Relationships between Left circumflex artery (LCX) and Left anterior descending (LAD) involvements and calcification in patients with Coronary heart disease(CHD): a cross-sectional study

Relationships between Left circumflex artery (LCX) and Left anterior descending (LAD) involvements and calcification in patients with Coronary heart disease(CHD): a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationships between Left circumflex artery (LCX) and Left anterior descending (LAD) involvements and calcification in patients with Coronary heart disease(CHD): a cross-sectional study Sara Hassani, Mobin Azami, Bahador Asadi, Aryobarzan Rahmatian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2248580/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study aimed to investigate the relationships between LM, LAD, and LCX lesions and calcification in patients referred to Imam Khomeini Hospital, Medical, and Research center (Tehran, Iran). Methods The present study was an applied, cross-sectional, and observational study conducted on hospitalized patients suffering from coronary heart disease (CHD). By non-random sampling, 50 CHD patients who met the inclusion criteria were selected. CT angiography and MRI results were investigated, and field data collected by checklists were analyzed in IBM SPSS Statistics v. 13.00. Results There was no relationship between LM involvement and calcification, with 80% sensitivity and 44% specificity in the diagnosis of LM involvement. By contrast, LAD involvement was significantly correlated with calcification, with 77.8% sensitivity and 83.3% specificity in diagnosing LAD involvement. Likewise, a significant association was observed between LCX involvement and calcification, with corresponding LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%, respectively. Conclusion There was a significant correlation between LAD/LCX and calcification; However, there was no meaningful connection between LM and calcification. Coronary heart disease (CHD) LCX LM LAD Coronary CT angiography Background Atherosclerosis is a systemic condition that causes death globally. Medium and large arteries, such as the carotid and coronary arteries, are usually affected. 52% of acute ischemic stroke (AIS) patients are non-symptomatic CAD. Two-thirds of patients suffering from AIS with no history of cardiac symptoms have coronary artery disease (CAS), and 3% of AIS patients have an increased chance of myocardial infarction[ 1 – 3 ]. The CAD risk associated with vascular involvement over two years is 50% higher in AIS individuals without coronary atherosclerosis. The chance of CAD combined with a vascular disease don't have cardiac symptoms is 4.36 times higher[ 4 , 5 ]. Arterial calcification is a common finding in computed tomography angiography (CTA) patients with AIS. Intracranial artery calcifications indicate subclinical CAD due to their substantial correlation with the coronary artery calcium score (CACS). Coronary heart disease (CHD) is the main mortality risk in developed countries and the United States.CHD causes severe pathogenicity, disability, and loss of efficiency and productivity, culminating in a rise in healthcare costs. The spectrum of CHD ranges from sudden cardiac death (SCD), ischemic cardiomyopathy (ICM), acute myocardial infarction (AMI), unstable angina, chronic stable angina to silent myocardial ischemia (SMI), and Mortalities caused by CHD have been declined remarkably over the past decades with the advent of novel modalities and surgical procedures[ 1 , 2 , 6 ]. Monitoring and studying fast cardiac cycles requires advanced imaging tools such as cardiac gating or ECG-gated angiography to trigger scans and collect data during specific phases of the cardiac cycle. By this technique, With this technique, patients no longer need to be hospitalized, compared to geography [ 7 ]. Coronary computed tomography angiography (CCTA) is a reliable non-invasive method for diagnosing and excluding artery disease (CAD) [ 8 , 9 ]. In addition to coronary stenosis, CCTA helps detect coronary atherosclerosis extent, severity, distribution, and composition. These imaging results add incremental value for predicting future adverse outcomes beyond clinical factors. Applications today frequently use many slices[ 3 , 6 ]. The ability of CAC scoring, a well-known technique, to categorize the chance of mortality from cardiovascular disease is exceedingly crucial. The best instrument for risk discrimination has continuously been demonstrated to be CAC in several sizable international registries[ 4 ]. Studies have connected coronary artery calcium (CAC) to increased heart attacks. The number of vessels in the coronary artery disease (CAD) was calculated as the proportion of each of the three major coronary arteries having a stenosis area of 70% or more. Before contrast media injection, radio opacities inside the vascular walls that were evident in many projections on the cine were thought to be indicators of significant coronary artery calcification. The SYNTAX classification provided a precise characterization of severe calcification[ 6 ]. For example, a calcium score (CS) of > 400 signifies a high cardiovascular event risk. So, it's necessary to take measures to prevent the formation of coronary plaques and advanced atherosclerosis. A higher CS is a hallmark of heart vessel narrowing or blockage [ 7 ]. A zero CS does not negate the presence of soft plaques but rejects the likelihood of CHD in the patient. CS is not a basis for the present existence, and such plaques are better seen in coronary CT angiography (CTA). But, a high CS alarm for soft plaques in coronary arteries. Soft plaque destabilization is a common cause of acute coronary syndrome (ACS). CS is a single criterion employed in routine cardiac CT scans [ 7 ]. A systematic review in Canada in 2010 showed that cardiac MRI (CMR) could be a potent possible assess coronary artery involvements for its sensitivity and reliable diagnostic properties, as well as no exposure to ionizing radiation [ 10 ]. A 2011 review by Konstantin Nikolaou and colleagues showed that CMR is an accurate and low-risk technique with optimal specificity and sensitivity to measure the severity of coronary artery stenosis [ 11 ]. Ganigara et al. (2016) studied patients in Australia and found that CMR can be used to diagnose and follow up on structural heart diseases[ 5 ]. Considering the above topics, we aim to investigate the relationship between LM, LAD, and LCX involvements and calcification in CHD patients. Methods This study investigated LM, LAD, and LCX involvements and calcification in patients referred to Imam Khomeini Hospital in the Cardiovascular Center, Medical and Research center (Tehran, Iran). The present study was an applied, cross-sectional, and observational study conducted on hospitalized patients with coronary heart disease (CHD). A total of 50 CHD patients who met the inclusion criteria were chosen by non-random sampling. All the patients were explained about the study, procedures, and how to cooperate, and then asked to sign the consent form for MRI experiments. CT angiography (CTA) images of patients with at least a single-vessel CHD were taken to ensure that patients had previously undergone conventional angiography. All stenosis cases were recorded, and CTA results were evaluated and compared with MRI results. Field data collected into checklists were analyzed in IBM SPSS Statistics v. 13.00. The mean and standard deviation (SD) have been used to represent quantitative data, and relative and absolute frequencies were used to assess qualitative VA variables. Data were analyzed using Chi-square and t-test at a remarkable level of 0.05. MRI sensitivity and specificity were ultimately measured and compared to the matching CTA-based patient values obtained. The customized strategy for ASCVD prevention is formed by risk assessment. Meanwhile, recent recommendations advise utilizing a global risk assessment structure cohort Equations to evaluate risk assessment[ 12 ]. It is typically assessed at the so-called "intermediate risk" level, which means that the best way to start treatment with preventive medicine is unknown and may require additional testing. The preferred CAC measure has historically been the Agatston score, a total score determined by the area of plaque calcification and the calcified plaque’s highest density. It can be used for gated and non-gated studies collected with 120 KV at 2.5–3 mm slice thickness[ 13 ]. Also frequently given are CAC percentiles based on ethnicity, gender, and age. The conventional CAC risk categories are as follows: 0 = shallow risk; 1–99 = mildly increased risk; 100–299 = moderately increased risk; and 300–1000 = moderate to substantially elevated risk. The crucial scoring system must be specified that the CAC-DRS categories have the same effects in the various scoring systems shown in Table 1 . The first modifier describes the scoring system: Visual estimation refers to Agatston[ 14 ].(Table 1 ) The vessel numbers (modifier N) with CAC (n = 1–4) have been found in a multivariate analysis of the MESA population to be prognostically synergistic to the total CAC, significantly in the CAC range of 1-300. Table 1 Coronary artery calcium data and reporting system categories based on the Agatston and visual scoring CAC-DRS category Agatston score Visual score Risk 0 0 0 Very low 1 1–99 1 Mild 2 100–299 2 Moderate 3 > 300 3 Moderate to severe Results The mean age of participants was 53.2 ± 12.4 years. In this study, 80% of the participants were male, and the remaining 20% were female.(Table 2 ) In this study, we did not detect a prominent linkage between LM involvement and calcification (p > 0.05), with LM involvement diagnosis sensitivity and specificity values of 80% and 44%.(Table 3 ) we detected a significant linkage between LAD involvement and calcification (p = 0.00), with LAD involvement diagnosis sensitivity and specificity values of 77.8% and 83.3%.(Table 4 ) Table 2 The frequency distribution of calcification for LM involvement in patients under study Calcification Total No. Minimal Mid Moderate Significance LM NL 11 44% 3 12% 4 16% 3 12% 4 16% 25 100% Minimal stenosis 0 0% 0 0% 1 100% 0 0% 0 0% 1 100% Mid stenosis 1 33.3% 0 0% 1 33.3% 1 33.3% 0 0% 3 100% Moderate stenosis 0 0% 0 0% 0 0% 0 0% 1 100% 1 100% Total 12 405 3 10% 6 20% 4 13.3% 5 16.7% 30 100% Table 3 The frequency distribution of calcification for LAD involvement in patients under study Calcification Total No. Minimal Mid Moderate Significance LAD NL 10 71.4% 3 21.4% 1 7.1% 0 0% 0 0% 14 100% Minimal stenosis 1 50% 0 0% 1 50% 0 0% 0 0% 2 100% Mid stenosis 0 0% 0 0% 2 40% 3 60% 0 0% 5 100% Moderate stenosis 0 0% 0 0% 0 0% 0 0% 2 100% 2 100% Severe stenosis 1 14.3% 0 0% 2 28.6% 1 14.3% 3 42.9% 7 100% Total 12 405 3 10% 6 20% 4 13.3% 5 16.7% 30 100% Table 4 The frequency distribution of calcification for LCX involvement in patients under study Calcification Total No. Minimal Mid Moderate Significance LCX NL 11 68.8% 2 12.5% 3 18.8% 0 0% 0 0% 16 100% Minimal stenosis 1 33.3% 1 33.3% 0 0% 0 0% 1 33.3% 3 100% Mid stenosis 0 0% 0 0% 1 25% 2 50% 1 25% 4 100% Moderate stenosis 0 0% 0 0% 1 33.3% 2 66.7% 0 0% 3 100% Severe stenosis 0 0% 0 0% 1 25% 0 0% 3 75% 4 100% Total 12 405 3 10% 6 20% 4 13.3% 5 16.7% 30 100% This study did not detect a significant linkage between LCX involvement and calcification (p = 0.00), with LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%.(Table 5 ) There was no significant relationship between RCA involvement and calcification (p = 0.00), with corresponding RCA involvement diagnosis sensitivity and specificity values of 61.1% and 75%. Table 5 The frequency distribution of calcification for RCA involvement in patients under study Calcification Total No. Minimal Mid Moderate Significance RCA NL 9 56.3% 2 12.5% 3 18.8% 2 12.5% 0 0% 16 100% Minimal stenosis 1 100% 0 0% 0 0% 0 0% 0 0% 1 100% Mid stenosis 1 16.7% 0 0% 3 50% 1 16.7% 1 16.7% 6 100% Moderate stenosis 0 0% 0 0% 0 0% 0 0% 2 100% 2 100% Severe stenosis 1 20% 1 20% 0 0% 1 20% 2 40% 5 100% Total 12 405 3 10% 6 20% 4 13.3% 5 16.7% 30 100% Discussion The results showed no relationship between LM involvement and calcification, with 80% sensitivity and 44% specificity in the diagnosis of LMD involvement was significantly correlated with calcification, with 77.8% sensitivity and 83.3% specificity in the diagnosis of LAD lesions, a significant association was observed between LCX involvement and calcification, with corresponding LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%. The effectiveness of 3D unenhanced steady-state free precession (SSFP) magnetic resonance angiography as a diagnostic tool and its quality (MRA) and MRA contrast enhancement was assessed in 50 patients with thoracic aortic disorders by Krishnam et al. (2010)[ 15 ]. Abnormal aortic findings such as aneurysms, coarctation, dissection, aortic graft, hematoma, thrombosis of the aortic arch, and aortoenteric fistula were reliably discovered on both datasets. The diagnostic accuracy, specificity, and sensitivity of SSFP MRA for detecting aortic lesions were 100%, utilizing CE-MRA as a standard reference. The findings demonstrated a promising method for achieving high-quality images and diagnostic accuracy to evaluate thoracic aortic lesions without using an intravenous contrast agent: free-breathing navigator-gated 3D SSFP MRA with non-selective radiofrequency stimulation. In agreement with our results, a 2010 systematic review in Canada showed that cardiac MRI (CMR) could be a possible way to assess coronary artery involvements for its sensitivity and reliable diagnostic properties, as well as no exposure to ionizing radiation [ 10 ]. Similar to our results, a 2011 review by Konstantin Nikolaou and colleagues showed that CMR is an accurate and low-risk technique with optimal sensitivity specificity and sensitivity (~ 90%) to measure the severity of coronary artery stenosis [ 11 ] In Germany, Emrich et al. (2015) studied 125 patients with chest pain and found that CMR can deliver a correct final diagnosis in 90% of patients with stenosis in the acute phase of the disease[ 16 ]. Our study's sensitivity and specificity values were 80% and 92%. This feature and the test’s high sensitivity qualify it as a confirmatory test, not simply for diagnosing and screening coronary artery involvements. Conclusion LAD and LCX involvements were significantly correlated with calcification, while there was no prominent relationship between LM involvement and calcification. The sensitivity and specificity in the diagnosis of LCX involvement were 72.2% and 91.7%. Declarations Ethics approval and consent to participate This study was approved by the Internal Ethics Committee of the Imam Khomeini Hospital in the Cardiovascular Center, Medical and Research center, Tehran, Iran. All participants were informed about the study and they gave their written consent before inclusion in the study. The authors confirmed that all methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects. Authors’ contributions SH did the experiment, analyzed the data and drafted the manuscript. MA helped in sample analysis and contributed to analyzing the results. BA and AR authors designed the study, critical interpretation of the data, wrote and revised the manuscript. All authors read the manuscript and approved the final version. Funding This study did not receive any external funding. Availability of data and materials The datasets used and analyzed during the present study are available from the corresponding author on reasonable request. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Acknowledgements Not applicable. References Feigin VL, Roth GA, Naghavi M, Parmar P, Krishnamurthi R, Chugh S, Mensah GA, Norrving B, Shiue I, Ng M: Global burden of stroke and risk factors in 188 countries, during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 . The Lancet Neurology 2016, 15 (9):913-924. Sigala F, Oikonomou E, Antonopoulos AS, Galyfos G, Tousoulis D: Coronary versus carotid artery plaques. Similarities and differences regarding biomarkers morphology and prognosis . Current opinion in pharmacology 2018, 39 :9-18. Gunnoo T, Hasan N, Khan MS, Slark J, Bentley P, Sharma P: Quantifying the risk of heart disease following acute ischaemic stroke: a meta-analysis of over 50 000 participants . BMJ open 2016, 6 (1):e009535. Zheng C, Yan S, Fu F, Zhao C, Guo D, Wang Z, Lu J: Cervicocephalic spotty calcium for the prediction of coronary atherosclerosis in patients with acute ischemic stroke . Frontiers in Neurology 2021:728. Lee JW, Hur J, Choi SI, Chun EJ, Kang J-W, Jin GY, Kim EY, Yong HS, Kang E-J, Han K: Incremental prognostic value of computed tomography in stroke: rationale and design of the IMPACTS study . The International Journal of Cardiovascular Imaging 2016, 32 (1):83-89. Yoo J, Song D, Baek J-H, Kim K, Kim J, Song T-J, Lee HS, Choi D, Kim YD, Nam HS: Poor long-term outcomes in stroke patients with asymptomatic coronary artery disease in heart CT . Atherosclerosis 2017, 265 :7-13. Iwasaki K, Matsumoto T: Relationship between coronary calcium score and high-risk plaque/significant stenosis . World Journal of Cardiology 2016, 8 (8):481. Budoff MJ, Dowe D, Jollis JG, Gitter M, Sutherland J, Halamert E, Scherer M, Bellinger R, Martin A, Benton R: Diagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter ACCURACY (Assessment by Coronary Computed Tomographic Angiography of Individuals Undergoing Invasive Coronary Angiography) trial . Journal of the American College of Cardiology 2008, 52 (21):1724-1732. Motwani M, Dey D, Berman DS, Germano G, Achenbach S, Al-Mallah MH, Andreini D, Budoff MJ, Cademartiri F, Callister TQ: Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis . European heart journal 2017, 38 (7):500-507. Secretariat MA: Cardiac magnetic resonance imaging for the diagnosis of coronary artery disease: an evidence-based analysis . Ontario Health Technology Assessment Series 2010, 10 (12):1. Nikolaou K, Alkadhi H, Bamberg F, Leschka S, Wintersperger BJ: MRI and CT in the diagnosis of coronary artery disease: indications and applications . Insights into imaging 2011, 2 (1):9-24. Ganigara M, Tanous D, Celermajer D, Puranik R: The role of cardiac MRI in the diagnosis and management of sinus venosus atrial septal defect . Annals of pediatric cardiology 2014, 7 (2):160. Ahn SS, Nam HS, Heo JH, Kim YD, Lee S-K, Han KH, Choi BW, Kim EY: Ischemic stroke: measurement of intracranial artery calcifications can improve prediction of asymptomatic coronary artery disease . Radiology 2013, 268 (3):842-849. Ramanathan S: Coronary artery calcium data and reporting system: strengths and limitations . World Journal of Radiology 2019, 11 (10):126. Krishnam MS, Tomasian A, Malik S, Desphande V, Laub G, Ruehm SG: Image quality and diagnostic accuracy of unenhanced SSFP MR angiography compared with conventional contrast-enhanced MR angiography for the assessment of thoracic aortic diseases . European radiology 2010, 20 (6):1311-1320. Emrich T, Emrich K, Abegunewardene N, Oberholzer K, Dueber C, Muenzel T, Kreitner KF: Cardiac MR enables diagnosis in 90% of patients with acute chest pain, elevated biomarkers and unobstructed coronary arteries . The British journal of radiology 2015, 88 (1049):20150025. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2248580","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":152248518,"identity":"6caa7144-5f4b-4241-ae39-b8007ddfe6ba","order_by":0,"name":"Sara Hassani","email":"","orcid":"","institution":"Pennsylvania Diagnostic Radiologist post-doctoral research fellowship, university Perelman school of medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Hassani","suffix":""},{"id":152248519,"identity":"6596dc92-4139-4244-93b3-1ab0690c3225","order_by":1,"name":"Mobin Azami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFACHoYDQFKOn72BgZkkLcaSPQdI0AICiRtuJBCpRbe99+Dhgpq6xJkz3xh+LqiwYeBv707Aq8XszLmEwzOOsRn3S+cYS884k8YgcebsBvxabuQYHOZh45GdOTvHQJq37TCDgUQuMVr+STBuuHnG+DfxWnjbDBQ33OAxI9IWkF94+xKAgZxWZs1zJo2HsF+O9x7+zPOtDhiVhzff5qmwkeNv78WvBQlwGIBIHmKVgwD7A1JUj4JRMApGwQgCAAsPSImW6Nc1AAAAAElFTkSuQmCC","orcid":"","institution":"Kurdistan University of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Mobin","middleName":"","lastName":"Azami","suffix":""},{"id":152248522,"identity":"e4a77ce9-ed1a-4cd5-b335-d820fd0a2e75","order_by":2,"name":"Bahador Asadi","email":"","orcid":"","institution":"AJA University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bahador","middleName":"","lastName":"Asadi","suffix":""},{"id":152248524,"identity":"bdf8eb2d-2da6-47c1-b84e-4cfbe840b9d4","order_by":3,"name":"Aryobarzan Rahmatian","email":"","orcid":"","institution":"Tehran university of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aryobarzan","middleName":"","lastName":"Rahmatian","suffix":""}],"badges":[],"createdAt":"2022-11-07 22:59:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2248580/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2248580/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":31011057,"identity":"1da168ad-d34b-47d2-90ce-53d6da9477bc","added_by":"auto","created_at":"2023-01-03 10:59:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":738567,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2248580/v1/7a93607b-e5b3-4118-99ee-edf5a3dd9300.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationships between Left circumflex artery (LCX) and Left anterior descending (LAD) involvements and calcification in patients with Coronary heart disease(CHD): a cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eAtherosclerosis is a systemic condition that causes death globally. Medium and large arteries, such as the carotid and coronary arteries, are usually affected. 52% of acute ischemic stroke (AIS) patients are non-symptomatic CAD. Two-thirds of patients suffering from AIS with no history of cardiac symptoms have coronary artery disease (CAS), and 3% of AIS patients have an increased chance of myocardial infarction[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The CAD risk associated with vascular involvement over two years is 50% higher in AIS individuals without coronary atherosclerosis. The chance of CAD combined with a vascular disease don't have cardiac symptoms is 4.36 times higher[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Arterial calcification is a common finding in computed tomography angiography (CTA) patients with AIS. Intracranial artery calcifications indicate subclinical CAD due to their substantial correlation with the coronary artery calcium score (CACS). Coronary heart disease (CHD) is the main mortality risk in developed countries and the United States.CHD causes severe pathogenicity, disability, and loss of efficiency and productivity, culminating in a rise in healthcare costs. The spectrum of CHD ranges from sudden cardiac death (SCD), ischemic cardiomyopathy (ICM), acute myocardial infarction (AMI), unstable angina, chronic stable angina to silent myocardial ischemia (SMI), and Mortalities caused by CHD have been declined remarkably over the past decades with the advent of novel modalities and surgical procedures[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMonitoring and studying fast cardiac cycles requires advanced imaging tools such as cardiac gating or ECG-gated angiography to trigger scans and collect data during specific phases of the cardiac cycle. By this technique, With this technique, patients no longer need to be hospitalized, compared to geography [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Coronary computed tomography angiography (CCTA) is a reliable non-invasive method for diagnosing and excluding artery disease (CAD) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to coronary stenosis, CCTA helps detect coronary atherosclerosis extent, severity, distribution, and composition. These imaging results add incremental value for predicting future adverse outcomes beyond clinical factors. Applications today frequently use many slices[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe ability of CAC scoring, a well-known technique, to categorize the chance of mortality from cardiovascular disease is exceedingly crucial. The best instrument for risk discrimination has continuously been demonstrated to be CAC in several sizable international registries[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Studies have connected coronary artery calcium (CAC) to increased heart attacks. The number of vessels in the coronary artery disease (CAD) was calculated as the proportion of each of the three major coronary arteries having a stenosis area of 70% or more. Before contrast media injection, radio opacities inside the vascular walls that were evident in many projections on the cine were thought to be indicators of significant coronary artery calcification. The SYNTAX classification provided a precise characterization of severe calcification[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For example, a calcium score (CS) of \u0026gt;\u0026thinsp;400 signifies a high cardiovascular event risk. So, it's necessary to take measures to prevent the formation of coronary plaques and advanced atherosclerosis. A higher CS is a hallmark of heart vessel narrowing or blockage [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. A zero CS does not negate the presence of soft plaques but rejects the likelihood of CHD in the patient. CS is not a basis for the present existence, and such plaques are better seen in coronary CT angiography (CTA). But, a high CS alarm for soft plaques in coronary arteries. Soft plaque destabilization is a common cause of acute coronary syndrome (ACS). CS is a single criterion employed in routine cardiac CT scans [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA systematic review in Canada in 2010 showed that cardiac MRI (CMR) could be a potent possible assess coronary artery involvements for its sensitivity and reliable diagnostic properties, as well as no exposure to ionizing radiation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A 2011 review by Konstantin Nikolaou and colleagues showed that CMR is an accurate and low-risk technique with optimal specificity and sensitivity to measure the severity of coronary artery stenosis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Ganigara et al. (2016) studied patients in Australia and found that CMR can be used to diagnose and follow up on structural heart diseases[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Considering the above topics, we aim to investigate the relationship between LM, LAD, and LCX involvements and calcification in CHD patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study investigated LM, LAD, and LCX involvements and calcification in patients referred to Imam Khomeini Hospital in the Cardiovascular Center, Medical and Research center (Tehran, Iran). The present study was an applied, cross-sectional, and observational study conducted on hospitalized patients with coronary heart disease (CHD). A total of 50 CHD patients who met the inclusion criteria were chosen by non-random sampling. All the patients were explained about the study, procedures, and how to cooperate, and then asked to sign the consent form for MRI experiments. CT angiography (CTA) images of patients with at least a single-vessel CHD were taken to ensure that patients had previously undergone conventional angiography. All stenosis cases were recorded, and CTA results were evaluated and compared with MRI results. Field data collected into checklists were analyzed in IBM SPSS Statistics v. 13.00. The mean and standard deviation (SD) have been used to represent quantitative data, and relative and absolute frequencies were used to assess qualitative VA variables. Data were analyzed using Chi-square and t-test at a remarkable level of 0.05. MRI sensitivity and specificity were ultimately measured and compared to the matching CTA-based patient values obtained.\u003c/p\u003e \u003cp\u003eThe customized strategy for ASCVD prevention is formed by risk assessment. Meanwhile, recent recommendations advise utilizing a global risk assessment structure cohort Equations to evaluate risk assessment[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It is typically assessed at the so-called \"intermediate risk\" level, which means that the best way to start treatment with preventive medicine is unknown and may require additional testing.\u003c/p\u003e \u003cp\u003eThe preferred CAC measure has historically been the Agatston score, a total score determined by the area of plaque calcification and the calcified plaque\u0026rsquo;s highest density. It can be used for gated and non-gated studies collected with 120 KV at 2.5\u0026ndash;3 mm slice thickness[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Also frequently given are CAC percentiles based on ethnicity, gender, and age. The conventional CAC risk categories are as follows: 0\u0026thinsp;=\u0026thinsp;shallow risk; 1\u0026ndash;99\u0026thinsp;=\u0026thinsp;mildly increased risk; 100\u0026ndash;299\u0026thinsp;=\u0026thinsp;moderately increased risk; and 300\u0026ndash;1000\u0026thinsp;=\u0026thinsp;moderate to substantially elevated risk.\u003c/p\u003e \u003cp\u003eThe crucial scoring system must be specified that the CAC-DRS categories have the same effects in the various scoring systems shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The first modifier describes the scoring system: Visual estimation refers to Agatston[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) The vessel numbers (modifier N) with CAC (n\u0026thinsp;=\u0026thinsp;1\u0026ndash;4) have been found in a multivariate analysis of the MESA population to be prognostically synergistic to the total CAC, significantly in the CAC range of 1-300.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoronary artery calcium data and reporting system categories based on the Agatston and visual scoring\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC-DRS category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgatston score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVisual score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery low\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u0026ndash;299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate to severe\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean age of participants was 53.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4 years. In this study, 80% of the participants were male, and the remaining 20% were female.(Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) In this study, we did not detect a prominent linkage between LM involvement and calcification (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), with LM involvement diagnosis sensitivity and specificity values of 80% and 44%.(Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) we detected a significant linkage between LAD involvement and calcification (p\u0026thinsp;=\u0026thinsp;0.00), with LAD involvement diagnosis sensitivity and specificity values of 77.8% and 83.3%.(Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe frequency distribution of calcification for LM involvement in patients under study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCalcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMid stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe frequency distribution of calcification for LAD involvement in patients under study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCalcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003cp\u003e71.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e21.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e7.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMid stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e14.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e28.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e14.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e42.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe frequency distribution of calcification for LCX involvement in patients under study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCalcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e68.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMid stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e66.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis study did not detect a significant linkage between LCX involvement and calcification (p\u0026thinsp;=\u0026thinsp;0.00), with LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%.(Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) There was no significant relationship between RCA involvement and calcification (p\u0026thinsp;=\u0026thinsp;0.00), with corresponding RCA involvement diagnosis sensitivity and specificity values of 61.1% and 75%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe frequency distribution of calcification for RCA involvement in patients under study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCalcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e56.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMid stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results showed no relationship between LM involvement and calcification, with 80% sensitivity and 44% specificity in the diagnosis of LMD involvement was significantly correlated with calcification, with 77.8% sensitivity and 83.3% specificity in the diagnosis of LAD lesions, a significant association was observed between LCX involvement and calcification, with corresponding LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%.\u003c/p\u003e \u003cp\u003eThe effectiveness of 3D unenhanced steady-state free precession (SSFP) magnetic resonance angiography as a diagnostic tool and its quality (MRA) and MRA contrast enhancement was assessed in 50 patients with thoracic aortic disorders by Krishnam et al. (2010)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Abnormal aortic findings such as aneurysms, coarctation, dissection, aortic graft, hematoma, thrombosis of the aortic arch, and aortoenteric fistula were reliably discovered on both datasets. The diagnostic accuracy, specificity, and sensitivity of SSFP MRA for detecting aortic lesions were 100%, utilizing CE-MRA as a standard reference. The findings demonstrated a promising method for achieving high-quality images and diagnostic accuracy to evaluate thoracic aortic lesions without using an intravenous contrast agent: free-breathing navigator-gated 3D SSFP MRA with non-selective radiofrequency stimulation.\u003c/p\u003e \u003cp\u003eIn agreement with our results, a 2010 systematic review in Canada showed that cardiac MRI (CMR) could be a possible way to assess coronary artery involvements for its sensitivity and reliable diagnostic properties, as well as no exposure to ionizing radiation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Similar to our results, a 2011 review by Konstantin Nikolaou and colleagues showed that CMR is an accurate and low-risk technique with optimal sensitivity specificity and sensitivity (~\u0026thinsp;90%) to measure the severity of coronary artery stenosis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn Germany, Emrich et al. (2015) studied 125 patients with chest pain and found that CMR can deliver a correct final diagnosis in 90% of patients with stenosis in the acute phase of the disease[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Our study's sensitivity and specificity values were 80% and 92%. This feature and the test\u0026rsquo;s high sensitivity qualify it as a confirmatory test, not simply for diagnosing and screening coronary artery involvements.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eLAD and LCX involvements were significantly correlated with calcification, while there was no prominent relationship between LM involvement and calcification. The sensitivity and specificity in the diagnosis of LCX involvement were 72.2% and 91.7%.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Internal Ethics Committee of the Imam Khomeini Hospital in the Cardiovascular Center, Medical and Research center, Tehran, Iran. All participants were informed about the study and they gave their written consent before inclusion in the study. The authors confirmed that all methods were carried out in accordance with relevant\u003c/p\u003e\n\u003cp\u003eguidelines and regulations. Informed consent was obtained from all subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSH did the experiment, analyzed the data and drafted the manuscript. MA helped in sample analysis and contributed to analyzing the results. BA and AR authors designed the study, critical interpretation of the data, wrote and revised the manuscript. All authors read the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the present study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFeigin VL, Roth GA, Naghavi M, Parmar P, Krishnamurthi R, Chugh S, Mensah GA, Norrving B, Shiue I, Ng M: \u003cstrong\u003eGlobal burden of stroke and risk factors in 188 countries, during 1990\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013\u003c/strong\u003e. \u003cem\u003eThe Lancet Neurology \u003c/em\u003e2016, \u003cstrong\u003e15\u003c/strong\u003e(9):913-924.\u003c/li\u003e\n\u003cli\u003eSigala F, Oikonomou E, Antonopoulos AS, Galyfos G, Tousoulis D: \u003cstrong\u003eCoronary versus carotid artery plaques. Similarities and differences regarding biomarkers morphology and prognosis\u003c/strong\u003e. \u003cem\u003eCurrent opinion in pharmacology \u003c/em\u003e2018, \u003cstrong\u003e39\u003c/strong\u003e:9-18.\u003c/li\u003e\n\u003cli\u003eGunnoo T, Hasan N, Khan MS, Slark J, Bentley P, Sharma P: \u003cstrong\u003eQuantifying the risk of heart disease following acute ischaemic stroke: a meta-analysis of over 50 000 participants\u003c/strong\u003e. \u003cem\u003eBMJ open \u003c/em\u003e2016, \u003cstrong\u003e6\u003c/strong\u003e(1):e009535.\u003c/li\u003e\n\u003cli\u003eZheng C, Yan S, Fu F, Zhao C, Guo D, Wang Z, Lu J: \u003cstrong\u003eCervicocephalic spotty calcium for the prediction of coronary atherosclerosis in patients with acute ischemic stroke\u003c/strong\u003e. \u003cem\u003eFrontiers in Neurology \u003c/em\u003e2021:728.\u003c/li\u003e\n\u003cli\u003eLee JW, Hur J, Choi SI, Chun EJ, Kang J-W, Jin GY, Kim EY, Yong HS, Kang E-J, Han K: \u003cstrong\u003eIncremental prognostic value of computed tomography in stroke: rationale and design of the IMPACTS study\u003c/strong\u003e. \u003cem\u003eThe International Journal of Cardiovascular Imaging \u003c/em\u003e2016, \u003cstrong\u003e32\u003c/strong\u003e(1):83-89.\u003c/li\u003e\n\u003cli\u003eYoo J, Song D, Baek J-H, Kim K, Kim J, Song T-J, Lee HS, Choi D, Kim YD, Nam HS: \u003cstrong\u003ePoor long-term outcomes in stroke patients with asymptomatic coronary artery disease in heart CT\u003c/strong\u003e. \u003cem\u003eAtherosclerosis \u003c/em\u003e2017, \u003cstrong\u003e265\u003c/strong\u003e:7-13.\u003c/li\u003e\n\u003cli\u003eIwasaki K, Matsumoto T: \u003cstrong\u003eRelationship between coronary calcium score and high-risk plaque/significant stenosis\u003c/strong\u003e. \u003cem\u003eWorld Journal of Cardiology \u003c/em\u003e2016, \u003cstrong\u003e8\u003c/strong\u003e(8):481.\u003c/li\u003e\n\u003cli\u003eBudoff MJ, Dowe D, Jollis JG, Gitter M, Sutherland J, Halamert E, Scherer M, Bellinger R, Martin A, Benton R: \u003cstrong\u003eDiagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter ACCURACY (Assessment by Coronary Computed Tomographic Angiography of Individuals Undergoing Invasive Coronary Angiography) trial\u003c/strong\u003e. \u003cem\u003eJournal of the American College of Cardiology \u003c/em\u003e2008, \u003cstrong\u003e52\u003c/strong\u003e(21):1724-1732.\u003c/li\u003e\n\u003cli\u003eMotwani M, Dey D, Berman DS, Germano G, Achenbach S, Al-Mallah MH, Andreini D, Budoff MJ, Cademartiri F, Callister TQ: \u003cstrong\u003eMachine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis\u003c/strong\u003e. \u003cem\u003eEuropean heart journal \u003c/em\u003e2017, 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\u003cem\u003eEuropean radiology \u003c/em\u003e2010, \u003cstrong\u003e20\u003c/strong\u003e(6):1311-1320.\u003c/li\u003e\n\u003cli\u003eEmrich T, Emrich K, Abegunewardene N, Oberholzer K, Dueber C, Muenzel T, Kreitner KF: \u003cstrong\u003eCardiac MR enables diagnosis in 90% of patients with acute chest pain, elevated biomarkers and unobstructed coronary arteries\u003c/strong\u003e. \u003cem\u003eThe British journal of radiology \u003c/em\u003e2015, \u003cstrong\u003e88\u003c/strong\u003e(1049):20150025.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Coronary heart disease (CHD), LCX, LM, LAD, Coronary CT angiography","lastPublishedDoi":"10.21203/rs.3.rs-2248580/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2248580/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the relationships between LM, LAD, and LCX lesions and calcification in patients referred to Imam Khomeini Hospital, Medical, and Research center (Tehran, Iran).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe present study was an applied, cross-sectional, and observational study conducted on hospitalized patients suffering from coronary heart disease (CHD). By non-random sampling, 50 CHD patients who met the inclusion criteria were selected. CT angiography and MRI results were investigated, and field data collected by checklists were analyzed in IBM SPSS Statistics v. 13.00.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere was no relationship between LM involvement and calcification, with 80% sensitivity and 44% specificity in the diagnosis of LM involvement. By contrast, LAD involvement was significantly correlated with calcification, with 77.8% sensitivity and 83.3% specificity in diagnosing LAD involvement. Likewise, a significant association was observed between LCX involvement and calcification, with corresponding LCX involvement diagnosis sensitivity and specificity values of 72.2% and 91.7%, respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere was a significant correlation between LAD/LCX and calcification; However, there was no meaningful connection between LM and calcification.\u003c/p\u003e","manuscriptTitle":"Relationships between Left circumflex artery (LCX) and Left anterior descending (LAD) involvements and calcification in patients with Coronary heart disease(CHD): a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-17 12:49:03","doi":"10.21203/rs.3.rs-2248580/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d043d4f6-b0c6-469a-89f5-546d46e63c80","owner":[],"postedDate":"November 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-01-03T10:59:24+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-17 12:49:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2248580","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2248580","identity":"rs-2248580","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}