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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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Research Article

A New Relational Database Including Clinical Data and Myocardial Perfusion Imaging Findings in Coronary Artery Disease

Author(s): Rosario Megna*, Mario Petretta, Bruno Alfano, Valeria Cantoni, Roberta Green, Stefania Daniele, Wanda Acampa, Carmela Nappi, Valeria Gaudieri, Roberta Assante, Emilia Zampella, Emanuela Mazziotti, Teresa Mannarino, Pietro Buongiorno and Alberto Cuocolo

Volume 15, Issue 7, 2019

Page: [661 - 671] Pages: 11

DOI: 10.2174/1573405614666180807110829

Price: $65

Abstract

Background: The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging.

Methods: We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer.

Results: There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate.

Conclusion: The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.

Keywords: Database, PostgreSQL, cardiac imaging, single-photon emission computed tomography, myocardial perfusion, coronary artery disease.

Graphical Abstract

[1]
Timmis A, Townsend N, Gale C, et al. European society of cardiology: Cardiovascular disease statistics 2017. Eur Heart J 2018; 39(7): 508-79.
[http://dx.doi.org/10.1093/eurheartj/ehx628] [PMID: 29190377]
[2]
Sanchis-Gomar F, Perez-Quilis C, Leischik R, Lucia A. Epidemiology of coronary heart disease and acute coronary syndrome. Ann Transl Med 2016; 4(13): 256.
[http://dx.doi.org/10.21037/atm.2016.06.33] [PMID: 27500157]
[3]
Mozaffarian D, Benjamin EJ, Alan S. Executive summary: Heart disease and stroke statistics - 2016 update: A report from the American heart association. Circulation 2016; 133: 447-54.
[http://dx.doi.org/10.1161/CIR.0000000000000366]
[4]
Lloyd-Jones DM, Leip EP, Larson MG, et al. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation 2006; 113(6): 791-8.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.105.548206] [PMID: 16461820]
[5]
Stamler J, Neaton JD. The Multiple Risk Factor Intervention Trial (MRFIT)-importance then and now. JAMA 2008; 300(11): 1343-5.
[http://dx.doi.org/10.1001/jama.300.11.1343] [PMID: 18799447]
[6]
Roger VL, Go AS, Lloyd-Jones DM, et al. Executive summary: heart disease and stroke statistics-2012 update: a report from the American Heart Association. Circulation 2012; 125(1): 188-97.
[http://dx.doi.org/10.1161/CIR.0b013e3182456d46] [PMID: 22215894]
[7]
Sidney S, Quesenberry CP Jr, Jaffe MG, et al. Recent trends in cardiovascular mortality in the United States and public health goals. JAMA Cardiol 2016; 1(5): 594-9.
[http://dx.doi.org/10.1001/jamacardio.2016.1326] [PMID: 27438477]
[8]
Lloyd-Jones DM. Slowing progress in cardiovascular mortality rates: you reap what you sow. JAMA Cardiol 2016; 1(5): 599-600.
[http://dx.doi.org/10.1001/jamacardio.2016.1348] [PMID: 27438674]
[9]
Meyer RJ. Commentary on R&D trends away from general medicine/cardiovascular drugs: Can the FDA help reverse the trend? Clin Pharmacol Ther 2017; 102(2): 186-8.
[http://dx.doi.org/10.1002/cpt.735] [PMID: 28636269]
[10]
Iskandrian AE, Dilsizian V, Garcia EV, et al. Myocardial perfusion imaging: Lessons learned and work to be done-update. J Nucl Cardiol 2018; 25(1): 39-52.
[http://dx.doi.org/10.1007/s12350-017-1093-7] [PMID: 29110288]
[11]
Acampa W, Rozza F, Zampella E, et al. Warranty period of normal stress myocardial perfusion imaging in hypertensive patients: A parametric survival analysis. J Nucl Cardiol 2018.
[http://dx.doi.org/10.1007/s12350-018-1285-9] [PMID: 29679222]
[12]
Petretta M, Acampa W, Daniele S, et al. Long-Term survival benefit of coronary revascularization in patients undergoing stress myocardial perfusion imaging. Circ J 2016; 80(2): 485-93.
[http://dx.doi.org/10.1253/circj.CJ-15-1093] [PMID: 26686993]
[13]
Petretta M, Cuocolo A. Screening asymptomatic patients with type 2 diabetes is recommended: Pro. J Nucl Cardiol 2015; 22(6): 1225-8.
[http://dx.doi.org/10.1007/s12350-015-0250-0] [PMID: 26391499]
[14]
Sabharwal NK. State of the art in nuclear cardiology. Heart 2017; 103(10): 790-9.
[http://dx.doi.org/10.1136/heartjnl-2015-308670] [PMID: 27920047]
[15]
Green R, Cantoni V, Petretta M, et al. Negative predictive value of stress myocardial perfusion imaging and coronary computed tomography angiography: A meta-analysis. J Nucl Cardiol 2017.
[PMID: 28205072]
[16]
Knuuti J, Ballo H, Juarez-Orozco LE, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J 2018; 39(35): 3322-30.
[http://dx.doi.org/10.1093/eurheartj/ehy267] [PMID: 29850808]
[17]
Piccinelli M, Garcia EV. advances in single-photon emission computed tomography hardware and software. Cardiol Clin 2016; 34(1): 1-11.
[http://dx.doi.org/10.1016/j.ccl.2015.06.001] [PMID: 26590775]
[18]
Alexiou S, Georgoulias P, Angelidis G, et al. Myocardial perfusion and left ventricular quantitative parameters obtained using gated myocardial SPECT: Comparison of three software packages. J Nucl Cardiol 2018; 25(3): 911-24.
[http://dx.doi.org/10.1007/s12350-016-0730-x] [PMID: 27873167]
[19]
Germano G, Kavanagh PB, Waechter P, et al. A new algorithm for the quantitation of myocardial perfusion SPECT. I: technical principles and reproducibility. J Nucl Med 2000; 41(4): 712-9.
[PMID: 10768574]
[20]
Berman DS, Kang X, Van Train KF, et al. Comparative prognostic value of automatic quantitative analysis versus semiquantitative visual analysis of exercise myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol 1998; 32(7): 1987-95.
[http://dx.doi.org/10.1016/S0735-1097(98)00501-4] [PMID: 9857883]
[21]
Postgre SQL. Available from: . https://www.postgresql.org/
[22]
Stonebraker M, Hanson EN, Potamianos S. The POSTGRES Rule Manager. IEEE Trans Softw Eng 1988; 14: 897-907.
[http://dx.doi.org/10.1109/32.42733]
[23]
Stonebraker M, Rowe LA, Hirohama M. The implementation of POSTGRES. IEEE Trans Knowl Data Eng 1990; 2: 125-42.
[http://dx.doi.org/10.1109/69.50912]
[24]
Silva S, Gouveia-Oliveira R, Maretzek A, et al. EURISWEB-Web-based epidemiological surveillance of antibiotic-resistant pneumococci in day care centers. BMC Med Inform Decis Mak 2003; 8: 3-9.
[25]
McSparron H, Blythe MJ, Zygouri C, Doytchinova IA, Flower DR. JenPep: a novel computational information resource for immunobiology and vaccinology. J Chem Inf Comput Sci 2003; 43(4): 1276-87.
[http://dx.doi.org/10.1021/ci030461e] [PMID: 12870921]
[26]
Herskovits EH, Owis MI, Chen R. Integrating data-mining support into a brain-image database using open-source components. Adv Med Sci 2008; 53(2): 172-81.
[http://dx.doi.org/10.2478/v10039-008-0009-9] [PMID: 18467275]
[27]
Massaut J, Reper P. Open source electronic health record and patient data management system for intensive care. Stud Health Technol Inform 2008; 141: 139-45.
[PMID: 18953134]
[28]
Staib F, Krupp M, Maass T, et al. CellMinerHCC: a microarray-based expression database for hepatocellular carcinoma cell lines. Liver Int 2014; 34(4): 621-31.
[http://dx.doi.org/10.1111/liv.12292] [PMID: 24016071]
[29]
Austin T, Sun S, Lim YS, et al. An electronic healthcare record server implemented in PostgreSQL. J Healthc Eng 2015; 6(3): 325-44.
[http://dx.doi.org/10.1260/2040-2295.6.3.325] [PMID: 26753438]
[30]
Guien C, Fabre A, Lagarde A, et al. OISO, automatic treatment of patients management in oncogenetics. Bull Cancer 2017; 104(7-8): 602-7.
[http://dx.doi.org/10.1016/j.bulcan.2017.06.003] [PMID: 28689638]
[31]
Singh H, Yadav G, Mallaiah R, et al. iNICU - Integrated neonatal care unit: capturing neonatal journey in an intelligent data way. J Med Syst 2017; 41(8): 132.
[http://dx.doi.org/10.1007/s10916-017-0774-8] [PMID: 28748430]
[32]
Tatikonda VK, El-Ocla H. BLOODR: blood donor and requester mobile application. mHealth 2017; 3: 40.
[http://dx.doi.org/10.21037/mhealth.2017.08.08] [PMID: 29184892]
[33]
Stripelis D, Ambite JL, Chiang YY, Eckel SP, Habre R. A Scalable data integration and analysis architecture for sensor data of pediatric asthma. Proc Int Conf Data Eng 2017; 2017: 1407-8.
[http://dx.doi.org/10.1109/ICDE.2017.198] [PMID: 29731601]
[34]
Santesoft PACS and DICOM software. Available from:. http://www.santesoft.com/downloads.html
[35]
Open Source Clinical Image and Object Management. Available from:. https://www.dcm4che.org/
[36]
Brown MS, Shah SK, Pais RC, et al. Database design and implementation for quantitative image analysis research. IEEE Trans Inf Technol Biomed 2005; 9(1): 99-108.
[http://dx.doi.org/10.1109/TITB.2004.837854] [PMID: 15787012]
[37]
Lee WJ, Yang CY, Liu KL, Liu HM, Ching YT, Chen SJ. Establishing a web-based DICOM teaching file authoring tool using open-source public software. J Digit Imaging 2005; 18(3): 169-75.
[http://dx.doi.org/10.1007/s10278-005-5171-z] [PMID: 15924271]
[38]
Evangelista N, Camapum J, Amemiya E. Communication and storage of digital medical images in database. Conf Proc IEEE Eng Med Biol Soc 2005; 5: 5471-4.
[http://dx.doi.org/10.1109/IEMBS.2005.1615721] [PMID: 17281491]
[39]
Guliato D, de Melo EV, Rangayyan RM, Soares RC. POSTGRESQL-IE: an image-handling extension for PostgreSQL. J Digit Imaging 2009; 22(2): 149-65.
[http://dx.doi.org/10.1007/s10278-007-9097-5] [PMID: 18214614]
[40]
Prado TC, de Macedo DDJ, Dantas MAR, von Wangenheim A. Optimization of PACS data persistency using indexed hierarchical data. J Digit Imaging 2014; 27(3): 297-308.
[http://dx.doi.org/10.1007/s10278-013-9665-9] [PMID: 24402455]
[41]
PostgreSQL Tools. Available from:. https://www.pgadmin.org/
[42]
The CentOS Project. Available from:. https://www.centos.org/
[43]
vSphere Hypervisor. Available from:. http://www.vmware.com/products/vsphere-hypervisor.html
[44]
pgAdmin Main Window. Available from:. https://www.pgadmin.org/docs/pgadmin3/1.22/main.html
[45]
Query tool. Available from:. https://www.pgadmin.org/docs/pgadmin3/1.22/query.html
[46]
Graphical Query builder. Available from:. https://www.pgadmin.org/docs/pgadmin3/1.22/gqb.html
[47]
CentOS. Available from:. https://wiki.centos.org/HowTos/Network/IPTables
[48]
PostgreSQL 9.2.24 Documentation. Chapter 19. Client Authentication. Available from:. https://www.postgresql.org/docs/9.2/static/auth-pg-hba-conf.html
[49]
Using pgAdmin III. Available from:. https://www.pgadmin.org/docs/pgadmin3/1.22/connect.html
[50]
SSL.. https://www.ssl.com/?s=protocol
[51]
17.9. Secure TCP/IP Connections with SSL. Available from:. https://www.postgresql.org/docs/9.2/static/ssl-tcp.html
[52]
SSH Protocol.. https://www.ssh.com/ssh/protocol/
[53]
17.10. Secure TCP/IP Connections with SSH Tunnels. Available from:. https://www.postgresql.org/docs/9.2/static/ssh-tunnels.html
[54]
Diamond GA, Staniloff HM, Forrester JS, Pollock BH, Swan HJC. Computer-assisted diagnosis in the noninvasive evaluation of patients with suspected coronary artery disease. J Am Coll Cardiol 1983; 1(2 Pt 1): 444-55.
[http://dx.doi.org/10.1016/S0735-1097(83)80072-2] [PMID: 6338081]
[55]
Juba S, Vannahme S, Volkov A. Learning PostgreSQL. United Kingdom: Packt Publishing Limited 2016.
[56]
Kaur M, Shaik B. PostgreSQL Development Essentials. United Kingdom: Packt Publishing Limited 2016.
[57]
The R Project for Statistical Computing. Available from:. https://www.r-project.org/
[58]
Package ‘RPostgreSQL’. Available from:. https://cran.r-project.org/web/packages/RPostgreSQL/RPostgreSQL.pdf
[59]
Haerder T, Reuter A. Principles of transaction-oriented database recovery. ACM Comput Surv 1983; 15: 287.
[http://dx.doi.org/10.1145/289.291]
[60]
PostgreSQL 7.3.2 Reference Manual. Available from:. https://www.postgresql.org/files/documentation/pdf/7.3/reference-7.3.2-A4.pdf
[61]
Sys.time. Available from:. https://www.rdocumentation.org/packages/base/versions/3.4.0/topics/Sys.time
[62]
Verberne HJ, Acampa W, Anagnostopoulos C, et al. EANM procedural guidelines for radionuclide myocardial perfusion imaging with SPECT and SPECT/CT: 2015 revision. Eur J Nucl Med Mol Imaging 2015; 42(12): 1929-40.
[http://dx.doi.org/10.1007/s00259-015-3139-x] [PMID: 26290421]
[63]
Hachamovitch R, Berman DS, Shaw LJ, et al. Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: differential stratification for risk of cardiac death and myocardial infarction. Circulation 1998; 97(6): 535-43.
[http://dx.doi.org/10.1161/01.CIR.97.6.535] [PMID: 9494023]
[64]
Klocke FJ, Baird MG, Lorell BH, et al. American heart association; American society for nuclear cardiology. ACC/AHA/ASNC guidelines for the clinical use of cardiac radionuclide imaging-executive summary: a report of the American College of Cardiology/American Heart Association task force on practice guidelines (ACC/AHA/ASNC Committee to revise the 1995 guidelines for the clinical use of cardiac radionuclide imaging). Circulation 2003; 108(11): 1404-18.
[PMID: 12975245]
[65]
Berman DS, Abidov A, Kang X, et al. Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation. J Nucl Cardiol 2004; 11(4): 414-23.
[http://dx.doi.org/10.1016/j.nuclcard.2004.03.033] [PMID: 15295410]
[66]
psqlODBC - PostgreSQL ODBC driver. Available from:. https://odbc.postgresql.org/
[67]
Access 2010. Available from:. https://docs.microsoft.com/en-us/previous-versions/office/developer/office-2010/ff604965(v=office.14)
[68]
DB-Engines. Available from:. https://db-engines.com/
[69]
Schmidt CO, Schössow J, Radke D, Krabbe C, Albers M, Henke J. Square2-A web application for data monitoring in epidemiological and clinical studies. Stud Health Technol Inform 2017; 235: 549-53.
[70]
Edlinger D, Sauter SK, Rinner C, et al. JADE: a tool for medical researchers to explore adverse drug events using health claims data. Appl Clin Inform 2014; 5(3): 621-9.
[http://dx.doi.org/10.4338/ACI-2014-04-RA-0036] [PMID: 25298803]
[71]
Rozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009. J Am Coll Cardiol 2013; 61(10): 1054-65.
[http://dx.doi.org/10.1016/j.jacc.2012.11.056] [PMID: 23473411]
[72]
Duvall WL, Rai M, Ahlberg AW, O’Sullivan DM, Henzlova MJ. A multi-center assessment of the temporal trends in myocardial perfusion imaging. J Nucl Cardiol 2015; 22(3): 539-51.
[http://dx.doi.org/10.1007/s12350-014-0051-x] [PMID: 25652080]
[73]
Iskandrian AE, Hage FG. Declining frequency of ischemia detection using stress myocardial perfusion imaging. J Am Coll Cardiol 2013; 61(10): 1066-8.
[http://dx.doi.org/10.1016/j.jacc.2012.12.009] [PMID: 23473412]
[74]
Brindis RG, Douglas PS, Hendel RC, et al. ACCF/ASNC appropriateness criteria for single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI): a report of the American College of Cardiology Foundation Quality Strategic Directions Committee Appropriateness Criteria Working Group and the American Society of Nuclear Cardiology endorsed by the American Heart Association. J Am Coll Cardiol 2005; 46(8): 1587-605.
[http://dx.doi.org/10.1016/j.jacc.2005.08.029] [PMID: 16226194]
[75]
Hendel RC, Berman DS, Di Carli MF, et al. ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR/SNM 2009 appropriate use criteria for cardiac radionuclide imaging: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the American Society of Nuclear Cardiology, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the Society of Cardiovascular Computed Tomography, the Society for Cardiovascular Magnetic Resonance, and the Society of Nuclear Medicine. Circulation 2009; 119(22): e561-87.
[PMID: 19451357]
[76]
Jouni H, Askew JW, Crusan DJ, Miller TD, Gibbons RJ. Temporal trends of single-photon emission computed tomography myocardial perfusion imaging in patients without prior coronary artery disease: A 22-year experience at a tertiary academic medical center. Am Heart J 2016; 176: 127-33.
[http://dx.doi.org/10.1016/j.ahj.2016.03.014] [PMID: 27264231]
[77]
Jouni H, Askew JW, Crusan DJ, Miller TD, Gibbons RJ. Temporal trends of single-photon emission computed tomography myocardial perfusion imaging in patients with coronary artery disease: A 22-year experience from a tertiary academic medical center. Circ Cardiovasc Imaging 2017; 10(7)e005628
[http://dx.doi.org/10.1161/CIRCIMAGING.116.005628] [PMID: 28687538]
[78]
Beller GA. Decrease in the frequency of stress-induced ischemia over the past two decades. J Nucl Cardiol 2013; 20(3): 322-3.
[http://dx.doi.org/10.1007/s12350-013-9720-4] [PMID: 23636967]

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