (CT FFR) algorithm, based on patient-specific lumped parameter models, for the detection of functionally significant stenosis defined by invasive FFR, and to compare the performance to anatomic evaluation of stenosis degree. Materials and Methods In this retrospective feasibility study, 77 vessels in 57 patients (42 of 57 [74%]) men; mean age, 58.5 years ± 9.2 [standard deviation]) who underwent clinically indicated coronary CT angiography within 60 days prior to an invasive FFR measurement were analyzed. Invasive FFR less than or equal to 0.80 was used to indicate a functionally significant stenosis. Diagnostic performance of CT FFR was evaluated and compared with evaluation of stenosis degree. Analysis was performed on a per-vessel basis. Results Invasive FFR revealed functionally significant stenoses in 37 vessels (48%). CT FFR showed a significantly increased ability to indicate functionally significant stenosis (area under the receiver operating characteristic curve [AUC], 0.87) compared with degree of stenosis at coronary CT angiography (AUC, 0.70; ΔAUC 0.17; P < .01). Using a cutoff of less than or equal to 0.80 for CT FFR and greater than or equal to 50% degree of stenosis at coronary CT angiography to indicate a significant stenosis, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 33 of 37 (89.2%), 31 of 40 (77.5%), 33 of 42 (78.6%), 31 of 35 (88.6%), and 64 of 77 (83.1%), respectively, for CT FFR, and 33 of 37 (89.2%), 17 of 40 (42.5%), 33 of 56 (58.9%), 17 of 21 (81.0%), and 50 of 77 (64.9%), respectively, for degree of stenosis at coronary CT angiography. Conclusion Diagnostic performance of on-site CT FFR was superior to stenosis evaluation at coronary CT angiography for identification of functionally significant coronary artery stenosis in patients suspected of having or known to have coronary artery disease.© RSNA, 2019See also commentary by Schoepf et al.
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Affiliation(s)
- Robbert W van Hamersvelt
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
| | - Michiel Voskuil
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
| | - Pim A de Jong
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
| | - Martin J Willemink
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
| | - Ivana Išgum
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
| | - Tim Leiner
- Departments of Radiology (R.W.v.H., P.A.d.J., M.J.W., T.L.) and Cardiology (M.V.), University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508GA Utrecht, the Netherlands; Department of Radiology, Stanford University School of Medicine, Stanford, Calif (M.J.W.); and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (I.I.)
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Diagnostic performance of a fast non-invasive fractional flow reserve derived from coronary CT angiography: an initial validation study. Clin Radiol 2019; 74:973.e1-973.e6. [PMID: 31537312 DOI: 10.1016/j.crad.2019.08.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 08/19/2019] [Indexed: 11/23/2022]
Abstract
AIM To validate the computed tomography (CT)-derived fractional flow reserve (FFRCT) that was computed by new, fast, automatic software and to compare the diagnostic accuracy between FFRCT and stenosis diagnosed at coronary CT angiography (CCTA). MATERIALS AND METHODS A total of 110 patients (76 males, 59±9 years) and 125 vessels underwent CCTA. FFRCT was computed by fast automatic software and compared with invasive FFR. The diagnostic performance between FFRCT and CCTA-diagnosed stenosis were compared on the per-patient and per-vessel level. RESULTS The computational time of FFRCT is 10±5 minutes (averaged over 125 vessels). The FFRCT has a good correlation with invasive FFR (r=0.59, p<0.0001) with a small bias of -0.02 (-0.26-0.23). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FFRCT were 76.5, 89.5, 89.7, and 76.1% on a vessel level. The area under the receiver operating characteristic curve of FFRCT was higher than CCTA-diagnosed stenosis (0.82 versus 0.72, P=0.034). CONCLUSION The computation of FFRCT is possible and reliable when using the new, fast, automatic software first employed in the present clinical study. The FFRCT has a good correlation with invasive FFR and provides better diagnostic performance than CCTA-diagnosed stenosis.
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Tesche C, Otani K, De Cecco CN, Coenen A, De Geer J, Kruk M, Kim YH, Albrecht MH, Baumann S, Renker M, Bayer RR, Duguay TM, Litwin SE, Varga-Szemes A, Steinberg DH, Yang DH, Kepka C, Persson A, Nieman K, Schoepf UJ. Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry. JACC Cardiovasc Imaging 2019; 13:760-770. [PMID: 31422141 DOI: 10.1016/j.jcmg.2019.06.027] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 06/10/2019] [Accepted: 06/19/2019] [Indexed: 01/10/2023]
Abstract
OBJECTIVES This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR). BACKGROUND CT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated. METHODS A total of 482 vessels from 314 patients (age 62.3 ± 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and ≥400) on a per-vessel level with invasive FFR as the reference standard. RESULTS The diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC ≥400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC ≥ 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001). CONCLUSIONS Machine-learning-based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621).
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Affiliation(s)
- Christian Tesche
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany; Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Munich, Germany
| | - Katharina Otani
- Advanced Therapies Innovation Department, Siemens Healthcare K.K., Tokyo, Japan
| | - Carlo N De Cecco
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Adriaan Coenen
- Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jakob De Geer
- Department of Radiology and Department of Medical and Health Sciences, Center for Medical Image Science and Visualization, CMIV, Linköping University, Linköping, Sweden
| | - Mariusz Kruk
- Coronary Disease and Structural Heart Diseases Department, Invasive Cardiology and Angiology Department, Institute of Cardiology, Warsaw, Poland
| | - Young-Hak Kim
- Department of Cardiology, Heart Institute Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Moritz H Albrecht
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Stefan Baumann
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; First Department of Medicine, Faculty of Medicine Mannheim, University Medical Centre Mannheim (UMM), University of Heidelberg, Mannheim, Germany
| | - Matthias Renker
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Department of Cardiology, Kerckhoff Heart Center, Bad Nauheim, Germany
| | - Richard R Bayer
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - Taylor M Duguay
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Sheldon E Litwin
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Daniel H Steinberg
- Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - Dong Hyun Yang
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Cezary Kepka
- Coronary Disease and Structural Heart Diseases Department, Invasive Cardiology and Angiology Department, Institute of Cardiology, Warsaw, Poland
| | - Anders Persson
- Department of Radiology and Department of Medical and Health Sciences, Center for Medical Image Science and Visualization, CMIV, Linköping University, Linköping, Sweden
| | - Koen Nieman
- Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, South Carolina.
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19
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Coenen A, Kim YH, Kruk M, Tesche C, De Geer J, Kurata A, Lubbers ML, Daemen J, Itu L, Rapaka S, Sharma P, Schwemmer C, Persson A, Schoepf UJ, Kepka C, Hyun Yang D, Nieman K. Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium. Circ Cardiovasc Imaging 2019; 11:e007217. [PMID: 29914866 DOI: 10.1161/circimaging.117.007217] [Citation(s) in RCA: 243] [Impact Index Per Article: 48.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Accepted: 04/25/2018] [Indexed: 12/31/2022]
Abstract
BACKGROUND Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necessarily imply hemodynamic relevance when fractional flow reserve (FFR) is used as reference. CTA-based FFR (CT-FFR), using computational fluid dynamics (CFD), improves the correlation with invasive FFR results but is computationally demanding. More recently, a new machine-learning (ML) CT-FFR algorithm has been developed based on a deep learning model, which can be performed on a regular workstation. In this large multicenter cohort, the diagnostic performance ML-based CT-FFR was compared with CTA and CFD-based CT-FFR for detection of functionally obstructive coronary artery disease. METHODS AND RESULTS At 5 centers in Europe, Asia, and the United States, 351 patients, including 525 vessels with invasive FFR comparison, were included. ML-based and CFD-based CT-FFR were performed on the CTA data, and diagnostic performance was evaluated using invasive FFR as reference. Correlation between ML-based and CFD-based CT-FFR was excellent (R=0.997). ML-based (area under curve, 0.84) and CFD-based CT-FFR (0.84) outperformed visual CTA (0.69; P<0.0001). On a per-vessel basis, diagnostic accuracy improved from 58% (95% confidence interval, 54%-63%) by CTA to 78% (75%-82%) by ML-based CT-FFR. The per-patient accuracy improved from 71% (66%-76%) by CTA to 85% (81%-89%) by adding ML-based CT-FFR as 62 of 85 (73%) false-positive CTA results could be correctly reclassified by adding ML-based CT-FFR. CONCLUSIONS On-site CT-FFR based on ML improves the performance of CTA by correctly reclassifying hemodynamically nonsignificant stenosis and performs equally well as CFD-based CT-FFR.
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Affiliation(s)
- Adriaan Coenen
- Department of Cardiology (A.C., M.L.L., J.D., K.N.) .,Department of Radiology (A.C., A.K., M.L.L., K.N.)
| | - Young-Hak Kim
- Erasmus University Medical Center, Rotterdam, the Netherlands. Department of Cardiology, Heart Institute (Y.-H.K.)
| | - Mariusz Kruk
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. Coronary Disease and Structural Heart Diseases Department, Institute of Cardiology, Warsaw, Poland (M.K., C.K.)
| | - Christian Tesche
- Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston (C.T., U.J.S.)
| | - Jakob De Geer
- Department of Radiology and Department of Medical and Health Sciences, Center for Medical Image Science and Visualization, Linköping University, Sweden (J.D.G., A.P.)
| | - Akira Kurata
- Department of Radiology (A.C., A.K., M.L.L., K.N.).,Department of Radiology, Ehime University Graduate School of Medicine, Japan (A.K.)
| | - Marisa L Lubbers
- Department of Cardiology (A.C., M.L.L., J.D., K.N.).,Department of Radiology (A.C., A.K., M.L.L., K.N.)
| | - Joost Daemen
- Department of Cardiology (A.C., M.L.L., J.D., K.N.)
| | - Lucian Itu
- Corporate Technology, Siemens SRL, Brasov, Romania (L.I.)
| | - Saikiran Rapaka
- Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ (S.R., P.S.)
| | - Puneet Sharma
- Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ (S.R., P.S.)
| | - Chris Schwemmer
- Computed Tomography-Research & Development, Siemens Healthcare GmbH, Forchheim, Germany (C.S.)
| | - Anders Persson
- Department of Radiology and Department of Medical and Health Sciences, Center for Medical Image Science and Visualization, Linköping University, Sweden (J.D.G., A.P.)
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston (C.T., U.J.S.)
| | - Cezary Kepka
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. Coronary Disease and Structural Heart Diseases Department, Institute of Cardiology, Warsaw, Poland (M.K., C.K.)
| | | | - Koen Nieman
- Department of Cardiology (A.C., M.L.L., J.D., K.N.).,Department of Radiology (A.C., A.K., M.L.L., K.N.).,Stanford University School of Medicine, Cardiovascular Institute, Stanford, CA, USA (K.N.)
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20
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Kohli A. CT FFR A paradigm shift in evaluation of coronary artery disease. Indian J Radiol Imaging 2019; 29:233-235. [PMID: 31741589 PMCID: PMC6857255 DOI: 10.4103/ijri.ijri_412_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 10/11/2019] [Accepted: 10/12/2019] [Indexed: 01/12/2023] Open
Affiliation(s)
- Anirudh Kohli
- Breach Candy Hospital Trust Mumbai, Maharashtra, India. E-mail:
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21
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Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry. AJR Am J Roentgenol 2019; 213:325-331. [PMID: 31039021 DOI: 10.2214/ajr.18.20774] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE. Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFRML). However, attenuation values vary according to the tube voltage used, and it has not been shown whether this significantly affects the diagnostic performance of cFFR and cFFRML. Therefore, the purpose of this study is to retrospectively evaluate the effect of tube voltage on the diagnostic performance of cFFRML. MATERIALS AND METHODS. A total of 525 coronary vessels in 351 patients identified in the MACHINE consortium registry were evaluated in terms of invasively measured FFR and cFFRML. CCTA examinations were performed with a tube voltage of 80, 100, or 120 kVp. For each tube voltage value, correlation (assessed by Spearman rank correlation coefficient), agreement (evaluated by intraclass correlation coefficient and Bland-Altman plot analysis), and diagnostic performance (based on ROC AUC value, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) of the cFFRML in terms of detection of significant stenosis were calculated. RESULTS. For tube voltages of 80, 100, and 120 kVp, the Spearman correlation coefficient for cFFRML in relation to the invasively measured FFR value was ρ = 0.684, ρ = 0.622, and ρ = 0.669, respectively (p < 0.001 for all). The corresponding intraclass correlation coefficient was 0.78, 0.76, and 0.77, respectively (p < 0.001 for all). Sensitivity was 100.0%, 73.5%, and 85.0%, and specificity was 76.2%, 79.0%, and 72.8% for tube voltages of 80, 100, and 120 kVp, respectively. The ROC AUC value was 0.90, 0.82, and 0.80 for 80, 100, and 120 kVp, respectively (p < 0.001 for all). CONCLUSION. CCTA-derived cFFRML is a robust method, and its performance does not vary significantly between examinations performed using tube voltages of 100 kVp and 120 kVp. However, because of rapid advancements in CT and postprocessing technology, further research is needed.
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22
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Alzahrani T, Tashkandi A, Sarkar A, Smuclovisky C, Earls JP, Choi AD. Practical Clinical Application of Cardiac Computed Tomography‐Derived Fractional Flow Reserve. CARDIOVASCULAR INNOVATIONS AND APPLICATIONS 2019. [DOI: 10.15212/cvia.2019.0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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23
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Additional diagnostic value of new CT imaging techniques for the functional assessment of coronary artery disease: a meta-analysis. Eur Radiol 2019; 29:3044-3061. [DOI: 10.1007/s00330-018-5919-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 10/30/2018] [Accepted: 11/27/2018] [Indexed: 12/14/2022]
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24
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Asher A, Singhal A, Thornton G, Wragg A, Davies C. FFR CT derived from computed tomography angiography: the experience in the UK. Expert Rev Cardiovasc Ther 2018; 16:919-929. [PMID: 30347174 DOI: 10.1080/14779072.2018.1538786] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
INTRODUCTION Non-invasive fractional flow reserve derived from CT coronary angiography (FFRCT) represents a novel technology to investigate coronary artery disease. The application of computational flow dynamics to anatomical data provides the clinician with a further functional assessment to inform decision-making in patients with coronary artery disease. In the UK FFRCT has received medical technology approval for use since February 2017. Areas covered: This article discusses the mathematical and physiological principles underpinning calculation of non-invasive fractional flow reserve (FFR), as well as discussing the differences between the commercially available technologies. Diagnostic accuracy, cost effectiveness and safety of non-invasive FFR from the early clinical trials is examined. Further to this the potential implications of the use of non-invasive FFR in clinical practice in the UK are discussed. Expert commentary: Non-invasive FFR represents a promising comprehensive imaging technology providing both anatomical and physiological data to accurately diagnose obstructive coronary artery disease. The technology has yet to prove to be cost effective in 'real world' cohorts before becoming integrated into everyday clinical practice and guidelines in the United Kingdom.
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Affiliation(s)
- Alex Asher
- a The Royal London Hospital and St Bartholomew's Hospital, London, Barts Health NHS Trust , London , UK
| | - Arvind Singhal
- a The Royal London Hospital and St Bartholomew's Hospital, London, Barts Health NHS Trust , London , UK
| | - George Thornton
- a The Royal London Hospital and St Bartholomew's Hospital, London, Barts Health NHS Trust , London , UK
| | - Andrew Wragg
- a The Royal London Hospital and St Bartholomew's Hospital, London, Barts Health NHS Trust , London , UK
| | - Ceri Davies
- a The Royal London Hospital and St Bartholomew's Hospital, London, Barts Health NHS Trust , London , UK
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25
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Fujimoto S, Kawasaki T, Kumamaru KK, Kawaguchi Y, Dohi T, Okonogi T, Ri K, Yamada S, Takamura K, Kato E, Kato Y, Hiki M, Okazaki S, Aoki S, Mitsouras D, Rybicki FJ, Daida H. Diagnostic performance of on-site computed CT-fractional flow reserve based on fluid structure interactions: comparison with invasive fractional flow reserve and instantaneous wave-free ratio. Eur Heart J Cardiovasc Imaging 2018; 20:343-352. [DOI: 10.1093/ehjci/jey104] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 04/23/2018] [Accepted: 07/03/2018] [Indexed: 01/10/2023] Open
Affiliation(s)
- Shinichiro Fujimoto
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Tomonori Kawasaki
- Department of Cardiovascular Medicine, Shin-Koga Hospital, Kurume, Japan
| | - Kanako K Kumamaru
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuko Kawaguchi
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Tomotaka Dohi
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Taichi Okonogi
- Department of Cardiovascular Medicine, Shin-Koga Hospital, Kurume, Japan
| | - Keiken Ri
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Sou Yamada
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Kazuhisa Takamura
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Etsuro Kato
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Yoshiteru Kato
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Makoto Hiki
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Shinya Okazaki
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
| | - Shigeki Aoki
- Department of Cardiovascular Medicine, Shin-Koga Hospital, Kurume, Japan
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Dimitris Mitsouras
- Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, The University of Ottawa, The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Frank J Rybicki
- Department of Radiology, The University of Ottawa, The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Hiroyuki Daida
- Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan
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Agasthi P, Kanmanthareddy A, Khalil C, Egbuche O, Yarlagadda V, Sachdeva R, Arsanjani R. Comparison of Computed Tomography derived Fractional Flow Reserve to invasive Fractional Flow Reserve in Diagnosis of Functional Coronary Stenosis: A Meta-Analysis. Sci Rep 2018; 8:11535. [PMID: 30069020 PMCID: PMC6070545 DOI: 10.1038/s41598-018-29910-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 07/19/2018] [Indexed: 12/14/2022] Open
Abstract
Computed Tomography derived Fractional Flow Reserve (CTFFR) is an emerging non-invasive imaging modality to assess functional significance of coronary stenosis. We performed a meta-analysis to compare the diagnostic performance of CTFFR to invasive Fractional Flow reserve (FFR). Electronic search was performed to identify relevant articles. Pooled Estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR) with corresponding 95% confidence intervals (CI) were calculated at the patient level as well as the individual vessel level using hierarchical logistic regression, summary receiver operating characteristic (SROC) curve and area under the curve were estimated. Our search yielded 559 articles and of these 17 studies was included in the analysis. A total of 2,191 vessels in 1294 patients were analyzed. Pooled estimates of sensitivity, specificity, LR+, LR- and DOR with corresponding 95% CI at per-patient level were 83% (79-87), 72% (68-76), 3.0 (2.6-3.5), 0.23 (0.18-0.29) and 13 (9-18) respectively. Pooled estimates of sensitivity, specificity, LR+, LR- and DOR with corresponding 95% CI at per-vessel level were 85% (83-88), 76% (74-79), 3.6 (3.3-4.0), 0.19 (0.16-0.22) and 19 (15-24). The area under the SROC curve was 0.89 for both per patient level and at the per vessel level. In our meta-analysis, CTFFR demonstrated good diagnostic performance in identifying functionally significant coronary artery stenosis compared to the FFR.
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Affiliation(s)
- Pradyumna Agasthi
- Division of Cardiovascular Diseases, Mayo Clinic Arizona, Phoenix, Arizona, USA.
| | - Arun Kanmanthareddy
- Division of Cardiovascular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Charl Khalil
- Division of Cardiovascular Diseases, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | - Obiora Egbuche
- Division of Cardiology, Department of Medicine, Morehouse School of Medicine, Atlanta, Georgia
| | - Vivek Yarlagadda
- Department of Internal Medicine, Atlanticare Regional Medical Center, Atlantic City, New Jersey, USA
| | - Rajesh Sachdeva
- Division of Cardiology, Department of Medicine, Morehouse School of Medicine, Atlanta, Georgia
| | - Reza Arsanjani
- Division of Cardiovascular Diseases, Mayo Clinic Arizona, Phoenix, Arizona, USA
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Xie X, Zheng M, Wen D, Li Y, Xie S. A new CFD based non-invasive method for functional diagnosis of coronary stenosis. Biomed Eng Online 2018; 17:36. [PMID: 29566702 PMCID: PMC5863834 DOI: 10.1186/s12938-018-0468-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 03/17/2018] [Indexed: 02/07/2023] Open
Abstract
Background Accurate functional diagnosis of coronary stenosis is vital for decision making in coronary revascularization. With recent advances in computational fluid dynamics (CFD), fractional flow reserve (FFR) can be derived non-invasively from coronary computed tomography angiography images (FFRCT) for functional measurement of stenosis. However, the accuracy of FFRCT is limited due to the approximate modeling approach of maximal hyperemia conditions. To overcome this problem, a new CFD based non-invasive method is proposed. Methods Instead of modeling maximal hyperemia condition, a series of boundary conditions are specified and those simulated results are combined to provide a pressure-flow curve for a stenosis. Then, functional diagnosis of stenosis is assessed based on parameters derived from the obtained pressure-flow curve. Results The proposed method is applied to both idealized and patient-specific models, and validated with invasive FFR in six patients. Results show that additional hemodynamic information about the flow resistances of a stenosis is provided, which cannot be directly obtained from anatomy information. Parameters derived from the simulated pressure-flow curve show a linear and significant correlations with invasive FFR (r > 0.95, P < 0.05). Conclusion The proposed method can assess flow resistances by the pressure-flow curve derived parameters without modeling of maximal hyperemia condition, which is a new promising approach for non-invasive functional assessment of coronary stenosis.
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Affiliation(s)
- Xinzhou Xie
- Department of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China.
| | - Minwen Zheng
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 15 West Changle Road, Xi'an, Shaanxi, People's Republic of China
| | - Didi Wen
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 15 West Changle Road, Xi'an, Shaanxi, People's Republic of China
| | - Yabing Li
- Department of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China
| | - Songyun Xie
- Department of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China
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28
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Donnelly PM, Kolossváry M, Karády J, Ball PA, Kelly S, Fitzsimons D, Spence MS, Celeng C, Horváth T, Szilveszter B, van Es HW, Swaans MJ, Merkely B, Maurovich-Horvat P. Experience With an On-Site Coronary Computed Tomography-Derived Fractional Flow Reserve Algorithm for the Assessment of Intermediate Coronary Stenoses. Am J Cardiol 2018; 121:9-13. [PMID: 29103607 DOI: 10.1016/j.amjcard.2017.09.018] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 09/09/2017] [Accepted: 09/12/2017] [Indexed: 12/28/2022]
Abstract
Fractional flow reserve (FFR) derived from coronary computed tomography angiography (CTA) is a new technique for the diagnosis of ischemic coronary artery stenoses. The aim of this prospective study was to evaluate the diagnostic performance of a novel on-site computed tomography-based fractional flow reserve algorithm (CT-FFR) compared with invasive FFR as the gold standard, and to determine whether its diagnostic performance is affected by interobserver variations in lumen segmentation. We enrolled 44 consecutive patients (64.6 ± 8.9 years, 34% female) with 60 coronary atherosclerotic lesions who underwent coronary CTA and invasive coronary angiography in 2 centers. An FFR value ≤0.8 was considered significant. Coronary CTA scans were evaluated by 2 expert readers, who manually adjusted the semiautomated coronary lumen segmentations for effective diameter stenosis (EDS) assessment and on-site CT-FFR simulation. The mean CT-FFR value was 0.77 ± 0.15, whereas the mean EDS was 43.6 ± 16.9%. The sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR versus EDS with a cutoff of 50% were the following: 91%, 72%, 63%, and 93% versus 52%, 87%, 69%, and 77%, respectively. The on-site CT-FFR demonstrated significantly better diagnostic performance compared with EDS (area under the curve 0.89 vs 0.74, respectively, p <0.001). The CT-FFR areas under the curve of the 2 readers did not show any significant difference (0.89 vs 0.88, p = 0.74). In conclusion, on-site CT-FFR simulation is feasible and has better diagnostic performance than anatomic stenosis assessment. Furthermore, the diagnostic performance of the on-site CT-FFR simulation algorithm does not depend on the readers' semiautomated lumen segmentation adjustments.
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Affiliation(s)
- Patrick M Donnelly
- Cardiovascular Imaging and Research Department, Ulster Hospital, South Eastern Health and Social Care Trust, Ulster University, Belfast, UK
| | - Márton Kolossváry
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Júlia Karády
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Peter A Ball
- Cardiovascular Imaging and Research Department, Ulster Hospital, South Eastern Health and Social Care Trust, Ulster University, Belfast, UK
| | - Stephanie Kelly
- Cardiovascular Imaging and Research Department, Ulster Hospital, South Eastern Health and Social Care Trust, Ulster University, Belfast, UK
| | - Donna Fitzsimons
- Cardiovascular Imaging and Research Department, Ulster Hospital, South Eastern Health and Social Care Trust, Ulster University, Belfast, UK
| | - Mark S Spence
- Cardiovascular Imaging and Research Department, Ulster Hospital, South Eastern Health and Social Care Trust, Ulster University, Belfast, UK
| | - Csilla Celeng
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Tamás Horváth
- Department of Hydrodynamic Systems, Budapest University of Technology and Economics, Faculty of Mechanical Engineering, Budapest, Hungary
| | - Bálint Szilveszter
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Hendrik W van Es
- Departments of Radiology, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Martin J Swaans
- Departments of Radiology, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Béla Merkely
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group (CIRG), Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.
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29
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Papafaklis MI, Mavrogiannis MC, Siogkas PK, Lakkas LS, Katsouras CS, Fotiadis DI, Michalis LK. Functional assessment of lesion severity without using the pressure wire: coronary imaging and blood flow simulation. Expert Rev Cardiovasc Ther 2017; 15:863-877. [PMID: 28902523 DOI: 10.1080/14779072.2017.1379899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Michail I. Papafaklis
- Second Department of Cardiology, University Hospital of Ioannina, Ioannina, Greece
- Michailideion Cardiac Center, Medical School, University of Ioannina, Ioannina, Greece
| | | | - Panagiotis K. Siogkas
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science, University of Ioannina, Ioannina, Greece
| | - Lampros S. Lakkas
- Second Department of Cardiology, University Hospital of Ioannina, Ioannina, Greece
| | | | - Dimitrios I. Fotiadis
- Michailideion Cardiac Center, Medical School, University of Ioannina, Ioannina, Greece
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science, University of Ioannina, Ioannina, Greece
| | - Lampros K. Michalis
- Second Department of Cardiology, University Hospital of Ioannina, Ioannina, Greece
- Michailideion Cardiac Center, Medical School, University of Ioannina, Ioannina, Greece
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30
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Tesche C, De Cecco CN, Albrecht MH, Duguay TM, Bayer RR, Litwin SE, Steinberg DH, Schoepf UJ. Coronary CT Angiography–derived Fractional Flow Reserve. Radiology 2017; 285:17-33. [DOI: 10.1148/radiol.2017162641] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Christian Tesche
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Carlo N. De Cecco
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Moritz H. Albrecht
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Taylor M. Duguay
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Richard R. Bayer
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Sheldon E. Litwin
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - Daniel H. Steinberg
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
| | - U. Joseph Schoepf
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260
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31
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Kolossváry M, Szilveszter B, Merkely B, Maurovich-Horvat P. Plaque imaging with CT-a comprehensive review on coronary CT angiography based risk assessment. Cardiovasc Diagn Ther 2017; 7:489-506. [PMID: 29255692 PMCID: PMC5716945 DOI: 10.21037/cdt.2016.11.06] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Accepted: 12/08/2016] [Indexed: 01/07/2023]
Abstract
CT based technologies have evolved considerably in recent years. Coronary CT angiography (CTA) provides robust assessment of coronary artery disease (CAD). Early coronary CTA imaging-as a gate-keeper of invasive angiography-has focused on the presence of obstructive stenosis. Coronary CTA is currently the only non-invasive imaging modality for the evaluation of non-obstructive CAD, which has been shown to contribute to adverse cardiac events. Importantly, improved spatial resolution of CT scanners and novel image reconstruction algorithms enable the quantification and characterization of atherosclerotic plaques. State-of-the-art CT imaging can therefore reliably assess the extent of CAD and differentiate between various plaque features. Recent studies have demonstrated the incremental prognostic value of adverse plaque features over luminal stenosis. Comprehensive coronary plaque assessment holds potential to significantly improve individual risk assessment incorporating adverse plaque characteristics, the extent and severity of atherosclerotic plaque burden. As a result, several coronary CTA based composite risk scores have been proposed recently to determine patients at high risk for adverse events. Coronary CTA became a promising modality for the evaluation of functional significance of coronary lesions using CT derived fractional flow reserve (FFR-CT) and/or rest/dynamic myocardial CT perfusion. This could lead to substantial reduction in unnecessary invasive catheterization procedures and provide information on ischemic burden of CAD. Discordance between the degree of stenosis and ischemia has been recognized in clinical landmark trials using invasive FFR. Both lesion stenosis and composition are possibly related to myocardial ischemia. The evaluation of lesion-specific ischemia using combined functional and morphological plaque information could ultimately improve the diagnostic performance of CTA and thus patient care. In this review we aimed to summarize current evidence on comprehensive coronary artery plaque assessment using coronary CTA.
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Affiliation(s)
- Márton Kolossváry
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Bálint Szilveszter
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Béla Merkely
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
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32
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Rajiah P, Maroules CD. Myocardial ischemia testing with computed tomography: emerging strategies. Cardiovasc Diagn Ther 2017; 7:475-488. [PMID: 29255691 DOI: 10.21037/cdt.2017.09.06] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Although cardiac computed tomography (CT) has high negative predictive value to exclude obstructive coronary artery disease (CAD), particularly in the low to intermediate risk population, it has low specificity in the diagnosis of ischemia-inducing lesions. This inability to predict hemodynamically significant stenosis hampers the ability of CT to be an effective gatekeeper for invasive angiography and to guide appropriate revascularization. Recent advances in CT technology have resulted in the development of multiple techniques to provide hemodynamic information and detect lesion-specific ischemia, namely CT perfusion (CTP), CT-derived fractional flow reserve (CT-FFR) and coronary transluminal attenuation gradient (TAG). In this article, we provide a perspective on these emerging CT techniques in the evaluation of myocardial ischemia.
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Affiliation(s)
- Prabhakar Rajiah
- Department of Radiology, Cardiothoracic Imaging, UT Southwestern Medical Center, Dallas, Texas, USA
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33
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Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease. JACC Cardiovasc Imaging 2017; 10:760-770. [DOI: 10.1016/j.jcmg.2016.09.028] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 09/01/2016] [Indexed: 11/22/2022]
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34
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Lee JH, Hartaigh BÓ, Han D, Rizvi A, Lin FY, Min JK. Fractional Flow Reserve Measurement by Computed Tomography: An Alternative to the Stress Test. Interv Cardiol 2016; 11:105-109. [PMID: 29588715 DOI: 10.15420/icr.2016:1:2] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Recent advances in computed tomographic technology have contributed towards improving coronary computed tomography angiography (CCTA) in determining the severity of coronary artery disease anatomically. Although the viability of CCTA has most often been confined to anatomical assessment, recent development has enabled evaluation of the haemodynamic significance of coronary artery disease. In light of this, CCTA-derived fractional flow reserve (FFRCT), a novel imaging modality, now permits the physiological assessment of coronary artery disease. To date, several studies have documented the diagnostic performance of FFRCT, and more trials are being performed that will further substantiate this technique. The present paper provides an overview and discussion of the available evidence for FFRCT in the clinical setting as well as potential future directions of FFRCT.
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Affiliation(s)
- Ji Hyun Lee
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA
| | - Bríain Ó Hartaigh
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA
| | - Donghee Han
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA
| | - Asim Rizvi
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA
| | - Fay Y Lin
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA.,Departments of Radiology and Medicine, Weill Cornell Medical College, New York, NY, USA
| | - James K Min
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital, New York, NY, USA.,Departments of Radiology and Medicine, Weill Cornell Medical College, New York, NY, USA
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35
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Wu W, Pan DR, Foin N, Pang S, Ye P, Holm N, Ren XM, Luo J, Nanjundappa A, Chen SL. Noninvasive fractional flow reserve derived from coronary computed tomography angiography for identification of ischemic lesions: a systematic review and meta-analysis. Sci Rep 2016; 6:29409. [PMID: 27377422 PMCID: PMC4932511 DOI: 10.1038/srep29409] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 06/16/2016] [Indexed: 12/17/2022] Open
Abstract
Detection of coronary ischemic lesions by fractional flow reserve (FFR) has been established as the gold standard. In recent years, novel computer based methods have emerged and they can provide simulation of FFR using coronary artery images acquired from coronary computed tomography angiography (FFRCT). This meta-analysis aimed to evaluate diagnostic performance of FFRCT using FFR as the reference standard. Databases of PubMed, Cochrane Library, EMBASE, Medion and Web of Science were searched. Seven studies met the inclusion criteria, including 833 stable patients (1377 vessels or lesions) with suspected or known coronary artery disease (CAD). The patient-based analysis showed pooled estimates of sensitivity, specificity and diagnostic odds ratio (DOR) for detection of ischemic lesions were 0.89 [95%confidence interval (CI), 0.85–0.93], 0.76 (95%CI, 0.64–0.84) and 26.21 (95%CI, 13.14–52.28). At a per-vessel or per-lesion level, the pooled estimates were as follows: sensitivity 0.84 (95%CI, 0.80–0.87), specificity 0.76 (95%CI, 0.67–0.83) and DOR 16.87 (95%CI, 9.41–30.25). Area under summary receiver operating curves was 0.90 (95%CI, 0.87–0.92) and 0.86 (95%CI, 0.83–0.89) at the two analysis levels, respectively. In conclusion, FFRCT technology achieves a moderate diagnostic performance for noninvasive identification of ischemic lesions in stable patients with suspected or known CAD in comparison to invasive FFR measurement.
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Affiliation(s)
- Wen Wu
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
| | - Dao-Rong Pan
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
| | - Nicolas Foin
- National Heart Research Institute, National Heart Centre Singapore, 169609, Singapore
| | - Si Pang
- Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Peng Ye
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
| | - Niels Holm
- Department of Cardiology, Aarhus University Hospital, Aarhus, 8000, Denmark
| | - Xiao-Min Ren
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
| | - Jie Luo
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
| | | | - Shao-Liang Chen
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, P.R. China
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