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DOI 10.34014/2227-1848-2024-3-6-16

RATING SCALES AND INDICATORS OF DIFFUSION TENSOR IMAGING IN PREDICTING MOTOR DEFICIT REGRESSION IN PATIENTS WITH CEREBRAL STROKE

R.R. Gizatullin1, L.R. Akhmadeeva1,2, D.E. Baykov1, G.V. Baykova1

1 Bashkir State Medical University, Ministry of Health of the Russian Federation, Ufa, Russia;

2 Bashkortostan Academy of Sciences, Ufa, Russia

 

Stroke and subsequent movement disorders are a significant medical and social problem. In 2021, 500 thousand newly diagnosed strokes were registered in the Russian Federation. No more than 10 % of people return to work within the first year after a stroke, 30 % remain disabled for life. In this regard, it is the relevant to predict motor disease outcomes at different periods in patients with a cerebral stroke. The currently existing severity scales are mostly used to characterize early movement disorders, and long-term effects often remain unassessed. There are no methods for predicting the degree of movement disorders in patients with a cerebral stroke in the long term. Objectively, information on the ratio of the level of brain damage and the likelihood of subsequent motor deficit improvement in vivo can be obtained from neuroimaging images. Predicting the severity of movement disorders is potentially possible by analyzing the state of CNS conducting pathways, primarily the corticospinal tracts. This paper presents our vision on using a clinical neuroimaging method to predict the regression of motor consequences after a cerebral stroke using neurological rating scales and visual assessment of the corticospinal tracts during MRI based on the modern literature analysis.

According to the literature, clinical scales used in the acute period of acute cerebrovascular accident correlate with the assessment of corticospinal tract profile. Therefore, the combination of these methods is promising while assessing motor deficit regression.

Key words: stroke, motor deficit, rehabilitation, neuroimaging.

 

Conflict of interest. The authors declare no conflict of interest.

Author contributions

Literature review, text writing: Gizatullin R.R.

Research concept and design: Akhmadeeva L.R., Baykov D.E.

Discussion, academic text editing: Baykova G.V.

 

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Received November 15, 2023; accepted March 01, 2024.

 

Information about the authors

Gizatullin Rinat Raisovich, Postgraduate Student, Department of Neurology, Bashkir State Medical University, Ministry of Health of the Russian Federation. 450008, Russia, Ufa, Lenin St., 3; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-0002-2418-0945

Akhmadeeva Leila Rinatovna, Doctor of Sciences (Medicine), Professor, Chair of Neurology, Bashkir State Medical University. 450008, Russia, Ufa, Lenin St., 3; Presidium Member, Academy of Sciences of the Republic of Bashkortostan. 450008, Russia, Ufa, Kirov St., 15; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-00002-1177-6424

Baykov Denis Enverovich, Doctor of Sciences (Medicine), Professor, Chair of General Surgery with the Course of Radiation Diagnostics of the Institute of Additional Professional Education, Bashkir State Medical University, Ministry of Health of the Russian Federation. 450008, Russia, Ufa, Lenin St., 3; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-0002-3210-6593

Baykova Galina Vladimirovna, Candidate of Sciences (Medicine), Associate Professor, Chair of Pediatrics the Course of the Institute of Additional Professional Education, Institute of Additional Professional Education, Bashkir State Medical University, Ministry of Health of the Russian Federation. 450008, Russia, Ufa, Lenin St., 3; e e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-6010-7454

 

For citation

Gizatullin R.R., Akhmadeeva L.R., Baykov D.E., Baykova G.V. Otsenochnye shkaly i pokazateli diffuzionno-tenzornoy MRT v prognozirovanii regressa dvigatel'nogo defitsita u patsientov, perenesshikh tserebral'nyy insul't [Rating scales and indicators of diffusion tensor imaging in predicting motor deficit regression in patients with cerebral stroke]. Ul'yanovskiy mediko-biologicheskiy zhurnal. 2024; 3: 6–16. DOI: 10.34014/2227-1848-2024-3-6-16 (in Russian).

 

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УДК 616.831-005.4

DOI 10.34014/2227-1848-2024-3-6-16

ОЦЕНОЧНЫЕ ШКАЛЫ И ПОКАЗАТЕЛИ ДИФФУЗИОННО-ТЕНЗЕРНОЙ МРТ В ПРОГНОЗИРОВАНИИ РЕГРЕССА ДВИГАТЕЛЬНОГО ДЕФИЦИТА У ПАЦИЕНТОВ, ПЕРЕНЕСШИХ ЦЕРЕБРАЛЬНЫЙ ИНСУЛЬТ

Р.Р. Гизатуллин1, Л.Р. Ахмадеева1,2, Д.Э. Байков1, Г.В. Байкова1

1 ФГБОУ ВО «Башкирский государственный медицинский университет» Минздрава России, г. Уфа, Россия;

2 ГБНУ «Академия наук Республики Башкортостан», г. Уфа, Россия

 

Инсульт и последующие вероятные двигательные нарушения являются значимой медико-социальной проблемой. В 2021 г. в Российской Федерации зарегистрировано 500 тыс. впервые выявленных инсультов. К трудовой деятельности в течение первого года после перенесенного инсульта возвращается не более 10 % людей, инвалидами на всю жизнь остаются 30 %. В связи с этим актуальной представляется задача прогнозирования моторных исходов заболевания в различные периоды у пациентов, перенесших церебральный инсульт. Существующие в настоящее время балльные шкалы тяжести состояния в большей степени применяются для характеристики ранних двигательных нарушений, а отдаленные последствия часто остаются не оцененными. Не существует методов прогнозирования степени двигательных нарушений у пациентов, перенесших церебральный инсульт, в долгосрочной перспективе. Объективно информацию о соотношении объема поражения головного мозга и вероятности последующей компенсации двигательного дефицита прижизненно можно получить по нейровизуализационным изображениям. Прогнозирование выраженности двигательных нарушений потенциально возможно путем анализа состояния проводящих путей центральной нервной системы, в первую очередь кортикоспинальных трактов. В настоящей работе представлено наше видение использования клинико-нейровизуализационного метода для прогнозирования регресса моторных последствий перенесенного церебрального инсульта с применением неврологических оценочных шкал и визуализационной оценки состояния кортикоспинальных трактов при магнитно-резонансной томографии на основании анализа современных публикаций.

Клинические шкалы, используемые в остром периоде острого нарушения мозгового кровообращения, по данным литературы, коррелируют с оценкой кортикоспинальных трактов, в связи с чем комбинация данных методов является перспективной с точки зрения оценки регресса двигательного дефицита.

Ключевые слова: инсульт, двигательный дефицит, реабилитация, нейровизуализация.

 

Конфликт интересов. Авторы заявляют об отсутствии конфликта интересов.

Вклад авторов

Обзор литературы, написание текста: Гизатуллин Р.Р.

Концепция и дизайн исследования: Ахмадеева Л.Р., Байков Д.Э.

Обсуждение, академическое редактирование текста: Байкова Г.В.

 

Литература

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  2. Christidi F., eds. Diffusion Tensor Imaging as a Prognostic Tool for Recovery in Acute and Hyperacute Stroke. Neurology International. 2022; 14 (4): 841–874.

  3. Tennant A., eds. Outcome following stroke. Disability and Rehabilitation. 1997; 19 (7): 278–284.

  4. Wilkinson P.R., eds. A long-term follow-up of stroke patients. Stroke. 1997; 28 (3): 507–512.

  5. Wade D.T., Skilbeck C.E., Langton Hewer R. Predicting Barthel ADL Score at 6 months after an acute stroke. Archives of Physical Medicine and Rehabilitation. 1983; 64: 24–28.

  6. Parker V.M., Wade D.T., Hewer R.L. Loss of arm function after stroke: measurement, frequency, and recovery. International Rehabilitation Medicine. 1986; 8 (2), 69–73.

  7. Olsen T.S. Arm and leg paresis as outcome predictors in stroke rehabilitation. Stroke. 1990; 21 (2): 247–251.

  8. Feys H., eds. Predicting motor recovery of the upper limb after stroke rehabilitation: value of a clinical examination. Physiotherapy Research International. 2000; 5 (1): 1–18.

  9. Henley S., eds. Who goes home? Predictive factors in stroke recovery. Journal of Neurology, Neurosurgery & Psychiatry. 1985; 48 (1): 1–6.

  10. Wade D.T., Langton Hewer R. Outlook after an acute stroke: urinary incontinence and loss of consciousness compared in 532 patients. Quarterly Journal of Medicine. 1985; 56: 601–608.

  11. Barer D.H., Mitchell J.R.A. Predicting the outcome of acute stroke: do multivariate models help? QJM: An International Journal of Medicine. 1989; 70 (1): 27–39.

  12. Kalra L., Smith D.H., Crome P. Stroke in patients aged over 75 years: outcome and predictors. Postgraduate Medical Journal. 1993; 69 (807): 33–36.

  13. Jimenez J., Morgan P.P. Predicting improvement in stroke patients referred for inpatient rehabilitation. Canadian Medical Association Journal. 1979; 121 (11): 1481.

  14. Henley S., eds. Who goes home? Predictive factors in stroke recovery. Journal of Neurology, Neurosurgery & Psychiatry. 1985; 48 (1): 1–6.

  15. Galski T., eds. Predicting length of stay, functional outcome, and aftercare in the rehabilitation of stroke patients. The dominant role of higher-order cognition. Stroke. 1993; 24 (12): 1794–1800.

  16. Engberg A., Garde B., Kreiner S. Rasch analysis in the development of a rating scale for assessment of mobility after stroke. Acta Neurologica Scandinavica. 1995; 91 (2): 118–127.

  17. Gowland C. Predicting sensorimotor recovery following stroke rehabilitation. Physiotherapy Canada. 1984; 36: 313–320.

  18. Loewen S.C., Anderson B.A. Predictors of stroke outcome using objective measurement scales. Stroke. 1990; 21 (1): 78–81.

  19. Duncan P.W., Propst M., Nelson S.G. Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Physical Therapy. 1983; 63 (10): 1606–1610.

  20. De Weerdt W., Lincoln N.B., Harrison M.A. Prediction of arm and hand function recovery in stroke patients. International Journal of Rehabilitation Research. 1987; 10: 110–112.

  21. De Weerdt W.J.G., Harrison M.A. Measuring recovery of arm-hand function in stroke patients: a comparison of the Brunnström-Fugl-Meyer test and the Action Research test. Physiotherapy Canada. 1985; 37: 65–70.

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  23. Liu G., eds. Motor recovery prediction with clinical assessment and local diffusion homogeneity after acute subcortical infarction. Stroke. 2017; 48 (8): 2121–2128.

  24. Puig J., eds. Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke. Neuroradiology. 2017; 59: 343–351.

  25. Bigourdan A., eds. Early fiber number ratio is a surrogate of corticospinal tract integrity and predicts motor recovery after stroke. Stroke. 2016; 47 (4): 1053–1059.

  26. Hendricks H.T., eds. Systematic review for the early prediction of motor and functional outcome after stroke by using motor-evoked potentials. Archives of Physical Medicine and Rehabilitation. 2002; 83 (9): 1303–1308.

  27. Thomalla G., eds. Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke. Neuroimage. 2004; 22 (4): 1767–1774.

  28. Puig J., eds. Wallerian degeneration in the corticospinal tract evaluated by diffusion tensor imaging correlates with motor deficit 30 days after middle cerebral artery ischemic stroke. American Journal of Neuroradiology. 2010; 31 (7): 1324–1330.

  29. Kunimatsu A., eds. Utilization of diffusion tensor tractography in combination with spatial normalization to assess involvement of the corticospinal tract in capsular/pericapsular stroke: feasibility and clinical implications. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine. 2007; 26 (6): 1399–1404.

  30. Newton J.M., Ward N.S., Parker G.J.M., eds. Non-invasive mapping of corticofugal fibres from multiple motor areas – elevance to stroke recovery. Brain. 2006; 129 (7): 1844–1858.

  31. Riley J.D., eds. Anatomy of stroke injury predicts gains from therapy. Stroke. 2011; 42 (2): 421–426.    

  32. Kim B., Winstein C. Can neurological biomarkers of brain impairment be used to predict poststroke motor recovery? A systematic review. Neurorehabilitation and Neural Repair. 2017; 31 (1): 3–24.

  33. Boyd L.A., eds. Biomarkers of stroke recovery: consensus-based core recommendations from the stroke recovery and rehabilitation roundtable. International Journal of Stroke. 2017; 12 (5): 480–493.

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  36. Туркин А.М. Отек головного мозга – возможности магнитно-резонансной томографии. Вестник рентгенологии и радиологии. 2009; 4-6: 4–11.

  37. Дробаха В.Е., Кулеш А.А., Шестаков В.В. Фракционная анизотропия белого и серого вещества головного мозга в остром периоде ишемического инсульта как маркер неврологического, когнитивного и функционального статуса. Медицинская визуализация. 2015; 6: 8–15.

  38. Chen J.L., Schlaug G. Resting state interhemispheric motor connectivity and white matter integrity correlate with motor impairment in chronic stroke. Frontiers Neurology. 2013; 4: 1–7.  

  39. Stinear C.M., Barber P.A., Smale P.R., eds. Functional potential in chronic stroke patients depends on corticospinal tract integrity. Brain. 2007; 130 (pt 1): 170–180.

  40. Paul T., Cieslak M., Hensel L., Wiemer V.M., Grefkes C., Grafton S.T., Volz L.J. The role of corticospinal and extrapyramidal pathways in motor impairment after stroke. Brain Communications. 2023; 5 (1): fcac301. DOI: 10.1093/braincomms/fcac301.

  41. Yu C., Zhu C., Zhang Y. A longitudinal diffusion tensor imaging study on wallerian degeneration of corticospinal tract after motor pathways stroke. Neuroimage. 2009; 47: 451–458.

  42. Schaechter J.D., Fricker Z.P., Perdue K.L. Microstructural status of ipsilesional and contralesional corticospinal tract correlates with motor skill in chronic stroke patients. Hum. Brain Mapp. 2009; 30: 3461–3474.

  43. Lindenberg R., Renga V., Zhu L.L. Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke. Neurology. 2010; 74: 280–287.  

  44. Кулеш А.А., Дробаха В.Е., Шестаков В.В. Магнитнорезонансная морфометрия головного мозга у пациентов с постинсультными когнитивными нарушениями. Пермский медицинский журнал. 2014; 31 (3): 39–45.

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  46. Beaulieu C. The Biological Basis of Diffusion Anisotropy. In: Johansen-Berg H., Behrens T. Diffusion MRI: From Quantitative Measurement to In Vivo Neuroanatomy. London: Elsevier, 2009. 490.

  47. Guo J., Wang S., Li R. Cognitive impairment and whole brain diffusion in patients with carotid artery disease and ipsilateral transient ischemic attack. Neurol. Res. 2014; 36 (1): 41–46.

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Поступила в редакцию 15.11.2023; принята 01.03.2024.

 

Авторский коллектив

Гизатуллин Ринат Раисович – аспирант кафедры неврологии, ФГБОУ ВО «Башкирский государственный медицинский университет» Минздрава России. 450008, Россия, г. Уфа, ул. Ленина, 3; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-0002-2418-0945

Ахмадеева Лейла Ринатовна – доктор медицинских наук, профессор кафедры неврологии, ФГБОУ ВО «Башкирский государственный медицинский университет». 450008, Россия, г. Уфа, ул. Ленина, 3; член Президиума, Академия наук Республики Башкортостан. 450008, Россия, г. Уфа, ул. Кирова, 15; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-00002-1177-6424

Байков Денис Энверович – доктор медицинских наук, профессор кафедры общей хирургии с курсом лучевой диагностики ИДПО, ФГБОУ ВО «Башкирский государственный медицинский университет» Минздрава России. 450008, Россия, г. Уфа, ул. Ленина, 3; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID ID: https://orcid.org/0000-0002-3210-6593

Байкова Галина Владимировна – кандидат медицинских наук, доцент кафедры педиатрии с курсом ИДПО, ФГБОУ ВО «Башкирский государственный медицинский университет» Минздрава России. 450008, Россия, г. Уфа, ул Ленина, д. 3 e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-6010-7454

 

Образец цитирования

Гизатуллин Р.Р., Ахмадеева Л.Р., Байков Д.Э., Байкова Г.В. Оценочные шкалы и показатели диффузионно-тензерной МРТ в прогнозировании регресса двигательного дефицита у пациентов, перенесших церебральный инсульт. Ульяновский медико-биологический журнал. 2024; 3: 6–16. DOI: 10.34014/2227-1848-2024-3-6-16.