Share:
Share this content in WeChat
X
Clinical Article
Preliminary study of diffusion tensor imaging and 18F-AV1451 PET tau protein brain imaging in the diagnosis and differential diagnosis of MCI
LI Xiaotong  WANG Kai  AI Lin 

Cite this article as: Li XT, Wang K, Ai L. Preliminary study of diffusion tensor imaging and 18F-AV1451 PET tau protein brain imaging in the diagnosis and differential diagnosis of MCI[J]. Chin J Magn Reson Imaging, 2022, 13(4): 5-14. DOI:10.12015/issn.1674-8034.2022.04.002.


[Abstract] Objective To study the value of diffusion tensor imaging (DTI) and 18F-AV1451 tau protein brain imaging in the diagnosis of mild cognitive impairment (MCI), and to make early diagnosis and early intervention treatment for MCI patients in the future.Materials and Methods This prospective study included 37 patients, 13 patients with amnesia mild cognitive impairment (aMCI), 13 patients with Alzheimer's disease (AD) and 11 normal controls (NC) were selected. 18F-AV1451 tau protein imaging and DTI were examined by positron emission tomography-computed tomography scanner and magnetic resonance imaging scanner. GE ADW workstation was used to automatically register fraction anisotropy (FA), apparent diffusion coefficient (ADC) and positron emission tomography images. The regions of interest in posterior cingulate gyrus, parahippocampal gyrus and middle temporal gyrus were delineated at the same level. FA value, ADC value, maximum standard uptake value and standard uptake value ratio (SUVr) were measured. The changes and correlation of FA, ADC and SUVr between the two groups were analyzed by rank sum test and Person correlation analysis.Results The positive predictive value, negative predictive value, sensitivity and specificity of 18F-AV1451 tau protein brain imaging in diagnosing aMCI patients were 70.0%, 57.1%, 53.8% and 72.7%, respectively. The numbers in AD group were 76.9%, 72.7%, 76.9% and 72.7%, respectively. There were significant differences in the SUVr values of left posterior cingulate gyrus and right parahippocampal gyrus between aMCI group and NC group (P=0.032,0.025). And there were significant differences between AD group and NC group in bilateral parahippocampal gyrus and left middle temporal gyrus (P=0.007, 0.007, 0.041). The SUVr values of the left posterior cingulate gyrus and the right parahippocampal gyrus in the AD group were significantly different from those in the aMCI group (P=0.032, 0.025). There was no significant difference in FA between aMCI group and NC group (P>0.05). But there was significant difference in ADC values in bilateral posterior cingulate gyrus, right parahippocampal gyrus and right middle temporal gyrus (P=0.024, 0.012, 0.024, 0.024). There was no significant difference in FA and ADC between AD group and NC group (P>0.05). There were significant differences in FA and ADC between aMCI group and AD group in bilateral posterior cingulate gyrus (P=0.047,0.047,0.047,0.012). For 6 aMCI patients who underwent 18F-AV1451 tau protein brain imaging and DTI examination, Pearson correlation analysis showed that there was no significant correlation between FA, ADC value and SUVr value in each site (P>0.05), but there was a negative correlation between ADC value and Minimental State Examination (MMSE) score in the right parahippocampal gyrus (r=-0.821, P=0.045). There was no significant correlation between FA, ADC and SUVr values of other parts and the scores of MMSE and Montrealcognitive assessment scale (P>0.05).Conclusions The detection of white matter injury in different parts of brain by DTI, especially the bilateral posterior cingulate gyrus, has certain significance in the early differentiation between aMCI and AD patients, and may be used as an index for the differential of aMCI and AD in the future. In addition, 18F-AV1451 tau protein brain imaging is more effective in differential diagnosis of aMCI, and the ADC value of the right parahippocampal gyrus is negatively correlated with the MMSE score, indicating that the clinical psychological scale score may reflect the microstructural changes in the brain tissue.
[Keywords] amnestic mild cognitive impairment;diffusion tensor imaging;positron emission tomography-computed tomography;magnetic resonance imaging

LI Xiaotong   WANG Kai   AI Lin*  

Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China

Ai L, E-mail: ailin@bjtth.org

Conflicts of interest   None.

Received  2021-12-09
Accepted  2022-03-21
DOI: 10.12015/issn.1674-8034.2022.04.002
Cite this article as: Li XT, Wang K, Ai L. Preliminary study of diffusion tensor imaging and 18F-AV1451 PET tau protein brain imaging in the diagnosis and differential diagnosis of MCI[J]. Chin J Magn Reson Imaging, 2022, 13(4): 5-14.DOI:10.12015/issn.1674-8034.2022.04.002

[1]
Babulal GM, Quiroz YT, Albensi BC, et al. Perspectives on ethnic and racial disparities in Alzheimer's disease and related dementias: update and areas of immediate need[J]. Alzheimers Dement, 2019, 15(2): 292-312. DOI: 10.1016/j.jalz.2018.09.009.
[2]
Jia JP, Li Y. The present and future of China's dementia[J]. Chin J Neurol, 2020, 53(2): 81-84. DOI: 10.3760/cma.j.issn.1006-7876.2020.02.001.
[3]
Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment: beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment[J]. J Intern Med, 2004, 256(3): 240-246. DOI: 10.1111/j.1365-2796.2004.01380.x.
[4]
Ma HR, Sheng LQ, Pan PL, et al. Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer's dementia: a meta-analysis[J]. Transl Neurodegener, 2018, 7: 9. DOI: 10.1186/s40035-018-0114-z.
[5]
Ashrafian H, Zadeh EH, Khan RH. Review on Alzheimer's disease: inhibition of amyloid beta and tau tangle formation[J]. Int J Biol Macromol, 2021, 167: 382-394. DOI: 10.1016/j.ijbiomac.2020.11.192.
[6]
Olsson B, Lautner R, Andreasson U, et al. CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis[J]. Lancet Neurol, 2016, 15(7): 673-684. DOI: 10.1016/S1474-4422(16)00070-3.
[7]
Franzmeier N, Koutsouleris N, Benzinger T, et al. Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning[J]. Alzheimers Dement, 2020, 16(3): 501-511. DOI: 10.1002/alz.12032.
[8]
Tae WS, Ham BJ, Pyun SB, et al. Current clinical applications of diffusion-tensor imaging in neurological disorders[J]. J Clin Neurol, 2018, 14(2): 129-140. DOI: 10.3988/jcn.2018.14.2.129.
[9]
Talwar P, Kushwaha S, Chaturvedi M, et al. Systematic review of different neuroimaging correlates in mild cognitive impairment and Alzheimer's disease[J]. Clin Neuroradiol, 2021, 31(4): 953-967. DOI: 10.1007/s00062-021-01057-7.
[10]
Chandra A, Dervenoulas G, Politis M, et al. Magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment[J]. J Neurol, 2019, 266(6): 1293-1302. DOI: 10.1007/s00415-018-9016-3.
[11]
Stone DB, Ryman SG, Hartman AP, et al. Specific white matter tracts and diffusion properties predict conversion from mild cognitive impairment to Alzheimer's disease[J]. Front Aging Neurosci, 2021, 13: 711579. DOI: 10.3389/fnagi.2021.711579.
[12]
Ricci M, Cimini A, Camedda R, et al. Tau biomarkers in dementia: positron emission tomography radiopharmaceuticals in tauopathy assessment and future perspective[J]. Int J Mol Sci, 2021, 22(23): 13002. DOI: 10.3390/ijms222313002.
[13]
Petersen RC. Mild cognitive impairment as a diagnostic entity[J]. J Intern Med, 2004, 256(3): 183-194. DOI: 10.1111/j.1365-2796.2004.01388.x.
[14]
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease[J]. Alzheimers Dement, 2011, 7(3): 263-269. DOI: 10.1016/j.jalz.2011.03.005.
[15]
Liew TM. The optimal short version of Montreal cognitive assessment in diagnosing mild cognitive impairment and dementia[J]. J Am Med Dir Assoc, 2019, 20(8): 1055.e1-1051055.e8. DOI: 10.1016/j.jamda.2019.02.004.
[16]
Arevalo-Rodriguez I, Smailagic N, Roqué-Figuls M, et al. Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI)[J]. Cochrane Database Syst Rev, 2021, 7: CD010783. DOI: 10.1002/14651858.CD010783.pub3.
[17]
Chandra A, Valkimadi PE, Pagano G, et al. Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment[J]. Hum Brain Mapp, 2019, 40(18): 5424-5442. DOI: 10.1002/hbm.24782.
[18]
Langa KM, Levine DA. The diagnosis and management of mild cognitive impairment: a clinical review[J]. JAMA, 2014, 312(23): 2551-2561. DOI: 10.1001/jama.2014.13806.
[19]
Senda M, Ishii K, Ito K, et al. A Japanese multicenter study on PET and other biomarkers for subjects with potential preclinical and prodromal Alzheimer's disease[J]. J Prev Alzheimers Dis, 2021, 8(4): 495-502. DOI: 10.14283/jpad.2021.37.
[20]
Hanseeuw BJ, Betensky RA, Jacobs HIL, et al. Association of amyloid and tau with cognition in preclinical alzheimer disease: a longitudinal study[J]. JAMA Neurol, 2019, 76(8): 915-924. DOI: 10.1001/jamaneurol.2019.1424.
[21]
Feng F, Huang WJ, Meng QQ, et al. Altered volume and structural connectivity of the Hippocampus in Alzheimer's disease and amnestic mild cognitive impairment[J]. Front Aging Neurosci, 2021, 13: 705030. DOI: 10.3389/fnagi.2021.705030.
[22]
Hong YJ, Yoon B, Lim SC, et al. Microstructural changes in the hippocampus and posterior cingulate in mild cognitive impairment and Alzheimer's disease: a diffusion tensor imaging study[J]. Neurol Sci, 2013, 34(7): 1215-1221. DOI: 10.1007/s10072-012-1225-4.
[23]
Zimny A, Szewczyk P, Trypka E, et al. Multimodal imaging in diagnosis of Alzheimer's disease and amnestic mild cognitive impairment: value of magnetic resonance spectroscopy, perfusion, and diffusion tensor imaging of the posterior cingulate region[J]. J Alzheimers Dis, 2011, 27(3): 591-601. DOI: 10.3233/JAD-2011-110254.
[24]
Zhu ZP, Zhu H. Research progress in imaging agents targeting Aβ and Tau protein in Alzheimer's disease[J]. Chin J Nucl Med Mol Imaging, 2018, 38(4): 291-294. DOI: 10.3760/cma.j.issn.2095-2848.2018.04.018.
[25]
Brendel M, Yousefi BH, Blume T, et al. Comparison of 18F-T807 and 18F-THK5117 PET in a mouse model of tau pathology[J]. Front Aging Neurosci, 2018, 10: 174. DOI: 10.3389/fnagi.2018.00174.
[26]
Jin Y, Jiao JS. Application of PET technique in cognitive impairment-related diseases[J]. Chin J Med, 2019, 54(5): 465-469, 460. DOI: 10.3969/j.issn.1008-1070.2019.05.001.
[27]
Brier MR, Gordon B, Friedrichsen K, et al. Tau and aβ imaging, CSF measures, and cognition in Alzheimer's disease[J]. Sci Transl Med, 2016, 8(338): 338ra66. DOI: 10.1126/scitranslmed.aaf2362.
[28]
Forno G, Lladó A, Hornberger M. Going round in circles-The Papez circuit in Alzheimer's disease[J]. Eur J Neurosci, 2021, 54(10): 7668-7687. DOI: 10.1111/ejn.15494.
[29]
Okazawa H, Ikawa M, Jung M, et al. Multimodal analysis using[11 C]PiB-PET/MRI for functional evaluation of patients with Alzheimer's disease[J]. EJNMMI Res, 2020, 10(1): 30. DOI: 10.1186/s13550-020-00619-z.
[30]
Song Z, Rubinski A, et al. Age-dependent amyloid deposition is associated with white matter alterations in cognitively normal adults during the adult life span[J]. Alzheimers Dement, 2020, 16(4): 651-661. DOI: 10.1002/alz.12062.
[31]
Chen YY, Bao J, Tan Y, et al. The study of the relationship between mild cognitive impairment and diffusion tensor imaging of white matter[J]. J Int Neurol Neurosurg, 2017, 44(2): 139-144. DOI: 10.16636/j.cnki.jinn.2017.02.006.

PREV The changes of functional connectivity on hemispheric level in depression patients with suicidal ideation: A functional magnetic resonance imaging study
NEXT Construction of a nomogram model for hemorrhagic transformation risk after mechanical thrombectomy in patients with acute stroke
  



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