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Faulder TI, Prematunga K, Moloi SB, Faulder LE, Jones R, Moxon JV. Agreement of Fractional Flow Reserve Estimated by Computed Tomography With Invasively Measured Fractional Flow Reserve: A Systematic Review and Meta-Analysis. J Am Heart Assoc 2024; 13:e034552. [PMID: 38726901 PMCID: PMC11179792 DOI: 10.1161/jaha.124.034552] [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: 01/18/2024] [Accepted: 03/21/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Fractional flow reserve (FFR) is the ratio of blood pressure measured distal to a stenosis and pressure proximal to a stenosis. FFR can be estimated noninvasively using computed tomography (CT) although the usefulness of this technique remains controversial. This meta-analysis evaluated the agreement of FFR estimated by CT (FFR-CT) with invasively measured FFR. The study also evaluated the diagnostic accuracy of FFR-CT, defined as the ability of FFR-CT to classify lesions as hemodynamically significant (invasive FFR ≤0.8) or insignificant (invasive FFR >0.8). METHODS AND RESULTS Forty-three studies reporting on 7291 blood vessels from 5236 patients were included. A moderate positive linear relationship between FFR-CT and invasively measured FFR was observed (Spearman correlation coefficient: 0.67). Agreement between the 2 measures increased as invasively measured FFR values approached 1. The overall diagnostic accuracy, sensitivity and specificity of FFR-CT were 82.2%, 80.9%, and 83.1%, respectively. Diagnostic accuracy of 90% could be demonstrated for FFR-CT values >0.90 and <0.49. The diagnostic accuracy of off-site tools was 79.4% and the diagnostic accuracy of on-site tools was 84.1%. CONCLUSIONS The agreement between FFR-CT and invasive FFR is moderate although agreement is highest in vessels with FFR-CT >0.9. Diagnostic accuracy varies widely with FFR-CT value but is above 90% for FFR-CT values >0.90 and <0.49. Furthermore, on-site and off-site tools have similar performance. Ultimately, FFR-CT may be a useful adjunct to CT coronary angiography as a gatekeeper for invasive coronary angiogram.
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Affiliation(s)
- Thomas I Faulder
- College of Medicine and Dentistry James Cook University Townsville QLD Australia
| | | | - Soniah B Moloi
- Department of Cardiology Townsville University Hospital Townsville QLD Australia
| | - Lauren E Faulder
- College of Medicine and Dentistry University of Adelaide Adelaide SA Australia
| | - Rhondda Jones
- Graduate Research School James Cook University Townsville QLD Australia
- Tropical Australian Academic Health Centre James Cook University Townsville QLD Australia
| | - Joseph V Moxon
- College of Medicine and Dentistry James Cook University Townsville QLD Australia
- The Australian Institute of Tropical Health and Medicine James Cook University Townsville QLD Australia
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2
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Zucker EJ. Cardiac Computed Tomography in Congenital Heart Disease. Radiol Clin North Am 2024; 62:435-452. [PMID: 38553179 DOI: 10.1016/j.rcl.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Computed tomography (CT) has emerged as a leading imaging modality in the evaluation of congenital heart disease (CHD). With ever-faster acquisition speed, decreasing radiation exposure, impeccable anatomic detail, optional functional data, and numerous post-processing tools, CT offers broad utility in CHD diagnosis, preoperative planning, and postoperative assessment. In this article, the far-reaching role of CT in CHD is reviewed, focusing on technical imaging considerations and key clinical applications.
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Affiliation(s)
- Evan J Zucker
- Department of Radiology, Divisions of Pediatric and Cardiovascular Imaging, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
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3
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Palicherla A, Ismayl M, Thandra A, Budoff M, Shaikh K. Evaluation of stable angina by coronary computed tomographic angiography versus standard of care: A systematic review and meta-analysis. CARDIOVASCULAR REVASCULARIZATION MEDICINE 2024; 59:67-75. [PMID: 37541837 DOI: 10.1016/j.carrev.2023.07.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 07/25/2023] [Accepted: 07/25/2023] [Indexed: 08/06/2023]
Abstract
INTRODUCTION There is limited data comparing Coronary Computed Tomography Angiography (CCTA) versus the usual Standard of care (SOC) in patients with suspected stable coronary artery disease (CAD). We aimed to perform a systematic review and meta-analysis to compare CCTA versus SOC in patients with stable CAD. METHODS We searched multiple databases for randomized controlled trials (RCTs) comparing CCTA with SOC, which included various functional testing approaches for evaluating stable CAD. We used a random-effects model to calculate risk ratios (RRs) with 95 % confidence intervals (CIs). Outcomes included all-cause mortality, myocardial infarction (MI), hospitalization for unstable angina (UA), invasive angiography, revascularization, percutaneous coronary intervention (PCI), and coronary artery bypass grafting (CABG). RESULTS We identified 6 RCTs with 19,881 patients with stable CAD, of which 9995 underwent CCTA, and 9886 underwent SOC. There were no significant differences between CCTA and SOC in terms of all-cause mortality (RR: 0.91; 95 % CI: 0.70-1.19; p = 0.50), MI (RR: 0.78; 95 % CI: 0.58-1.05; p = 0.11), hospitalizations for UA (RR: 1.20; 95 % CI: 0.95-1.51;p = 0.12), invasive angiography (RR: 0.71; 95 % CI: 0.32-1.61; p = 0.42), revascularization (RR:1.25; 95 % CI: 0.83-1.89; p = 0.29), PCI (RR: 1.20; 95 % CI: 0.78-1.85; p = 0.40), and CABG rates (RR: 0.89; 95 % CI: 0.530-1.49; p = 0.65). CONCLUSION In patients with stable CAD, CCTA is associated with similar outcomes compared to the usual Standard of care. Given its potential to quickly rule out severe obstructive disease, its ability to provide non-invasive physiology and identify non-obstructive CAD with plaque information makes it an attractive addition to the available armamentarium to evaluate chest pain.
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Affiliation(s)
- Anirudh Palicherla
- Internal Medicine, Creighton University School of Medicine, Omaha, NE, United States of America.
| | - Mahmoud Ismayl
- Internal Medicine, Creighton University School of Medicine, Omaha, NE, United States of America
| | - Abhishek Thandra
- Interventional Cardiology, Creighton University School of Medicine, Omaha, NE, United States of America.
| | - Matthew Budoff
- David Geffen School of Medicine at UCLA, Los Angeles, United States of America.
| | - Kashif Shaikh
- University of Tennessee, Knoxville, United States of America
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Sun Z, Silberstein J, Vaccarezza M. Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment. J Cardiovasc Dev Dis 2024; 11:22. [PMID: 38248892 PMCID: PMC10816599 DOI: 10.3390/jcdd11010022] [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: 11/22/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 01/23/2024] Open
Abstract
Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.
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Affiliation(s)
- Zhonghua Sun
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
| | - Jenna Silberstein
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
| | - Mauro Vaccarezza
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
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5
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Dell’Aversana S, Ascione R, Vitale RA, Cavaliere F, Porcaro P, Basile L, Napolitano G, Boccalatte M, Sibilio G, Esposito G, Franzone A, Di Costanzo G, Muscogiuri G, Sironi S, Cuocolo R, Cavaglià E, Ponsiglione A, Imbriaco M. CT Coronary Angiography: Technical Approach and Atherosclerotic Plaque Characterization. J Clin Med 2023; 12:7615. [PMID: 38137684 PMCID: PMC10744060 DOI: 10.3390/jcm12247615] [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: 11/11/2023] [Revised: 12/08/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Coronary computed tomography angiography (CCTA) currently represents a robust imaging technique for the detection, quantification and characterization of coronary atherosclerosis. However, CCTA remains a challenging task requiring both high spatial and temporal resolution to provide motion-free images of the coronary arteries. Several CCTA features, such as low attenuation, positive remodeling, spotty calcification, napkin-ring and high pericoronary fat attenuation index have been proved as associated to high-risk plaques. This review aims to explore the role of CCTA in the characterization of high-risk atherosclerotic plaque and the recent advancements in CCTA technologies with a focus on radiomics plaque analysis.
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Affiliation(s)
- Serena Dell’Aversana
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Raffaele Ascione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Raffaella Antonia Vitale
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Fabrizia Cavaliere
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Piercarmine Porcaro
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Luigi Basile
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | | | - Marco Boccalatte
- Coronary Care Unit, Santa Maria delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (M.B.); (G.S.)
| | - Gerolamo Sibilio
- Coronary Care Unit, Santa Maria delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (M.B.); (G.S.)
| | - Giovanni Esposito
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Anna Franzone
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Giuseppe Di Costanzo
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Giuseppe Muscogiuri
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, Piazza OMS 1, 24127 Bergamo, Italy; (G.M.); (S.S.)
| | - Sandro Sironi
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, Piazza OMS 1, 24127 Bergamo, Italy; (G.M.); (S.S.)
- School of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Baronissi, Italy;
| | - Enrico Cavaglià
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Andrea Ponsiglione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
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Feng Y, Li B, Fu R, Hao Y, Wang T, Guo H, Ma J, Baier G, Yang H, Feng Q, Zhang L, Liu Y. A simplified coronary model for diagnosis of ischemia-causing coronary stenosis. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107862. [PMID: 37857024 DOI: 10.1016/j.cmpb.2023.107862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/26/2023] [Accepted: 10/11/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND AND OBJECTIVE The functional assessment of the severity of coronary stenosis from coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR) has recently attracted interest. However, existing algorithms run at high computational cost. Therefore, this study proposes a fast calculation method of FFR for the diagnosis of ischemia-causing coronary stenosis. METHODS We combined CCTA and machine learning to develop a simplified single-vessel coronary model for rapid calculation of FFR. First, a zero-dimensional model of single-vessel coronary was established based on CCTA, and microcirculation resistance was determined through the relationship between coronary pressure and flow. In addition, a coronary stenosis model based on machine learning was introduced to determine stenosis resistance. Computational FFR (cFFR) was then obtained by combining the zero-dimensional model and the stenosis model with inlet boundary conditions for resting (cFFRr) and hyperemic (cFFRh) aortic pressure, respectively. We retrospectively analyzed 75 patients who underwent clinically invasive FFR (iFFR), and verified the model accuracy by comparison of cFFR with iFFR. RESULTS The average computing time of cFFR was less than 2 s. The correlations between cFFRr and cFFRh with iFFR were r = 0.89 (p < 0.001) and r = 0.90 (p < 0.001), respectively. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio for cFFRr and cFFRh were 90.7%, 95.0%, 89.1%, 76.0%, 98.0%, 8.7, 0.1 and 92.0%, 95.0%, 90.9%, 79.2%, 98.0%, 10.5, 0.1, respectively. CONCLUSIONS The proposed model enables rapid prediction of cFFR and exhibits high diagnostic performance in selected patient cohorts. The model thus provides an accurate and time-efficient computational tool to detect ischemia-causing stenosis and assist with clinical decision-making.
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Affiliation(s)
- Yili Feng
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Bao Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Ruisen Fu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Yaodong Hao
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Tongna Wang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Huanmei Guo
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Junling Ma
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Gerold Baier
- Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Haisheng Yang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China
| | - Quansheng Feng
- Department of Cardiology, the First People's Hospital of Guangshui, Guangshui, Hubei 432700, China
| | - Liyuan Zhang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China.
| | - Youjun Liu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China.
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7
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Zhang LY, Gan YR, Wang YZ, Xie DX, Kou ZK, Kou XQ, Zhang YL, Li B, Mao R, Liang TX, Xie J, Jin JJ, Yang JM. Fractional flow reserve measured via left internal mammary artery after coronary artery bypass grafting: Two case reports. World J Clin Cases 2023; 11:3045-3051. [PMID: 37215412 PMCID: PMC10198084 DOI: 10.12998/wjcc.v11.i13.3045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/15/2023] [Accepted: 03/21/2023] [Indexed: 04/25/2023] Open
Abstract
BACKGROUND The fractional flow reserve (FFR) has made the treatment of coronary heart disease more precise. However, there are few reports on the measurement of FFR via the left internal mammary artery (LIMA). Herein, we described the determination of further treatments by measuring FFR via the LIMA in 2 cases after coronary artery bypass grafting (CABG).
CASE SUMMARY Case 1 was a 66-year-old male who was admitted due to “chest tightness after CABG.” The patient underwent CABG 7 years prior due to coronary heart disease. Coronary artery angiography showed complete occlusion of the left anterior descending artery (LAD), and subtotal occlusion of the third segment of the right coronary artery. On arterial angiography, there was 85% stenosis at the distal end of the anastomosis of the LIMA-LAD graft. FFR via LIMA was determined at 0.75. Thus, balloon dilation was performed in Case 1. FFR after balloon dilation was 0.94. Case 2 was a 60-year-old male who was admitted due to “chest tightness after CABG.” The patient underwent CABG 6 years prior due to coronary heart disease. There was 60% segmental stenosis in the middle segment of LAD and 75% anastomotic stenosis. FFR measured via LIMA was 0.83 (negative); thus the intervention was not performed. Case 2 was given drug treatments. At the 3-mo follow-up, there was no recurrence of chest tightness or shortness of breath in both cases. They are currently under continual follow-up.
CONCLUSION We provided evidence that FFR measurement via grafted blood vessels, especially LIMA, after CABG is a good method to determine the intervention course.
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Affiliation(s)
- Li-Ying Zhang
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
- Provincial Level Key Laboratory for Molecular Medicine of Major Diseases and Prevention and Treatment with Traditional Chinese Medicine Research in Gansu Colleges and Universities, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
| | - Yi-Rong Gan
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Yan-Zhen Wang
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Ding-Xiong Xie
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Zong-Ke Kou
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Xiao-Qing Kou
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Yun-Long Zhang
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Bing Li
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Rui Mao
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Tian-Xiang Liang
- Gansu Institute of Cardiovascular Diseases, Lanzhou 730050, Gansu Province, China
| | - Jing Xie
- Department of Functional, Lanzhou First People’s Hospital, Lanzhou 730050, Gansu Province, China
| | - Jian-Jian Jin
- Department of Cardiology, The First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China
| | - Jin-Mei Yang
- Department of Functional, Lanzhou First People’s Hospital, Lanzhou 730050, Gansu Province, China
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Zhou Y, Liu C, Zhang Z, Chen J, Zhao D, Li L, Tong M, Zhang G. Identification and validation of diagnostic biomarkers of coronary artery disease progression in type 1 diabetes via integrated computational and bioinformatics strategies. Comput Biol Med 2023; 159:106940. [PMID: 37075605 DOI: 10.1016/j.compbiomed.2023.106940] [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: 12/11/2022] [Revised: 04/03/2023] [Accepted: 04/14/2023] [Indexed: 04/21/2023]
Abstract
OBJECTIVE Our study aimed to identify early peripheral blood diagnostic biomarkers and elucidate the immune mechanisms of coronary artery disease (CAD) progression in patients with type 1 diabetes mellitus (T1DM). METHODS Three transcriptome datasets were retrieved from the Gene Expression Omnibus (GEO) database. Gene modules associated with T1DM were selected with weighted gene co-expression network analysis. Differentially expressed genes (DEGs) between CAD and acute myocardial infarction (AMI) peripheral blood tissues were identified using limma. Candidate biomarkers were selected with functional enrichment analysis, node gene selection from a constructed protein-protein interaction (PPI) network, and 3 machine learning algorithms. Candidate expression was compared, and the receiver operating characteristic curve (ROC) and nomogram were constructed. Immune cell infiltration was assessed with the CIBERSORT algorithm. RESULTS A total of 1283 genes comprising 2 modules were detected as the most associated with T1DM. In addition, 451 DEGs related to CAD progression were identified. Among them, 182 were common to both diseases and mainly enriched in immune and inflammatory response regulation. The PPI network yielded 30 top node genes, and 6 were selected using the 3 machine learning algorithms. Upon validation, 4 genes (TLR2, CLEC4D, IL1R2, and NLRC4) were recognized as diagnostic biomarkers with the area under the curve (AUC) > 0.7. All 4 genes were positively correlated with neutrophils in patients with AMI. CONCLUSION We identified 4 peripheral blood biomarkers and provided a nomogram for early diagnosing CAD progression to AMI in patients with T1DM. The biomarkers were positively associated with neutrophils, indicating potential therapeutic targets.
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Affiliation(s)
- Yufei Zhou
- Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Chunjiang Liu
- Department of General Surgery, Division of Vascular Surgery, Shaoxing People's Hospital, Shaoxing, 312000, China
| | - Zhongzheng Zhang
- Department of Rehabilitation, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, Anhui, 230000, China
| | - Jian Chen
- Department of Rehabilitation, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, Anhui, 230000, China
| | - Di Zhao
- Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Linnan Li
- Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Mingyue Tong
- Department of Rehabilitation, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, Anhui, 230000, China.
| | - Gang Zhang
- Department of Rehabilitation, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, Anhui, 230000, China.
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Evaluation of the Advantages of Myocardial Blood Flow Index in the Diagnosis of Chronic Obstructive Coronary Artery Disease Versus Coronary Computed Tomography Angiography: A Feasibility Study. IRANIAN JOURNAL OF RADIOLOGY 2022. [DOI: 10.5812/iranjradiol-123693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: There is a hidden relationship between the degree of coronary artery stenosis and downstream myocardial remodeling. The mutual influence in myocardial ischemia and myocardial remodeling provides an index for quantifying the myocardial blood flow based on the principles of physics. Objectives: This study aimed to evaluate the advantages of myocardial blood flow index (MBFI) in the diagnosis of chronic obstructive coronary artery disease (CAD). Patients and Methods: The data of 68 patients (39 males; mean age: 57.0 ± 10.20 years) with suspected CAD were analyzed retrospectively, including the imaging findings of coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) within one week. The MBFI was also calculated for the patients. After determining the optimal cut-off value based on ICA (stenosis ≥ 70%) as the gold standard test, the diagnostic performance of MBFI and CCTA was compared. The diagnostic accuracy was examined by the receiver operating characteristic (ROC) curve. For statistical analysis, chi-square test was performed to analyze influence data, and a P-value less than 0.05 was considered statistically significant. Results: In 68 cases evaluated in this study, the average scan dose of CCTA was 3.02 ± 1.15 mSv. There were 28 cases with stenosis ≥ 70%. The optimal cutoff value of MBFI and CCTA was 0.111 and 70%, respectively. Also, the area under the curve (AUC) for MBFI and CCTA was 0.857 and 0.621 (Z = 2.091, P = 0.0365), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value were 92.31%, 92.86%, 88.89%, and 95.12% for MBFI and 61.54%, 78.57%, 64.00%, and 76.74% for CCTA, respectively. The diagnostic accuracy was also estimated at 92.65% for MBFI and 72.06% for CCTA (χ2 = 9.844, P = 0.0017). Conclusion: In this study, MBFI performed better than CCTA in identifying lesions with stenosis ≥ 70%. A lower MBFI indicated the need for an upcoming active intervention, while a higher MBFI suggested avoiding unnecessary invasive testing.
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10
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Wamil M, Goncalves M, Rutherford A, Borlotti A, Pellikka PA. Multi-modality cardiac imaging in the management of diabetic heart disease. Front Cardiovasc Med 2022; 9:1043711. [DOI: 10.3389/fcvm.2022.1043711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease.
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11
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Farkouh ME, Mathew V. Angiography-Based Measurement of Myocardial Ischemia. J Am Coll Cardiol 2022; 80:2102-2103. [DOI: 10.1016/j.jacc.2022.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 10/17/2022] [Indexed: 11/22/2022]
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12
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Geerlings-Batt J, Sun Z. Evaluation of the Relationship between Left Coronary Artery Bifurcation Angle and Coronary Artery Disease: A Systematic Review. J Clin Med 2022; 11:jcm11175143. [PMID: 36079071 PMCID: PMC9457427 DOI: 10.3390/jcm11175143] [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: 06/28/2022] [Revised: 08/16/2022] [Accepted: 08/30/2022] [Indexed: 11/30/2022] Open
Abstract
Recent studies have suggested a relationship between wide left coronary artery bifurcation (left anterior descending [LAD]-left circumflex [LCx]) angle and coronary artery disease (CAD). Current literature is multifaceted. Different studies have analysed this relationship using computational fluid dynamics, by considering CAD risk factors, and from simple causal-comparative and correlational perspectives. Hence, the purpose of this systematic review was to critically evaluate the current literature and determine whether there is sufficient evidence available to prove the relationship between LAD-LCx angle and CAD. Five electronic databases (ProQuest, Scopus, PubMed, CINAHL Plus with Full Text, and Emcare) were used to locate relevant texts, which were then screened according to predefined eligibility criteria. Thirteen eligible articles were selected for review. Current evidence suggests individuals with a wide LAD-LCx angle experience altered haemodynamics at the bifurcation site compared to those with narrower angles, which likely facilitates a predisposition to developing CAD. However, further research is required to determine causality regarding relationships between LAD-LCx angle and CAD risk factors. Insufficient valid evidence exists to support associations between LAD-LCx angle and degree of coronary stenosis, and future haemodynamic analyses should explore more accurate coronary artery modelling, as well as CAD progression in already stenosed bifurcations.
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Yan H, Gao Y, Zhao N, Geng W, Hou Z, An Y, Zhang J, Lu B. Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis. Front Cardiovasc Med 2022; 8:788703. [PMID: 35097009 PMCID: PMC8792740 DOI: 10.3389/fcvm.2021.788703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/21/2021] [Indexed: 11/13/2022] Open
Abstract
Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard.Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed.Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P < 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P < 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P < 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P < 0.05).Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.
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Kanne JP, Bai H, Bernheim A, Chung M, Haramati LB, Kallmes DF, Little BP, Rubin GD, Sverzellati N. COVID-19 Imaging: What We Know Now and What Remains Unknown. Radiology 2021; 299:E262-E279. [PMID: 33560192 PMCID: PMC7879709 DOI: 10.1148/radiol.2021204522] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Infection with SARS-CoV-2 ranges from an asymptomatic condition to a severe and sometimes fatal disease, with mortality most frequently being the result of acute lung injury. The role of imaging has evolved during the pandemic, with CT initially being an alternative and possibly superior testing method compared with reverse transcriptase-polymerase chain reaction (RT-PCR) testing and evolving to having a more limited role based on specific indications. Several classification and reporting schemes were developed for chest imaging early during the pandemic for patients suspected of having COVID-19 to aid in triage when the availability of RT-PCR testing was limited and its level of performance was unclear. Interobserver agreement for categories with findings typical of COVID-19 and those suggesting an alternative diagnosis is high across multiple studies. Furthermore, some studies looking at the extent of lung involvement on chest radiographs and CT images showed correlations with critical illness and a need for mechanical ventilation. In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have been ascribed to COVID-19, sometimes contributing to neurologic and abdominal manifestations. Finally, artificial intelligence has shown promise for use in determining both the diagnosis and prognosis of COVID-19 pneumonia with respect to both radiography and CT.
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Affiliation(s)
- Jeffrey P. Kanne
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Harrison Bai
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Adam Bernheim
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Michael Chung
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Linda B Haramati
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - David F. Kallmes
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Brent P. Little
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Geoffrey D. Rubin
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
| | - Nicola Sverzellati
- From the Department of Radiology University of Wisconsin School of Medicine and Public Health (J.P.K.); Department of Diagnostic Imaging Rhode Island Hospital and Warren Alpert Medical School of Brown University (H.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (A.B.); Department of Radiology Icahn School of Medicine at Mount Sinai 1 Gustave Levy Place, New York, NY 10029 (M.C.); Montefiore Medical Center Albert Einstein College of Medicine Departments of Radiology and Medicine 111 East 210 Street Bronx, NY 10467 (L.B.H.); Department of Radiology Mayo Clinic 200 First St SW Rochester, MN 55905 (D.F.K.); Department of Radiology Massachusetts General Hospital 55 Fruit Street Boston, MA 02114 (B.P.L.); Department of Medical Imaging University of Arizona College of Medicine Tucson, AZ (G.R.); Scienze Radiologiche, Department of Medicine and Surgery University of Parma V. Gramsci 14, 43126, Parma Italy (N.S.)
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Sabbah M, Engstrøm T, De Backer O, Søndergaard L, Lønborg J. Coronary Assessment and Revascularization Before Transcutaneous Aortic Valve Implantation: An Update on Current Knowledge. Front Cardiovasc Med 2021; 8:654892. [PMID: 34095249 PMCID: PMC8175649 DOI: 10.3389/fcvm.2021.654892] [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: 01/17/2021] [Accepted: 03/18/2021] [Indexed: 12/22/2022] Open
Abstract
Transcutaneous aortic valve implantation (TAVI) has led to a paradigm shift in the treatment of severe aortic stenosis (AS) in the elderly and is expanding to still younger and lower-risk patients with severe AS as an alternative to surgical aortic valve replacement (SAVR). While the role of coronary artery bypass grafting with SAVR is well-documented, the analog of percutaneous coronary intervention with TAVI is less so. The aim of this review is to provide an overview of the important challenges in treating severe AS and co-existing coronary artery disease in patients planned for TAVI.
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Affiliation(s)
- Muhammad Sabbah
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Thomas Engstrøm
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Ole De Backer
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Lars Søndergaard
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jacob Lønborg
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
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Fink N, Rueckel J, Kaestle S, Schwarze V, Gresser E, Hoppe B, Rudolph J, Goller S, Kunz WG, Ricke J, Sabel BO. Evaluation of patients with respiratory infections during the first pandemic wave in Germany: characteristics of COVID-19 versus non-COVID-19 patients. BMC Infect Dis 2021; 21:167. [PMID: 33568104 PMCID: PMC7875010 DOI: 10.1186/s12879-021-05829-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 01/22/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Characteristics of COVID-19 patients have mainly been reported within confirmed COVID-19 cohorts. By analyzing patients with respiratory infections in the emergency department during the first pandemic wave, we aim to assess differences in the characteristics of COVID-19 vs. Non-COVID-19 patients. This is particularly important regarding the second COVID-19 wave and the approaching influenza season. METHODS We prospectively included 219 patients with suspected COVID-19 who received radiological imaging and RT-PCR for SARS-CoV-2. Demographic, clinical and laboratory parameters as well as RT-PCR results were used for subgroup analysis. Imaging data were reassessed using the following scoring system: 0 - not typical, 1 - possible, 2 - highly suspicious for COVID-19. RESULTS COVID-19 was diagnosed in 72 (32,9%) patients. In three of them (4,2%) the initial RT-PCR was negative while initial CT scan revealed pneumonic findings. 111 (50,7%) patients, 61 of them (55,0%) COVID-19 positive, had evidence of pneumonia. Patients with COVID-19 pneumonia showed higher body temperature (37,7 ± 0,1 vs. 37,1 ± 0,1 °C; p = 0.0001) and LDH values (386,3 ± 27,1 vs. 310,4 ± 17,5 U/l; p = 0.012) as well as lower leukocytes (7,6 ± 0,5 vs. 10,1 ± 0,6G/l; p = 0.0003) than patients with other pneumonia. Among abnormal CT findings in COVID-19 patients, 57 (93,4%) were evaluated as highly suspicious or possible for COVID-19. In patients with negative RT-PCR and pneumonia, another third was evaluated as highly suspicious or possible for COVID-19 (14 out of 50; 28,0%). The sensitivity in the detection of patients requiring isolation was higher with initial chest CT than with initial RT-PCR (90,4% vs. 79,5%). CONCLUSIONS COVID-19 patients show typical clinical, laboratory and imaging parameters which enable a sensitive detection of patients who demand isolation measures due to COVID-19.
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Affiliation(s)
- Nicola Fink
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany.
- Comprehensive Pneumology Center (CPC-M), German Center for Lung Research (DZL), 81377, Munich, Germany.
| | - Johannes Rueckel
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Sophia Kaestle
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Vincent Schwarze
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Eva Gresser
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Boj Hoppe
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Jan Rudolph
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Sophia Goller
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Jens Ricke
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Bastian O Sabel
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
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Tancredi T, DeWaters A, McGillen KL. Renal ultrasound findings secondary to COVID-19 related collapsing focal segmental glomerulosclerosis - A case report. Clin Imaging 2020; 71:34-38. [PMID: 33171364 PMCID: PMC7644181 DOI: 10.1016/j.clinimag.2020.11.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 10/14/2020] [Accepted: 11/02/2020] [Indexed: 12/28/2022]
Abstract
SARS-CoV-2 (COVID-19) is well known to have extrapulmonary manifestations, including acute renal failure. While radiologic findings of COVID-19 pulmonary-involvement have been described, renal findings associated with COVID-19 have not. We present a case of a 38-year-old Afro-Caribbean female diagnosed with COVID-19 whose renal ultrasound showed increased parenchymal echogenicity, decreased global color Doppler signal with elevated resistive indices, but no large vessel thrombi. Non-targeted renal biopsy demonstrated collapsing focal segmental glomerulosclerosis (FSGS), likely secondary to COVID-19 infection, which may be a specific manifestation of this disease that has been predominantly reported in Black patients. We report several findings on renal ultrasound with duplex Doppler not previously associated with COVID, specifically with FSGS, which in conjunction can be useful to both the radiologist and the clinician, potentially pointing them in the direction of this diagnosis and early treatment. Renal ultrasound provides benefit in cases of COVID-19 with acute kidney injury. Collapsing focal segmental glomerulosclerosis can occur secondary to COVID-19. This entity occurs nearly exclusively in Black patients. Ultrasound may show echogenic kidneys, elevated resistive index, altered perfusion. When these sonographic features are seen, clinicians should consider biopsy.
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Affiliation(s)
- Tyler Tancredi
- Penn State Health Milton S Hershey Medical Center, 500 University Drive, Hershey, PA 17033, United States of America
| | - Ami DeWaters
- Penn State Health Milton S Hershey Medical Center, 500 University Drive, Hershey, PA 17033, United States of America
| | - Kathryn L McGillen
- Penn State Health Milton S Hershey Medical Center, 500 University Drive, Hershey, PA 17033, United States of America.
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Caruso D, Polici M, Zerunian M, Pucciarelli F, Polidori T, Guido G, Rucci C, Bracci B, Muscogiuri E, De Dominicis C, Laghi A. Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients. Radiol Med 2020; 126:243-249. [PMID: 33044733 PMCID: PMC7548413 DOI: 10.1007/s11547-020-01291-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/13/2020] [Indexed: 01/10/2023]
Abstract
INTRODUCTION COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. MATERIALS AND METHODS From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p < 0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis. RESULTS Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66 ± 16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63 ± 15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55 ± 0.26L vs 0.43 ± 0.23L, p = 0.0005) and fibrotic alterations (0.05 ± 0.03 L vs 0.04 ± 0.03 L, p < 0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p < 0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p < 0.001), respectively. CONCLUSIONS Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.
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Affiliation(s)
- Damiano Caruso
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Michela Polici
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Marta Zerunian
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Francesco Pucciarelli
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Tiziano Polidori
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Gisella Guido
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Carlotta Rucci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Benedetta Bracci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Emanuele Muscogiuri
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Chiara De Dominicis
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy.
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