Preview

Нервно-мышечные болезни

Расширенный поиск

РОЛЬ КОЛИЧЕСТВЕННОЙ МАГНИТНО-РЕЗОНАНСНОЙ ТОМОГРАФИИ И СПЕКТРОСКОПИИ СКЕЛЕТНЫХ МЫШЦ В ОЦЕНКЕ РЕЗУЛЬТАТОВ КЛИНИЧЕСКИХ ИССЛЕДОВАНИЙ (ЧАСТЬ I)


https://doi.org/10.17650/2222-8721-2016-6-4-10-20

Полный текст:

Аннотация

В последние годы наблюдается прогресс в терапии многих ранее считавшихся неизлечимыми нервно-мышечных болезней. Это служит толчком для разработки новых неинвазивных методов оценки результатов лечения. Данные методы можно разделить на 3 основные категории: функциональные пробы, биологические маркеры различных жидкостей организма и методы формирования изображений. Среди последних ядерная магнитно-резонансная томография (МРТ) предлагает большой спектр возможностей для определения таких характеристик скелетных мышц, как состав, функция и метаболизм. Сегодня в протоколы клинического исследования обычно входят следующие 3 метода оценки МРТ: 1) анализ площади поперечного сечения или объема мышц; 2) процент внутримышечного жира; 3) количество воды в режиме Т2. Эти методы отражают соответственно количественную характеристику трофики мышц, хронические жировые дегенеративные изменения и отек (или в более широком смысле «активность болезни»). Из первых двух следует 4-й биомаркер – объем сократительной ткани. Картирование жировой фракции, получаемое в режиме Dixon, доказало свою способность обнаруживать небольшие изменения в составе мышц и неоднократно демонстрировало высокую чувствительность по сравнению со стандартной функциональной оценкой. Данный способ оценки результатов, вероятнее всего, будет утвержден регулирующими органами.

Универсальность контрастных агентов, применяемых при МРТ,  предоставляет множество дополнительных возможностей для определения характеристик скелетных мышц, что приведет к увеличению количества предлагаемых биомаркеров. Ультракороткое время появления эхо-сигнала (ultra-shortechotime, UTE), усиление гадолинием и МРТ-эластография изучаются в качестве кандидатов для оценки интерстициального фиброза скелетных мышц. Существует несколько способов измерения мышечной перфузии и оксигенации  с помощью МРТ.  Режим магнитно-резонансной (МР)  диффузии, аналогично алгоритмам анализа структуры ткани, может давать дополнительную информацию о мышечной организации на микрои мезоскопическом уровнях [1]. Спектроскопия по фосфору 31P является эталонным методом для неинвазивной оценки мышечной активности во время и после тренировки. Спектроскопия по фосфору 31Р в дистрофичной мышце в состоянии покоя [1] проявляется значительными нарушениями, а отдельные резонансные пики могут давать информацию о целостности клеточных мембран.

Значительные усилия направлены в сторону уменьшения времени формирования изображений с помощью различных подходов, таких как выделение сигналов жира и воды на Т2-картированных изображениях, сформированных либо по одному МР-сканированию, либо с использованием нескольких МР-сканирований. В ближайшем будущем ожидается эффективное уменьшение длительности обследования. Это увеличит привлекательность метода оценки результатов МРТ мышц и будет в дальнейшем содействовать его интеграции в клинические исследовательские испытания.

Об авторах

P. G. Carlier
Institute of Myology, Pitie-Salpetriere University Hospital; CEA, DSV, I2BM, MIRCen, NMR Laboratory; National Academy of Sciences, United Institute for Informatics Problems
Франция


B. Marty
Institute of Myology, Pitie-Salpetriere University Hospital; CEA, DSV, I2BM, MIRCen, NMR Laboratory
Франция


O. Scheidegger
Institute of Myology, Pitie-Salpetriere University Hospital; Support Center for Advanced Neuroimaging (SCAN), Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern
Франция


P. Loureiro de Sousa
Strasbourg University, CNRS, ICube
Франция


P.-Y. Baudin
Consultants for Research in Imaging and Spectroscopy
Бельгия


Е. Snezhko
National Academy of Sciences, United Institute for Informatics Problems
Беларусь


D. Vlodavets
N.I. Prirogov Russian National Medical Research University, Clinical Research Institute of Pediatrics
Россия


Список литературы

1. Bryant N.D., Li K., Does M.D. et al. Multi-parametric MRI characterization of inflammation in murine skeletal muscle. NMR Biomed 2014;27:716–25.

2. Arechavala-Gomeza V., Anthony K., Morgan J., Muntoni F. Antisense oligonucleotide-mediated exon skipping for Duchenne muscular dystrophy: Progress and challenges. Curr Gene Ther 2012;12:152–60.

3. Blat Y., Blat S. Drug discovery of therapies for duchenne muscular dystrophy. J Biomol Screen 2015;10:1189–203. Epub 2015 May 14.

4. Bushby K., Finkel R., Wong B. et al. Ataluren treatment of patients with nonsense mutation dystrophinopathy. Muscle Nerve 2014;50:477–87.

5. Buyse G.M., Voit T., Schara U. et al. Efficacy of idebenone on respiratory function in patients with Duchenne muscular dystrophy not using glucocorticoids (DELOS): A double-blind randomised placebo-controlled phase 3 trial. Lancet 2015;385:1748–57.

6. Cirak S., Arechavala-Gomeza V., Guglieri M. et al. Exon skipping and dystrophin restoration in patients with Duchenne muscular dystrophy after systemic phosphorodiamidate morpholino oligomer treatment: An openlabel, phase 2, dose-escalation study. Lancet 2011;378:595–605.

7. Douglas A.G.L., Wood M.J.A. Splicing therapy for neuromuscular disease. Mol Cell Neurosci 2013;56:169–85.

8. Erriquez D., Perini G., Ferlini A. Noncoding RNAs in muscle dystrophies. Int J Mol Sci 2013;14:19681–704.

9. Mercuri E., Muntoni F. Muscular dystrophy: New challenges and review of the current clinical trials. Curr Opin Pediatr 2013;25:701–7.

10. Muntoni F., Wood M.J.A. Targeting RNA to treat neuromuscular disease. Nat Rev Drug Discov 2011;10:621–37.

11. Scotter E.L., Shaw C.E. Neuromuscular disease: New insights and avenues for therapy. Lancet Neurol 2013;12:13–5.

12. Touznik A., Lee J.J.A., Yokota T. New developments in exon skipping and splice modulation therapies for neuromuscular diseases. Expert Opin Biol Ther 2014;14: 809–19.

13. Voit T., Topaloglu H., Straub V. et al. Safety and efficacy of drisapersen for the treatment of Duchenne muscular dystrophy (DEMAND II): An exploratory, randomised, placebocontrolled phase 2 study. Lancet Neurol 2014;13:987–96.

14. Decostre V., Canal A., Ollivier G. et al. Wrist flexion and extension torques measured by highly sensitive dynamometer in healthy subjects from 5 to 80 years. BMC Musculoskelet Disord 2015;16:4. Epub 2015 Jan 31.

15. Hogrel J.-Y., Allenbach Y., Canal A. et al. Four-year longitudinal study of clinical and functional endpoints in sporadic inclusion body myositis: Implications for therapeutic trials. Neuromuscul Disord 2014;24:604–10.

16. Lynn S., Aartsma-Rus A., Bushby K. et al. Measuring clinical effectiveness of medicinal products for the treatment of Duchenne muscular dystrophy. Neuromuscul Disord 2015;25:96–105.

17. Mayhew A., Mazzone E.S., Eagle M. et al. Development of the performance of the upper limb module for Duchenne muscular dystrophy. Dev Med Child Neurol 2013;55:1038–45.

18. Mazzone E., De Sanctis R., Fanelli L. et al. Hammersmith functional motor scale and motor function measure-20 in non ambulant SMA patients. Neuromuscul Disord 2014;24:347–52.

19. Mazzone E.S., Vasco G., Palermo C. et al. A critical review of functional assessment tools for upper limbs in Duchenne muscular dystrophy. Dev Med Child Neurol 2012;54:879–85.

20. McDonald C.M., Henricson E.K., Abresch R.T. et al. The 6-minute walk test and other clinical endpoints in duchenne muscular dystrophy: Reliability, concurrent validity, and minimal clinically important differences from a multicenter study. Muscle Nerve 2013;48:357–68.

21. Pane M., Mazzone E.S., Sormani M.P. et al. 6 Minute walk test in Duchenne MD patients with different mutations: 12 month changes. PLoS One 2014;9:e83400.

22. Scott E., Eagle M., Mayhew A. et al. Development of a functional assessment scale for ambulatory boys with Duchenne muscular dystrophy. Physiother Res Int 2012;17:101–9.

23. Seferian A.M., Moraux A., Annoussamy M. et al. Upper limb strength and function changes during a one-year follow-up in nonambulant patients with Duchenne Muscular Dystrophy: An observational multicenter trial. PLoS One 2015a;10:e0113999.

24. Seferian A.M., Moraux A., Canal A. et al. Upper limb evaluation and one-year follow up of non-ambulant patients with spinal muscular atrophy: An observational multicenter trial. PLoS One 2015b;10:e0121799.

25. Servais L., Deconinck N., Moraux A. et al. Innovative methods to assess upper limb strength and function in non-ambulant Duchenne patients. Neuromuscul Disord 2013;23:139–48.

26. Strimbu K., Tavel J.A. What are biomarkers? Curr Opin HIV AIDS 2010;5:463–6.

27. Vasan R.S. Biomarkers of cardiovascular disease: Molecular basis and practical considerations. Circulation 2006;113:2335–62.

28. Tofts P.S. Quantitative MRI of the brain: Measuring changes caused by disease. John Wiley, 2003.

29. Hollingsworth K.G., de Sousa P.L., Straub V., Carlier P.G. Towards harmonization of protocols for MRI outcome measures in skeletal muscle studies: Consensus recommendations from two TREAT-NMD NMR workshops, 2 May 2010, Stockholm, Sweden, 1–2 October 2009, Paris, France. Neuromuscul Disord 2012;22(Suppl 2): S54–67.

30. Hunter D.J., Zhang W., Conaghan P.G. et al. Systematic review of the concurrent and predictive validity of MRI biomarkers in OA. Osteoarthr Cartil 2011;19: 557–88.

31. Jovicich J., Marizzoni M., Sala-Llonch R. et al. Brain morphometry reproducibility in multi-center 3T MRI studies: Acomparison of cross-sectional and longitudinal segmentations. Neuroimage 2013;83:472–84.

32. Mills K.L., Tamnes C.K. Methods and considerations for longitudinal structural brain imaging analysis across development. Dev Cogn Neurosci 2014;9:172–90.

33. Xi W., Perdanasari A.T., Ong Y. et al. Objective breast volume, shape and surface area assessment: a systematic review of breast measurement methods. Aesthetic Plast Surg 2014;38:1116–30.

34. Mitsiopoulos N., Baumgartner R.N., Heymsfield S.B. et al. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol 1998;85:115–22.

35. Barnouin Y., Butler-Browne G., Voit T. et al. Manual segmentation of individual muscles of the quadriceps femoris using MRI: A reappraisal. J Magn Reson Imaging 2014;40:239–47.

36. Fischmann A., Hafner P., Gloor M. et al. Quantitative MRI and loss of free ambulation in Duchenne muscular dystrophy. J Neurol 2013;260:969–74.

37. Thomas M.S., Newman D., Leinhard O.D. et al. Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system. Eur Radiol 2014;24:2279–91.

38. Wagner K.R., Fleckenstein J.L., Amato A.A. et al. A phase I/IItrial of MYO-029 in adult subjects with muscular dystrophy. Ann Neurol 2008;63:561–71.

39. e Lima K.M.M., da Matta T.T., de Oliveira L.F. Reliability of the rectus femoris muscle cross-sectional area measurements by ultrasonography. Clin Physiol Funct Imaging 2012;32:221–6.

40. Strandberg S., Wretling M.-L., Wredmark T., Shalabi A. Reliability of computed tomography measurements in assessment of thigh muscle cross-sectional area and attenuation. BMC Med Imaging 2010;10:18.

41. Williams S.A., Reid S., Elliott C. et al. Muscle volume alterations in spastic muscles immediately following botulinum toxin type-A treatment in children with cerebral palsy. Dev Med Child Neurol 2013;55:813–20.

42. Smeulders M.J.C., van den Berg S., Oudeman J. et al. Reliability of in vivo determination of forearm muscle volume using 3.0 T magnetic resonance imaging. J Magn Reson Imaging 2010;31:1252–5.

43. Yasuda T., Loenneke J.P., Thiebaud R.S., Abe T. Effects of detraining after blood flowrestricted low-intensity concentric or eccentric training on muscle size and strength. J Physiol Sci 2015;65:139–44.

44. Wokke B.H., van den Bergen J.C., Versluis M.J. et al. Quantitative MRI and strength measurements in the assessment of muscle quality in Duchenne muscular dystrophy. Neuromuscul Disord 2014b;24:409–16.

45. Hogrel J.-Y., Barnouin Y., Azzabou N. et al. NMR imaging estimates of muscle volume and intramuscular fat infiltration in the thigh: Variations with muscle, gender, and age. Age 2015;37(3):9798.

46. Morse C.I., Degens H., Jones D.A. The validity of estimating quadriceps volume from single MRI cross-sections in young men. Eur J Appl Physiol 2007;100:267–74.

47. Tanaka N.I., Kanehisa H. Applicability of single muscle CSA for predicting segmental muscle volume in young men. Int J Sports Med 2014;35:608–14.

48. Fischmann A., Morrow J.M., Sinclair C.D.J. et al. Improved anatomical reproducibility in quantitative lower-limb muscle MRI. J Magn Reson Imaging 2014;39:1033–8.

49. Ravaglia S., Pichiecchio A., Ponzio M. et al. Changes in skeletal muscle qualities during enzyme replacement therapy in lateonset type II glycogenosis: Temporal and spatial pattern of mass vs. strength response. J Inherit Metab Dis 2010;33:737–45.

50. Morrow J.M., Sinclair C.D.J., Fischmann A. et al. MRI biomarker assessment of neuromuscular disease progression: A prospective observational cohort study. Lancet Neurol 2015;4422:1–13.

51. Sproule D.M., Montgomery M.J., Punyanitya M. et al. Thigh muscle volume measured by magnetic resonance imaging is stable over a 6-month interval in spinal muscular atrophy. J Child Neurol 2011;26:1252–9.

52. Karlsson A., Rosander J., Romu T. et al. Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water-fat MRI. J Magn Reson Imaging 2015;41: 1558–69.

53. Mattei J.P., Le Fur Y., Cuge N. et al. Segmentation of fascias, fat and muscle from magnetic resonance images in humans: The DISPIMAG software. Magn Reson Mater Physics Biol Med 2006;19:275–9.

54. Kornegay J.N., Bogan J.R., Bogan D.J. et al. Canine models of Duchenne muscular dystrophy and their use in therapeutic strategies. Mamm Genome 2012;23:85–108.

55. Carlier P.G., Shukelovich A., Baudin P.Y. et al. Fast, precise, interactive segmentation of skeletal muscle NMR images. Neuromuscul Disord 2014;24:836–37.

56. Bley T.A., Wieben O., Francois C.J. et al. Fat and water magnetic resonance imaging. J Magn Reson Imaging 2010;31:4–18.

57. Hu H.H., Kan H.E. Quantitative proton MR techniques for measuring fat. NMR Biomed 2013;26:1609–29.

58. Lamminen A.E. Magnetic resonance imaging of primary skeletal muscle diseases: Patterns of distribution and severity of involvement. Br J Radiol 1990;63:946–50.

59. Willis T.A., Hollingsworth K.G., Coombs A. et al. Quantitative muscle MRI as an assessment tool for monitoring disease progression in LGMD2I: a multicentre longitudinal study. PLoS One 2013;8:e70993.

60. Leroy-Willig A., Willig T.N., HenryFeugeas M.C. et al. Body composition determined with MR in patients with Duchenne muscular dystrophy, spinal muscular atrophy, and normal subjects. Magn Reson Imaging 1997;15:737–44.

61. Pichiecchio A., Uggetti C., Egitto M.G. et al. Quantitative MR evaluation of body composition in patients with Duchenne muscular dystrophy. Eur Radiol 2002;12:2704–9.

62. Ma J. Dixon techniques for water and fat imaging. J Magn Reson Imaging 2008;28:543–58.

63. Wokke B.H., Bos C., Reijnierse M. et al. Comparison of dixon and T1-weighted MR methods to assess the degree of fat infiltration in duchenne muscular dystrophy patients. J Magn Reson Imaging 2013;38:619–24.

64. Hu H.H., Börnert P., Hernando D. et al. ISMRM workshop on fat-water separation: Insights, applications and progress in MRI. Magn Reson Med. 2012;68:378–88.

65. Azzabou N., Loureiro de Sousa P., Caldas E., Carlier P.G. Validation of a generic approach to muscle water T2 determination at 3T in fatinfiltrated skeletal muscle. J Magn Reson Imaging 2015b;41:645–53.

66. Longo R., Pollesello P., Ricci C. et al. Proton MR spectroscopy in quantitative in vivo determination of fat content in human liver steatosis. J Magn Reson Imaging 1995;5:281–5.

67. Azzabou N., Carlier P.G. Fat quantification and T2 measurement. Pediatr Radiol 2014;44:1620–1.

68. Kim H.K,. Serai S., Merrow A.C. et al. Objective measurement of minimal fat in normal skeletal muscles of healthy children using T2 relaxation time mapping (T2 maps) and MR spectroscopy. Pediatr Radiol 2014;44:149–57.

69. Forbes S.C., Willcocks R.J., Triplett W.T. et al. Magnetic resonance imaging and spectroscopy assessment of lower extremity skeletal muscles in boys with Duchenne muscular dystrophy: a multicenter cross sectional study. PLoS One 2014;9:e106435.

70. Garrood P., Hollingsworth K.G., Eagle M. et al. MR imaging in Duchenne muscular dystrophy: quantification of T1-weighted signal, contrast uptake, and the effects of exercise. J Magn Reson Imaging 2009;30:1130–8.

71. Kim H.K., Laor T., Horn P.S. et al. T2 mapping in Duchenne muscular dystrophy: Distribution of disease activity and correlation with clinical assessments. Radiology 2010;255:899–908.

72. Kim H.K., Serai S., Lindquist D. et al. Quantitative Skeletal Muscle MRI: Part 2, MR Spectroscopy and T2 Relaxation Time Mapping-Comparison Between Boys With Duchenne Muscular Dystrophy and Healthy Boys. Amer J Roentgenol 2015;205:216–23.

73. Willcocks R.J., Arpan I.A, Forbes S.C. et al. Longitudinal measurements of MRI-T2 in boys with Duchenne muscular dystrophy: effects of age and disease progression. Neuromuscul Disord 2014;24:393–401.

74. Carlier P.G. Global T2 versus water T2 in NMR imaging of fatty infiltrated muscles: different methodology, different information and different implications. Neuromuscul Disord 2014;24:390–2.

75. Bonati U., Schmid M., Hafner P. et al. Longitudinal 2-point dixon muscle magnetic resonance imaging in becker muscular dystrophy. Muscle Nerve 2015b;51:918–21.

76. Hogrel J.Y., Wary C., Moraux A. et al. Longitudinal functional and NMR assessment of upper limbs in Duchenne muscular dystrophy. Neurology 2016: epub ahead of print.

77. Wary C., Azzabou N., Giraudeau C. et al. Quantitative NMRI and NMRS identify augmented disease progression after loss of ambulation in forearms of boys with Duchenne muscular dystrophy. NMR Biomed 2015b;28:1150–62.

78. Arpan I., Willcocks R.J., Forbes S.C. et al. Examination of effects of corticosteroids on skeletal muscles of boys with DMD using MRI and MRS. Neurology 2014;83: 974–80.

79. Hollingsworth K.G., Garrood P., Eagle M. et al. Magnetic resonance imaging in Duchenne muscular dystrophy: Longitudinal assessment of natural history over 18 months. Muscle Nerve 2013a;48:586–8.

80. Janssen B.H., Voet N.B.M., Nabuurs C.I. et al. Distinct disease phases in muscles of facioscapulohumera dystrophy patients identified by MR detected fat Infiltration. PLoS One 2014;9:e85416.

81. Fischmann A., Hafner P., Fasler S. et al. Quantitative MRI can detect subclinical disease progression in muscular dystrophy. J Neurol 2012;259:1648–54.

82. Carlier P.G., Azzabou N., de Sousa P.L. et al. Skeletal muscle quantitative nuclear magnetic resonance imaging follow-up of adult Pompe patients. J Inherit Metab Dis 2015;38:565–72.

83. Nardo L., Karampinos D.C., Lansdown D.A. et al. Quantitative assessment of fat infiltration in the rotator cuff muscles using water-fat MRI. J Magn Reson Imaging 2014;39: 1178–85.

84. Nozaki T., Tasaki A., Horiuchi S. et al. Quantification of fatty degeneration within the supraspinatus muscle by using a 2-point dixon method on 3-T MRI. Amer J Roentgenol 2015;205:116–22.

85. Bryan W.W., Reisch J.S., McDonald G. et al. Magnetic resonance imaging of muscle in amyotrophic lateral sclerosis. Neurology 1998;51:110–3.

86. Karampinos D.C., Baum T., Nardo L. et al. Characterization of the regional distribution of skeletal muscle adipose tissue in type 2 diabetes using chemical shift-based water/fat separation. J Magn Reson Imaging 2012;35:899–907.

87. Lee Y.H., Lee H.S., Lee H.E. et al. Whole-body muscle MRI in patients with hyperkalemic periodic paralysis carrying the SCN4A mutation T704M: evidence for chronic progressive myopathy with selective muscle involvement. J Clin Neurol 2015;11:331–8.

88. Alizai H., Nardo L., Karampinos D.C. et al. Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shiftbasedwater/fat separation inMRstudies of the calf of post-menopausal women. Eur Radiol 2012;22:1592–600.

89. Azzabou N., Hogrel J.-Y., Carlier P.G. NMR based biomarkers to study age-related changes in the human quadriceps. Exp Gerontol 2015a;70:54–60.

90. Csapo R., Malis V., Sinha U. et al. Ageassociated differences in triceps surae muscle composition and strength – an MRI-based cross-sectional comparison of contractile, adipose and connective tissue. BMC Musculoskelet Disord 2014;15:209. Epub 2014 Jun 17.

91. Morrow J.M., Sinclair C.D.J., Fischmann A. et al. Reproducibility, and age, body-weight and gender dependency of candidate skeletal muscle MRI outcome measures in healthy volunteers. Eur Radiol 2014;24:1610–20.

92. Schwenzer N.F., Martirosian P., Machann J. et al. Aging effects on human calf muscle properties assessed by MRI at 3 Tesla. J Magn Reson Imaging 2009a;29: 1346–54.

93. Bonati U., Hafner P., Schädelin S. et al. Quantitative muscle MRI: A powerful surrogate outcome measure in Duchenne muscular dystrophy. Neuromuscul Disord 2015a;25:679–85.

94. Wary C., Azzabou N., Giraudeau C. et al. Quantitative NMRI and NMRS identify augmented disease progression after loss of ambulation in forearms of boys with Duchenne muscular dystrophy. NMR Biomed 2015a;28:1150–62.


Для цитирования:


Carlier P.G., Marty B., Scheidegger O., Loureiro de Sousa P., Baudin P., Snezhko Е., Vlodavets D. РОЛЬ КОЛИЧЕСТВЕННОЙ МАГНИТНО-РЕЗОНАНСНОЙ ТОМОГРАФИИ И СПЕКТРОСКОПИИ СКЕЛЕТНЫХ МЫШЦ В ОЦЕНКЕ РЕЗУЛЬТАТОВ КЛИНИЧЕСКИХ ИССЛЕДОВАНИЙ (ЧАСТЬ I). Нервно-мышечные болезни. 2016;6(4):10-20. https://doi.org/10.17650/2222-8721-2016-6-4-10-20

For citation:


Carlier P.G., Marty B., Scheidegger O., Loureiro de Sousa P., Baudin P.Y., Snezhko Е., Vlodavets D. SKELETAL MUSCLE QUANTITATIVE NUCLEAR MAGNETIC RESONANCE IMAGING AND SPECTROSCOPY AS AN OUTCOME MEASURE FOR CLINICAL TRIALS (PART I). Neuromuscular Diseases. 2016;6(4):10-20. (In Russ.) https://doi.org/10.17650/2222-8721-2016-6-4-10-20

Просмотров: 250


Creative Commons License
Контент доступен под лицензией Creative Commons Attribution 4.0 License.


ISSN 2222-8721 (Print)
ISSN 2413-0443 (Online)