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Kampaktsis PN, Hennecken C, Shetty M, McLaughlin L, Rampidis G, Samaras A, Avgerinos D, Spilias N, Kuno T, Briasoulis A, Einstein AJ. Current and Emerging Approaches for Primary Prevention of Coronary Artery Disease Using Cardiac Computed Tomography. Curr Cardiol Rep 2024:10.1007/s11886-024-02104-8. [PMID: 39066990 DOI: 10.1007/s11886-024-02104-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/12/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE OF REVIEW To summarize the current use of cardiac computed tomography (CT) technologies as well as their pertinent evidence in regards to prevention of coronary artery disease (CAD). RECENT FINDINGS Cardiac CTA has now become a main non-invasive method for the evaluation of symptomatic CAD. In addition to coronary calcium score, other CT technologies such as atherosclerotic plaque analysis, fractional flow reserve estimation by CT, pericoronary fat attenuation, and endothelial wall shear stress have emerged. Whether the use of CT modalities can enhance risk prediction and prevention in CAD has not been fully answered. We discuss the evidence for coronary artery calcium scoring and coronary CT angiography in primary prevention and the current barriers to their use. We attempt to delineate what can be done to expand use and what studies are needed to broaden adoption in the future. We also examine the potential roles of emerging CT technologies. Finally, we describe potential clinical approaches to prevention that would incorporate cardiac CT technologies.
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Affiliation(s)
- Polydoros N Kampaktsis
- Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, 177 Fort Washington Ave, MHB2, New York, NY, 10032, USA.
- Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, New York, NY, USA.
- Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece.
| | - Carolyn Hennecken
- Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, 177 Fort Washington Ave, MHB2, New York, NY, 10032, USA
| | - Mrinali Shetty
- Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, 177 Fort Washington Ave, MHB2, New York, NY, 10032, USA
- Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, New York, NY, USA
| | - Laura McLaughlin
- Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, 177 Fort Washington Ave, MHB2, New York, NY, 10032, USA
| | - Georgios Rampidis
- Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece
| | - Athanasios Samaras
- Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece
| | | | - Nikolaos Spilias
- Cardiovascular Division, University of Miami Health System, Miami, FL, USA
| | | | | | - Andrew J Einstein
- Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, 177 Fort Washington Ave, MHB2, New York, NY, 10032, USA
- Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, New York, NY, USA
- Department of Radiology, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, New York, NY, USA
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Sabouret P, Santos RD. Coronary artery calcium score in the young: is it time to update the guidelines? Eur J Prev Cardiol 2024; 31:1058-1060. [PMID: 38330237 DOI: 10.1093/eurjpc/zwae050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024]
Affiliation(s)
- Pierre Sabouret
- Heart Institute and Action Group, Pitié-Salpétrière, Sorbonne University, 47-83 Bd. de l'Hôpital, 75013 Paris, France
- National College of French Cardiologists, 13 rue Niepce, 75014, Paris, France
| | - Raul D Santos
- Lipid Clinic Heart Institute (InCor), University of Sao Paulo Medical School Hospital, Av. Dr. Eneas C. Aguiar 44, 05403-000, Sao Paulo, Brazil
- Academic Research Organization, Hospital Israelita Albert Einstein, Av. Albert Einstein, 627/701, 05652-900, Sao Paulo, Brazil
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3
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Rodriguez F, Dudum R. Beyond Primary Prevention: The Intersection of Severe Coronary Calcium, Left Main Coronary Calcium, and Diabetes. JACC Cardiovasc Imaging 2024; 17:777-779. [PMID: 38520427 DOI: 10.1016/j.jcmg.2024.01.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 01/25/2024] [Indexed: 03/25/2024]
Affiliation(s)
- Fatima Rodriguez
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine, Stanford University, Stanford, California, USA; Center for Digital Health, Stanford University, Stanford, California, USA.
| | - Ramzi Dudum
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine, Stanford University, Stanford, California, USA
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Williams MC, Shanbhag AD, Zhou J, Michalowska AM, Lemley M, Miller RJH, Killekar A, Waechter P, Gransar H, Van Kriekinge SD, Builoff V, Feher A, Miller EJ, Bateman T, Dey D, Berman D, Slomka PJ. Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry. Eur Heart J Cardiovasc Imaging 2024; 25:976-985. [PMID: 38376471 PMCID: PMC11210989 DOI: 10.1093/ehjci/jeae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/22/2023] [Accepted: 01/30/2024] [Indexed: 02/21/2024] Open
Abstract
AIMS Vessel-specific coronary artery calcification (CAC) is additive to global CAC for prognostic assessment. We assessed accuracy and prognostic implications of vessel-specific automated deep learning (DL) CAC analysis on electrocardiogram (ECG) gated and attenuation correction (AC) computed tomography (CT) in a large multi-centre registry. METHODS AND RESULTS Vessel-specific CAC was assessed in the left main/left anterior descending (LM/LAD), left circumflex (LCX), and right coronary artery (RCA) using a DL model trained on 3000 gated CT and tested on 2094 gated CT and 5969 non-gated AC CT. Vessel-specific agreement was assessed with linear weighted Cohen's Kappa for CAC zero, 1-100, 101-400, and >400 Agatston units (AU). Risk of major adverse cardiovascular events (MACE) was assessed during 2.4 ± 1.4 years follow-up, with hazard ratios (HR) and 95% confidence intervals (CI). There was strong to excellent agreement between DL and expert ground truth for CAC in LM/LAD, LCX and RCA on gated CT [0.90 (95% CI 0.89 to 0.92); 0.70 (0.68 to 0.73); 0.79 (0.77 to 0.81)] and AC CT [0.78 (0.77 to 0.80); 0.60 (0.58 to 0.62); 0.70 (0.68 to 0.71)]. MACE occurred in 242 (12%) undergoing gated CT and 841(14%) of undergoing AC CT. LM/LAD CAC >400 AU was associated with the highest risk of MACE on gated (HR 12.0, 95% CI 7.96, 18.0, P < 0.001) and AC CT (HR 4.21, 95% CI 3.48, 5.08, P < 0.001). CONCLUSION Vessel-specific CAC assessment with DL can be performed accurately and rapidly on gated CT and AC CT and provides important prognostic information.
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Affiliation(s)
- Michelle C Williams
- British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Aakash D Shanbhag
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
- Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Jianhang Zhou
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Anna M Michalowska
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Mark Lemley
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Robert J H Miller
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary AB, Canada
| | - Aditya Killekar
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Parker Waechter
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Heidi Gransar
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Serge D Van Kriekinge
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Valerie Builoff
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Attila Feher
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Edward J Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Timothy Bateman
- Cardiovascular Imaging Technologies LLC, Kansas City, MO, USA
| | - Damini Dey
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Daniel Berman
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
| | - Piotr J Slomka
- Departments of Medicine (Division of Artificial Intelligence), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, 6500 Wilshire Blvd, Floor 4, Los Angeles 90048 CA, USA
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Gennari AG, Rossi A, De Cecco CN, van Assen M, Sartoretti T, Giannopoulos AA, Schwyzer M, Huellner MW, Messerli M. Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes. Int J Cardiovasc Imaging 2024; 40:951-966. [PMID: 38700819 PMCID: PMC11147943 DOI: 10.1007/s10554-024-03080-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 03/09/2024] [Indexed: 06/05/2024]
Abstract
Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.
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Affiliation(s)
- Antonio G Gennari
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Alexia Rossi
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Carlo N De Cecco
- Division of Cardiothoracic Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA
- Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Emory University, Atlanta, GA, USA
| | - Marly van Assen
- Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Emory University, Atlanta, GA, USA
| | - Thomas Sartoretti
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Andreas A Giannopoulos
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
| | - Moritz Schwyzer
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Martin W Huellner
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Michael Messerli
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland.
- University of Zurich, Zurich, Switzerland.
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Lungu CN, Creteanu A, Mehedinti MC. Endovascular Drug Delivery. Life (Basel) 2024; 14:451. [PMID: 38672722 PMCID: PMC11051410 DOI: 10.3390/life14040451] [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: 02/06/2024] [Revised: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
Drug-eluting stents (DES) and balloons revolutionize atherosclerosis treatment by targeting hyperplastic tissue responses through effective local drug delivery strategies. This review examines approved and emerging endovascular devices, discussing drug release mechanisms and their impacts on arterial drug distribution. It emphasizes the crucial role of drug delivery in modern cardiovascular care and highlights how device technologies influence vascular behavior based on lesion morphology. The future holds promise for lesion-specific treatments, particularly in the superficial femoral artery, with recent CE-marked devices showing encouraging results. Exciting strategies and new patents focus on local drug delivery to prevent restenosis, shaping the future of interventional outcomes. In summary, as we navigate the ever-evolving landscape of cardiovascular intervention, it becomes increasingly evident that the future lies in tailoring treatments to the specific characteristics of each lesion. By leveraging cutting-edge technologies and harnessing the potential of localized drug delivery, we stand poised to usher in a new era of precision medicine in vascular intervention.
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Affiliation(s)
- Claudiu N. Lungu
- Department of Functional and Morphological Science, Faculty of Medicine and Pharmacy, Dunarea de Jos University, 800010 Galati, Romania;
| | - Andreea Creteanu
- Department of Pharmaceutical Technology, University of Medicine and Pharmacy Grigore T Popa, 700115 Iași, Romania
| | - Mihaela C. Mehedinti
- Department of Functional and Morphological Science, Faculty of Medicine and Pharmacy, Dunarea de Jos University, 800010 Galati, Romania;
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7
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Lima MR, Lopes PM, Ferreira AM. Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment. Ther Adv Cardiovasc Dis 2024; 18:17539447241249650. [PMID: 38708947 PMCID: PMC11075618 DOI: 10.1177/17539447241249650] [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: 09/12/2023] [Accepted: 03/08/2024] [Indexed: 05/07/2024] Open
Abstract
Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.
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Affiliation(s)
- Maria Rita Lima
- Department of Cardiology, Hospital Santa Cruz, Centro Hospitalar Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, Carnaxide, Lisbon 2790-134, Portugal
| | - Pedro M. Lopes
- Department of Cardiology, Hospital Santa Cruz, Centro Hospitalar Lisboa Ocidental, Carnaxide, Portugal
| | - António M. Ferreira
- Department of Cardiology, Hospital Santa Cruz, Centro Hospitalar Lisboa Ocidental, Carnaxide, Portugal
- UNICA – Cardiovascular CT and MR Unit, Hospital da Luz, Lisbon, Portugal
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Garg PK, Bhatia HS, Allen TS, Grainger T, Pouncey AL, Dichek D, Virmani R, Golledge J, Allison MA, Powell JT. Assessment of Subclinical Atherosclerosis in Asymptomatic People In Vivo: Measurements Suitable for Biomarker and Mendelian Randomization Studies. Arterioscler Thromb Vasc Biol 2024; 44:24-47. [PMID: 38150519 PMCID: PMC10753091 DOI: 10.1161/atvbaha.123.320138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
BACKGROUND One strategy to reduce the burden of cardiovascular disease is the early detection and treatment of atherosclerosis. This has led to significant interest in studies of subclinical atherosclerosis, using different phenotypes, not all of which are accurate reflections of the presence of asymptomatic atherosclerotic plaques. The aim of part 2 of this series is to provide a review of the existing literature on purported measures of subclinical disease and recommendations concerning which tests may be appropriate in the prevention of incident cardiovascular disease. METHODS We conducted a critical review of measurements used to infer the presence of subclinical atherosclerosis in the major conduit arteries and focused on the predictive value of these tests for future cardiovascular events, independent of conventional cardiovascular risk factors, in asymptomatic people. The emphasis was on studies with >10 000 person-years of follow-up, with meta-analysis of results reporting adjusted hazard ratios (HRs) with 95% CIs. The arterial territories were limited to carotid, coronary, aorta, and lower limb arteries. RESULTS In the carotid arteries, the presence of plaque (8 studies) was independently associated with future stroke (pooled HR, 1.89 [1.04-3.44]) and cardiac events (7 studies), with a pooled HR, 1.77 (1.19-2.62). Increased coronary artery calcium (5 studies) was associated with the risk of coronary heart disease events, pooled HR, 1.54 (1.07-2.07) and increasing severity of calcification (by Agaston score) was associated with escalation of risk (13 studies). An ankle/brachial index (ABI) of <0.9, the pooled HR for cardiovascular death from 7 studies was 2.01 (1.43-2.81). There were insufficient studies of either, thoracic or aortic calcium, aortic diameter, or femoral plaque to synthesize the data based on consistent reporting of these measures. CONCLUSIONS The presence of carotid plaque, coronary artery calcium, or abnormal ankle pressures seems to be a valid indicator of the presence of subclinical atherosclerosis and may be considered for use in biomarker, Mendelian randomization and similar studies.
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Affiliation(s)
- Parveen K Garg
- Division of Cardiology, University of Southern California, Keck School of Medicine, Los Angeles (G.P.)
| | - Harpreet S Bhatia
- Division of Cardiovascular Medicine, University of California San Diego (B.H., A.T., A.M.A.)
| | - Tara S Allen
- Division of Cardiovascular Medicine, University of California San Diego (B.H., A.T., A.M.A.)
| | - Tabitha Grainger
- Department of Surgery & Cancer, Imperial College London (G.T., P.A.-L., P.J.T.)
| | - Anna L Pouncey
- Department of Surgery & Cancer, Imperial College London (G.T., P.A.-L., P.J.T.)
| | - David Dichek
- Division of Cardiology, Department of Medicine, University of Washington, Seattle (D.D.)
| | | | - Jonathan Golledge
- Queensland Research Centre for Peripheral Vascular Disease, James Cook University and Townsville University Hospital, Australia (G.J.)
| | - Matthew A Allison
- Division of Cardiovascular Medicine, University of California San Diego (B.H., A.T., A.M.A.)
| | - Janet T Powell
- Department of Surgery & Cancer, Imperial College London (G.T., P.A.-L., P.J.T.)
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Caminati A, Zompatori M, Fuccillo N, Sonaglioni A, Elia D, Cassandro R, Trevisan R, Rispoli A, Pelosi G, Harari S. Coronary artery calcium score is a prognostic factor for mortality in idiopathic pulmonary fibrosis. Minerva Med 2023; 114:815-824. [PMID: 35671002 DOI: 10.23736/s0026-4806.22.08018-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Cardiovascular diseases are frequent in idiopathic pulmonary fibrosis (IPF) and impact on survival. We investigated the association of coronary artery calcium (CAC) score at IPF diagnosis and during mid-term follow-up, with adverse cardiovascular events and all-cause mortality. METHODS Consecutive patients with IPF were retrospectively analyzed. Demographic data, smoking history, comorbidities and pulmonary function tests (PFTs) were recorded. All patients had at least two chest high resolution computed tomography (HRCT) performed 2 years apart. The total CAC score and visual fibrotic score were calculated, and all clinically significant cardiovascular events and deaths were reported. RESULTS The population consisted of 79 patients (57 males, mean age: 74.4±7.6 years); 67% of patients had a history of smoking, 48% of hypertension, 37% of dyslipidemia and 22.8% of diabetes. The visual score was 21.28±7.99% at T0 and 26.54±9.34% at T1, respectively (T1-T0 5.26±6.13%, P<0.001). CAC score at T0 and at T1 was 537.93±839.94 and 759.98±1027.6, respectively (T1-T0 224.66±406.87, P<0.001). Mean follow-up time was 2.47±1.1 years. On multivariate analysis, male sex (HR=3.58, 95% CI: 1.14-11.2) and CAC score at T0 (HR=1.04, 95% CI: 1.01-1.07) correlated with mortality and cardiovascular events. CAC score at T0≥405 showed 82% sensitivity and 100% specificity for predicting mortality and adverse cardiovascular events. CONCLUSIONS IPF patients with a CAC score at diagnosis ≥405 have a poor prognosis over a mid-term follow-up. A higher CAC score is associated with mortality and cardiovascular events.
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Affiliation(s)
- Antonella Caminati
- Unit of Pneumology and Semi-Intensive Respiratory Therapy, Section of Respiratory Pathophysiology and Pulmonary Hemodynamics, IRCCS MultiMedica, Milan, Italy -
| | - Maurizio Zompatori
- Department of Diagnostic Imaging, IRCCS MultiMedica, Milan, Italy
- DIMES Department, University of Bologna, Bologna, Italy
| | - Nicoletta Fuccillo
- Unit of Pneumology and Semi-Intensive Respiratory Therapy, Section of Respiratory Pathophysiology and Pulmonary Hemodynamics, IRCCS MultiMedica, Milan, Italy
| | | | - Davide Elia
- Unit of Pneumology and Semi-Intensive Respiratory Therapy, Section of Respiratory Pathophysiology and Pulmonary Hemodynamics, IRCCS MultiMedica, Milan, Italy
| | - Roberto Cassandro
- Unit of Pneumology and Semi-Intensive Respiratory Therapy, Section of Respiratory Pathophysiology and Pulmonary Hemodynamics, IRCCS MultiMedica, Milan, Italy
| | - Roberta Trevisan
- Department of Diagnostic Imaging, IRCCS MultiMedica, Milan, Italy
| | - Anna Rispoli
- Department of Diagnostic Imaging, IRCCS MultiMedica, Milan, Italy
| | - Giuseppe Pelosi
- Intercompany Service of Pathological Anatomy, Scientific and Technological Pole, IRCCS MultiMedica, Milan, Italy
| | - Sergio Harari
- Unit of Pneumology and Semi-Intensive Respiratory Therapy, Section of Respiratory Pathophysiology and Pulmonary Hemodynamics, IRCCS MultiMedica, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
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10
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Schade DS, Hickey M, Eaton RP. Interpreting the Coronary Artery Calcium Score - Critical Information for the Practicing Physician. Am J Med 2023; 136:1070-1075. [PMID: 37660746 DOI: 10.1016/j.amjmed.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/05/2023]
Abstract
Coronary artery calcium scanning is a routine test for assessing the severity of atherosclerosis in asymptomatic individuals. This inexpensive, noninvasive test quantifies the calcium deposition in the 4 principal coronary arteries. Correct interpretation is important to the physician (for recommending therapy) and to the patient (for determining his or her lifetime risk of a cardiovascular event). A score of 0 indicates that a cardiovascular event is extremely unlikely in the next 5 years. In contrast, a score greater than 0 portends a coronary event. The higher the score, the greater the risk. Both the arterial location of the calcium and the number of coronary arteries involved alter the interpretation of the calcium score. At any given age, females have significantly lower scores than males. One-third of individuals with scores greater than 1000 will have a cardiovascular event within 3 years. For all elevated calcium scores, aggressive treatment is warranted, including significant lifestyle changes and medications to reduce low-density lipoprotein cholesterol. Understanding the importance of the coronary artery calcium score will result in improved therapy and patient compliance.
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Affiliation(s)
- David S Schade
- University of New Mexico Health Sciences Center, Albuquerque.
| | - Martin Hickey
- University of New Mexico Health Sciences Center, Albuquerque
| | - R Philip Eaton
- University of New Mexico Health Sciences Center, Albuquerque
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11
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Foldyna B, Basmagi S, Zangeneh FA, Wagner M, Doktorov K, Matveeva A, Denecke T, Gohmann RF, Lücke C, Gutberlet M, Lehmkuhl L. CT-derived coronary artery calcium density is affected by regional lesion distribution and image reconstruction parameters. Clin Imaging 2023; 103:109980. [PMID: 37677856 DOI: 10.1016/j.clinimag.2023.109980] [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: 05/23/2023] [Revised: 08/17/2023] [Accepted: 08/28/2023] [Indexed: 09/09/2023]
Abstract
PURPOSE The prognostic relevance of coronary artery calcium (CAC) density, assessed from cardiac CT scans, is established. However, the influence of CAC distribution, volume, image reconstruction, and clinical factors on CAC density warrants further examination. METHODS In this study, 120 patients underwent non-contrast ECG-gated cardiac CT scans using a prospectively defined CAC scoring protocol with 1-, 3-, and 5-mm thick image reconstructions, both with and without a 20% image overlap. We segmented CAC in all reconstructions and assessed the relationship between CAC density, volume, and number of detected calcifications/patient. RESULTS Overall, 75/120 (63%) patients (66% men, mean age 63 ± 11 years) presented CAC across 342 segments. CAC density, CAC volume, and the number of detected calcifications decreased with increasing slice thickness (p < 0.001 for all); these effects were slightly reduced by image overlap (p < 0.001 for all). Higher CAC density correlated with greater CAC volume (ρ = 0.62; p < 0.001) and more calcified segments per person (ρ = 0.32; p = 0.006). Higher CAC density was also associated with lower patient weight (beta: -0.6, 95%CI: -1.1--0.1, p = 0.022) and increased high-density lipoprotein (HDL) levels (beta: 0.7, 95%CI: 0.0-1.4, p = 0.046). In a multivariable analysis adjusted for clinical covariates, lower CAC density was associated with broader CAC distribution (i.e., a higher number of calcified segments at a given CAC volume; beta-coefficient: -58.9; 95%CI: -84.7 to -33.1; p < 0.001). CONCLUSION CAC density is significantly impacted by regional CAC distribution and image reconstruction, potentially confounding its prognostic value. Accounting for these factors may improve patient risk assessment, management, and cardiovascular health outcomes.
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Affiliation(s)
- Borek Foldyna
- Cardiovascular Imaging Research Center, Massachusetts General Hospital - Harvard Medical School, 165 Cambridge Street, Suite 400, 02114 Boston, USA; Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany.
| | - Said Basmagi
- Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany
| | | | - Matthias Wagner
- Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany
| | - Kalin Doktorov
- Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany
| | - Anna Matveeva
- Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany
| | - Timm Denecke
- Clinic for Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Robin F Gohmann
- Department of Diagnostic and Interventional Radiology, Heart Center Leipzig at University of Leipzig, Leipzig, Germany
| | - Christian Lücke
- Department of Diagnostic and Interventional Radiology, Heart Center Leipzig at University of Leipzig, Leipzig, Germany
| | - Matthias Gutberlet
- Department of Diagnostic and Interventional Radiology, Heart Center Leipzig at University of Leipzig, Leipzig, Germany
| | - Lukas Lehmkuhl
- Clinic for Radiology, Heart Center Bad Neustadt a.d. Saale, Bad Neustadt a.d. Saale, Germany
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12
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Takahashi D, Fujimoto S, Nozaki YO, Kudo A, Kawaguchi YO, Takamura K, Hiki M, Sato E, Tomizawa N, Daida H, Minamino T. Fully automated coronary artery calcium quantification on electrocardiogram-gated non-contrast cardiac computed tomography using deep-learning with novel Heart-labelling method. EUROPEAN HEART JOURNAL OPEN 2023; 3:oead113. [PMID: 38035036 PMCID: PMC10683040 DOI: 10.1093/ehjopen/oead113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/14/2023] [Accepted: 10/26/2023] [Indexed: 12/02/2023]
Abstract
Aims To develop an artificial intelligence (AI)-model which enables fully automated accurate quantification of coronary artery calcium (CAC), using deep learning (DL) on electrocardiogram (ECG)-gated non-contrast cardiac computed tomography (gated CCT) images. Methods and results Retrospectively, 560 gated CCT images (including 60 synthetic images) performed at our institution were used to train AI-model, which can automatically divide heart region into five areas belonging to left main (LM), left anterior descending (LAD), circumflex (LCX), right coronary artery (RCA), and another. Total and vessel-specific CAC score (CACS) in each scan were manually evaluated. AI-model was trained with novel Heart-labelling method via DL according to the manual-derived results. Then, another 409 gated CCT images obtained in our institution were used for model validation. The performance of present AI-model was tested using another external cohort of 400 gated CCT images of Stanford Center for Artificial Intelligence of Medical Imaging by comparing with the ground truth. The overall accuracy of the AI-model for total CACS classification was excellent with Cohen's kappa of k = 0.89 and 0.95 (validation and test, respectively), which surpasses previous research of k = 0.89. Bland-Altman analysis showed little difference in individual total and vessel-specific CACS between AI-derived CACS and ground truth in test cohort (mean difference [95% confidence interval] were 1.5 [-42.6, 45.6], -1.5 [-100.5, 97.5], 6.6 [-60.2, 73.5], 0.96 [-59.2, 61.1], and 7.6 [-134.1, 149.2] for LM, LAD, LCX, RCA, and total CACS, respectively). Conclusion Present Heart-labelling method provides a further improvement in fully automated, total, and vessel-specific CAC quantification on gated CCT.
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Affiliation(s)
- Daigo Takahashi
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Shinichiro Fujimoto
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yui O Nozaki
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Ayako Kudo
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yuko O Kawaguchi
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Kazuhisa Takamura
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Makoto Hiki
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Eisuke Sato
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Nobuo Tomizawa
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hiroyuki Daida
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
| | - Tohru Minamino
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo Bunkyo-ku, Tokyo 113-8421, Japan
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13
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Dudum R, Dardari ZA, Feldman DI, Berman DS, Budoff MJ, Miedema MD, Nasir K, Rozanski A, Rumberger JA, Shaw L, Dzaye O, Caínzos-Achirica M, Patel J, Blaha MJ. Coronary Artery Calcium Dispersion and Cause-Specific Mortality. Am J Cardiol 2023; 191:76-83. [PMID: 36645939 PMCID: PMC9928903 DOI: 10.1016/j.amjcard.2022.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/11/2022] [Accepted: 12/18/2022] [Indexed: 01/15/2023]
Abstract
Coronary artery calcium (CAC) measures subclinical atherosclerosis and improves risk stratification. CAC characteristics-including vessel(s) involved, number of vessels, volume, and density-have been shown to differentially impact risk. We assessed how dispersion-either the number of calcified vessels or CAC phenotype (diffuse, normal, and concentrated)-impacted cause-specific mortality. The CAC Consortium is a retrospective cohort of 66,636 participants without coronary heart disease (CHD) who underwent CAC scoring. This study included patients with CAC >0 (n = 28,147). CAC area, CAC density, and CAC phenotypes (derived from the index of diffusion = 1 - [CAC in most concentrated vessel/total Agatston score]) were calculated. The associations between CAC characteristics and cause-specific mortality were assessed. The participant details included (n = 28,147): mean age 58.3 years, 25% female, 89.6% White, and 66% had 2+ calcified vessels. Diabetes, hypertension, and hyperlipidemia were predictors of multivessel involvement (p <0.001). After controlling for the overall CAC score, those with 4-vessel CAC involvement had more CAC area and less dense calcifications than those with 1-vessel. There was a graded increase in all-cause and cardiovascular disease (CVD)- and CHD-specific mortality as the number of calcified vessels increased. Among those with ≥2 vessels involved (n = 18,516), a diffuse phenotype was associated with a higher CVD-specific mortality and had a trend toward higher all-cause and CHD-specific mortality than a concentrated CAC phenotype. Diffuse CAC involvement was characterized by less dense calcification, more CAC area, multiple coronary vessel involvement, and presence of certain traditional risk factors. There is a graded increase in all-cause and CVD- and CHD-specific mortality with increasing CAC dispersion.
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Affiliation(s)
- Ramzi Dudum
- Department of Cardiovascular Medicine, Stanford University, Stanford, California; Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland
| | - Zeina A Dardari
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland
| | - David I Feldman
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland; Department of Medicine, The Johns Hopkins Hospital, Baltimore, Maryland
| | - Daniel S Berman
- Department of Nuclear Cardiology/Cardiac Imaging, Cedars-Sinai Medical Center, Los Angeles, California
| | - Matthew J Budoff
- Department of Medicine, Harbor-UCLA Medical Center, Torrance, California
| | - Michael D Miedema
- Minneapolis Heart Institute and Minneapolis Heart Institute Foundation, Minneapolis, Minnesota
| | - Khurram Nasir
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland; Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas
| | - Alan Rozanski
- Department of Medicine, St. Luke's Roosevelt Hospital Center, New York, New York
| | - John A Rumberger
- Department of Cardiovascular Imaging, Princeton Longevity Center, Princeton, New Jersey
| | - Leslee Shaw
- Department of Radiology and Medicine, Weill Cornell Medical College, New York, New York
| | - Omar Dzaye
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland
| | - Miguel Caínzos-Achirica
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland; Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas
| | - Jaideep Patel
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland; Johns Hopkins Heart and Vascular Institute at Greater Baltimore Medical Center, Baltimore, Maryland
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland; Department of Cardiology, the Johns Hopkins Hospital, Baltimore, Maryland.
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14
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Laway BA, Rasool A, Baba MS, Misgar RA, Bashir MI, Wani AI, Choh N, Shah O, Lone A, Shah Z. High prevalence of coronary artery calcification and increased risk for coronary artery disease in patients with Sheehan syndrome-A case-control study. Clin Endocrinol (Oxf) 2023; 98:375-382. [PMID: 36567411 DOI: 10.1111/cen.14871] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/22/2022] [Accepted: 12/22/2022] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Patients with Sheehan syndrome (SS) are predisposed to coronary artery disease (CAD) due to risk factors like abdominal obesity, dyslipidemia and chronic inflammation. In addition to estimate CAD risk enhancers like high sensitive C reactive protein (hsCRP), apolipoprotein B (ApoB) and lipoprotein A [Lp(a)], this study applies Framingham risk score (FRS) and coronary artery calcium (CAC) score to compute a 10-year probability of cardiovascular (CV) events in SS patients. DESIGN Case-control study Sixty-three SS patients, on a stable hormonal replacement treatment except for growth hormone and 65 age, body mass index and parity-matched controls. MEASUREMENTS Measurement of serum hsCRP, ApoB and Lp(a) and estimation of CAC with 16-row multislice computed tomography scanner. RESULTS The concentrations of hsCRP, ApoB and Lp(a) were significantly higher in SS patients than in controls (p < .01). After calculating FRS, 95.2% of SS patients were classified as low risk, 4.8% as intermediate risk and all controls were classified as low risk for probable CV events. CAC was detected in 50.7% SS patients and 7.6% controls (p = .006). According to the CAC score, 26.9% SS patients were classified as at risk (CAC > 10) for incident CV events as against 1.6% controls. The mean Multi-Ethnic Study of Atherosclerosis (MESA) score was significantly higher in patients with SS than controls. CAC corelated significantly with fasting blood glucose (r = .316), ApoB (r = .549), LP(a) (r = .310) and FRS (r = .294). CONCLUSION Significant number of asymptomatic SS patients have high coronary artery calcium score and are classified at risk for CAD.
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Affiliation(s)
- Bashir Ahmad Laway
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Abid Rasool
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Mohammad Salem Baba
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Raiz Ahmad Misgar
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Mir Iftikhar Bashir
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Arshad Iqbal Wani
- Department of Endocrinology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Naseer Choh
- Department of Radiology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Omair Shah
- Department of Radiology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Ajaz Lone
- Department of Cardiology, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
| | - Zaffar Shah
- Department of Immunology & Molecular Medicine, Sher-I- Kashmir Institute of Medical Sciences, Srinagar, Kashmir, India
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15
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Agarwala A, Satish P, Al Rifai M, Mehta A, Cainzos-Achirica M, Shah NS, Kanaya AM, Sharma GV, Dixon DL, Blumenthal RS, Natarajan P, Nasir K, Virani SS, Patel J. Identification and Management of Atherosclerotic Cardiovascular Disease Risk in South Asian Populations in the U.S. JACC. ADVANCES 2023; 2:100258. [PMID: 38089916 PMCID: PMC10715803 DOI: 10.1016/j.jacadv.2023.100258] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 11/15/2022] [Accepted: 12/13/2022] [Indexed: 12/20/2023]
Abstract
South Asians (SAs, individuals with ancestry from Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) are among the fastest growing ethnic subgroups in the United States. SAs typically experience a high prevalence of diabetes, abdominal obesity, and hypertension, among other cardiovascular disease risk factors, which are often under recognized and undermanaged. The excess coronary heart disease risk in this growing population must be critically assessed and managed with culturally appropriate preventive services. Accordingly, this scientific document prepared by a multidisciplinary group of clinicians and investigators in cardiology, internal medicine, pharmacy, and SA-centric researchers describes key characteristics of traditional and nontraditional cardiovascular disease risk factors, compares and contrasts available risk assessment tools, discusses the role of blood-based biomarkers and coronary artery calcium to enhance risk assessment and prevention strategies, and provides evidenced-based approaches and interventions that may reduce coronary heart disease disparities in this higher-risk population.
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Affiliation(s)
- Anandita Agarwala
- Center for Cardiovascular Disease Prevention, Baylor Scott and White Health Heart Hospital Baylor Plano, Plano, Texas, USA
| | - Priyanka Satish
- Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas, USA
| | - Mahmoud Al Rifai
- Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas, USA
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, South Asian Cardiovascular Health Initiative (SACHI), Baltimore, Maryland, USA
| | - Anurag Mehta
- Pauley Heart Center, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Miguel Cainzos-Achirica
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, South Asian Cardiovascular Health Initiative (SACHI), Baltimore, Maryland, USA
- Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Spain
- Hospital del Mar, Parc Salut Mar, Barcelona, Spain
| | - Nilay S. Shah
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Alka M. Kanaya
- Division of General Internal Medicine, University of California San Francisco, San Francisco, California, USA
| | - Garima V. Sharma
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, South Asian Cardiovascular Health Initiative (SACHI), Baltimore, Maryland, USA
| | - Dave L. Dixon
- Pauley Heart Center, Virginia Commonwealth University, Richmond, Virginia, USA
- Department of Pharmacotherapy & Outcomes Science, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Roger S. Blumenthal
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, South Asian Cardiovascular Health Initiative (SACHI), Baltimore, Maryland, USA
| | - Pradeep Natarajan
- Cardiovascular Disease Initiative Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Cardiovascular Research Center Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Khurram Nasir
- Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas, USA
- Center for Outcomes Research, Houston Methodist, Houston, Texas, USA
| | - Salim S. Virani
- Aga Khan University, Karachi, Pakistan
- Texas Heart Institute, Baylor College of Medicine, Houston, Texas, USA
| | - Jaideep Patel
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, South Asian Cardiovascular Health Initiative (SACHI), Baltimore, Maryland, USA
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16
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Baskaran L, Lee JK, Ko MSM, Al’Aref SJ, Neo YP, Ho JS, Huang W, Yoon YE, Han D, Nakanishi R, Tan SY, Al-Mallah M, Budoff MJ, Shaw LJ. Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort. Front Cardiovasc Med 2023; 10:1059839. [PMID: 36733301 PMCID: PMC9887040 DOI: 10.3389/fcvm.2023.1059839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 01/02/2023] [Indexed: 01/18/2023] Open
Abstract
Background The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use. Methods Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE. Results Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783). Conclusion In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.
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Affiliation(s)
- Lohendran Baskaran
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore,Duke-NUS Medical School, National University of Singapore, Singapore, Singapore,*Correspondence: Lohendran Baskaran,
| | - Jing Kai Lee
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Michelle Shi Min Ko
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Subhi J. Al’Aref
- Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Yu Pei Neo
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Jien Sze Ho
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore,Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Weiting Huang
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore,Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | | | - Donghee Han
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Rine Nakanishi
- Department of Cardiovascular Medicine, Toho University Graduate School of Medicine, Tokyo, Japan
| | - Swee Yaw Tan
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore,Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Mouaz Al-Mallah
- Houston Methodist DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, TX, United States
| | - Matthew J. Budoff
- Department of Medicine, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Leslee J. Shaw
- Icahn School of Medicine at Mount Sinai, Blavatnik Family Women’s Health Research Institute, New York, NY, United States
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17
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Lopez-Mattei J, Yang EH, Baldassarre LA, Agha A, Blankstein R, Choi AD, Chen MY, Meyersohn N, Daly R, Slim A, Rochitte C, Blaha M, Whelton S, Dzaye O, Dent S, Milgrom S, Ky B, Iliescu C, Mamas MA, Ferencik M. Cardiac computed tomographic imaging in cardio-oncology: An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT). Endorsed by the International Cardio-Oncology Society (ICOS). J Cardiovasc Comput Tomogr 2023; 17:66-83. [PMID: 36216699 DOI: 10.1016/j.jcct.2022.09.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 09/01/2022] [Accepted: 09/12/2022] [Indexed: 11/21/2022]
Abstract
Cardio-Oncology is a rapidly growing sub-specialty of medicine, however, there is very limited guidance on the use of cardiac CT (CCT) in the care of Cardio-Oncology patients. In order to fill in the existing gaps, this Expert Consensus statement comprised of a multidisciplinary collaboration of experts in Cardiology, Radiology, Cardiovascular Multimodality Imaging, Cardio-Oncology, Oncology and Radiation Oncology aims to summarize current evidence for CCT applications in Cardio-Oncology and provide practice recommendations for clinicians.
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Affiliation(s)
| | - Eric H Yang
- UCLA Cardio-Oncology Program, Division of Cardiology, Department of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | | | - Ali Agha
- Department of Cardiology, Baylor College of Medicine, Houston, TX, USA
| | - Ron Blankstein
- Division of Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Andrew D Choi
- Division of Cardiology and Department of Radiology, The George Washington University School of Medicine, Washington, DC, USA
| | - Marcus Y Chen
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nandini Meyersohn
- Division of Cardiovascular Imaging, Department of Radiology, Massachusetts General Hospital, USA
| | - Ryan Daly
- Franciscan Health Indianapolis, Indianapolis, IN, USA
| | | | - Carlos Rochitte
- InCor Heart Institute, University of São Paulo Medical School, São Paulo, Brazil
| | - Michael Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Seamus Whelton
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Omar Dzaye
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Susan Dent
- Duke Cancer Institute, Department of Medicine, Duke University, Durham, NC, USA
| | - Sarah Milgrom
- Department of Radiation Oncology, University of Colorado, Boulder, CO, USA
| | - Bonnie Ky
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Cezar Iliescu
- Heart and Vascular Institute, Lee Health, Fort Myers, FL, USA
| | - Mamas A Mamas
- Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, UK
| | - Maros Ferencik
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA
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18
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Ihdayhid AR, Lan NSR, Williams M, Newby D, Flack J, Kwok S, Joyner J, Gera S, Dembo L, Adler B, Ko B, Chow BJW, Dwivedi G. Evaluation of an artificial intelligence coronary artery calcium scoring model from computed tomography. Eur Radiol 2023; 33:321-329. [PMID: 35986771 PMCID: PMC9755106 DOI: 10.1007/s00330-022-09028-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 06/07/2022] [Accepted: 07/13/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. METHODS Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1-10, 11-100, 101-400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). RESULTS Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman's r = 0.90, 95% confidence interval [CI] 0.89-0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98-0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland-Altman analysis demonstrated little difference (1.69, 95% limits of agreement: -41.22, 44.60) and there was almost excellent agreement (Cohen's κ = 0.90, 95% CI 0.88-0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. CONCLUSIONS This artificial intelligence-based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. KEY POINTS • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)-based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.
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Affiliation(s)
- Abdul Rahman Ihdayhid
- Department of Cardiology, Fiona Stanley Hospital, Perth, Australia.
- Harry Perkins Institute of Medical Research, Curtin University, Perth, Australia.
| | - Nick S R Lan
- Department of Cardiology, Fiona Stanley Hospital, Perth, Australia
- Harry Perkins Institute of Medical Research, University of Western Australia, Perth, Australia
| | - Michelle Williams
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, Scotland, UK
| | - David Newby
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, Scotland, UK
| | | | | | | | - Sahil Gera
- Harry Perkins Institute of Medical Research, University of Western Australia, Perth, Australia
| | - Lawrence Dembo
- Department of Cardiology, Fiona Stanley Hospital, Perth, Australia
- Envision Medical Imaging, Perth, Australia
| | | | - Brian Ko
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Melbourne, Australia
| | | | - Girish Dwivedi
- Department of Cardiology, Fiona Stanley Hospital, Perth, Australia.
- Harry Perkins Institute of Medical Research, University of Western Australia, Perth, Australia.
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19
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Lin FY, Goebel BP, Lee BC, Lu Y, Baskaran L, Yoon YE, Maliakal GT, Gianni U, Bax AM, Sengupta PP, Slomka PJ, Dey DS, Rozanski A, Han D, Berman DS, Budoff MJ, Miedema MD, Nasir K, Rumberger J, Whelton SP, Blaha MJ, Shaw LJ. Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium. J Cardiovasc Comput Tomogr 2023; 17:28-33. [PMID: 36376147 DOI: 10.1016/j.jcct.2022.10.001] [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: 05/13/2022] [Revised: 09/15/2022] [Accepted: 10/28/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND Machine learning (ML) models of risk prediction with coronary artery calcium (CAC) and CAC characteristics exhibit high performance, but are not inherently interpretable. OBJECTIVES To determine the direction and magnitude of impact of CAC characteristics on 10-year all-cause mortality (ACM) with explainable ML. METHODS We analyzed asymptomatic subjects in the CAC consortium. We trained ML models on 80% and tested on 20% of the data with XGBoost, using clinical characteristics + CAC (ML 1) and additional CAC characteristics of CAC density and number of calcified vessels (ML 2). We applied SHAP, an explainable ML tool, to explore the relationship of CAC and CAC characteristics with 10-year all-cause and CV mortality. RESULTS 2376 deaths occurred among 63,215 patients [68% male, median age 54 (IQR 47-61), CAC 3 (IQR 0-94.3)]. ML2 was similar to ML1 to predict all-cause mortality (Area Under the Curve (AUC) 0.819 vs 0.821, p = 0.23), but superior for CV mortality (0.847 vs 0.845, p = 0.03). Low CAC density increased mortality impact, particularly ≤0.75. Very low CAC density ≤0.75 was present in only 4.3% of the patients with measurable density, and 75% occurred in CAC1-100. The number of diseased vessels did not increase mortality overall when simultaneously accounting for CAC and CAC density. CONCLUSION CAC density contributes to mortality risk primarily when it is very low ≤0.75, which is primarily observed in CAC 1-100. CAC and CAC density are more important for mortality prediction than the number of diseased vessels, and improve prediction of CV but not all-cause mortality. Explainable ML techniques are useful to describe granular relationships in otherwise opaque prediction models.
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Affiliation(s)
- Fay Y Lin
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Population Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Benjamin P Goebel
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Benjamin C Lee
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Yao Lu
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Lohendran Baskaran
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Cardiology, National Heart Centre Singapore, Singapore
| | - Yeonyee E Yoon
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Sungnam, South Korea
| | - Gabriel Thomas Maliakal
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Computer Science, Michigan State University, East Lansing, MI, USA
| | - Umberto Gianni
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - A Maxim Bax
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Partho P Sengupta
- Division of Cardiology, Rutgers Robert Wood Medical School and University Hospital, New Brunswick, NJ, USA
| | - Piotr J Slomka
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Damini S Dey
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alan Rozanski
- Department of Cardiology, Mount Sinai St. Luke's Hospital, New York, NY, USA
| | - Donghee Han
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Berman
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Matthew J Budoff
- Department of Medicine, Lundquist Institute at Harbor UCLA Medical Center, Torrance, CA, USA
| | - Michael D Miedema
- Cardiovascular Prevention, Minneapolis Heart Institute Foundation, Minneapolis Heart Institute, Minneapolis, MN, USA
| | - Khurram Nasir
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist Hospital, Houston, TX, USA
| | - John Rumberger
- Princeton Longevity Center, Princeton Forrestal Village, Princeton, NJ, USA
| | - Seamus P Whelton
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Leslee J Shaw
- Department of Population Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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20
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Kumar P, Bhatia M. Coronary Artery Calcium Data and Reporting System (CAC-DRS): A Primer. J Cardiovasc Imaging 2023; 31:1-17. [PMID: 36693339 PMCID: PMC9880346 DOI: 10.4250/jcvi.2022.0029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/23/2022] [Accepted: 06/06/2022] [Indexed: 01/26/2023] Open
Abstract
The Coronary Artery Calcium Data and Reporting System (CAC-DRS) is a standardized reporting method for calcium scoring on computed tomography. CAC-DRS is applied on a per-patient basis and represents the total calcium score with the number of vessels involved. There are 4 risk categories ranging from CAC-DRS 0 to CAC-DRS 3. CAC-DRS also provides risk prediction and treatment recommendations for each category. The main strengths of CAC-DRS include a detailed and meaningful representation of CAC, improved communication between physicians, risk stratification, appropriate treatment recommendations, and uniform data collection, which provides a framework for education and research. The major limitations of CAC-DRS include a few missing components, an overly simple visual approach without any standard reference, and treatment recommendations lacking a basis in clinical trials. This consistent yet straightforward method has the potential to systemize CAC scoring in both gated and non-gated scans.
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Affiliation(s)
- Parveen Kumar
- Department of Radiodiagnosis & Imaging, Fortis Escort Heart Institute, New Delhi, India
| | - Mona Bhatia
- Department of Radiodiagnosis & Imaging, Fortis Escort Heart Institute, New Delhi, India
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21
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Zhao Y, Malik S, Criqui MH, Allison MA, Budoff MJ, Sandfort V, Wong ND. Coronary calcium density in relation to coronary heart disease and cardiovascular disease in adults with diabetes or metabolic syndrome: the Multi-ethnic Study of Atherosclerosis (MESA). BMC Cardiovasc Disord 2022; 22:536. [PMID: 36494811 PMCID: PMC9733236 DOI: 10.1186/s12872-022-02956-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 11/14/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Coronary artery calcium (CAC) density is inversely associated with coronary heart disease (CHD) and cardiovascular disease (CVD) risk. We examined this relation in those with diabetes mellitus (DM) or metabolic syndrome (MetS). METHODS We studied 3,818 participants with non-zero CAC scores from the Multiethnic Study of Atherosclerosis and classified them as DM, MetS (without DM) or neither DM/MetS. Risk factor-adjusted CAC density was calculated and examined in relation to incident CHD and CVD events over a median follow-up of 15 years among these three disease groups. RESULTS Adjusted CAC density was 2.54, 2.61 and 2.69 among those with DM, MetS or neither DM/MetS. Hazard ratios (HRs) for CHD per 1 SD increase of CAC density was 0.91 (95% CI: 0.72-1.16), 0.70 (95% CI: 0.56-0.87) and 0.79 (95% CI: 0.66-0.95) for those with DM, MetS or neither DM/MetS groups and were 0.77 (95% CI: 0.64-0.94), 0.83 (95% CI: 0.70-0.99) and 0.82 (95% CI: 0.71-0.95) for CVD, respectively. Adjustment for CAC density increased the HRs of CAC volume for CHD/CVD events. Compared to prediction models with or without single CAC measures, c-statistics of models with CAC volume and density were the highest ranging 0.67-0.72. CONCLUSION CAC density is lower among patients with DM or MetS than those with neither DM/MetS and is inversely associated with future CHD/CVD risk among them. Including CAC density in risk assessment among those with MetS may improve prediction of CHD and CVD.
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Affiliation(s)
- Yanglu Zhao
- grid.19006.3e0000 0000 9632 6718Department of Epidemiology, University of California Los Angeles, Los Angeles, USA ,grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
| | - Shaista Malik
- grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
| | - Michael H. Criqui
- grid.266100.30000 0001 2107 4242Division of Preventive Medicine, University of California San Diego, San Diego, USA
| | - Matthew A. Allison
- grid.266100.30000 0001 2107 4242Division of Preventive Medicine, University of California San Diego, San Diego, USA
| | - Matthew J. Budoff
- grid.239844.00000 0001 0157 6501Lindquist Institute, Harbor-UCLA Medical Center, Los Angeles, USA
| | - Veit Sandfort
- grid.94365.3d0000 0001 2297 5165Radiology & Imaging Sciences, National Institutes of Health, Bethesda, USA
| | - Nathan D. Wong
- grid.19006.3e0000 0000 9632 6718Department of Epidemiology, University of California Los Angeles, Los Angeles, USA ,grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
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22
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Luo F, Luo J, Liu F, Qiu Y, Tian X, Zeng L, Zhang Z, Li X, Yang Y. Coronary artery calcium and cystatin C for risk stratification of MACCEs and all-cause death in symptomatic patients. Clin Cardiol 2022; 46:195-203. [PMID: 36484372 PMCID: PMC9933108 DOI: 10.1002/clc.23959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/27/2022] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES The aim of this study was to examine the independent and joint associations of baseline coronary artery calcium score (CACS) and cystatin C (Cys-C) with the risk of major adverse cardiac and cerebrovascular events (MACCEs) and all-cause death in symptomatic populations. METHODS The study included 7140 patients with symptom of chest pain who underwent cardiac computerized tomography examinations to measure CACS. All of them had serum Cys-C results. Endpoints were set for MACCEs and all-cause death events. RESULTS A total of 7140 participants were followed for a median of 1106 days. A total of 305 patients had experienced MACCEs and 191 patients had experienced all-cause death. CACS ≥ 100 and Cys-C ≥ 0.995 mg/L were independently associated with an increased risk of MACCEs (adjusted hazard ratio [HR]: 1.46; 95% confidence interval [CI]: 1.15-1.85; p = .002 and adjusted HR: 1.57; 95% CI: 1.24-2.00; p < .001, respectively). Compared with CACS < 100 and Cys-C < 0.995 mg/L patients, CACS ≥ 100 and Cys-C ≥ 0.995 mg/L patients had the highest risk of MACCEs and all-cause death (adjusted HR: 2.33; 95% CI: 1.64-3.29; p < .001 and adjusted HR: 2.85; 95% CI: 1.79-4.55; p < .001, respectively). Even in patients with CACS < 100, Cys-C ≥ 0.995 mg/L was also associated with a higher risk of MACCEs and all-cause death than Cys-C < 0.995 mg/L (adjusted HR: 1.76; p = .003 and adjusted HR: 2.02; p = .007, respectively). CONCLUSIONS The combined stratification of CACS and Cys-C showed an incremental risk of MACCEs and all-cause death, reflecting complementary prognostic value. Our results support the combination of the two indicators for risk stratification and event prediction.
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Affiliation(s)
- Fan Luo
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Jun‐Yi Luo
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Fen Liu
- Xinjiang Key Laboratory of Cardiovascular Disease Research, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research InstituteThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Ya‐Jing Qiu
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Xin‐Xin Tian
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Lu Zeng
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Zhuo‐Ran Zhang
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Xiao‐Mei Li
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina,Xinjiang Key Laboratory of Cardiovascular Disease Research, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research InstituteThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina
| | - Yi‐Ning Yang
- Department of CardiologyThe First Affiliated Hospital of Xinjiang Medical UniversityUrumqiXinjiangChina,Department of CardiologyPeople's Hospital of Xinjiang Uygur Autonomous RegionUrumqiXinjiangChina
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23
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Tummala R, Han D, Friedman J, Hayes S, Thomson L, Gransar H, Slomka P, Rozanski A, Dey D, Berman D. Association between plaque localization in proximal coronary segments and MACE outcomes in patients with mild CAC: Results from the EISNER study. Am J Prev Cardiol 2022; 12:100423. [PMID: 36199447 PMCID: PMC9529495 DOI: 10.1016/j.ajpc.2022.100423] [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: 07/27/2022] [Revised: 09/20/2022] [Accepted: 09/26/2022] [Indexed: 11/28/2022] Open
Abstract
Objective Coronary artery calcium score (CAC) is a validated tool to predict and reclassify cardiovascular risk. Additional metrics such as regional distribution and extent of CAC over Agatston CAC score may allow further risk stratification. In this study, we evaluate the prognostic significance of proximal CAC involvement in asymptomatic population from the prospective EISNER (Early-Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) registry, focusing on patients with mild CAC (score 1-99). Methods This study included a total of 2,047 adult asymptomatic subject who underwent baseline CAC scan and 14-year follow-up for MACE, defined as myocardial infarction, late revascularization, or cardiac death. Proximal involvement was defined as presence of CAC in the LM, proximal LAD, LCX or RCA. CAC was categorized as 0, 1-99, and ≥100. Results 1,090 (53.2%) subjects had no CAC, 576 (28.1%) had CAC 1-99, and 381 (18.7%) had CAC ≥100. Proximal involvement was seen in 67.2% of subjects with CAC 1-99 and 97.3% of subjects with CAC ≥100. In the CAC 1-99 category, the presence of proximal CAC was associated with increased MACE risk after adjustment for CAC score, CAC extent and conventional risk factors compared to those without proximal CAC (HR: 2.84 95% CI: 1.29-6.25, p=0.009). Conclusion In asymptomatic subjects with CAC scores of 1-99, the presence and extent of proximal CAC plaques provides strong independent prognostic information in predicting MACE
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Affiliation(s)
- Ramyashree Tummala
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Donghee Han
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - John Friedman
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sean Hayes
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Louise Thomson
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Heidi Gransar
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Piotr Slomka
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alan Rozanski
- Division of Cardiology, Mount Sinai Morningside Hospital, New York, New York
| | - Damini Dey
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel Berman
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Corresponding author at: 8700 Beverly Blvd, Los Angeles, California, 90048, United States
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24
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Yu J, Qian L, Sun W, Nie Z, Zheng D, Han P, Shi H, Zheng C, Yang F. Automated total and vessel-specific coronary artery calcium (CAC) quantification on chest CT: direct comparison with CAC scoring on non-contrast cardiac CT. BMC Med Imaging 2022; 22:177. [PMID: 36241978 PMCID: PMC9563469 DOI: 10.1186/s12880-022-00907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 10/04/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND This study aimed to evaluate the artificial intelligence (AI)-based coronary artery calcium (CAC) quantification and regional distribution of CAC on non-gated chest CT, using standard electrocardiograph (ECG)-gated CAC scoring as the reference. METHODS In this retrospective study, a total of 405 patients underwent non-gated chest CT and standard ECG-gated cardiac CT. An AI-based algorithm was used for automated CAC scoring on chest CT, and Agatston score on cardiac CT was manually quantified. Bland-Altman plots were used to evaluate the agreement of absolute Agatston score between the two scans at the patient and vessel levels. Linearly weighted kappa (κ) was calculated to assess the reliability of AI-based CAC risk categorization and the number of involved vessels on chest CT. RESULTS The AI-based algorithm showed moderate reliability for the number of involved vessels in comparison to measures on cardiac CT (κ = 0.75, 95% CI 0.70-0.79, P < 0.001) and an assignment agreement of 76%. Considerable coronary arteries with CAC were not identified with a per-vessel false-negative rate of 59.3%, 17.8%, 34.9%, and 34.7% for LM, LAD, CX, and RCA on chest CT. The leading causes for false negatives of LM were motion artifact (56.3%, 18/32) and segmentation error (43.8%, 14/32). The motion artifact was almost the only cause for false negatives of LAD (96.6%, 28/29), CX (96.7%, 29/30), and RCA (100%, 34/34). Absolute Agatston scores on chest CT were underestimated either for the patient and individual vessels except for LAD (median difference: - 12.5, - 11.3, - 5.6, - 18.6 for total, LM, CX, and RCA, all P < 0.01; - 2.5 for LAD, P = 0.18). AI-based total Agatston score yielded good reliability for risk categorization (weighted κ 0.86, P < 0.001) and an assignment agreement of 86.7% on chest CT, with a per-patient false-negative rate of 15.2% (28/184) and false-positive rate of 0.5% (1/221) respectively. CONCLUSIONS AI-based per-patient CAC quantification on non-gated chest CT achieved a good agreement with dedicated ECG-gated CAC scoring overall and highly reliable CVD risk categorization, despite a slight but significant underestimation. However, it is challenging to evaluate the regional distribution of CAC without ECG-synchronization.
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Affiliation(s)
- Jie Yu
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Lijuan Qian
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Wengang Sun
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Zhuang Nie
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - DanDan Zheng
- ShuKun (BeiJing) Technology Co. Ltd., Jinhui Bd, Qiyang Rd, Beijing, 100000 China
| | - Ping Han
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Heshui Shi
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Chuansheng Zheng
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
| | - Fan Yang
- grid.412839.50000 0004 1771 3250Department of Radiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, 1277 Jiefang Ave., Wuhan, 430022 Hubei Province China ,grid.412839.50000 0004 1771 3250Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022 Hubei Province China
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25
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Chin JC, Maroules CD, Lin AH, Graning RE, Pressley CR. Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population. Fed Pract 2022; 39:382-388. [PMID: 36583089 PMCID: PMC9794164 DOI: 10.12788/fp.0318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Background Cigarette smoking is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). Concomitant use of low-dose computed tomography (LDCT) for coronary artery calcium (CAC) scoring with lung cancer screening (LCS) has been proposed to further determine ASCVD risk and mortality. We aimed to determine the validity of LDCT in identifying CAC and its impact on statin management. Methods We conducted a retrospective review from November 2020 to May 2021 of Military Health System (MHS) beneficiaries who received LCS with LDCT and were referred for CAC scoring with electrocardiogram-gated CT. Of the 190 participants initially identified, 170 met study eligibility. The Agatston method was used to score CAC on both scan types. Results Participants had a mean (SD) age of 62.1 (4.6) years and were 70.6% male. CAC was seen more on ECG-gated CT compared with LDCT (88% vs 74%, P < .001). The Spearman correlation and Kendall W coefficient of concordance of CAC scores between the 2 scan types was 0.945 (P < .001) and 0.643, respectively. The κ statistic between CAC scores on the 2 different scans was 0.49 (SEκ = 0.048; 95% CI, -0.726-1.706), and the weighted κ statistic was 0.711. Bland-Altman analysis demonstrated a mean bias of 111.45 Agatston units, with limits of agreement between -268.64 and 491.54, suggesting CAC scores on electrocardiogram-gated CT were on average about 111 units higher than those on LDCT. There was a statistically significant proportion of nonstatin participants who met statin criteria based on additional CAC reporting (P < .001). Conclusions CAC scores are highly correlated and concordant between LDCT and electrocardiogram-gated CT. Smokers undergoing annual LDCT may benefit from concomitant CAC scoring to help stratify ASCVD risk.
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Gupta A, Bera K, Kikano E, Pierce JD, Gan J, Rajdev M, Ciancibello LM, Gupta A, Rajagopalan S, Gilkeson RC. Coronary Artery Calcium Scoring: Current Status and Future Directions. Radiographics 2022; 42:947-967. [PMID: 35657766 DOI: 10.1148/rg.210122] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Amit Gupta
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Kaustav Bera
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Elias Kikano
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Jonathan D Pierce
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Jonathan Gan
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Maharshi Rajdev
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Leslie M Ciancibello
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Aekta Gupta
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Sanjay Rajagopalan
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
| | - Robert C Gilkeson
- From the Department of Radiology (Amit Gupta, K.B., E.K., J.D.P., J.G., M.R., L.M.C., R.C.G.) and Harrington Heart & Vascular Institute (S.R.), University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Medicine, Mercy Health-St. Elizabeth Youngstown Hospital, Youngstown, OH (Aekta Gupta)
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Adikari D, Gharleghi R, Zhang S, Jorm L, Sowmya A, Moses D, Ooi SY, Beier S. A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD cohort study. BMJ Open 2022; 12:e054881. [PMID: 35725256 PMCID: PMC9214399 DOI: 10.1136/bmjopen-2021-054881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
INTRODUCTION Coronary artery disease (CAD) is the leading cause of death worldwide. More than a quarter of cardiovascular events are unexplained by current absolute cardiovascular disease risk calculators, and individuals without clinical risk factors have been shown to have worse outcomes. The 'anatomy of risk' hypothesis recognises that adverse anatomical features of coronary arteries enhance atherogenic haemodynamics, which in turn mediate the localisation and progression of plaques. We propose a new risk prediction method predicated on CT coronary angiography (CTCA) data and state-of-the-art machine learning methods based on a better understanding of anatomical risk for CAD. This may open new pathways in the early implementation of personalised preventive therapies in susceptible individuals as a potential key in addressing the growing burden of CAD. METHODS AND ANALYSIS GeoCAD is a retrospective cohort study in 1000 adult patients who have undergone CTCA for investigation of suspected CAD. It is a proof-of-concept study to test the hypothesis that advanced image-derived patient-specific data can accurately predict long-term cardiovascular events. The objectives are to (1) profile CTCA images with respect to variations in anatomical shape and associated haemodynamic risk expressing, at least in part, an individual's CAD risk, (2) develop a machine-learning algorithm for the rapid assessment of anatomical risk directly from unprocessed CTCA images and (3) to build a novel CAD risk model combining traditional risk factors with these novel anatomical biomarkers to provide a higher accuracy CAD risk prediction tool. ETHICS AND DISSEMINATION The study protocol has been approved by the St Vincent's Hospital Human Research Ethics Committee, Sydney-2020/ETH02127 and the NSW Population and Health Service Research Ethics Committee-2021/ETH00990. The project outcomes will be published in peer-reviewed and biomedical journals, scientific conferences and as a higher degree research thesis.
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Affiliation(s)
- Dona Adikari
- Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
- Cardiology Department, The Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Ramtin Gharleghi
- School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia
| | - Shisheng Zhang
- School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia
| | - Louisa Jorm
- Centre for Big Data Research in Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Arcot Sowmya
- School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, Australia
| | - Daniel Moses
- School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, Australia
- Department of Medical Imaging, The Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Sze-Yuan Ooi
- Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
- Cardiology Department, The Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Susann Beier
- School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia
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28
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Al Rifai M, Ahmed AI, Al-Mallah MH. Evaluating coronary atherosclerosis progression among South Asians. Atherosclerosis 2022; 353:30-32. [PMID: 35753821 DOI: 10.1016/j.atherosclerosis.2022.06.1016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 06/09/2022] [Accepted: 06/14/2022] [Indexed: 11/15/2022]
Affiliation(s)
- Mahmoud Al Rifai
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
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Winkel DJ, Suryanarayana VR, Ali AM, Görich J, Buß SJ, Mendoza A, Schwemmer C, Sharma P, Schoepf UJ, Rapaka S. Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre dataset. Eur Heart J Cardiovasc Imaging 2022; 23:846-854. [PMID: 34322693 DOI: 10.1093/ehjci/jeab119] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 05/26/2021] [Indexed: 12/24/2022] Open
Abstract
AIMS To present and validate a fully automated, deep learning (DL)-based branch-wise coronary artery calcium (CAC) scoring algorithm on a multi-centre dataset. METHODS AND RESULTS We retrospectively included 1171 patients referred for a CAC computed tomography examination. Total CAC scores for each case were manually evaluated by a human reader. Next, each dataset was fully automatically evaluated by the DL-based software solution with output of the total CAC score and sub-scores per coronary artery (CA) branch [right coronary artery (RCA), left main (LM), left anterior descending (LAD), and circumflex (CX)]. Three readers independently manually scored the CAC for all CA branches for 300 cases from a single centre and formed the consensus using a majority vote rule, serving as the reference standard. Established CAC cut-offs for the total Agatston score were used for risk group assignments. The performance of the algorithm was evaluated using metrics for risk class assignment based on total Agatston score, and unweighted Cohen's Kappa for branch label assignment. The DL-based software solution yielded a class accuracy of 93% (1085/1171) with a sensitivity, specificity, and accuracy of detecting non-zero coronary calcium being 97%, 93%, and 95%. The overall accuracy of the algorithm for branch label classification was 94% (LM: 89%, LAD: 91%, CX: 93%, RCA: 100%) with a Cohen's kappa of k = 0.91. CONCLUSION Our results demonstrate that fully automated total and vessel-specific CAC scoring is feasible using a DL-based algorithm. There was a high agreement with the manually assessed total CAC from a multi-centre dataset and the vessel-specific scoring demonstrated consistent and reproducible results.
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Affiliation(s)
- David J Winkel
- Department of Radiology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland.,Siemens Healthineers, 755 College Rd E, 08540 Princeton, NJ, USA
| | | | - A Mohamed Ali
- Siemens Healthcare Private Limited, Unit No. 9A, 9th Floor, North Tower, Mumbai 400079, India
| | - Johannes Görich
- Das Radiologische Zentrum - Radiology Center, Sinsheim-Eberbach-Walldorf-Heidelberg, Germany
| | - Sebastian Johannes Buß
- Das Radiologische Zentrum - Radiology Center, Sinsheim-Eberbach-Walldorf-Heidelberg, Germany
| | - Axel Mendoza
- Siemens Healthineers, 755 College Rd E, 08540 Princeton, NJ, USA
| | - Chris Schwemmer
- Siemens Healthineers, Siemensstrasse 1, 91301 Forchheim, Germany
| | - Puneet Sharma
- Siemens Healthineers, 755 College Rd E, 08540 Princeton, NJ, USA
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, 29425 Charleston, SC, USA
| | - Saikiran Rapaka
- Siemens Healthineers, 755 College Rd E, 08540 Princeton, NJ, USA
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30
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Wang X, Chen X, Chen Z, Zhang M. Arterial Calcification and Its Association With Stroke: Implication of Risk, Prognosis, Treatment Response, and Prevention. Front Cell Neurosci 2022; 16:845215. [PMID: 35634461 PMCID: PMC9130460 DOI: 10.3389/fncel.2022.845215] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/28/2022] [Indexed: 01/07/2023] Open
Abstract
Stroke is a leading cause of death worldwide. Vascular calcification (VC), defined as deposition of calcium-phosphate complexes in the vessels, is considered as the characteristic of vascular aging. Calcifications at different vessel layers have different implications. Intimal calcification is closely related to atherosclerosis and affects plaque stability, while medial calcification can cause arterial stiffening and reduce compliance. Accumulating evidence suggested that arterial calcifications, including calcifications in the intracranial artery, coronary artery, and carotid artery, are associated with the risk, prognosis, and treatment response of stroke. VC can not only serve as a marker of atherosclerosis, but cause cerebral hemodynamic impairment. In addition, calcifications in large arteries are associated with cerebral small vessel disease. In this review, we summarize the findings of recently published studies focusing on the relationship between large artery calcification and the risk, prognosis, treatment response, and prevention of stroke and also discuss possible mechanisms behind those associations.
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Affiliation(s)
- Xiang Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xinghang Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Zhuohui Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Mengqi Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Mengqi Zhang,
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31
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Atkins KM, Weiss J, Zeleznik R, Bitterman DS, Chaunzwa TL, Huynh E, Guthier C, Kozono DE, Lewis JH, Tamarappoo BK, Nohria A, Hoffmann U, Aerts HJWL, Mak RH. Elevated Coronary Artery Calcium Quantified by a Validated Deep Learning Model From Lung Cancer Radiotherapy Planning Scans Predicts Mortality. JCO Clin Cancer Inform 2022; 6:e2100095. [PMID: 35084935 DOI: 10.1200/cci.21.00095] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Coronary artery calcium (CAC) quantified on computed tomography (CT) scans is a robust predictor of atherosclerotic coronary disease; however, the feasibility and relevance of quantitating CAC from lung cancer radiotherapy planning CT scans is unknown. We used a previously validated deep learning (DL) model to assess whether CAC is a predictor of all-cause mortality and major adverse cardiac events (MACEs). METHODS Retrospective analysis of non-contrast-enhanced radiotherapy planning CT scans from 428 patients with locally advanced lung cancer is performed. The DL-CAC algorithm was previously trained on 1,636 cardiac-gated CT scans and tested on four clinical trial cohorts. Plaques ≥ 1 cubic millimeter were measured to generate an Agatston-like DL-CAC score and grouped as DL-CAC = 0 (very low risk) and DL-CAC ≥ 1 (elevated risk). Cox and Fine and Gray regressions were adjusted for lung cancer and cardiovascular factors. RESULTS The median follow-up was 18.1 months. The majority (61.4%) had a DL-CAC ≥ 1. There was an increased risk of all-cause mortality with DL-CAC ≥ 1 versus DL-CAC = 0 (adjusted hazard ratio, 1.51; 95% CI, 1.01 to 2.26; P = .04), with 2-year estimates of 56.2% versus 45.4%, respectively. There was a trend toward increased risk of major adverse cardiac events with DL-CAC ≥ 1 versus DL-CAC = 0 (hazard ratio, 1.80; 95% CI, 0.87 to 3.74; P = .11), with 2-year estimates of 7.3% versus 1.2%, respectively. CONCLUSION In this proof-of-concept study, CAC was effectively measured from routinely acquired radiotherapy planning CT scans using an automated model. Elevated CAC, as predicted by the DL model, was associated with an increased risk of mortality, suggesting a potential benefit for automated cardiac risk screening before cancer therapy begins.
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Affiliation(s)
- Katelyn M Atkins
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA.,Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA
| | - Jakob Weiss
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Diagnostic and Interventional Radiology, University Hospital, Freiburg, Germany
| | - Roman Zeleznik
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Danielle S Bitterman
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Tafadzwa L Chaunzwa
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Elizabeth Huynh
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA
| | - Christian Guthier
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA
| | - David E Kozono
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA
| | - John H Lewis
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Anju Nohria
- Department of Cardiovascular Medicine, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA
| | - Udo Hoffmann
- Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands
| | - Raymond H Mak
- Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.,Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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32
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Winkelmann MT, Jacoby J, Schwemmer C, Faby S, Krumm P, Artzner C, Bongers MN. Fully Automated Artery-Specific Calcium Scoring Based on Machine Learning in Low-Dose Computed Tomography Screening. ROFO-FORTSCHR RONTG 2022; 194:763-770. [PMID: 35081651 DOI: 10.1055/a-1717-2703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
PURPOSE Evaluation of machine learning-based fully automated artery-specific coronary artery calcium (CAC) scoring software, using semi-automated software as a reference. METHODS A total of 505 patients underwent non-contrast-enhanced calcium scoring computed tomography (CSCT). Automated, machine learning-based software quantified the Agatston score (AS), volume score (VS), and mass score (MS) of each coronary artery [right coronary artery (RCA), left main (LM), circumflex (CX) and left anterior descending (LAD)]. Identified CAC of readers who annotated the data with semi-automated software served as a reference standard. Statistics included comparisons of evaluation time, agreement of identified CAC, and comparisons of the AS, VS, and MS of the reference standard and the fully automated algorithm. RESULTS The machine learning-based software correlated strongly with the reference standard for the AS, VS, and MS (Spearman's rho > 0.969) (p < 0.001), with excellent agreement (ICC > 0.919) (p < 0.001). The mean assessment time of the reference standard was 59 seconds (IQR 39-140) and that of the automated algorithm was 5.9 seconds (IQR 3.9-16) (p < 0.001). The Bland-Altman plots mean difference and 1.96 upper and lower limits of agreement for all arteries combined were: AS 0.996 (1.33 to 0.74), VS 0.995 (1.40 to 0.71), and MS 0.995 (1.35 to 0.74). The mean bias was minimal: 0.964-1.0429. Risk class assignment showed high accuracy for the AS in total (weighed κ = 0.99) and for each individual artery (κ = 0.96-0.99) with corresponding correct risk group assignment in 497 of 505 patients (98.4 %). CONCLUSION The fully automated artery-specific coronary calcium scoring algorithm is a time-saving procedure and shows excellent correlation and agreement compared with the clinically established semi-automated approach. KEY POINTS · Very high correlation and agreement between fully automatic and semi-automatic calcium scoring software.. · Less time-consuming than conventional semi-automatic methods.. · Excellent tool for artery-specific calcium scoring in a clinical setting.. CITATION FORMAT · Winkelmann MT, Jacoby J, Schwemmer C et al. Fully Automated Artery-Specific Calcium Scoring Based on Machine Learning in Low-Dose Computed Tomography Screening. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1717-2703.
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Affiliation(s)
- Moritz T Winkelmann
- Department for Diagnostic and Interventional Radiology, Eberhard Karls Universitat Tubingen, Tuebingen, Germany
| | - Johann Jacoby
- Institute of Clinical Epidemiology and Applied Biometry, Eberhard Karls Universitat Tubingen, Tuebingen, Germany
| | - Chris Schwemmer
- Siemens Healthcare GmbH, Forchheim, Siemens Healthcare GmbH, Forchheim, Germany
| | - Sebastian Faby
- Computed Tomography, Siemens Healthcare GmbH, Forchheim, Germany
| | - Patrick Krumm
- Department for Diagnostic and Interventional Radiology, Eberhard Karls Universitat Tubingen, Tuebingen, Germany
| | - Christoph Artzner
- Department for Diagnostic and Interventional Radiology, Eberhard Karls Universitat Tubingen, Tuebingen, Germany
| | - Malte N Bongers
- Department for Diagnostic and Interventional Radiology, Eberhard Karls Universitat Tubingen, Tuebingen, Germany
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33
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Zhao N, Gao Y, Xu B, Yang W, Song L, Jiang T, Xu L, Hu H, Li L, Chen W, Li D, Zhang F, Fan L, Lu B. Effect of Coronary Calcification Severity on Measurements and Diagnostic Performance of CT-FFR With Computational Fluid Dynamics: Results From CT-FFR CHINA Trial. Front Cardiovasc Med 2022; 8:810625. [PMID: 35047581 PMCID: PMC8761984 DOI: 10.3389/fcvm.2021.810625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 11/30/2021] [Indexed: 11/28/2022] Open
Abstract
Aims: To explore the effect of coronary calcification severity on the measurements and diagnostic performance of computed tomography-derived fractional flow reserve (FFR; CT-FFR). Methods: This study included 305 patients (348 target vessels) with evaluable coronary calcification (CAC) scores from CT-FFR CHINA clinical trial. The enrolled patients all received coronary CT angiography (CCTA), CT-FFR, and invasive FFR examinations within 7 days. On both per-patient and per-vessel levels, the measured values, accuracy, and diagnostic performance of CT-FFR in identifying hemodynamically significant lesions were analyzed in all CAC score groups (CAC = 0, > 0 to <100, ≥ 100 to <400, and ≥ 400), with FFR as reference standard. Results: In total, the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under receiver operating characteristics curve (AUC) of CT-FFR were 85.8, 88.7, 86.9, 87.8, 87.1%, 0.90 on a per-patient level and 88.3, 89.3, 89.5, 88.2, 88.9%, 0.88 on a per-vessel level, respectively. Absolute difference of CT-FFR and FFR values tended to elevate with increased CAC scores (CAC = 0: 0.09 ± 0.10; CAC > 0 to <100: 0.06 ± 0.06; CAC ≥ 100 to <400: 0.09 ± 0.10; CAC ≥ 400: 0.11 ± 0.13; p = 0.246). However, no statistically significant difference was found in patient-based and vessel-based diagnostic performance of CT-FFR among all CAC score groups. Conclusion: This prospective multicenter trial supported CT-FFR as a viable tool in assessing coronary calcified lesions. Although large deviation of CT-FFR has a tendency to correlate with severe calcification, coronary calcification has no significant influence on CT-FFR diagnostic performance using the widely-recognized cut-off value of 0.8.
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Affiliation(s)
- Na Zhao
- Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Gao
- Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Yang Gao
| | - Bo Xu
- Catheterization Laboratories, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Weixian Yang
- Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lei Song
- Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tao Jiang
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Li Xu
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lin Li
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenqiang Chen
- Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Dumin Li
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Feng Zhang
- Department of Cardiology, Teda International Cardiovascular Hospital, Tianjin, China
| | - Lijuan Fan
- Department of Radiology, Teda International Cardiovascular Hospital, Tianjin, China
| | - Bin Lu
- Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Bin Lu
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van Praagh GD, Wang J, van der Werf NR, Greuter MJW, Mastrodicasa D, Nieman K, van Hamersvelt RW, Oostveen LJ, de Lange F, Slart RHJA, Leiner T, Fleischmann D, Willemink MJ. Coronary Artery Calcium Scoring: Toward a New Standard. Invest Radiol 2022; 57:13-22. [PMID: 34261083 PMCID: PMC10072789 DOI: 10.1097/rli.0000000000000808] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Although the Agatston score is a commonly used quantification method, rescan reproducibility is suboptimal, and different CT scanners result in different scores. In 2007, McCollough et al (Radiology 2007;243:527-538) proposed a standard for coronary artery calcium quantification. Advancements in CT technology over the last decade, however, allow for improved acquisition and reconstruction methods. This study aims to investigate the feasibility of a reproducible reduced dose alternative of the standardized approach for coronary artery calcium quantification on state-of-the-art CT systems from 4 major vendors. MATERIALS AND METHODS An anthropomorphic phantom containing 9 calcifications and 2 extension rings were used. Images were acquired with 4 state-of-the-art CT systems using routine protocols and a variety of tube voltages (80-120 kV), tube currents (100% to 25% dose levels), slice thicknesses (3/2.5 and 1/1.25 mm), and reconstruction techniques (filtered back projection and iterative reconstruction). Every protocol was scanned 5 times after repositioning the phantom to assess reproducibility. Calcifications were quantified as Agatston scores. RESULTS Reducing tube voltage to 100 kV, dose to 75%, and slice thickness to 1 or 1.25 mm combined with higher iterative reconstruction levels resulted in an on average 36% lower intrascanner variability (interquartile range) compared with the standard 120 kV protocol. Interscanner variability per phantom size decreased by 34% on average. With the standard protocol, on average, 6.2 ± 0.4 calcifications were detected, whereas 7.0 ± 0.4 were detected with the proposed protocol. Pairwise comparisons of Agatston scores between scanners within the same phantom size demonstrated 3 significantly different comparisons at the standard protocol (P < 0.05), whereas no significantly different comparisons arose at the proposed protocol (P > 0.05). CONCLUSIONS On state-of-the-art CT systems of 4 different vendors, a 25% reduced dose, thin-slice calcium scoring protocol led to improved intrascanner and interscanner reproducibility and increased detectability of small and low-density calcifications in this phantom. The protocol should be extensively validated before clinical use, but it could potentially improve clinical interscanner/interinstitutional reproducibility and enable more consistent risk assessment and treatment strategies.
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Affiliation(s)
| | - Jia Wang
- Department of Environmental Health and Safety, Stanford University, Stanford CA
| | | | | | | | | | | | - Luuk J Oostveen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen
| | - Frank de Lange
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen
| | | | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht
| | | | - Martin J Willemink
- From the Department of Radiology, Stanford University School of Medicine, Stanford, CA
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Chen W, Li H, Lu Z, Guo Q, Liu X, Sun R, Zhang J, Huang J, Chen Q, Wang J, Shen J, Zhang Y. The ratio of the max-to-mean coronary artery calcium score in the most calcified vessel is associated with the presence of coronary artery disease. Eur J Radiol 2021; 147:110134. [PMID: 34979296 DOI: 10.1016/j.ejrad.2021.110134] [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: 08/24/2021] [Revised: 12/18/2021] [Accepted: 12/24/2021] [Indexed: 11/17/2022]
Abstract
PURPOSE This study aimed to clarify the relationship between the severity of the calcium burden in the most calcified coronary vessel and coronary artery disease (CAD). METHOD Of 2150 patients, 376 examined by both coronary computed tomographic angiography and invasive coronary angiography (ICA) within 30 days at Sun Yat-sen Memorial Hospital between March 2011 and July 2020 were included. Three coronary artery calcium scores (CACSs), including the Agatston score, volume score, and mass score, and other clinical variables were recorded. The ratio of max-to-mean CACS in the most calcified vessel (CACSmax:mean) was defined as the CACS in the most calcified vessel/average CACS of the four major epicardial coronary arteries. Logistic regression and least absolute shrinkage and selection operator (LASSO) analyses were performed to assess the relationship between CACSmax:mean and CAD. RESULTS CACSmax:mean was higher in 81.1% of subjects diagnosed with CAD than in subjects without CAD. In multivariate logistic regression analysis, CACSmax:mean determined by the Agatston score, volumetric score, and mass score was associated with CAD. In LASSO analysis, Agatston scoremax:mean (not the total Agatston score or other CACSmax:mean) had the strongest correlation with CAD (β = 0.125). AUCs in the training set and the validation set were 0.811 and 0.789, respectively. Increased age, diabetes and hypertension correlated with higher Agatston scoremax:mean. CONCLUSIONS In addition to total CACS, CACSmax:mean may be a novel diagnostic parameter for CAD, showing the calcium burden severity.
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Affiliation(s)
- Wenya Chen
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Hongwei Li
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Zhijiao Lu
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China
| | - Qi Guo
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Xiao Liu
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Runlu Sun
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Jie Zhang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Jingjing Huang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Qian Chen
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Junjie Wang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China
| | - Jun Shen
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China.
| | - Yuling Zhang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China.
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36
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Blaha MJ, Dzaye O. Subthreshold coronary artery calcium - Redefining the coronary artery calcium score of zero? J Cardiovasc Comput Tomogr 2021; 16:155-157. [PMID: 34862148 DOI: 10.1016/j.jcct.2021.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 11/12/2021] [Indexed: 11/28/2022]
Affiliation(s)
- Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, USA.
| | - Omar Dzaye
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, USA
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37
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Zheng J, Lu B. Current Progress of Studies of Coronary CT for Risk Prediction of Major Adverse Cardiovascular Event (MACE). J Cardiovasc Imaging 2021; 29:301-315. [PMID: 34719895 PMCID: PMC8592676 DOI: 10.4250/jcvi.2021.0016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 05/16/2021] [Accepted: 05/31/2021] [Indexed: 11/22/2022] Open
Abstract
Cardiovascular disease is a serious threat to human health, and early risk prediction of major adverse cardiovascular event in people suspected of coronary heart disease can help guide prevention and clinical decisions. Coronary computed tomography (CT) is a useful imaging tool for evaluation of coronary heart disease, and its ability to reflect coronary atherosclerosis shows potential value for risk prediction. In recent years, various new techniques and studies of coronary CT have emerged for risk prediction of major adverse cardiovascular event in people suspected of coronary heart disease. We will review the background and current study advances of using coronary artery calcium score, coronary CT angiography, and artificial intelligence in this field.
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Affiliation(s)
- Jianan Zheng
- Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bin Lu
- Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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38
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Graby J, Khavandi A, Thompson D, Downie P, Antoniades C, Rodrigues JCL. CT coronary angiography-guided cardiovascular risk screening in asymptomatic patients: is it time? Clin Radiol 2021; 76:801-811. [PMID: 34404515 DOI: 10.1016/j.crad.2021.07.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/13/2021] [Indexed: 12/14/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death in the UK, whilst millions live with various forms of the disease. Coronary artery disease constitutes a significant portion of this morbidity and mortality, and is the leading cause of premature death. Increasing focus is thus being placed on the optimisation of CVD prevention, where risk screening plays a key role. Indeed, the decline in age-adjusted cardiovascular mortality achieved up to now has been largely attributed to primary preventative therapies (e.g., statins) introduced earlier in the disease process. National initiatives exist to improve cardiovascular health at a population level, but in its current form, CVD screening at the individual level is predominantly undertaken using multivariate risk scores based on population-based data. These have multiple innate flaws, highlighted in this review. Non-invasive imaging plays a key role in the screening of other disease processes, helping to personalise the screening process. Although the coronary artery calcium score as a screening tool has a role in national and international guidance, whether a shift to screening with computed tomography coronary angiography (CTCA) is now appropriate is open for discussion. Image acquisition techniques continue to improve with reducing radiation exposure and an ever-expanding evidence-base for additional prognostic data offered by CTCA. This enables the potential identification of sub-clinical atherosclerosis, including with novel artificial intelligence techniques. This review aims to report current guidelines regarding cardiac CT imaging in the asymptomatic primary prevention setting, advances in various CT technologies and future opportunities for progress in this field.
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Affiliation(s)
- J Graby
- Department of Cardiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK; Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK
| | - A Khavandi
- Department of Cardiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK
| | - D Thompson
- Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK
| | - P Downie
- Department of Laboratory Medicine, Salisbury District Hospital, Odstock Road, Salisbury, SP2 8BJ, UK
| | - C Antoniades
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
| | - J C L Rodrigues
- Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK; Department of Radiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK.
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Trab T, Attar R, Jensen SE, Grøntved S, Frøkjær JB, Polcwiartek C, Nielsen RE. Coronary artery calcium in patients with schizophrenia. BMC Psychiatry 2021; 21:422. [PMID: 34425769 PMCID: PMC8381587 DOI: 10.1186/s12888-021-03412-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 08/03/2021] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Coronary heart disease (CHD) is a major cause of increased mortality rates in patients with schizophrenia. Moreover, coronary artery calcium (CAC) score is associated with CHD. We hypothesized that patients with schizophrenia have more CAC than the general population and aimed to investigate the CAC score in patients with schizophrenia compared to norms based on the general population. Additionally, this study investigated if age, sex, diabetes, dyslipidemia and smoking were associated with the CAC score. METHODS In a cross-sectional study, 163 patients with schizophrenia underwent cardiac computed tomography, and the CAC score was measured and compared to norms by classifying the CAC scores in relation to the age- and gender matched norm 50th, 75th and 90th percentiles. Logistic and linear regression were carried out to investigate explanatory variables for the presence and extent of CAC, respectively. RESULTS A total of 127 (77.9%) patients had a CAC score below or equal to the matched 50th, 20 (12.3%) above the 75th and nine (5.5%) above the 90th percentile. Male sex (P < 0.05), age (P < 0.001) and smoking (P < 0.05) were associated with the presence of CAC while age (P < 0.001) and diabetes (P < 0.01) were associated with the extent of CAC. CONCLUSIONS The amount of CAC in patients with schizophrenia follows norm percentiles, and variables associated with the CAC score are similar in patients with schizophrenia and the general population. These findings indicate that the CAC score may not be sufficient to detect the risk of CHD in patients with schizophrenia. Future studies should explore other measures of subclinical CHD, including measures of peripheral atherosclerosis or cardiac autonomic neuropathy to improve early detection and intervention. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02885792 , September 1, 2016.
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Affiliation(s)
- Trine Trab
- Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark.
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark.
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
| | - Rubina Attar
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Svend Eggert Jensen
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Simon Grøntved
- Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
| | - Jens Brøndum Frøkjær
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
- Department of Radiology, Aalborg University Hospital, Aalborg, Denmark
| | | | - René Ernst Nielsen
- Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
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40
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Mortensen MB, Blaha MJ. Is There a Role of Coronary CTA in Primary Prevention? Current State and Future Directions. Curr Atheroscler Rep 2021; 23:44. [PMID: 34146160 DOI: 10.1007/s11883-021-00943-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/17/2021] [Indexed: 01/19/2023]
Abstract
PURPOSE OF REVIEW Information on subclinical atherosclerosis burden provides prognostic information on atherosclerotic cardiovascular disease (ASCVD) risk beyond what can be achieved by traditional risk factors alone and may therefore improve allocation of preventive treatment in primary prevention. The purpose of this review is to discuss the potential role and value of assessing subclinical atherosclerosis using coronary artery calcium (CAC) versus computed tomography angiography (CTA) among asymptomatic patients in the context of current primary prevention cholesterol guidelines. RECENT FINDINGS Since 2013, primary prevention cholesterol guidelines have lowered the treatment threshold for initiating statin therapy resulting in high statin eligibility and sensitivity for detecting ASCVD events. Thus, one of the main advantages of assessing subclinical atherosclerosis is to identify those individuals who are at so low ASCVD risk that preventive treatment may safely be withhold. Numerous studies have shown that both CAC and CTA provide highly valuable information on ASCVD risk in the individual patient. However, while extensive data exist regarding the ability of CAC to improve treatment allocation in the context of primary prevention guidelines, such data is sparse for CTA. Furthermore, there is no data to show that CTA improves risk classification and treatment allocation in primary prevention beyond what can be achieved by assessment of CAC. Although CTA provides important information regarding prognosis in symptomatic patients undergoing clinical CTA, there is no strong evidence to support its use in the primary prevention setting. Thus, the potential value of CTA in primary prevention is not clear and is currently not recommended by guidelines.
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Affiliation(s)
- Martin Bødtker Mortensen
- Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard, 8200, Aarhus N, Denmark. .,Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD, USA.
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD, USA
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41
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Influence of coronary dominance on coronary artery calcification burden. Clin Imaging 2021; 77:283-286. [PMID: 34171741 DOI: 10.1016/j.clinimag.2021.06.008] [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: 02/21/2021] [Revised: 05/29/2021] [Accepted: 06/06/2021] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To evaluate the influence of coronary artery dominance on observed coronary artery calcification burden in outpatients presenting for coronary computed tomography angiography (CCTA). METHODS A 12-month retrospective review was performed of all CCTAs at a single institution. Coronary arterial dominance, Agatston score and presence or absence of cardiovascular risk factors including hypertension (HTN), hyperlipidemia (HLD), diabetes and smoking were recorded. Dominance groups were compared in terms of calcium score adjusted for covariates using analysis of covariance based on ranks. Only covariates observed to be significant independent predictors of the relevant outcome were included in each analysis. All statistical tests were conducted at the two-sided 5% significance level. RESULTS 1223 individuals, 618 women and 605 men were included, mean age 60 years (24-93 years). Right coronary dominance was observed in 91.7% (n = 1109), left dominance in 8% (n = 98), and codominance in 1.3% (n = 16). The distribution of patients among Agatston score severity categories significantly differed between codominant and left (p = 0.008), and codominant and right (p = 0.022) groups, with higher prevalence of either zero or severe CAC in the codominant patients. There was no significant difference in Agatston score between dominance groups. In the subset of individuals with coronary artery calcification, Agatston score was significantly higher in codominant versus left dominant patients (mean Agatston score 595 ± 520 vs. mean 289 ± 607, respectively; p = 0.049), with a trend towards higher scores in comparison to the right-dominant group (p = 0.093). Significance was not maintained upon adjustment for covariates. CONCLUSIONS While the distribution of Agatston score severity categories differed in codominant versus right- or left-dominant patients, there was no significant difference in Agatston score based on coronary dominance pattern in our cohort. Reporting and inclusion of codominant subsets in larger investigations may elucidate whether codominant anatomy is associated with differing risk.
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Marlevi D, Edelman ER. Vascular Lesion-Specific Drug Delivery Systems: JACC State-of-the-Art Review. J Am Coll Cardiol 2021; 77:2413-2431. [PMID: 33985687 PMCID: PMC8238531 DOI: 10.1016/j.jacc.2021.03.307] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/08/2021] [Accepted: 03/21/2021] [Indexed: 01/15/2023]
Abstract
Drug delivery is central to modern cardiovascular care, where drug-eluting stents, bioresorbable scaffolds, and drug-coated balloons all aim to restore perfusion while inhibiting exuberant healing. The promise and enthusiasm of these devices has in some cases exceeded demonstration of efficacy and even understanding of driving mechanisms. The authors review the means of drug delivery in each device, outlining how the technologies affect vascular behavior. They focus on how drug retention and response are governed by lesion morphology: lipid displacing drug-specific binding sites, calcium inhibiting diffusion, blocking thrombi or promoting luminal washout, and vascular healing steering hyperplastic developments. In this regard, the authors outline the fundamental impact of vascular structure on drug delivery and review the development of contemporary and future devices for coronary and peripheral intervention. They look toward a future where incorporating information on lesion distribution is central to therapeutic success and envision a transition toward lesion-specific treatment for improved interventional outcomes.
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Affiliation(s)
- David Marlevi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
| | - Elazer R Edelman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
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de Vos BD, Lessmann N, de Jong PA, Išgum I. Deep Learning-Quantified Calcium Scores for Automatic Cardiovascular Mortality Prediction at Lung Screening Low-Dose CT. Radiol Cardiothorac Imaging 2021; 3:e190219. [PMID: 33969304 DOI: 10.1148/ryct.2021190219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 01/05/2021] [Accepted: 01/20/2021] [Indexed: 01/06/2023]
Abstract
Purpose To examine the prognostic value of location-specific arterial calcification quantities at lung screening low-dose CT for the prediction of cardiovascular disease (CVD) mortality. Materials and Methods This retrospective study included 5564 participants who underwent low-dose CT from the National Lung Screening Trial between August 2002 and April 2004, who were followed until December 2009. A deep learning network was trained to quantify six types of vascular calcification: thoracic aorta calcification (TAC); aortic and mitral valve calcification; and coronary artery calcification (CAC) of the left main, the left anterior descending, and the right coronary artery. TAC and CAC were determined in six evenly distributed slabs spatially aligned among chest CT images. CVD mortality prediction was performed with multivariable logistic regression using least absolute shrinkage and selection operator. The methods were compared with semiautomatic baseline prediction using self-reported participant characteristics, such as age, history of smoking, and history of illness. Statistical significance between the prediction models was tested using the nonparametric DeLong test. Results The prediction model was trained with data from 4451 participants (median age, 61 years; 37.9% women) and then tested on data from 1113 participants (median age, 61 years; 37.9% women). The prediction model using calcium scores achieved a C statistic of 0.74 (95% CI: 0.69, 0.79), and it outperformed the baseline model using only participant characteristics (C statistic, 0.69; P = .049). Best results were obtained when combining all variables (C statistic, 0.76; P < .001). Conclusion Five-year CVD mortality prediction using automatically extracted image-based features is feasible at lung screening low-dose CT.© RSNA, 2021.
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Affiliation(s)
- Bob D de Vos
- Department of Biomedical Engineering and Physics (B.D.d.V., I.I.), Cardiovascular Institute (B.D.d.V., I.I.), and Department of Radiology and Nuclear Medicine (I.I.), Amsterdam University Medical Center, Meibergdreef 9, Amsterdam, the Netherlands; and Image Sciences Institute (B.D.d.V., N.L., I.I.) and Department of Radiology (P.A.d.J., I.I.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Nikolas Lessmann
- Department of Biomedical Engineering and Physics (B.D.d.V., I.I.), Cardiovascular Institute (B.D.d.V., I.I.), and Department of Radiology and Nuclear Medicine (I.I.), Amsterdam University Medical Center, Meibergdreef 9, Amsterdam, the Netherlands; and Image Sciences Institute (B.D.d.V., N.L., I.I.) and Department of Radiology (P.A.d.J., I.I.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Pim A de Jong
- Department of Biomedical Engineering and Physics (B.D.d.V., I.I.), Cardiovascular Institute (B.D.d.V., I.I.), and Department of Radiology and Nuclear Medicine (I.I.), Amsterdam University Medical Center, Meibergdreef 9, Amsterdam, the Netherlands; and Image Sciences Institute (B.D.d.V., N.L., I.I.) and Department of Radiology (P.A.d.J., I.I.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Ivana Išgum
- Department of Biomedical Engineering and Physics (B.D.d.V., I.I.), Cardiovascular Institute (B.D.d.V., I.I.), and Department of Radiology and Nuclear Medicine (I.I.), Amsterdam University Medical Center, Meibergdreef 9, Amsterdam, the Netherlands; and Image Sciences Institute (B.D.d.V., N.L., I.I.) and Department of Radiology (P.A.d.J., I.I.), University Medical Center Utrecht, Utrecht, the Netherlands
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Chamberlin J, Kocher MR, Waltz J, Snoddy M, Stringer NFC, Stephenson J, Sahbaee P, Sharma P, Rapaka S, Schoepf UJ, Abadia AF, Sperl J, Hoelzer P, Mercer M, Somayaji N, Aquino G, Burt JR. Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value. BMC Med 2021; 19:55. [PMID: 33658025 PMCID: PMC7931546 DOI: 10.1186/s12916-021-01928-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 01/26/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be demonstrated in the context of current screening modalities. Here, we present findings on the performance of an AI convolutional neural network (CNN) prototype (AI-RAD Companion, Siemens Healthineers) that automatically detects pulmonary nodules and quantifies coronary artery calcium volume (CACV) on low-dose chest CT (LDCT), and compare results to expert radiologists. We also correlate AI findings with adverse cardiopulmonary outcomes in a retrospective cohort of 117 patients who underwent LDCT. METHODS A total of 117 patients were enrolled in this study. Two CNNs were used to identify lung nodules and CACV on LDCT scans. All subjects were used for lung nodule analysis, and 96 subjects met the criteria for coronary artery calcium volume analysis. Interobserver concordance was measured using ICC and Cohen's kappa. Multivariate logistic regression and partial least squares regression were used for outcomes analysis. RESULTS Agreement of the AI findings with experts was excellent (CACV ICC = 0.904, lung nodules Cohen's kappa = 0.846) with high sensitivity and specificity (CACV: sensitivity = .929, specificity = .960; lung nodules: sensitivity = 1, specificity = 0.708). The AI findings improved the prediction of major cardiopulmonary outcomes at 1-year follow-up including major adverse cardiac events and lung cancer (AUCMACE = 0.911, AUCLung Cancer = 0.942). CONCLUSION We conclude the AI prototype rapidly and accurately identifies significant risk factors for cardiopulmonary disease on standard screening low-dose chest CT. This information can be used to improve diagnostic ability, facilitate intervention, improve morbidity and mortality, and decrease healthcare costs. There is also potential application in countries with limited numbers of cardiothoracic radiologists.
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Affiliation(s)
- Jordan Chamberlin
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Madison R Kocher
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Jeffrey Waltz
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Madalyn Snoddy
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Natalie F C Stringer
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Joseph Stephenson
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | | | | | | | - U Joseph Schoepf
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Andres F Abadia
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | | | | | - Megan Mercer
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Nayana Somayaji
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Gilberto Aquino
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA
| | - Jeremy R Burt
- Department of Radiology, Medical University of South Carolina, Charleston, SC, 29403, USA.
- MUSC-ART, Cardiothoracic Imaging, 25 Courtenay Drive, MSC 226, 2nd Floor, Rm 2256, Charleston, SC, 29425, USA.
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45
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Cheong BYC, Wilson JM, Spann SJ, Pettigrew RI, Preventza OA, Muthupillai R. Coronary artery calcium scoring: an evidence-based guide for primary care physicians. J Intern Med 2021; 289:309-324. [PMID: 33016506 DOI: 10.1111/joim.13176] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 08/24/2020] [Indexed: 12/12/2022]
Abstract
Primary care physicians often must decide whether statin therapy would be appropriate (in addition to lifestyle modification) for managing asymptomatic individuals with borderline or intermediate risk for developing atherosclerotic cardiovascular disease (ASCVD), as assessed on the basis of traditional risk factors. In appropriate subjects, a simple, noninvasive measurement of coronary artery calcium can help clarify risk. Coronary atherosclerosis is a chronic inflammatory disease, with atherosclerotic plaque formation involving intimal inflammation and repeated cycles of erosion and fibrosis, healing and calcification. Atherosclerotic plaque formation represents the prognostic link between risk factors and future clinical events. The presence of coronary artery calcification is almost exclusively an indication of coronary artery disease, except in certain metabolic conditions. Coronary artery calcification can be detected and quantified in a matter of seconds by noncontrast electrocardiogram-gated low-dose X-ray computed tomography (coronary artery calcium scoring [CACS]). Since the publication of the seminal work by Dr. Arthur Agatston in 1990, a wealth of CACS-based prognostic data has been reported. In addition, recent guidelines from various professional societies conclude that CACS may be considered as a tool for reclassifying risk for atherosclerotic cardiovascular disease in patients otherwise assessed to have intermediate risk, so as to more accurately inform decisions about possible statin therapy in addition to lifestyle modification as primary preventive therapy. In this review, we provide an overview of CACS, from acquisition to interpretation, and summarize the scientific evidence for and the appropriate use of CACS as put forth in current clinical guidelines.
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Affiliation(s)
- B Y C Cheong
- From the, Department of Cardiovascular Radiology, Texas Heart Institute, Houston, TX, USA.,Department of Diagnostic and Interventional Radiology, CHI St. Luke's Health-Baylor St. Luke's Medical Center, Houston, TX, USA.,Department of Cardiology, CHI St. Luke's Health-Baylor St. Luke's Medical Center, Houston, TX, USA
| | - J M Wilson
- Department of Cardiology, HCA Houston Healthcare Medical Center, Houston, TX, USA
| | - S J Spann
- The University of Houston College of Medicine, Houston, TX, USA
| | - R I Pettigrew
- College of Medicine and Department of Biomedical Engineering, Texas A&M University, Houston, TX, USA
| | - O A Preventza
- Division of Cardiothoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA.,Department of Cardiovascular Surgery, Texas Heart Institute, Houston, TX, USA
| | - R Muthupillai
- From the, Department of Cardiovascular Radiology, Texas Heart Institute, Houston, TX, USA.,Department of Diagnostic and Interventional Radiology, CHI St. Luke's Health-Baylor St. Luke's Medical Center, Houston, TX, USA
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46
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Liu H, Wingert A, Wang J, Zhang J, Wang X, Sun J, Chen F, Khalid SG, Jiang J, Zheng D. Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods. Front Cardiovasc Med 2021; 8:597568. [PMID: 33644127 PMCID: PMC7903898 DOI: 10.3389/fcvm.2021.597568] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 01/18/2021] [Indexed: 12/21/2022] Open
Abstract
Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.
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Affiliation(s)
- Haipeng Liu
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.,Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Aleksandra Wingert
- Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Jian'an Wang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jucheng Zhang
- Department of Clinical Engineering, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xinhong Wang
- Department of Radiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Syed Ghufran Khalid
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
| | - Jun Jiang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
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47
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End-to-End, Pixel-Wise Vessel-Specific Coronary and Aortic Calcium Detection and Scoring Using Deep Learning. Diagnostics (Basel) 2021; 11:diagnostics11020215. [PMID: 33540660 PMCID: PMC7913112 DOI: 10.3390/diagnostics11020215] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/28/2021] [Accepted: 01/28/2021] [Indexed: 01/08/2023] Open
Abstract
Conventional scoring and identification methods for coronary artery calcium (CAC) and aortic calcium (AC) result in information loss from the original image and can be time-consuming. In this study, we sought to demonstrate an end-to-end deep learning model as an alternative to the conventional methods. Scans of 377 patients with no history of coronary artery disease (CAD) were obtained and annotated. A deep learning model was trained, tested and validated in a 60:20:20 split. Within the cohort, mean age was 64.2 ± 9.8 years, and 33% were female. Left anterior descending, right coronary artery, left circumflex, triple vessel, and aortic calcifications were present in 74.87%, 55.82%, 57.41%, 46.03%, and 85.41% of patients respectively. An overall Dice score of 0.952 (interquartile range 0.921, 0.981) was achieved. Stratified by subgroups, there was no difference between male (0.948, interquartile range 0.920, 0.981) and female (0.965, interquartile range 0.933, 0.980) patients (p = 0.350), or, between age <65 (0.950, interquartile range 0.913, 0.981) and age ≥65 (0.957, interquartile range 0.930, 0.9778) (p = 0.742). There was good correlation and agreement for CAC prediction (rho = 0.876, p < 0.001), with a mean difference of 11.2% (p = 0.100). AC correlated well (rho = 0.947, p < 0.001), with a mean difference of 9% (p = 0.070). Automated segmentation took approximately 4 s per patient. Taken together, the deep-end learning model was able to robustly identify vessel-specific CAC and AC with high accuracy, and predict Agatston scores that correlated well with manual annotation, facilitating application into areas of research and clinical importance.
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48
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Orringer CE, Blaha MJ, Blankstein R, Budoff MJ, Goldberg RB, Gill EA, Maki KC, Mehta L, Jacobson TA. The National Lipid Association scientific statement on coronary artery calcium scoring to guide preventive strategies for ASCVD risk reduction. J Clin Lipidol 2021; 15:33-60. [PMID: 33419719 DOI: 10.1016/j.jacl.2020.12.005] [Citation(s) in RCA: 112] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 12/21/2022]
Abstract
An Expert Panel of the National Lipid Association reviewed the evidence related to the use of coronary artery calcium (CAC) scoring in clinical practice for adults seen for primary prevention of atherosclerotic cardiovascular disease. Recommendations for optimal use of this test in adults of various races/ethnicities, ages and multiple domains of primary prevention, including those with a 10-year ASCVD risk <20%, those with diabetes or the metabolic syndrome, and those with severe hypercholesterolemia were provided. Recommendations were also made on optimal timing for repeat calcium scoring after an initial test, use of CAC scoring in those taking statins, and its role in informing the clinician patient discussion on the benefit of aspirin and anti-hypertensive drug therapy. Finally, a vision is provided for the future of coronary calcium scoring.
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Affiliation(s)
- Carl E Orringer
- University of Miami, Miller School of Medicine, Cardiovascular Division.
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease
| | - Ron Blankstein
- Brigham and Women's Hospital, Harvard Medical School, Cardiovascular Division
| | | | - Ronald B Goldberg
- Diabetes Research Institute, University of Miami Miller School of Medicine
| | - Edward A Gill
- University of Colorado School of Medicine, Anschutz Campus
| | - Kevin C Maki
- Department of Applied Health Science, School of Public Health, and Midwest Biomedical Research, Indiana University
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49
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Al Rifai M, Kanaya AM, Kandula NR, Cainzos-Achirica M, Patel J, Budoff M, Criqui MH, Blaha MJ, Virani SS. Distribution of calcium volume, density, number, and type of coronary vessel with calcified plaque in South Asians in the US and other race/ethnic groups: The MASALA and MESA studies. Atherosclerosis 2021; 317:16-21. [PMID: 33333344 PMCID: PMC7790973 DOI: 10.1016/j.atherosclerosis.2020.12.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/26/2020] [Accepted: 12/02/2020] [Indexed: 01/12/2023]
Abstract
BACKGROUND AND AIMS South Asians (SA) experience disproportionately higher rates of atherosclerotic cardiovascular disease (ASCVD) events than non-Hispanic whites (NHW) and several other Asian groups. The coronary artery calcium (CAC) Agatston score may not capture the unique characteristics of coronary plaque in SA. We therefore evaluated the prevalence and patterns of advanced CAC measures (specific coronary vessel involvement, CAC volume and density) in SA versus other race/ethnicities. METHODS We combined data from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) and Multi-Ethnic Study of Atherosclerosis (MESA) cohorts. We used multivariable-adjusted linear regression models to compare advanced CAC measures between SA and other ethnicities. RESULTS Our analyses included 7,625 individuals (810 SA, 2,622 whites, 1,893 African Americans, 1,496 Hispanics, 803 Chinese Americans) with mean (SD) age 62 (10) years and 48% men. In adjusted analyses, compared to NHW, SA had lower overall CAC volume [beta coefficient (95% CI)] [-0.46 (-0.62,-0.29)] but higher overall CAC density [0.14 (0.11,0.18)]. These trends were similar when SA were compared to non-whites (Hispanics, Chinese Americans, and African Americans). SA had higher overall [0.07 (0.03,0.12)] and right coronary artery [0.09 (0.03,0.16)] CAC density compared to non-whites, while CAC volume was not significantly different between these two groups. CONCLUSIONS SA have lower CAC volume compared to NHW but similar compared to non-whites. Overall CAC density is higher among SA compared to NHW and non-whites. Future longitudinal studies of ASCVD events are required to confirm the prognostic significance of these findings among SA.
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Affiliation(s)
- Mahmoud Al Rifai
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Alka M Kanaya
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Namratha R Kandula
- Feinberg School of Medicine, Division of General Internal Medicine, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Miguel Cainzos-Achirica
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, USA; Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Jaideep Patel
- Heart Center, Division of Cardiology, Virginia Commonwealth University Medical Center, Richmond, VA, USA
| | - Matthew Budoff
- Division of Cardiology, Los Angeles Biomedical Research Institute, Torrance, CA, USA
| | - Michael H Criqui
- Division of Preventive Medicine, Department of Family Medicine and Public Health, USA; University of California, San Diego School of Medicine, CA, USA
| | - Michael J Blaha
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, USA; Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Salim S Virani
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA; Division of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center and Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
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50
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Lipinski J, Margevicius S, Schluchter MD, Wilson DL, McComsey GA, Longenecker CT. Statin effect on coronary calcium distribution, mass and volume scores and associations with immune activation among HIV+ persons on antiretroviral therapy. Antivir Ther 2021; 25:419-427. [PMID: 33901017 DOI: 10.3851/imp3389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/15/2020] [Indexed: 10/21/2022]
Abstract
BACKGROUND Inflammation has been associated with whole heart coronary artery calcification (CAC) among people with HIV (PWH) on antiretroviral therapy (ART); however, prior studies have not evaluated the distribution of calcium or separated mass versus volume scores, which are differentially associated with clinical events in the general population. Statins may also have a greater effect on CAC mass compared with volume. METHODS 147 PWH were randomized 1:1 to rosuvastatin 10 mg or placebo and followed for 96 weeks. We re-analysed coronary calcium scans from 0, 48 and 96 weeks to determine mass and volume scores and measures of CAC diffusivity. Mixed effects models and generalized estimating equations were used to examine longitudinal associations of CAC with treatment and biomarkers. RESULTS Median age at study entry was 46 years; 78% were male and 68% African American. Median CD4+ was 613 and half were on protease inhibitors. Randomization to statin therapy was not associated with a change in mass score, volume score, number of involved vessels or diffusivity index (all P>0.1). Soluble CD14 was associated with the presence of CAC (P=0.05) and borderline associated with number of involved vessels (P=0.07) across all three time points. CONCLUSIONS In PWH on ART, moderate intensity rosuvastatin does not appear to have a significant effect on volume, mass or regional distribution of CAC over 96 weeks. We extend previous cross-sectional observations to show that soluble CD14 is associated with whole heart CAC over time and independently of age and systolic blood pressure.
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Affiliation(s)
- Jerry Lipinski
- Department of Internal Medicine, University of California, San Diego, San Diego, CA, USA
| | | | - Mark D Schluchter
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - David L Wilson
- Case Western Reserve University School of Engineering, Cleveland, OH, USA
| | - Grace A McComsey
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA.,University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Chris T Longenecker
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA.,University Hospitals Cleveland Medical Center, Cleveland, OH, USA
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