NEGALIOJA Širdies magnetinio rezonanso tyrimo įvadinis kursas
Papildoma informacija
| Tema | Trukmė |
|---|---|
| Fizikos pagrindai, saugumas, prietaisai ir šMRT metodika | 18.00 val. |
| Išeminės širdies ligos šMRT diagnostika | 80.00 val. |
| Neišeminės kilmės širdies ligų (kardiomiopatijų, miokardito) šMRT diagnostika, šMRT taikant širdį resinchronizuojantį gydymą | 128.00 val. |
| Perikardo ligų šMRT diagnostika | 48.00 val. |
| Stambiųjų kraujagyslių ligų šMRT diagnostika | 48.00 val. |
| Širdies vožtuvų ydų šMRT diagnostika | 60.00 val. |
| Įgimtų širdies ydų šMRT diagnostika | 60.00 val. |
| Širdies darinių ir užširdinių radinių šMRT diagnostika | 24.00 val. |
| Dirbtinio intelekto (DI) taikymas šMRT | 14.00 val. |
• Klinikinių atvejų aptarimai;
• Praktinis darbas šMRT aplinkoje;
• Darbas su vaizdų analizės programine įranga;
• Individualus mokymas ir savarankiškas darbas.
• Ugdyti gebėjimą parinkti ir taikyti tinkamus šMRT protokolus pagal klinikines indikacijas;
• Išmokyti atlikti, vertinti ir interpretuoti šMRT tyrimus;
• Formuoti gebėjimą diagnozuoti pagrindines širdies ir kraujagyslių ligas naudojant šMRT;
• Užtikrinti praktinių kompetencijų įgijimą, leidžiantį savarankiškai dirbti šMRT srityje.
| Dėstytojas | Teorijos val. | Praktikos val. |
|---|---|---|
| Paulius Bučius | 10 | 46 |
| Audra Banišauskaitė | 4 | 20 |
| Justina Jurevičiūtė | 6 | 20 |
| Antanas Jankauskas | 30 | 64 |
| Tomas Lapinskas | 38 | 70 |
| Lina Padervinskienė | 28 | 60 |
| Audronė Vaitiekienė | 28 | 56 |
3 mėnesių trukmės kursą sudarys i) paskaitos – seminarai (132 val.); ii) praktiniai užsiėmimai (20 val. per savaitę), kuriuos sudarys dalyvavimas šMRT tyrimų atlikimo ir vertinimo metu; iii) savarankiškas darbas – specialistas eksperto priežiūroje turės įvertinti nemažiau kaip 200 širdies MR tyrimų.
Medicininį chalatą
Kurso dalyvių skaičius grupėje: 3–5
Fizika, saugumas, prietaisai ir širdies MR tyrimo metodika
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8. Suinesiaputra A, Bluemke DA, Cowan BR, et al. Quantification of LV function and mass by cardiovascular magnetic resonance: multi-center variability and consensus contours. J Cardiovasc Magn Reson. 2015;17(1):63. doi:10.1186/s12968-015-0170-9.
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11. Bissell MM, Raimondi F, Ait Ali L, et al. 4D Flow Cardiovascular Magnetic Resonance Consensus Statement: 2023 Update. J Cardiovasc Magn Reson. 2023;25(1):40. doi:10.1186/s12968-023-00942-z.
12. von Knobelsdorff-Brenkenhoff F, Schulz-Menger J. Cardiovascular Magnetic Resonance in the Guidelines of the European Society of Cardiology: A Comprehensive Summary and Update. J Cardiovasc Magn Reson. 2023;25(1):42. doi:10.1186/s12968-023-00950-z.
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Išeminė širdies liga
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19. Patel AR, Salerno M, Kwong RY, et al. Stress Cardiac Magnetic Resonance Myocardial Perfusion Imaging: JACC Review Topic of the Week. J Am Coll Cardiol. 2021;78(16):1655-1668. doi:10.1016/j.jacc.2021.08.022.
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24. Edvardsen T, Asch FM, Davidson B, et al. Non-Invasive Imaging in Coronary Syndromes: Recommendations of the EACVI and ASE. J Am Soc Echocardiogr. 2022;35(4):329-354. doi:10.1016/j.echo.2021.12.012.
Miokardo ligos
25. Lurz P, Luecke C, Eitel I, et al. Comprehensive Cardiac Magnetic Resonance Imaging in Patients With Suspected Myocarditis: The MyoRacer-Trial. J Am Coll Cardiol. 2016;67(15):1800-11. doi:10.1016/j.jacc.2016.02.013.
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27. Drazner MH, Bozkurt B, Cooper LT, et al. 2024 ACC Expert Consensus Decision Pathway on Strategies and Criteria for the Diagnosis and Management of Myocarditis. J Am Coll Cardiol. 2025;85(4):391-431. doi:10.1016/j.jacc.2024.10.080.
28. Arbelo E, Protonotarios A, Gimeno JR, et al. 2023 ESC Guidelines for the Management of Cardiomyopathies. Eur Heart J. 2023;44(37):3503-3626. doi:10.1093/eurheartj/ehad194.
29. Schulz-Menger J, Collini V, Gröschel J, et al. 2025 ESC Guidelines for the management of myocarditis and pericarditis: Developed by the task force for the management of myocarditis and pericarditis of the European Society of Cardiology (ESC), endorsed by the Association for European Paediatric and Congenital Cardiology (AEPC) and the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2025;46(48):5100-5180. doi:10.1093/eurheartj/ehaf120.
30. Ellims AH, Iles LM, Ling LH, et al. A comprehensive evaluation of myocardial fibrosis in hypertrophic cardiomyopathy with cardiac magnetic resonance imaging. Eur Heart J Cardiovasc Imaging. 2014;15(10):1108-16.
31. Bossone E, Lyon A, Citro R, et al. Takotsubo cardiomyopathy: an integrated multi-imaging approach. Eur Heart J Cardiovasc Imaging. 2014;15(4):366-77.
32. Smedema JP, et al. Evaluation of the accuracy of gadolinium-enhanced CMR in the diagnosis of cardiac sarcoidosis. J Am Coll Cardiol. 2005;45:1683-90.
33. Heymans S, Lakdawala NK, Tschöpe C, Klingel K. Dilated Cardiomyopathy: Causes, Mechanisms, and Current and Future Treatment Approaches. Lancet. 2023;402(10406):998-1011. doi:10.1016/S0140-6736(23)01241-2.
34. Eichhorn C, Koeckerling D, Reddy RK, et al. Risk Stratification in Nonischemic Dilated Cardiomyopathy Using CMR Imaging: A Systematic Review and Meta-Analysis. JAMA. 2024;332(12):1015-1025. doi:10.1001/jama.2024.13946.
35. Castrichini M, De Luca A, De Angelis G, et al. Magnetic Resonance Imaging Characterization and Clinical Outcomes of Dilated and Arrhythmogenic Left Ventricular Cardiomyopathies. J Am Coll Cardiol. 2024;83(19):1841-1851. doi:10.1016/j.jacc.2024.02.041.
36. Di Marco A, Brown PF, Bradley J, et al. Improved Risk Stratification for Ventricular Arrhythmias and Sudden Death in Patients With Nonischemic Dilated Cardiomyopathy. J Am Coll Cardiol. 2021;77(23):2890-2905. doi:10.1016/j.jacc.2021.04.030.
Perikardo ligos
37. Cosyns B, Plein S, Nihoyanopoulos P, et al. European Association of Cardiovascular Imaging (EACVI) position paper: multimodality imaging in pericardial disease. Eur Heart J Cardiovasc Imaging. 2015;16(1):12-31.
38. Klein AL, Wang TKM, Cremer PC, et al. Pericardial Diseases: International Position Statement on New Concepts and Advances in Multimodality Cardiac Imaging. JACC Cardiovasc Imaging. 2024;17(8):937-988. doi:10.1016/j.jcmg.2024.04.010.
39. Wang TKM, Klein AL, Cremer PC, et al. 2025 Concise Clinical Guidance: An ACC Expert Consensus Statement on the Diagnosis and Management of Pericarditis. J Am Coll Cardiol. 2025. doi:10.1016/j.jacc.2025.05.023.
40. Antonopoulos AS, Vrettos A, Androulakis E, et al. Cardiac Magnetic Resonance Imaging of Pericardial Diseases: A Comprehensive Guide. Eur Heart J Cardiovasc Imaging. 2023;24(8):983-998. doi:10.1093/ehjci/jead092.
41. Al-Kazaz M, Klein AL, Oh JK, et al. Pericardial Diseases and Best Practices for Pericardiectomy: JACC State-of-the-Art Review. J Am Coll Cardiol. 2024;84(6):561-580. doi:10.1016/j.jacc.2024.05.048.
Stambiosios kraujagyslės
42. Burman ED, Keegan J, Kilner PJ. Aortic root measurement by cardiovascular magnetic resonance: specification of planes and lines of measurement and corresponding normal values. Circ Cardiovasc Imaging. 2008;1(2):104-13.
43. Burman ED, Keegan J, Kilner PJ. Pulmonary artery diameters, cross sectional areas and area changes measured by cine cardiovascular magnetic resonance in healthy volunteers. J Cardiovasc Magn Reson. 2016;18:12.
44. Mazzolai L, Aboyans V, Agewall S, et al. 2024 ESC Guidelines for the management of peripheral arterial and aortic diseases. Eur Heart J. 2024;45(36):3538-3700. doi:10.1093/eurheartj/ehae179.
45. Isselbacher EM, Preventza O, Hamilton Black III J, et al. 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease. J Am Coll Cardiol. 2022;80(24):e223-e393. doi:10.1016/j.jacc.2022.08.004.
46. Isselbacher EM, Preventza O, Hamilton Black III J, et al. 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease. J Am Coll Cardiol. 2022;80(24):e223-e393. doi:10.1016/j.jacc.2022.08.004.
47. Kawel-Boehm N, Hetzel SJ, et al. Society for Cardiovascular Magnetic Resonance reference values ("normal values") in cardiovascular magnetic resonance: 2025 update. J Cardiovasc Magn Reson. 2025;27(1):101853. doi:10.1016/j.jocmr.2025.101853.
48. Bissell MM, Raimondi F, Ait Ali L, et al. 4D Flow Cardiovascular Magnetic Resonance Consensus Statement: 2023 Update. J Cardiovasc Magn Reson. 2023;25(1):40. doi:10.1186/s12968-023-00942-z.
Širdies vožtuvų ydos
49. Vahanian A, Beyersdorf F, Praz F, et al. 2021 ESC/EACTS Guidelines for the management of valvular heart disease. Eur Heart J. 2022;43(7):561-632. doi:10.1093/eurheartj/ehab395.
50. Otto CM, Nishimura RA, Bonow RO, et al. 2020 ACC/AHA Guideline for the Management of Patients With Valvular Heart Disease. J Am Coll Cardiol. 2021;77(4):e25-e197. doi:10.1016/j.jacc.2020.11.018.
51. Zoghbi WA, Adams D, Bonow RO, et al. Recommendations for Noninvasive Evaluation of Native Valvular Regurgitation: A Report from the ASE/EACVI. J Am Soc Echocardiogr. 2017;30(4):303-371. doi:10.1016/j.echo.2017.01.007.
52. Myerson SG. Heart valve disease: investigation by cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2012;14:7. doi:10.1186/1532-429X-14-7.
53. Uretsky S, Gillam L, Lang R, et al. Discordance between echocardiography and MRI in the assessment of mitral regurgitation severity: a prospective multicenter trial. J Am Coll Cardiol. 2015;65(11):1078-1088. doi:10.1016/j.jacc.2014.12.047.
54. Myerson SG. CMR in Evaluating Valvular Heart Disease: Diagnosis, Severity, and Outcomes. JACC Cardiovasc Imaging. 2021;14(10):2020-2032. doi:10.1016/j.jcmg.2020.09.029.
55. Dweck MR, Joshi S, Murigu T, et al. Midwall fibrosis is an independent predictor of mortality in patients with aortic stenosis. J Am Coll Cardiol. 2011;58(12):1271-1279. doi:10.1016/j.jacc.2011.03.064.
56. Gorecka M, Bissell MM, Higgins DM, et al. Rationale and Clinical Applications of 4D Flow Cardiovascular Magnetic Resonance in Assessment of Valvular Heart Disease: A Comprehensive Review. J Cardiovasc Magn Reson. 2022;24(1):49. doi:10.1186/s12968-022-00882-0.
Širdies dariniai
57. Motwani M, Kidambi A, Herzog BA, et al. MR imaging of cardiac tumors and masses: a review of methods and clinical applications. Radiology. 2013;268(1):26-43. doi:10.1148/radiol.13121233.
58. Srichai MB, Junor C, Rodriguez LL, et al. Clinical, imaging, and pathologic characteristics of cardiac masses. JACC Cardiovasc Imaging. 2011;4(7):725-734. doi:10.1016/j.jcmg.2011.04.009.
59. Pazos-López P, Pozo E, Siqueira ME, et al. Value of CMR for the differential diagnosis of cardiac masses. JACC Cardiovasc Imaging. 2014;7(9):896-905. doi:10.1016/j.jcmg.2014.05.009.
60. Rahsepar AA, Delgado V, Bax JJ, et al. Multimodality imaging of cardiac tumors: part 1 and part 2. JACC Cardiovasc Imaging. 2020;13(8):1812-1832. doi:10.1016/j.jcmg.2020.03.020.
Įgimtos širdies ydos
61. Stout KK, Daniels CJ, Aboulhosn JA, et al. 2018 AHA/ACC Guideline for the Management of Adults With Congenital Heart Disease. J Am Coll Cardiol. 2019;73(12):e81-e192. doi:10.1016/j.jacc.2018.08.1029.
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63. Kilner PJ, Geva T, Kaemmerer H, et al. Recommendations for cardiovascular magnetic resonance in adults with congenital heart disease from the SCMR. J Cardiovasc Magn Reson. 2010;12:26. doi:10.1186/1532-429X-12-26.
64. Fratz S, Chung T, Greil GF, et al. Guidelines and protocols for cardiovascular magnetic resonance in children and adults with congenital heart disease. J Cardiovasc Magn Reson. 2013;15:51. doi:10.1186/1532-429X-15-51.
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Atsitiktiniai (užširdiniai) dariniai
66. Rodrigues JC, Lyen SM, Loughborough W, et al. Extra-cardiac findings in cardiovascular magnetic resonance: what the imaging cardiologist needs to know. J Cardiovasc Magn Reson. 2016;18(1):26. doi:10.1186/s12968-016-0246-1.
67. Irwin RB, Newton T, Peebles C, et al. Incidental extra-cardiac findings on clinical CMR. Eur Heart J Cardiovasc Imaging. 2013;14(2):158-166. doi:10.1093/ehjci/jes133.
68. Sohns JM, Staab W, Sohns C, et al. Incidental extracardiac findings in cardiovascular magnetic resonance imaging: frequency and clinical relevance. Eur Radiol. 2014;24(4):818-826. doi:10.1007/s00330-013-3078-1.
Dirbtinio intelekto (DI) taikymas šMRT
69. Petersen SE, Abdulkareem M, Leiner T, et al. Artificial intelligence will transform cardiac imaging – opportunities and challenges. Eur Heart J. 2019;40(25):1977-1980. doi:10.1093/eurheartj/ehz682.
70. Bai W, Sinclair M, Tarroni G, et al. Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. J Cardiovasc Magn Reson. 2018;20(1):65. doi:10.1186/s12968-018-0471-x.
71. Neisius U, El-Rewaidy H, Nakamori S, et al. Artificial intelligence in cardiovascular magnetic resonance: current applications and future directions. J Cardiovasc Magn Reson. 2023;25(1):17. doi:10.1186/s12968-023-00914-3.