Share：
Share this content in WeChat
X
[Chinese][PDF]191
• Clinical Article •
Study on cerebral perfusion characteristic network of type 2 diabetes mellitus patients based on MR arterial spin labeling imaging
BAN Qiqi  QU Hang  WANG Wei  ZHAO Yi  ZHU Zhu 

Cite this article as: BAN Q Q, QU H, WANG W, et al. Study on cerebral perfusion characteristic network of type 2 diabetes mellitus patients based on MR arterial spin labeling imaging[J]. Chin J Magn Reson Imaging, 2024, 15(8): 73-77, 102. DOI:10.12015/issn.1674-8034.2024.08.011.


[Abstract] Objective To analyze the cerebral microcirculation blood flow perfusion and perfusion patterns in patients with type 2 diabetes mellitus (T2DM) by using MR arterial spin labeling (ASL), and to analyze the correlation between these changes and biochemical indexes.Materials and Methods Twenty-eight patients who met our T2DM diagnostic criteria and 26 healthy control (HC) were selected in this study. We conducted ASL, principal component analysis, and calculated the cerebral blood flow (CBF) and perfusion feature network on subjects.Results Compared with HC group, the perfusion areas including bilateral paracentral lobules, left supplementary motor area, the middle bilateral gyrus cinguli, left opercular part of the inferior frontal gyrus, left middle temporal gyrus, and left inferior temporal gyrus in diabetic patients were significantly lower (P<0.05, GRF adjusted). The ratios of the variance components of the two disease-related perfusion networks to the total variance were 17.6% and 11.7% (95% confidence interval), and they were statistically significant. The first perfusion network characteristic expression value was significantly positively correlated with fasting blood glucose (r=0.32, P=0.001), and the extracted CBF of the diabetic group using the second perfusion characteristic network as a template was negatively correlated with the patient's fasting blood glucose (r=0.12, P =0.03).Conclusions The diabetic patients had low regional cerebral blood flow. Principal component-based perfusion characteristics can identify patients with diabetes. The changes in perfusion patterns reflected the remodeling of cerebral blood flow perfusion, which had more important value and significance for the early diagnosis and intervention of diabetic microangiopathy.
[Keywords] type 2 diabetes mellitus；arterial spin labeling；magnetic resonance imaging；principal component analysis；perfusion characteristics

BAN Qiqi1, 2   QU Hang1   WANG Wei1   ZHAO Yi1   ZHU Zhu1*  

1 Department of Medical Imaging, the Affiliated Hospital of Yangzhou University, Yangzhou 225009, China

2 Graduate School of Dalian Medical University, Dalian 116000, China

Corresponding author: ZHU Z, E-mail: zhuzhu04060117@sina.com

Conflicts of interest   None.

Received  2024-01-18
Accepted  2024-07-12
DOI: 10.12015/issn.1674-8034.2024.08.011
Cite this article as: BAN Q Q, QU H, WANG W, et al. Study on cerebral perfusion characteristic network of type 2 diabetes mellitus patients based on MR arterial spin labeling imaging[J]. Chin J Magn Reson Imaging, 2024, 15(8): 73-77, 102. DOI:10.12015/issn.1674-8034.2024.08.011.

[1]
BIESSELS G J, DESPA F. Cognitive decline and dementia in diabetes mellitus: mechanisms and clinical implications[J]. Nat Rev Endocrinol, 2018, 14(10): 591-604. DOI: 10.1038/s41574-018-0048-7.
[2]
VAN SLOTEN T, SCHRAM M. Understanding depression in type 2 diabetes: a biological approach in observational studies[J/OL]. F1000Res, 2018, 7: F1000 Faculty Rev-1283 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/30135724/. DOI: 10.12688/f1000research.13898.1.
[3]
XUE M, XU W, OU Y N, et al. Diabetes mellitus and risks of cognitive impairment and dementia: A systematic review and meta-analysis of 144 prospective studies[J/OL]. Ageing Res Rev, 2019, 55: 100944 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/31430566/. DOI: 10.1016/j.arr.2019.100944.
[4]
VAN SLOTEN T T, SEDAGHAT S, CARNETHON M R, et al. Cerebral microvascular complications of type 2 diabetes: stroke, cognitive dysfunction, and depression[J]. Lancet Diabetes Endocrinol, 2020, 8(4): 325-336. DOI: 10.1016/S2213-8587(19)30405-X.
[5]
HU Y, LI Q, CHEN L, et al. Multidelay arterial spin-labeled perfusion magnetic resonance imaging in healthy individuals: A single-center experience[J]. Neurol India, 2019, 67(3): 829-833. DOI: 10.4103/0028-3886.263246.
[6]
IANNOTTI G R, NADIN I, IVANOVA V, et al. Specificity of quantitative functional brain mapping with arterial spin-labeling for preoperative assessment[J]. AJNR Am J Neuroradiol, 2023, 44(11): 1302-1308. DOI: 10.3174/ajnr.A8006.
[7]
RUSSO A, SILVESTRO M, TESSITORE A, et al. Arterial spin labeling MRI applied to migraine: current insights and future perspectives[J/OL]. J Headache Pain, 2023, 24(1): 71 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/37322466/. DOI: 10.1186/s10194-023-01597-y.
[8]
LIU J, YANG X, LI Y, et al. Cerebral blood flow alterations in type 2 diabetes mellitus: A systematic review and meta-analysis of arterial spin labeling studies[J/OL]. Front Aging Neurosci. 2022, 14: 847218. [2024-01-18]. https://doi.org/10.3389/fnagi.2022.847218. DOI: 10.3389/fnagi.2022.847218.
[9]
MENG M, LIU F, MA Y, et al. The identification and cognitive correlation of perfusion patterns measured with arterial spin labeling MRI in Alzheimer's disease[J/OL]. Alzheimers Res Ther, 2023, 15(1): 75 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/37038198/. DOI: 10.1186/s13195-023-01222-9.
[10]
MANZANERA O M, MELES S K, LEENDERS K L, et al. Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data[J/OL]. Int J Neural Syst, 2019, 29(9): 1950010 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/31046514/. DOI: 10.1142/S0129065719500102.
[11]
Chinese Diabetes Society. Guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020 edition)[J]. Chin J Diabetes Mellitus, 2021, 13(4): 315-409. DOI: 10.3760/cma.j.cn115791-20210221-00095.
[12]
RAU A, SCHROTER N, BLAZHENETS G, et al. The metabolic spatial covariance pattern of definite idiopathic normal pressure hydrocephalus: an FDG PET study with principal components analysis[J/OL]. Alzheimers Res Ther, 2023, 15(1): 202 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/37980531/. DOI: 10.1186/s13195-023-01339-x.
[13]
LYU J, DUAN Q, XIAO S, et al. Arterial spin labeling‐based MRI estimation of penumbral tissue in acute ischemic stroke[J/OL]. J Magn Reson Imaging, 2023, 57(4): 1241-1247. [2024-01-18]. https://doi.org/10.1002/jmri.28364. DOI: 10.1002/jmri.28364.
[14]
WONG A M, YAN F X, LIU H L. Comparison of three-dimensional pseudo-continuous arterial spin labeling perfusion imaging with gradient-echo and spin-echo dynamic susceptibility contrast MRI[J]. J Magn Reson Imaging, 2014, 39(2): 427-433. DOI: 10.1002/jmri.24178.
[15]
CHAU A C, CHEUNG E Y, CHAN K, et al. Impaired cerebral blood flow in type 2 diabetes mellitus- a comparative study with subjective cognitive decline, vascular dementia and Alzheimer's disease subjects[J/OL]. NeuroImage: Clinical, 2020, 27: 102302. [2024-01-18]. https://doi.org/10.1016/j.nicl.2020.102302. DOI: 10.1016/j.nicl.2020.102302.
[16]
BANGEN K J, WERHANE M L, WEIGAND A J, et al. Reduced regional cerebral blood flow relates to poorer cognition in older adults with type 2 diabetes[J/OL]. Front Aging Neurosci, 2018, 10: 270 [2024-01-18]. https://doi.org/10.3389/fnagi.2018.00270. DOI: 10.3389/fnagi.2018.00270.
[17]
DAI W, DUAN W, ALFARO F J, et al. The resting perfusion pattern associates with functional decline in type 2 diabetes[J]. Neurobiol Aging, 2017, 60: 192-202. DOI: 10.1016/j.neurobiolaging.2017.09.004.
[18]
HU B, YAN L F, SUN Q, et al. Disturbed neurovascular coupling in type 2 diabetes mellitus patients: Evidence from a comprehensive fMRI analysis[J/OL]. NeuroImage: Clinical, 2019, 22: 10180 [2024-01-18]. https://doi.org/10.1016/j.nicl.2019.101802. DOI: 10.1016/j.nicl.2019.101802.
[19]
CUI Y, LIANG X, GU H, et al. Cerebral perfusion alterations in type 2 diabetes and its relation to insulin resistance and cognitive dysfunction[J]. Brain Imaging Behav, 2017, 11(5): 1248-1257. DOI: 10.1007/s11682-016-9583-9.
[20]
LAST D, ALSOP D C, ABDULJALIL A M, et al. Global and regional effects of type 2 diabetes on brain tissue volumes and cerebral vasoreactivity[J]. Diabetes Care, 2007, 30(5): 1193-1199. DOI: 10.2337/dc06-2052.
[21]
LI M, LI Y, ZHAO K, et al. Abnormal cerebral blood flow and brain function in type 2 diabetes mellitus[J/OL]. Endocrine, 2023 [2024-01-18]. https://doi.org/10.1007/s12020-023-03342-6. DOI: 10.1007/s12020-023-03342-6.
[22]
TIEHUIS A, VINCKEN K, VAN DEN BERG E, et al. Cerebral perfusion in relation to cognitive function and type 2 diabetes[J]. Diabetologia, 2008, 51(7): 1321-1326. DOI: 10.1007/s00125-008-1041-9.
[23]
CHUNG C C, PIMENTEL D, JOR'DAN A J, et al. Inflammation-associated declines in cerebral vasoreactivity and cognition in type 2 diabetes[J]. Neurology, 2015, 85(5): 450-458. DOI: 10.1212/WNL.0000000000001820.
[24]
YU S F, HONG C T, CHEN W T, et al. Metformin adherence and the risk of cardiovascular disease: a population-based cohort study[J/OL]. Ther Adv Chronic Dis, 2023, 14: 20406223231163115 [2024-01-18]. https://doi.org/10.1177/20406223231163115. DOI: 10.1177/20406223231163115.
[25]
KINAAN M, DING H, TRIGGLE C R J M P, et al. Metformin: An old drug for the treatment of diabetes but a new drug for the protection of the endothelium[J]. Med Princ Pract, 2015, 24(5): 401-415. DOI: 10.1159/000381643.
[26]
QU H, GAO J Y, LI C, et al. Regional neural activity homogeneity and anatomical brain alterations in type 2 diabetes[J]. Journal of Clinical Radiology, 2016, 35(4): 512-517. DOI: 10.13437/j.cnki.jcr.2016.04.006.
[27]
HUANG X, WEN Z, TONG Y, et al. Altered resting cerebral blood flow specific to patients with diabetic retinopathy revealed by arterial spin labeling perfusion magnetic resonance imaging:[J]. Acta Radiologica, 2021, 62(4): 524-532. DOI: 10.1177/0284185120932391.
[28]
YAO L, YANG C, ZHANG W, et al. A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes - Science Direct[J/OL]. Front Neuroendocrinol, 2021, 62: 100915 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/33862036/. DOI: 10.1016/j.yfrne.2021.100915.
[29]
MOULTON C D, COSTAFREDA S G, HORTON P, et al. Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes[J]. Brain Imaging Behav, 2015, 9(4): 651-662. DOI: 10.1007/s11682-014-9348-2.
[30]
YU K K, CHEING G L, CHEUNG C, et al. Gray matter abnormalities in type 1 and type 2 diabetes: A dual disorder ALE quantification[J/OL]. Front Neurosci, 15:638861 [2024-01-18]. https://doi.org/10.3389/fnins.2021.638861. DOI: 10.3389/fnins.2021.638861.
[31]
JANSEN J F, VAN BUSSEL F C, VAN DE HAAR H J, et al. Cerebral blood flow, blood supply, and cognition in type 2 diabetes mellitus[J/OL]. Sci Rep.2016, 6(1): 10 [2024-01-18]. https://pubmed.ncbi.nlm.nih.gov/27920431/. DOI: 10.1038/s41598-016-0003-6.
[32]
SCHULINGKAMP R J, PAGANO T C, HUNG D, et al. Insulin receptors and insulin action in the brain: Review and clinical implications[J]. Neurosci Biobehav Rev, 2001, 24(8): 855-872. DOI: 10.1016/S0149-7634(00)00040-3.

PREV Research on aquaporin magnetic resonance molecular imaging of hippocampal subfields in Alzheimer,s disease
NEXT Evaluation of rest-state fMRI in patients with lumbar disc herniation based on ALFF
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn