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Evaluation of Cerebral Blood Flow Using Arterial Spin Labeling in Patients with Chronic Kidney Disease

만성 콩팥병 환자들에서 동맥 스핀 표지 기법을 이용한 뇌 관류상태의 평가

  • Se Won Oh (Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Samel Park (Department of Internal Medicine, Soonchunhyang University Cheonan Hospital) ;
  • Nam-jun Cho (Department of Internal Medicine, Soonchunhyang University Cheonan Hospital) ;
  • Hyo-Wook Gil (Department of Internal Medicine, Soonchunhyang University Cheonan Hospital) ;
  • Eun Young Lee (Department of Internal Medicine, Soonchunhyang University Cheonan Hospital) ;
  • Hyung Geun Oh (LEE & OH Neurology Clinic) ;
  • Sung-Tae Park (Department of Radiology, Soonchunhyang University Seoul Hospital)
  • 오세원 (가톨릭대학교 의과대학 은평성모병원 영상의학과) ;
  • 박삼엘 (순천향대학교 천안병원 신장내과) ;
  • 조남준 (순천향대학교 천안병원 신장내과) ;
  • 길효욱 (순천향대학교 천안병원 신장내과) ;
  • 이은영 (순천향대학교 천안병원 신장내과) ;
  • 오형근 (이앤오 신경과) ;
  • 박성태 (순천향대학교 서울병원 영상의학과)
  • Received : 2020.04.30
  • Accepted : 2020.05.16
  • Published : 2020.07.01

Abstract

Purpose This study aimed to compare the brain perfusion status of patients with chronic kidney disease to a normal control group to identify any significant differences. Materials and Methods The perfusion state of the brain was measured by MRI using the arterial spin labeling technique in 36 patients undergoing hemodialysis due to chronic kidney disease and 36 normal controls. Images were then analyzed in a voxel-wise manner to detect brain areas showing significant perfusion differences between the two groups. Results Patients with chronic kidney disease showed increased perfusion in the form of large clusters across the right fronto-parieto-temporal lobe and the left parieto-occipital lobe. In addition, perfusion increased in the bilateral thalami, midbrain, pons, and cerebellum (p < 0.01, familywise error corrected). Conclusion Brain perfusion appears to increase in patients with chronic kidney disease compared to normal controls. Uremic toxicity is thought to be the cause of this increase as it can cause damage to the microscopic blood vessels and their surrounding structures.

목적 만성 콩팥병 환자에서 뇌 관류상태를 측정하여 정상 대조군과 차이가 있는지 알아보고자 하였다. 대상과 방법 만성 콩팥병으로 혈액 투석을 받는 환자 36명과 정상 대조군 36명에 대해 동맥스핀 표지 기법을 이용한 자기공명영상으로 뇌의 관류상태를 측정한 뒤 이를 voxel-wise로 분석하여 유의한 차이를 보이는 부위를 표준 영상 공간에 나타냈다. 결과 만성 콩팥병 환자들은 우측 전두엽, 두정엽, 측두엽과 좌측 두정엽과 후두엽의 백질 부위에 걸쳐 큰 군집의 형태로 관류 증가가 나타났다. 또한 양측 시상 부위와 중뇌, 뇌교 및 양측 소뇌에서도 관류 증가 소견을 보였다(p < 0.01, family-wise error corrected). 결론 만성 콩팥병 환자에서 뇌의 관류는 증가되어 있는 것으로 생각되며 이는 요독증 물질의 독성에 의한 미시적인 혈관 및 혈관 주위 구조물의 손상에 의한 것으로 생각된다.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea funded by the Ministry of Science and ICT (NRF-2017R1C1B5018379).

References

  1. Drawz P, Rahman M. Chronic kidney disease. Ann Intern Med 2015;162:ITC1-ITC16 https://doi.org/10.7326/AITC201506020
  2. Yaffe K, Ackerson L, Kurella Tamura M, Le Blanc P, Kusek JW, Sehgal AR, et al. Chronic kidney disease and cognitive function in older adults: findings from the chronic renal insufficiency cohort cognitive study. J Am Geriatr Soc 2010;58:338-345 https://doi.org/10.1111/j.1532-5415.2009.02670.x
  3. Toyoda K, Ninomiya T. Stroke and cerebrovascular diseases in patients with chronic kidney disease. Lancet Neurol 2014;13:823-833 https://doi.org/10.1016/S1474-4422(14)70026-2
  4. Bugnicourt JM, Godefroy O, Chillon JM, Choukroun G, Massy ZA. Cognitive disorders and dementia in CKD: the neglected kidney-brain axis. J Am Soc Nephrol 2013;24:353-363 https://doi.org/10.1681/ASN.2012050536
  5. Stinghen AE, Pecoits-Filho R. Vascular damage in kidney disease: beyond hypertension. Int J Hypertens 2011;2011:232683
  6. Seifter JL, Samuels MA. Uremic encephalopathy and other brain disorders associated with renal failure. Semin Neurol 2011;31:139-143 https://doi.org/10.1055/s-0031-1277984
  7. Chen HJ, Zhang LJ, Lu GM. Multimodality MRI findings in patients with end-stage renal disease. Biomed Res Int 2015;2015:697402
  8. Grobner T. Gadolinium--a specific trigger for the development of nephrogenic fibrosing dermopathy and nephrogenic systemic fibrosis? Nephrol Dial Transplant 2006;21:1104-1108 https://doi.org/10.1093/ndt/gfk062
  9. Detre JA, Leigh JS, Williams DS, Koretsky AP. Perfusion imaging. Magn Reson Med 1992;23:37-45 https://doi.org/10.1002/mrm.1910230106
  10. Chappell MA, Groves AR, Whitcher B, Woolrich MW. Variational bayesian inference for a nonlinear forward model. IEEE Trans Signal Process 2008;57:223-236 https://doi.org/10.1109/TSP.2008.2005752
  11. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage 2014;92:381-397 https://doi.org/10.1016/j.neuroimage.2014.01.060
  12. Prohovnik I, Post J, Uribarri J, Lee H, Sandu O, Langhoff E. Cerebrovascular effects of hemodialysis in chronic kidney disease. J Cereb Blood Flow Metab 2007;27:1861-1869 https://doi.org/10.1038/sj.jcbfm.9600478
  13. Liu HS, Hartung EA, Jawad AF, Ware JB, Laney N, Port AM, et al. Regional cerebral blood flow in children and young adults with chronic kidney disease. Radiology 2018;288:849-858 https://doi.org/10.1148/radiol.2018171339
  14. Shah SV, Shukla AM, Bose C, Basnakian AG, Rajapurkar M. Recent advances in understanding the pathogenesis of atherosclerosis in CKD patients. J Ren Nutr 2015;25:205-208 https://doi.org/10.1053/j.jrn.2014.10.024
  15. Cho NJ, Park S, Lee EY, Oh SW, Oh HG, Gil HW. Association of intracranial artery calcification with cognitive impairment in hemodialysis patients. Med Sci Monit 2019;25:5036-5043 https://doi.org/10.12659/MSM.914658
  16. Bosch A, Scheppach JB, Harazny JM, Raff U, Eckardt KU, Schmieder RE, et al. Retinal capillary and arteriolar changes in patients with chronic kidney disease. Microvasc Res 2018;118:121-127 https://doi.org/10.1016/j.mvr.2018.03.008
  17. Viggiano D, Wagner CA, Martino G, Nedergaard M, Zoccali C, Unwin R, et al. Mechanisms of cognitive dysfunction in CKD. Nat Rev Nephrol 2020 [in press] doi: http://dx.doi.org/10.1038/s41581-020-0266-9
  18. Vanholder R, De Smet R, Glorieux G, Argiles A, Baurmeister U, Brunet P, et al. Review on uremic toxins: classification, concentration, and interindividual variability. Kidney Int 2003;63:1934-1943 https://doi.org/10.1046/j.1523-1755.2003.00924.x
  19. Segal MS, Baylis C, Johnson RJ. Endothelial health and diversity in the kidney. J Am Soc Nephrol 2006;17:323-324 https://doi.org/10.1681/ASN.2005121296
  20. Khatri M, Wright CB, Nickolas TL, Yoshita M, Paik MC, Kranwinkel G, et al. Chronic kidney disease is associated with white matter hyperintensity volume: the Northern Manhattan Study (NOMAS). Stroke 2007;38:3121-3126 https://doi.org/10.1161/STROKEAHA.107.493593
  21. Chou MC, Hsieh TJ, Lin YL, Hsieh YT, Li WZ, Chang JM, et al. Widespread white matter alterations in patients with end-stage renal disease: a voxelwise diffusion tensor imaging study. AJNR Am J Neuroradiol 2013;34:1945-1951 https://doi.org/10.3174/ajnr.A3511
  22. Kong X, Wen JQ, Qi RF, Luo S, Zhong JH, Chen HJ, et al. Diffuse interstitial brain edema in patients with endstage renal disease undergoing hemodialysis: a tract-based spatial statistics study. Medicine (Baltimore) 2014;93:e313
  23. Alsop DC, Detre JA, Golay X, Gunther M, Hendrikse J, Hernandez-Garcia L, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2015;73:102-116 https://doi.org/10.1002/mrm.25197
  24. Pinto J, Chappell MA, Okell TW, Mezue M, Segerdahl AR, Tracey I, et al. Calibration of arterial spin labeling data-potential pitfalls in post-processing. Magn Reson Med 2020;83:1222-1234 https://doi.org/10.1002/mrm.28000