Cerebral Metabolism in Patients with Cognitive Disorders: a Combined Magnetic Resonance Spectroscopy and Positron Emission Tomography Study
- 7 Downloads
Objectives. Magnetic resonance spectroscopy (MRS) allows the contents of many metabolites in living tissues to be assessed. There is a good number of studies analyzing MRS data in Alzheimer’s disease (AD), though their results are contradictory. In this regard, there is value in comparing MRS data with fluorodeoxyglucose (FDG) positron emission tomography (PET) results, which assess the functional state of nervous tissue. The present study provides a comparison of MRI scan data in AD and moderate cognitive impairment (MCI) with the characteristics of cerebral glucose metabolism assessed from FDG-PET data. Materials and methods. Multivoxel proton MRS of the supraventricular region was carried out in patients with AD (n = 16) and MCI (n = 14). The following metabolite ratios were determined: NAA/Cr, Cho/Cr, and NAA/Cho (NAA is N-acetylaspartate, Cr is creatine, and Cho is choline). Patients underwent neurological investigation, assessment of cognitive status, and PET scans with FDG. Results. Patients with AD showed decreases in NAA/Cr and Cho/Cr in the white matter of the medial cortex of the supraventricular areas of both hemispheres. The MCI group showed a decrease in the NAA/Cr ratio in only one area of the white matter of the left hemisphere, adjacent to the parietal cortex. Positive correlations were found between NAA/Cr and Cho/Cr with measures of cognitive status and with the rate of glucose metabolism measured from PET data in the frontal, parietal, and temporal areas and the cingulate cortex. Conclusions. The decrease in the NAA/Cr ratio in the supraventricular white matter and the medial cortex in AD and the correlation of this parameter with cognitive test results and cerebral glucose metabolism constitute evidence that it may have diagnostic value, reflecting the severity of cognitive impairments. Assessment of the NAA/Cr ratio should be carried out with consideration of the fact that dementia alters the concentrations of both metabolites (NAA and Cr).
Keywordsmagnetic resonance spectroscopy Alzheimer’s disease cognitive impairments N-acetylaspartate choline creatine positron emission tomography
Unable to display preview. Download preview PDF.
- 4.P. Trzepacz, P. Yu, J. Sun, K. Schuh, et al., Alzheimer’s Disease Neuroimaging Initiative, “Comparison of neuroimaging modalities for the prediction of conversion from mild cognitive impairment to Alzheimer’s dementia,” Neurobiol. Aging, 35, No. 1, 143–151 (2014), https://doi.org/ https://doi.org/10.1016/j.neurobiolaging.2013.06.018.CrossRefGoogle Scholar
- 6.P. B. Barker, A. Bizzi, N. De Stefano, et al., Clinical MR Spectroscopy: Techniques and Applications, Cambridge University Press (2009).Google Scholar
- 7.K. K. Haga, Y. P. Khor, A. Farrall, and J. M. Wardlaw, “A systematic review of brain metabolite changes, measured with 1H magnetic resonance spectroscopy, in healthy aging,” Neurobiol. Aging, 30, 353–363 (2009), https://doi.org/ https://doi.org/10.1016/j.neurobiolaging.2007.07.005.CrossRefGoogle Scholar
- 8.C. Stagg and D. Rothman (eds.), Magnetic Resonance Spectroscopy. Tools for Neuroscience Research and Emerging Clinical Applications, Elsevier (2014).Google Scholar
- 9.N. A. Semenova, T. A. Akhadov, A. V. Petryaikin, et al., “Metabolic impairments and the interaction of metabolic processes in the frontoparietal cortex of the brain in severe craniocerebral trauma. A study using local 1H magnetic resonance spectroscopy,” Biokhimiya, 77, No. 4, 493500 (2012).Google Scholar
- 12.K. Kantarci, R. C. Petersen, and B. F. Boeve, “1H-MR spectroscopy in common dementias,” Neurology, 63, No. 8, 1393–1398 (2004), https://doi.org/ https://doi.org/10.1212/01.wnl.0000141849.21256.ac.CrossRefGoogle Scholar
- 14.B. B. Frederick, A. Satlin, D. A. Yurgelun-Todd, and P. F. Renshaw, “In vivo proton magnetic resonance spectroscopy of Alzheimer’s disease in the parietal and temporal lobes,” Biol. Psychiatry, 42, No. 2, 147–150 (1997), https://doi.org/ https://doi.org/10.1016/s0006-3223(97)00242-4.CrossRefGoogle Scholar
- 18.A. Pfefferbaum, E. Adalsteinsson, D. Spielman, et al., “In vivo spectroscopic quantification of the N-acetyl moiety, creatine, and choline from large volumes of brain gray and white matter: effects of normal aging,” Magn. Reson. Med., 41, No. 2, 276–284 (1999), https://doi. org/10.1002/(sici)1522-2594(199902)41:2<276::aid-mrm10>3.3.co.Google Scholar
- 19.K. R. Krishnan, H. C. Charles, P. M. Doraiswamy, et al., “Randomized, placebo-controlled trial of the effects of donepezil on neuronal markers and hippocampal volumes in Alzheimer’s disease,” Am. J. Psychiatry, 160, No. 11, 2003–2011 (2003), https://doi.org/ https://doi.org/10.1176/appi.ajp.160.11.2003.CrossRefGoogle Scholar
- 20.S. Chantal, M. Labelle, R. W. Bouchard, et al., “Correlation of regional proton magnetic resonance spectroscopic metabolic changes with cognitive deficits in mild Alzheimer disease,” Arch. Neurol., 59, No.6, 955962 (2002), https://doi.org/ https://doi.org/10.1001/archneur.59.6.955.CrossRefGoogle Scholar
- 24.A. M. N. Coutinho, F. H. G. Porto, P. F. Zampieri, et al., “Analysis of the posterior cingulate cortex with [18F]FDG-PET and Naa/mI in mild cognitive impairment and Alzheimer’s disease: Correlations and differences between the two methods,” Dement. Neuropsychol., 9, No. 4, 385–393 (2015), https://doi.org/ https://doi.org/10.1590/1980-57642015DN94000385.CrossRefGoogle Scholar
- 25.S. V. Medvedev, T. Yu. Skvortsova, and R. N. Krasikova, PET in Russia: Positron Emission Tomography in the Clinic and Physiology, St. Petersburg (2008).Google Scholar
- 26.A. A. Bogdan, Yu. G. Khomenko, G. V. Kataeva, and T. N. Trofimova, “Principles of data grouping in assessment of the results of multivoxel spectroscopic investigations of the brain,” Luch. Diagnost. Ter., 4, No. 7, 15–19 (2016).Google Scholar
- 28.J. M. Allman, N. A. Tetreault, A. Y. Hakeem, et al., “The von Economo neurons in frontoinsular and anterior cingulate cortex,” Ann. N. Y. Acad. Sci., 1225, 59–71 (2011), https://doi.org/ https://doi.org/10.1111/j.1749-6632.2011.06011.x.
- 29.J. Talairach and P. Tournoux, Co-Planar Stereotactic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging, Thieme, New York (1988).Google Scholar
- 30.Statistical Parametric Mapping, www.fi l.ion.ucl.ac.uk/spm/, acc. May 15, 2018.Google Scholar
- 31.WFU PickAtlas, www.nitrc.org/projects/wfu_pickatlas/, acc. May 15, 2018.
- 32.I. Yakushev, C. Landvogt, H. G. Buchholz, et al., “Choice of reference area in studies of Alzheimer’s disease using positron emission tomography with fluorodeoxyglucose-F18,” Psychiatry Res., 164, No. 2, 143–153 (2008), http://dx.doi.org/ https://doi.org/10.1016/j.pscychresns.2007.11.004.CrossRefGoogle Scholar
- 33.Yu. G. Khomenko, A. A. Bogdan, G. V. Kataeva, and E. M. Chernysheva, “Use of multivoxel magnetic resonance spectroscopy in investigations of patients with cognitive disorders,” Vestn. Stankt- Peterburg. Univ. Ser. 4, Fiz, Khim., 3, No. 1, 82–89 (2016).Google Scholar
- 35.E. A. Gromova, A. A. Bogdan, G. V. Kataeva, et al., “Characteristics of the functional state of brain structures in HIV-infected patients,” Luch. Diagnost., 1, 41–48 (2016).Google Scholar
- 36.K. Weissenborn, B. Ahl, D. Fischer-Wasels, et al., “Correlations between magnetic resonance spectroscopy alterations and cerebral ammonia and glucose metabolism in cirrhotic patients with and without hepatic encephalopathy,” Gut, 56, No. 12, 1736–1742 (2007), http:// dx.doi.org/ https://doi.org/10.1136/gut.2006.110569.CrossRefGoogle Scholar
- 38.J. O’Neill, J. L. Eberling, N. Schuff, et al., “Method to correlate 1H MRSI and 18FDG-PET,” Magn. Reson. Med., 43, No. 2, 244–50 (2000), https://doi.org/10.1002/(sici)1522-2594(200002)43:2<244:: aid-mrm11>3.3.co.Google Scholar