Determination of Characteristics of Infectious Endocarditis Based on Intelligent Processing of Ultrasonic Images
DOI:
https://doi.org/10.18372/1990-5548.74.17292Keywords:
echocardiography, endocarditis, valve disease, intelligent processing, echographic imagesAbstract
The paper presents the pathogenetic factors in the development of infective endocarditis and identifies its predictors. The need for an echographic study associated with the search for the anatomical characteristics of infective endocarditis is shown: vegetation, destructive lesions (valve aneurysms, perforation or prolapse, etc.), the presence of abscesses, in the case of a prosthesis, a new divergence of the valve prosthesis may be a characteristic feature. A classification of research methods is presented that includes classical approaches of echocardiography (transthoracic, transesophageal) and new multidetector computed tomographic angiography and positron emission tomography with 18F-fluorodeoxyglucose and the need for their use in different cases is determined. A block diagram of an intelligent diagnostic system for infective endocarditis has been developed. To process the obtained images in order to diagnose and determine the geometric dimensions, shapes, quantity, location, characteristics of infective endocarditis, it is proposed to use convolutional neural networks that allow solving the problem of image segmentation.
References
G. Habib, B. Hoen, P. Tornos, F. Thuny, B. Prendergast, I. Vilacosta, et al., “ESC Committee for Practice Guidelines (CPG). Guidelines on the prevention, diagnosis, and treatment of infective endocarditis (new version 2009): The Task Force on the Prevention,” Diagnosis, and Treatment of Infective Endocarditis of the European Society of Cardiology (ESC). Eur Heart J, 2009, 30:2369–413. https://doi.org/10.1093/eurheartj/ehp285.
Gilbert Habib, Luigi Badano, Christophe Tribouilloy, Isidre Vilacosta, and Jose Luis Zamorano, “Recommendations for the practice of echocardiography in infective endocarditis,” European Journal of Echocardiography (2010) 11, 202–219. https://doi.org/10.1093/ejechocard/jeq004.
D. G. Karalis, R. C. Bansal, AJ Hauck, J. J. Jr. Ross, P. M. Applegate, K. R. Jutzy, et al., “Transesophageal echocardiographic recognition of subaortic complications in aortic valve endocarditis. Clinical and surgical implications,” Circulation, 1992, 86:353–62. https://doi.org/10.1161/01.CIR.86.2.353.
W. G. Daniel, A. Mügge, R. P. Martin, et al., “Improvement in the diagnosis of abscesses associated with endocarditis by transesophageal echocardiography,” N Engl J Med, 1991; 324:795–800. https://doi.org/10.1056/NEJM199103213241203
G. Di Salvo, G. Habib, V. Pergola, J. F. Avierinos, E. Phlip, J. P. Casalta. et al., “Echocardiography predicts embolic events in infective endocarditis,” J Am Coll Cardiol, 2001, 37:1069–76. https://doi.org/10.1016/S0735-1097(00)01206-7.
F. Thuny, G. Di Salvo, O. Belliard, J. F. Avierinos, V. Pergola, V. Rosenberg, et al., “Risk of embolism and death in infective endocarditis: prognostic value of echocardiography: a prospective multicenter study,” Circulation, 2005, 112:69–75. https://doi.org/10.1161/CIRCULATIONAHA.104.493155.
I. Vilacosta, C. Graupner, J. A. San Roman, C. Sarria, R. Ronderos, C. Fernandez, et al., “Risk of embolization after institution of antibiotic therapy for infective endocardi tis,” J Am Coll Cardiol, 2002, 39:1489–95. https://doi.org/10.1016/S0735-1097(02)01790-4.
R. Erbel, F. Liu, J. Ge, S. Rohmann, I. Kupferwasser, “Identification of high-risk subgroups in infective endocarditis and the role of echocardiography,” Eur Heart J, 1995, 16:588–602. https://doi.org/10.1093/oxfordjournals.eurheartj.a060961.
A. J. Sanfilippo, M. H. Picard, J. B. Newell, E. Rosas, R Davidoff, J. D. Thomas, et al., “Echocardiographic assessment of patients with infectious endocarditis: prediction of risk for complication,” J Am Coll Cardiol, 1991, 18:1191–9. https://doi.org/10.1016/0735-1097(91)90535-H.
A. Mugge, W. G. Daniel, G. Frank, P. R. Lichtlen, “Echocardiography in infective endocarditis: reassessment of prognostic implications of vegetation size determined by the transthoracic and the transesophageal approach,” J Am Coll Cardiol, 1989, 14:631–8. https://doi.org/10.1016/0735-1097(89)90104-6.
S. A. Dickerman, E. Abrutyn, B. Barsic, E. Bouza, E. Cecchi, A. Moreno. et al., “The relationship between the initiation of antimicrobial therapy and the incidence of stroke in infective endocarditis: an analysis from the ICE Prospective Cohort Study (ICE-PCS),” Am Heart J, 2007, 154:1086–94. https://doi.org/10.1016/j.ahj.2007.07.023.
C. H. Cabell, K. K. Pond, G. E. Peterson, D. T. Durack, G. R. Corey, D. J. Anderson, et al., “The risk of stroke and death in patients with aortic and mitral valve endocarditis,” Am Heart J, 2001, 142:75–80. https://doi.org/10.1067/mhj.2001.115790.
S. Rohmann, R. Erbel, H. Darius, G. Gorge, T. Makowski, R. Zotz et al. "Prediction of rapid versus prolonged healing of infective endocarditis by monitoring vegetation size," J Am Soc Echocardiogr, 1991; 4:465–74. https://doi.org/10.1016/S0894-7317(14)80380-5.
A. Bayer, A. Bolger, K. Taubert, W. Wilson, J. Steckelberg, A. Karchmer, et al., “Diagnosis and management of infective endocarditis and its complications,” Circulation, 1998, 98: 2936–48. https://doi.org/10.1161/01.CIR.98.25.2936.
Anna Gomes, Peter Paul van Geel, Michiel Santing, Niek H. J. Prakken, Mathilde L. Ruis, Sander van Assen, Riemer H. J. A. Slart, Bhanu Sinha, Andor W. J. M. Glaudemans, “Imaging infective endocarditis: Adherence to a diagnostic flowchart and direct comparison of imaging techniques,” Journal of Nuclear Cardiology, vol. 27, no. 2, pp. 592–608. https://doi.org/10.1007/s12350-018-1383-8.
Michael Z. Zgurovsky, Viktor M. Sineglazov, Olena I. Chumachenko, Artificial Intelligence Systems Based on Hybrid Neural Networks, Springer, 2020, https://link.springer.com/book/10.1007/978-3-030-48453-8. Customer can order it via https://www.springer.com/gp/book/9783030484521
Victor Sineglazov, Kirill Riazanovskiy, Alexander Klanovets, Elena Chumachenko, Nikolai Linnik, "Intelligent tuberculosis activity assessment system based on an ensemble of neural networks," Computers in Biology and Medicine, vol. 147, August 2022, 105800. https://doi.org/10.1016/j.compbiomed.2022.105800.
B. Tapasvi, Dr. N. Udaya Kumar, and Dr. E. Gnanamanoharan, "A Survey on Semantic Segmenta-tion using Deep Learning Techniques," International Journal of Engineering Research & Technology (IJERT) ICRADL, Issue 05, vol. 09, 2021.
G. Habib, P. Lancellotti, M. J. Antunes, M. G. Bongiorni, J. P. Casalta, F. Del Zotti, et al., “ESC Guidelines for the management of infective endocarditis: the task force for the management of infective endocarditis of the European Society of Cardiology (ESC),” Endorsed by: European Association for Cardio-Thoracic Surgery (EACTS), the European Association of Nuclear Medicine (EANM). Eur Heart J., 2015, 36:3075–128. https://doi.org/10.1093/eurheartj/ehv319.
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