Migrenli Hastalarda volBrain Yöntemi ile Serebellumun Hacimsel Analizi

Year 2023, Volume: 12 Issue: 1, 223 - 239, 25.03.2023

Özgür Palancı , Zekeriya Alioğlu , Ali Faruk Özyaşar , Kübra Erten , Vildan Altunayoglu Cakmak , İlker Eyüboğlu

https://doi.org/10.37989/gumussagbil.1228314

Abstract

Migren, geniş bir semptom yelpazesine sahip tekrarlayan bir baş ağrısı sendromudur. Migren tanısı çoğunlukla baş ağrısının özellikleri ve diğer semptomlar dikkate alınarak geriye dönük olarak konur. Migren baş ağrısının nasıl başladığı ve hangi beyin bölgelerinde meydana geldiği yeterince bilinmemektedir. Beyin sapı çekirdeklerinin uyarılabilirliğindeki değişikliklerin endojen ağrı mekanizmalarını etkilediği ve trigeminovasküler yapıların tek taraflı tutulumunun migren gelişiminde etkili mekanizmalar olduğu bilinmektedir. Migren hastalığında serebellumun rolünü anlamak, sinirbilimde oldukça yeni bir konudur. Çalışmamıza 19 Migren Hastası (MH) ve 14 Sağlıklı Kontrolör (SK) katıldı. Serebellumun hacimsel analizi için otomatik beyin hacmi hesaplama yöntemi olan volbrain ceres yöntemi kullanılmış ve beyincik yapılarının hacimleri elde edilmiştir. Verilerin analizinde SPSS 22.0 programı kullanılmış ve anlamlılık düzeyi p<0.05 olarak kabul edilmiştir. MH crus I, Crus II, lobus VIIB VIIIA, VIIIB ve IX'un gri madde hacimlerinde önemli bir artış var. Hastalık süresi ve atak sıklığına göre serebellum yapıları incelendiğinde serebellum, crusII, lobül VIIB ve lobül VIIIA'nın gri cevher hacimlerinde anlamlı artış saptandı. Bu bölgeler, saldırı frekansı ile pozitif bir korelasyon gösterdi. Sonuç olarak posterior serebellar yapılar, atakların sıklığı ve hastalığın süresi ile örtüşen bir aktivite göstermektedir. Beyincikte hacimsel veya fonksiyonel değişiklikler migren ağrısının patofizyolojisinde etkili olduğunu gösterir.

Keywords

migren, serebellum, volBrain

Thanks

emeklerinizden dolayı teşekkür ederim.

Volumetric Analysis of the Cerebellum with the volBrain Method in Patients with Migraine

Abstract

Migraine is a recurrent headache syndrome with a wide spectrum of symptoms. The diagnosis of migraine is mostly made retrospectively, taking into account the characteristics of the headache and other symptoms. It is not known enough how migraine headache starts and in which brain regions it occurs. It is known that changes in the excitability of brainstem nuclei affect endogenous pain mechanisms and unilateral involvement of trigeminovascular structures are effective mechanisms in migraine development. Understanding the role of the cerebellum in migraine disease is a fairly new topic in neuroscience. 19 Mıgraıne Patıents (MP) and 14 Healthy Controllers (HC) partıcıpated ın our study. For the volumetric analysis of the cerebellum, the ceres method of volbrain, which is an automatic brain volume calculation method, was used and the volumes of the cerebellum structures were obtained. SPSS 22.0 program was used for the analysis of the data and the level of significance was accepted as p<0.05. There is a significant increase in gray matter volumes of MP crus I, Crus II, lobus VIIB VIIIA, VIIIB and IX. When the cerebellum structures were examined according to the disease duration and attack frequency, a significant increase was found in the gray matter volumes of the cerebellum, crusII, lobule VIIB, and lobule VIIIA. These regions showed a positive correlation with attack frequency. As a result, posterior cerebellar structures show an activity that overlaps with the frequency of attacks and the duration of the disease. Volumetric or functional changes in the cerebellum indicate that it is effective in the pathophysiology of migraine pain.

Keywords

Cerebellum, Migrain, volBrain

References

• 1. Baloh, RW. (1997). “Neurotology of Migraine”. Headache: The Journal of Head and Face Pain, 37, 615-621.
• 2. Mehnert, J. and May, A. (2019). “Functional and Structural Alterations in the Migraine Cerebellum”. Journal of Cerebral Blood Flow & Metabolism. 39, 730-739. https://doi.org/10.1177/0271678X17722109
• 3. Silberstein, S. (2004). “Migraine Pathophysiology and its Clinical Implications”. Cephalalgia. 24, 2-7. https://doi.org/10.1111/j.1468-2982.2004.00892.x
• 4. Çelebi, A. (1990). Ağrıları ÖHB. kranial nevraljiler ve yüz ağrılarının sınıflanması ve tanı kriterleri. Uluslararası Baş Ağrısı Derneği, Baş Ağrıları Sınıflama Komitesi Orhanlar matbaası.
• 5. Palancı, Ö. Kalaycıoğlu, A. Acer, N. Eyüpoğlu, İ. and Çakmak, VA. (2018). “Volume Calculation of Brain Structures in Migraine Disease by Using Mristudio”. NeuroQuantology, 16 (10), 8-13. doi: 10.14704/nq.2018.16.10.1692
• 6. Restuccia, D. Vollono, C. Piero, Id. Martucci, L. and Zanini, S. (2013) “Different Levels of Cortical Excitability Reflect Clinical Fluctuations in Migraine”. Cephalalgia, 33, 1035-1047. https://doi.org/10.1177/033310241348219
• 7. Bolay, H. and Dalkara, T. (2003). “Birincil Basagrilarinin Fizyopatolojisi”. Turkiye Klinikleri J Neurol, 1, 98-102.
• 8. Vincent, M. and Hadjikhani, N. (2007). “The Cerebellum and Migraine”. Headache: The Journal of Head and Face Pain, 47, 820-833. https://doi.org/10.1111/j.1526-4610.2006.00715.x
• 9. Liu, H-Y. Lee, P-L. Chou, K-H. Lai, K-L. Wang,Y F. Chen, and S-P. et al. (2020). “The Cerebellum Is Associated with 2-year Prognosis In Patients with High-Frequency Migraine”. The Journal of Headache and Pain, 21, 1-10. https://doi.org/10.1186/s10194-020-01096-4
• 10. Cutrer, FM. and Baloh, RW. (1992). “Migraine‐associated Dizziness Headache” The Journal of Head and Face Pain, 32, 300-304.
• 11. Peres, F. (2005). “Epidemiology of Migraine”. Atlas of Migraine and Other Headaches, 2nd edn Taylor & Francis, London and New York, 41-49.
• 12. Sullivan, EV. Zahr, NM. Saranathan, M. Pohl, KM. and Pfefferbaum, A. (2019). “Convergence of Three Parcellation Approaches Demonstrating Cerebellar Lobule Volume Deficits In Alcohol Use Disorder”. NeuroImage: Clinical, 24, 101974. https://doi.org/10.1016/j.nicl.2019.101974
• 13. Manjón, JV. and Coupé, P. (2016). “volBrain: An Online MRI Brain Volumetry System”. Frontiers in Neuroinformatics, 10, 30. https://doi.org/10.3389/fninf.2016.00030
• 14. Akazawa, K. Sakamoto, R. Nakajima, S. Wu, D. Li, Y. and Oishi, K. (2019). “Automated Generation Of Radiologic Descriptions on Brain Volume Changes From T1-Weighted MR Images: Initial Assessment Of Feasibility”. Frontiers in Neurology, 10, 7. https://doi.org/10.3389/fneur.2019.00007
• 15. Tae, W-S. Ham, B-J. Pyun, S-B. Kang, S-H. Kim, and B-J. (2018). “Current Clinical Applications of Diffusion Tensor Imaging in Neurological Disorders”. Journal of Clinical Neurology, 14, 129-140. https://doi.org/10.3988/jcn.2018.14.2.129
• 16. Qin, Z. He, X-W. Zhang, J. Xu, S. Li, G-F. and Su, J. (2019). “Structural Changes of Cerebellum And Brainstem In Migraine Without Aura”. The Journal of Headache and Pain, 20, 93. https://doi.org/10.1186/s10194-019-1045-5
• 17. Parker, KL. (2016). “Timing Tasks Synchronize Cerebellar and Frontal Ramping Activity and Theta Oscillations: Implications for Cerebellar Stimulation in Diseases of Impaired Cognition”. Frontiers in Psychiatry, 6,190. https://doi.org/10.3389/fpsyt.2015.00190
• 18. Schwedt, TJ. Chiang, C-C. Chong, CD. and Dodick, DW. (2015). “Functional MRI of Migraine”. The Lancet Neurology, 14, 81-91. https://doi.org/10.1016/S1474-4422(14)70193-0
• 19. Noseda, R. (2022). “Cerebro-Cerebellar Networks in Migraine Symptoms and Headache”. Frontiers in Pain Research, 3. 10.3389/fpain.2022.940923
• 20. Noseda, R. and Burstein, R. (2013). “Migraine Pathophysiology: Anatomy of the trigeminovascular Pathway and Associated Neurological Symptoms, Cortical Spreading Depression, Sensitization, and Modulation of Pain”. PAIN®, 154, 44-53. https://doi.org/10.1016/j.pain.2013.07.021