Metabolite ratios in white and gray matter obtained with miltivoxel H-MRS in patients with cognitive impairment

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Khomenko, Galina V. Kataeva, Andrey A. Bogdan, Elena M. Chernysheva This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4472879/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract It is wellknown that there are technical difficulties in assessing absolute metabolite concentrations from peak values during in vivo magnetic resonance spectroscopy. At the same time, in other neuroimaging methods, for example, positron emission tomography, relative evaluations are widely used, when a radiopharmaceutical accumulation in the region of interest is normalized to its accumulation in the reference area. In this study we used the same approach in multivoxel magnetic resonance spectroscopy and evaluated the metabolites ratios in gray and white matter. The ratios of N-acethylaspartate, creatine and choline in gray and white matter in supraventricular area were studied in patients with cognitive impairment and age-related healthy controls. The creatine ratios in white and gray matter differed significantly in the observed groups and correlated with the cognitive tests scores and cortex thickness. The obtained results show that for the correct interpretation of magnetic resonance spectroscopy data could be useful to evaluate not only traditional metabolites ratios, but also ratios of metabolite concentrations in white and gray matter. magnetic resonance spectroscopy creatine dementia cognitive disorders metabolites ratios Figures Figure 1 Figure 2 Introduction Magnetic resonance spectroscopy (MRS) allows receiving data on different metabolites concentration in brain tissue in vivo, that is of great interest for the study of neurodegenerative diseases pathogenesis. The multivoxel MRS is of particular interest because of its capability to evaluate metabolite concentrations in white and gray matter in different brain regions simultaneously. In clinical practice, the most common is proton MRS (1H-MRS) and three major resonances evaluated are N-acethylaspartate (NAA), creatine (Cr) and choline (Cho). NAA corresponds to one of the most abundant amino acids in the central nervous system (CNS). It is considered to be the neuronal integrity marker, as it is contained in neurons bodies, axons and dendrites. It was found that higher NAA concentration correlates with the better CNS functional state. NAA decreases in diseases associated with destruction of the nervous tissue (strokes, tumors, multiple sclerosis, etc.). Its content can decrease both with irreversible nervous tissue damage, and with transient functional disorders, which can then be compensated under the influence of treatment [ 1 , 2 ]. In addition, NAA content decreases with age [ 3 ]. Cr is a combined peak of phosphocreatine and creatine, nitrogen-containing carboxylic acids, participate in energy metabolism in the muscle and nerve cells, plays a vital role in the cellular energy storage and transport. Glial cells contain 2–4 times more Cr than neurons in vitro. Despite the possible limitations, Cr is commonly used as an internal referent for the calculation of metabolite ratios in MRS examinations, as the evaluation of absolute metabolites concentrations in MRS is complicated because areas under the resonance peaks depend on the technical characteristics of the MR scanner, the features of the pulse sequence, data processing algorithms [ 1 , 2 ]. Cho is a peak consisting of trimethylamine groups of phosphocholine and glycerophosphocholine and a small amount of free choline. These compounds are important intermediates of lipid metabolism. Increased cell growth can be accompanied by an increase of intermediate products of lipid metabolism. They are associated with the disintegration and synthesis of membranes, and increased in diseases in which accelerated renewal of membranes is observed. A large number of them are also found in glial cells. The increase in Cho is characteristic for the processes associated with the membranes disintegration (demyelination, neuroinflammation, etc.). NAA, Cr and Cho concentrations differs in white and gray matter. Widerman et al. (2001) reported that Cr content in parietal gray matter was 113% of white matter. They also reported about the regional variations in metabolite concentrations: NAA in frontal gray matter was 86% of parietal gray matter and 85% of its concentration in white matter [ 5 ]. Wang&Li (1998) showed that NAA, Cr, and Cho concentrations in gray matter were significantly higher than in white matter. The averaged NAA, Cr, and Cho concentrations in gray matter were 11.0, 9.7, and 1.9 mM/liter, respectively, in comparison with 7.5, 5.2, and 1.6 mM/liter in white matter [ 6 ]. MacKay et al. (1996) revealed higher content of creatine-containing metabolites and/or lower NAA content in frontal white matter in subjects with subcortical ischemic vascular dementia compared to controls [ 7 ]. Hetherington et al. (1994) estimated that in healthy subjects Cr content was significantly lower in white matter than gray (p < 0.01), with a white/gray content ratio of 0.8, in agreement with biopsy [ 8 ]. There are several controversial studies, showed that the use of Cr as an internal referent may distort the results of MRS data evaluation [ 4 ]. Thus, on the one hand, there are technical difficulties in assessing the absolute values ​​of metabolite concentrations from peak values. On the other hand, using ratios like NAA/Cr brings the possibility of incorrectly assessing changes, because the rstio depends on the concentration of both metabolites — NAA and Cr. At the same time, in other neuroimaging methods, for example, in positron emissiom tomography, relative metabolism evaluations are widely used, when a radiopharmaceutical accumulation in the region of interest (ROI) is normalized to its accumulation in the reference areas, usually in the cerebellum, sensorimotor or insular cortex [ 15 ]. In this study we tried to use the same approach in multivoxel MRS and evaluate the ratios of the same metabolites in the medial cortex to their content in the adjacent white matter. Thus, the purpose of this research was to study ratios of the metabolites concentrations in gray and white matter in supraventricular area (in patients with dementia and mild cognitive impairment) in order to evaluate their possible diagnostic significance. Methods Group of 38 patients (17 with different types of dementia, 21 - mild cognitive impairment, MCI) and 10 healthy individuals as age-relevant control group) were examined. All patients underwent the standard neurological examination. Evaluation of the cognitive impairment severity was performed using the following scales: a mini-mental State Examination (MMSE), a maximum score of 30 points; The Montreal Cognitive Status Assessment Scale (MoCA), the frontal assessment battery (FAB) with a maximum score of 18 points; clock drawing test (CDT) with a maximum score of 10 point. The choice of short screening scales was due to the possibility of their use in a neurologist daily practice. The brief characteristic of the examined patients is presented in Table 1 . Table 1 The brief characteristic of the examined groups Diagnosis Number of patients Age Cognitive tests scores* MMSE MoCA FAB CDT m f Mean SD Mean SD Mean SD Mean SD Mean SD Dementia 8 9 69,6 7,7 16,3 6,3 11,8 5,5 12,3 6,3 4,0 1,7 Alzheimer disease (AD) 3 5 69,2 8,6 18 5,3 14,5 4,1 13,4 1,1 4,0 1,8 Frontotemporal degeneration (FTD) 3 0 67,2 6,2 9,3 8,5 5,7 6,4 6 5,6 2,0 2,0 Vascular dementia 0 3 78,3 2,9 14,3 1,5 14,3 1,5 11,3 3,8 4,0 1,0 Lewy bodies dementia 2 1 72,5 3,5 20,7 4,9 14,7 4,2 12,5 3,5 4,0 0,0 MCI 5 16 64,1 10,1 25,9 2,4 23,0 4,1 15,3 1,9 8,7 1,7 Age-relevant control group 2 8 54,5 8,1 - - - - - - - - MMSE - Mini-Mental State Examination, MoCA - Montreal Cognitive Status Assessment Scale, FAB - frontal assessment battery, CDT - clock drawing test MRI was performed on Achieva 3T scanner (Philips). Multivoxel 1H-MRS in supraventricular region, TE/TR = 144/2000 ms (TE – time of echo, TR – repetition time), pulse sequence 2D PRESS (Point Resolved Spectroscopic Sequence). The PRESS is based on a double-spin echo experiment consisting of 90 degree radio frequency (RF) pulse for excitation and two 180 degree refocusing pulses applied in frequency-selective way in the presence of a magnetic field gradient for the extraction of a planar slice. With the use of orthogonal slice orientations, the voxel volume for MRS is extracted as the intersection of the three slices. PRESS provides better signal to noise ratio in comparison with another spectroscopic sequences [ 1 , 2 ]. Anatomical localization of voxels is presented on Fig. 1. The area of MRS study − 8*9 voxels (10*10*15 mm), whole volume 80*90*15 mm was divided into 9 regions of interest (ROI): 6 in white matter (WM) of semioval centers (3 ROIs: anterior, medium and posterior for each hemisphere) and 3 ROIs in gray matter (GM) of medial cortex. The detailed description and justification for this approach for estimating the data of the multivoxel MRS is given in [ 12 ]. NAA/Cr, NAA/Cho, Cho/Cr ratios (NAA – N-acethyl aspartate, Cr – creatine, Cho – choline) were analyzed separately for each ROI. Besides that, ratios of metabolite peaks in three areas of gray matter (GM) (ROIs 7, 8 and 9 according Fig. 1) to the averaged values in all ROIs in supraventricular white matter (WM) were calculated for NAA, Cr and Cho. FreeSurfer V. 7.1.1. was used for morphometry. Morphometry was carried out using the FreeSurfer V. 7.1.1 program, the area of brain volumes normalized to intracranial volume were calculated from T1 images. Results NAA/Cr, Cho/Cr and NAA/Cho ratios were significantly lower in dementia group compared to both MCI and controls (p < 0,01). These findings are in accordance with our previous studies on smaller group of cognitively impaired patients [ 13 ]. Metabolite ratios in ROIs medial cortex and averaged values in supraventrivular white matter shown in Table 2 . The ratio of Cr in WM to Cr in GM were significantly higher (p < 0.01) in the dementia group (possibly due to the cortex atrophy). NAA in WM to NAA in GM ratios in two ROIs also shown the similar difference. Table 2 Ratios of Cr content in white matter to the corresponding areas of medial cortex, p-level for multiple groups comparison according to Kruskal-Wallis test. Metabolites ratios Dementia MCI Controls p Mean SD Mean SD Mean SD Cr GM7/ WM 0.88 0.13 1.03 0.09 1.02 0.06 p = 0.0001 Cr GM8/ WM 1.04 0.11 1.18 0.08 1.18 0.10 p = 0.0002 Cr GM9/ WM 0.98 0.11 1.14 0.11 1.13 0.12 p = 0.0003 NAA GM7/ WM 0.73 0.11 0.90 0.11 0.80 0.05 p = 0.0111 NAA GM8/ WM 0.86 0.08 0.93 0.07 0.92 0.07 p = 0.0114 NAA GM9/ WM 0.85 0.10 0.81 0.08 0.91 0.11 p = 0.2655 *Numbers of areas given in accordance with ROIs in Fig. 1 Ratios of Cho content in WM and GM did not differ in the examined groups. As shown in Table 3 , Cr GM/WM ratios in all ROIs and NAA in one ROI correlated with MMSE, MoCA, FAB and CDT tests scores. Table 3 Correlations of metabolites ratios with cognitive tests scores Ratios in ROIs* Cognitive tests MMSE MoCA FAB CDT r p r p r p r p Cr GM7/ WM 0.37 0.0100 0.44 0.0027 0.47 0.0013 0.51 0.0003 Cr GM8/ WM 0.41 0.0056 0.47 0.0011 0.42 0.0052 0.49 0.0007 Cr GM9/ WM 0.43 0.0038 0.43 0.0038 0.38 0.0141 0.44 0.0030 NAA GM7/ WM - - - - 0.46 0.0017 - - NAA GM8/ WM - - - - - - - - NAA GM9/ WM - - - - - - - - * Numbers of areas given in accordance with ROIs in Fig. 1 Also negative correlations of the metabolites ratios with the age of patients were revealed: Cr GM7/ WM (r=-0.46; p = 0.0037), Cr GM8/ WM (r=-0.41; p = 0.0114), Cr GM9/ WM (r=-0.42; p = 0.0088). It is possible that the revealed correlations reflect the severity of cortical atrophy, which is obviously more pronounced in patients with dementia. To verify this assumption, the metabolite ratios were compared with the thickness of the cortex in the ROIs according to morphometry data (Table 4 ). Table 4 Correlations of metabolites ratios with cortical volumes. Ratios in ROIs ROI Caudal anterior cingulate R Caudal anterior cingulate L Posterior cingulate R Posterior cingulate L r p r p r p r p Cr GM7/ WM 0.35 0.0311 0.34 0.0386 - - - - Cr GM8/ WM 0.50 0.0015 - - 0.37 0.0211 0.37 0.0220 Cr GM9/ WM 0.46 0.0044 - - - - - - NAA GM7/ WM - - - - - - - - NAA GM8/ WM - - - - - - - - NAA GM9/ WM - - - - - - - - Interestingly, the volume of the cingulate cortex was associated with the creatine ratio in the gray and white matter, but not NAA and choline. Discussion and conclusion According to the literature, the decrease in the NAA/Cr ratio in the temporal area and posterior cingulate gyrus, medial occipital cortex, hippocampus, etc is found in dementia. [ 9 ]. During the development of the disease, NAA changes become more common and are found in the parietal, temporal and frontal lobes [ 10 ]. The decrease in NAA/Cr is non-specific and is found in different types of dementia [ 11 ]. We found that the content of Cr and NAA in white matter and gray matter in medial cortex differs significantly in dementia, mild cognitive impairment, and age-related normal controls. In dementia, concentrations of these metabolites in gray matter decrease in relation to the white matter, probably due to the cortex atrophy. These ratios of Cr correlated with the cognitive tests scores. Also similar correlations of NAA ratios were revealed, but less pronounced. Changes in metabolites content ratios in white and gray matter in patients with dementia and MCI could appear dew to pathogenic processes associated with dementia, and with age-related changes of cortex thickness. It is known that the normal concentration of Cr is higher in gray matter than in white, the Cr content slowly increasing with age. Despite this, it is considered that the Cr concentration remains sufficiently stable to use it as an internal referent. Nevertheless, the revealed dependencies may indicate the alterations of Cr concentration in the brain tissue of patients with dementia, that is in accordance with the conceptions of energy metabolic changes in this category of patients. Thus, it is known that there is a decrease in the intensity of glucose metabolism in the parietal, temporal and frontal association cortical areas in BA patients with its relatively normal or increased metabolism in the primary sensorimotor and visual cortex, cerebellum, basal ganglia and thalamus. In addition, according to the results obtained in several research [ 14 ], BA and MCI is characterised with mitochondrial disfunctions and alteration of the adenosine triphosphate synthesis that can be revealed using 31P MRS. In the current research differences of Cr concentration ratio in white and gray matter in demented and non-demented groups were revealed. This fact brings into a question the use of Cr as an internal reference for the evaluation of other metabolites concentrations (NAA, Cho and others) for the patients with dementia and mild cognitive impaitment. For example, in case of simultaneous decrease of NAA and Cr concentrations the implementation of commonly used NAA/Cr ratio for the neuronal integrity evaluation will mask NAA decrease. Thus, the diagnostic significance of NAA/Cr ratio for the evaluation of neuronal integrity in such cases could have limited diagnostic value. The obtained results show that for the correct interpretation of MRS data both for the clinical and scientific purposes could be useful to evaluate not only traditional metabolites ratios, but also creatine concentration, ratios of metabolite concentrations in white and gray matter and the cortex atrophy level. Besides that, ratios of creatine peaks in gray and in white matter could be considered as an additional indicator for assessing atrophy, especially considering the fact that the morphometric analysis requires significant time and computational resources. The revealed changes of metabolite ratios in patients with dementia possibly have the diagnostic value in neurodegenerative diseases, but follow-up studies are required to clarify their diagnostic significance. Limitations. Different nosologies are presented in the dementia group, however, the purpose of this work was not to study the features of MRS in different types of dementia, but the study of a possible new methodological approach to assessing data from multivoxel MRS. Another limitation is that there was no complete coincidence of the regions of interest for MRS and morphometry there the standard ROIs, embedded in atlases were used. It was due to the technical difficulties of transferring the exact coordinates of MRS voxels for each patient to the available MRI data. The authors will try to solve these technical difficulties in the subsequent work. Declarations Ethical Approval The study was approved by the Ethical Committee of the N.P. Bechtereva Institute of the Human Brain of the Russian Academy of Sciences, Protocol No. 1, 01/19/2017. All participants signed an informed consent to participate and publish the results of the study. Funding The research carried out according to the state assignment of of the N.P. Bechtereva Institute of the Human Brain of the Russian Academy of Sciences, N 0133-2016-0002. Author Contribution Y.K. and G.K. wrote the main manuscript text and statistical data analysis, A.B. performed HMRS and MRI examination and analysis, E.C. made cognitive functions and clinical symptoms evaluation, all authors reviewed the manuscript. Availability of data and materials Not applicable. References Clinical MR Spectroscopy: Techniques and Applications. Barker P.B., Bizzi A., De Stefano N., Gullapalli R.P., Lin D. M. Cambridge University Press (2009). Magnetic Resonance Spectroscopy. Tools for Neuroscience Research and Emerging Clinical Applications/ Eds. C. Stagg, D. Rothman. Elsevier Academic Press (2014). Li B.S.Y., Wang H., Gonena O. Metabolite ratios to assumed stable creatine level may confound the quantification of proton brain MR spectroscopy /Magnetic Resonance Imaging 21, 923–928 (2003). Haga K.K., Khor Y.P., Farrall A., Wardlaw J.M. A systematic review of brain metabolite changes, measured with 1 H magnetic resonance spectroscopy, in healthy aging. Neurobiology of Aging 30 353–363 (2009). Widerman, D., Schuff, N., Matson, G.B., Soher, B.J., Du, A.T., Maudsley, A.A., Weiner, M.W., Short echo time multislice proton magnetic resonance spectroscopic imaging in human brain: metabolite distributions and reliability. Magn. Reson. Imaging 19 (8), 10873–11080 (2001). Wang Y., Li S.J. Differentiation of metabolic concentrations between gray matter and white matter of human brain by in vivo 1H magnetic resonance spectroscopy. Magn Reson Med, 39(1), 28–33 (1998). MacKay S., Meyerhoff D.J., Constans J.M., Norman D., Fein G., Weiner M.W. Regional gray and white matter metabolite differences in subjects with AD, with subcortical ischemic vascular dementia, and elderly controls with 1H magnetic resonance spectroscopic imaging. Arch Neurol., 53(2), 167–74 (1996). Mason G.F., Pan J.W., Ponder S.L., Twieg D.B., Pohost G.M., Hetherington H.P. Detection of brain glutamate and glutamine in spectroscopic images at 4.1 T. Magn Reson Med, 32(1), 142–145 (1994). Kantarci K., Jack C.R., Xu Y.C. Regional metabolic patterns inmild cognitive impairment and Alzheimer’s disease: A 1H MRS study. Neurology, 55, 2, 210–217 (2000). Frederick B.B., Satlin A., Yurgelun-Todd D.A., Renshaw P.F. In vivo proton magnetic resonance spectroscopy of Alzheimer’s disease in the parietal and temporal lobes. Biol. Psychiatry,42,2,147–150 (1997). Graff-Radford J., Kantarci K. Magnetic resonance spectroscopy in Alzheimer’s disease. Neuropsychiatric Disease and Treatment, 687–696 (2013). Bogdan A.A., Khomenko J.G., Kataeva G.V., Trofimova T.N. Principles of data grouping in assessment of human brain multivoxel spectroscopic studies. Luchevaya diagnostica i terapiya, 4(7), 15–19 (2016). Khomenko Y.G., Bogdan A.A., Kataeva G.V., Chernysheva E.M., Multivoxel magnetic resonance spectroscopy in the examination of patients with cognitive disorders// Vestnik Sankt-Peterburgskogo universiteta. Seriya 4. Fizika. Khimiya, 3(1), 82–89 (2016). Das N, Ren J, Spence JS, Rackley A and Chapman SB. Relationship of Parieto-Occipital Brain Energy Phosphate Metabolism and Cognition Using 31P MRS at 7-Tesla in Amnestic Mild Cognitive Impairment. Front. Aging Neurosci, 12, 222(2020). doi: 10.3389/fnagi.2020.00222 Khomenko Ju.G., Susin D.S., Kataeva G.V., Irishina Ju.A., Zavolokov I.G. Characteristics of cerebral glucose metabolism in patients with cognitive impairment in Parkinson's disease. Zhurnal nevrologii i psikhiatrii imeni S.S. Korsakova, 5, 46–51 (2017). doi: 10.17116/jnevro20171175146-5 Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Segonne, F., Salat, D.H., Busa, E., Seidman, L.J., Goldstein, J., Kennedy, D., Caviness, V., Makris, N., Rosen, B., Dale, A.M. Automatically parcellating the human cerebral cortex. Cereb Cortex 14, 11–22 (2004). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4472879","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312796816,"identity":"044318dd-acbc-48a6-be9c-c7476b558c59","order_by":0,"name":"Yulia G. 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Granov Russian Scientific Center for Radiology and Surgical Technologies","correspondingAuthor":false,"prefix":"","firstName":"Galina","middleName":"V.","lastName":"Kataeva","suffix":""},{"id":312796818,"identity":"7362859c-500e-44fa-a3d9-16ac949663b6","order_by":2,"name":"Andrey A. Bogdan","email":"","orcid":"","institution":"St. Petersburg State Electrotechnical University \"LETI\" named after V.I. Ulyanov (Lenin)","correspondingAuthor":false,"prefix":"","firstName":"Andrey","middleName":"A.","lastName":"Bogdan","suffix":""},{"id":312796819,"identity":"f4bc65d8-4e00-4bb5-b5a7-55d46dc13033","order_by":3,"name":"Elena M. Chernysheva","email":"","orcid":"","institution":"N.P. Bechtereva Institute of the Human Brain of Russian Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"M.","lastName":"Chernysheva","suffix":""}],"badges":[],"createdAt":"2024-05-24 13:47:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4472879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4472879/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58516764,"identity":"e675341f-91de-40c0-a960-bf6b6c2f4852","added_by":"auto","created_at":"2024-06-17 16:50:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293438,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e(а) — MRS anatomical localization in the supraventricular region;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(b) — localization of regions of interest in white (1-3 and 4-6) and gray matter (7-9).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4472879/v1/e5d52ac79322e5350381a90a.png"},{"id":58516763,"identity":"dea67830-e77f-450b-8ce1-701b9cd885dd","added_by":"auto","created_at":"2024-06-17 16:50:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":603910,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eExample of MR spectra in control group (A) and dementia (B).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4472879/v1/ed4841ef16270c27adfbaf6b.png"},{"id":59004064,"identity":"950cc11f-0ca2-4341-8133-9602d4197ab5","added_by":"auto","created_at":"2024-06-25 07:40:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1598288,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4472879/v1/fb366b59-e73d-4100-bb6d-9ee6f59df28a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Metabolite ratios in white and gray matter obtained with miltivoxel H-MRS in patients with cognitive impairment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMagnetic resonance spectroscopy (MRS) allows receiving data on different metabolites concentration in brain tissue in vivo, that is of great interest for the study of neurodegenerative diseases pathogenesis. The multivoxel MRS is of particular interest because of its capability to evaluate metabolite concentrations in white and gray matter in different brain regions simultaneously. In clinical practice, the most common is proton MRS (1H-MRS) and three major resonances evaluated are N-acethylaspartate (NAA), creatine (Cr) and choline (Cho).\u003c/p\u003e \u003cp\u003eNAA corresponds to one of the most abundant amino acids in the central nervous system (CNS). It is considered to be the neuronal integrity marker, as it is contained in neurons bodies, axons and dendrites. It was found that higher NAA concentration correlates with the better CNS functional state. NAA decreases in diseases associated with destruction of the nervous tissue (strokes, tumors, multiple sclerosis, etc.). Its content can decrease both with irreversible nervous tissue damage, and with transient functional disorders, which can then be compensated under the influence of treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition, NAA content decreases with age [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCr is a combined peak of phosphocreatine and creatine, nitrogen-containing carboxylic acids, participate in energy metabolism in the muscle and nerve cells, plays a vital role in the cellular energy storage and transport. Glial cells contain 2\u0026ndash;4 times more Cr than neurons in vitro. Despite the possible limitations, Cr is commonly used as an internal referent for the calculation of metabolite ratios in MRS examinations, as the evaluation of absolute metabolites concentrations in MRS is complicated because areas under the resonance peaks depend on the technical characteristics of the MR scanner, the features of the pulse sequence, data processing algorithms [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCho is a peak consisting of trimethylamine groups of phosphocholine and glycerophosphocholine and a small amount of free choline. These compounds are important intermediates of lipid metabolism. Increased cell growth can be accompanied by an increase of intermediate products of lipid metabolism. They are associated with the disintegration and synthesis of membranes, and increased in diseases in which accelerated renewal of membranes is observed. A large number of them are also found in glial cells. The increase in Cho is characteristic for the processes associated with the membranes disintegration (demyelination, neuroinflammation, etc.).\u003c/p\u003e \u003cp\u003eNAA, Cr and Cho concentrations differs in white and gray matter. Widerman et al. (2001) reported that Cr content in parietal gray matter was 113% of white matter. They also reported about the regional variations in metabolite concentrations: NAA in frontal gray matter was 86% of parietal gray matter and 85% of its concentration in white matter [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWang\u0026amp;Li (1998) showed that NAA, Cr, and Cho concentrations in gray matter were significantly higher than in white matter. The averaged NAA, Cr, and Cho concentrations in gray matter were 11.0, 9.7, and 1.9 mM/liter, respectively, in comparison with 7.5, 5.2, and 1.6 mM/liter in white matter [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMacKay et al. (1996) revealed higher content of creatine-containing metabolites and/or lower NAA content in frontal white matter in subjects with subcortical ischemic vascular dementia compared to controls [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHetherington et al. (1994) estimated that in healthy subjects Cr content was significantly lower in white matter than gray (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with a white/gray content ratio of 0.8, in agreement with biopsy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are several controversial studies, showed that the use of Cr as an internal referent may distort the results of MRS data evaluation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThus, on the one hand, there are technical difficulties in assessing the absolute values ​​of metabolite concentrations from peak values. On the other hand, using ratios like NAA/Cr brings the possibility of incorrectly assessing changes, because the rstio depends on the concentration of both metabolites \u0026mdash; NAA and Cr. At the same time, in other neuroimaging methods, for example, in positron emissiom tomography, relative metabolism evaluations are widely used, when a radiopharmaceutical accumulation in the region of interest (ROI) is normalized to its accumulation in the reference areas, usually in the cerebellum, sensorimotor or insular cortex [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study we tried to use the same approach in multivoxel MRS and evaluate the ratios of the same metabolites in the medial cortex to their content in the adjacent white matter.\u003c/p\u003e \u003cp\u003eThus, the purpose of this research was to study ratios of the metabolites concentrations in gray and white matter in supraventricular area (in patients with dementia and mild cognitive impairment) in order to evaluate their possible diagnostic significance.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eGroup of 38 patients (17 with different types of dementia, 21 - mild cognitive impairment, MCI) and 10 healthy individuals as age-relevant control group) were examined. All patients underwent the standard neurological examination. Evaluation of the cognitive impairment severity was performed using the following scales: a mini-mental State Examination (MMSE), a maximum score of 30 points; The Montreal Cognitive Status Assessment Scale (MoCA), the frontal assessment battery (FAB) with a maximum score of 18 points; clock drawing test (CDT) with a maximum score of 10 point. The choice of short screening scales was due to the possibility of their use in a neurologist daily practice. The brief characteristic of the examined patients is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe brief characteristic of the examined groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eNumber of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c5\" namest=\"c4\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c13\" namest=\"c6\"\u003e \u003cp\u003eCognitive tests scores*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eFAB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eCDT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003em\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ef\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlzheimer disease (AD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1,8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrontotemporal degeneration (FTD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular dementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLewy bodies dementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge-relevant\u003c/p\u003e \u003cp\u003econtrol group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eMMSE - Mini-Mental State Examination, MoCA - Montreal Cognitive Status Assessment Scale, FAB - frontal assessment battery, CDT - clock drawing test\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMRI was performed on Achieva 3T scanner (Philips). Multivoxel 1H-MRS in supraventricular region, TE/TR\u0026thinsp;=\u0026thinsp;144/2000 ms (TE \u0026ndash; time of echo, TR \u0026ndash; repetition time), pulse sequence 2D PRESS (Point Resolved Spectroscopic Sequence). The PRESS is based on a double-spin echo experiment consisting of 90 degree radio frequency (RF) pulse for excitation and two 180 degree refocusing pulses applied in frequency-selective way in the presence of a magnetic field gradient for the extraction of a planar slice. With the use of orthogonal slice orientations, the voxel volume for MRS is extracted as the intersection of the three slices. PRESS provides better signal to noise ratio in comparison with another spectroscopic sequences [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnatomical localization of voxels is presented on Fig.\u0026nbsp;1. The area of MRS study \u0026minus;\u0026thinsp;8*9 voxels (10*10*15 mm), whole volume 80*90*15 mm was divided into 9 regions of interest (ROI): 6 in white matter (WM) of semioval centers (3 ROIs: anterior, medium and posterior for each hemisphere) and 3 ROIs in gray matter (GM) of medial cortex. The detailed description and justification for this approach for estimating the data of the multivoxel MRS is given in [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNAA/Cr, NAA/Cho, Cho/Cr ratios (NAA \u0026ndash; N-acethyl aspartate, Cr \u0026ndash; creatine, Cho \u0026ndash; choline) were analyzed separately for each ROI. Besides that, ratios of metabolite peaks in three areas of gray matter (GM) (ROIs 7, 8 and 9 according Fig.\u0026nbsp;1) to the averaged values in all ROIs in supraventricular white matter (WM) were calculated for NAA, Cr and Cho.\u003c/p\u003e \u003cp\u003eFreeSurfer V. 7.1.1. was used for morphometry. Morphometry was carried out using the FreeSurfer V. 7.1.1 program, the area of brain volumes normalized to intracranial volume were calculated from T1 images.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eNAA/Cr, Cho/Cr and NAA/Cho ratios were significantly lower in dementia group compared to both MCI and controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0,01). These findings are in accordance with our previous studies on smaller group of cognitively impaired patients [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMetabolite ratios in ROIs medial cortex and averaged values in supraventrivular white matter shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The ratio of Cr in WM to Cr in GM were significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in the dementia group (possibly due to the cortex atrophy). NAA in WM to NAA in GM ratios in two ROIs also shown the similar difference.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRatios of Cr content in white matter to the corresponding areas of medial cortex, p-level for multiple groups comparison according to Kruskal-Wallis test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolites ratios\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDementia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.0114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.2655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e*Numbers of areas given in accordance with ROIs in Fig.\u0026nbsp;1\u003c/h2\u003e \u003cp\u003eRatios of Cho content in WM and GM did not differ in the examined groups.\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Cr GM/WM ratios in all ROIs and NAA in one ROI correlated with MMSE, MoCA, FAB and CDT tests scores.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations of metabolites ratios with cognitive tests scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRatios in ROIs*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eCognitive tests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eFAB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eCDT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e* Numbers of areas given in accordance with ROIs in Fig.\u0026nbsp;1\u003c/h2\u003e \u003cp\u003eAlso negative correlations of the metabolites ratios with the age of patients were revealed: Cr GM7/ WM (r=-0.46; p\u0026thinsp;=\u0026thinsp;0.0037), Cr GM8/ WM (r=-0.41; p\u0026thinsp;=\u0026thinsp;0.0114), Cr GM9/ WM (r=-0.42; p\u0026thinsp;=\u0026thinsp;0.0088).\u003c/p\u003e \u003cp\u003eIt is possible that the revealed correlations reflect the severity of cortical atrophy, which is obviously more pronounced in patients with dementia. To verify this assumption, the metabolite ratios were compared with the thickness of the cortex in the ROIs according to morphometry data (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations of metabolites ratios with cortical volumes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRatios in ROIs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eROI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCaudal anterior cingulate R\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCaudal anterior cingulate L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePosterior cingulate R\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003ePosterior cingulate L\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM7/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM8/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAA GM9/ WM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInterestingly, the volume of the cingulate cortex was associated with the creatine ratio in the gray and white matter, but not NAA and choline.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion and conclusion","content":"\u003cp\u003eAccording to the literature, the decrease in the NAA/Cr ratio in the temporal area and posterior cingulate gyrus, medial occipital cortex, hippocampus, etc is found in dementia. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. During the development of the disease, NAA changes become more common and are found in the parietal, temporal and frontal lobes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The decrease in NAA/Cr is non-specific and is found in different types of dementia [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that the content of Cr and NAA in white matter and gray matter in medial cortex differs significantly in dementia, mild cognitive impairment, and age-related normal controls. In dementia, concentrations of these metabolites in gray matter decrease in relation to the white matter, probably due to the cortex atrophy. These ratios of Cr correlated with the cognitive tests scores. Also similar correlations of NAA ratios were revealed, but less pronounced. Changes in metabolites content ratios in white and gray matter in patients with dementia and MCI could appear dew to pathogenic processes associated with dementia, and with age-related changes of cortex thickness.\u003c/p\u003e \u003cp\u003eIt is known that the normal concentration of Cr is higher in gray matter than in white, the Cr content slowly increasing with age. Despite this, it is considered that the Cr concentration remains sufficiently stable to use it as an internal referent. Nevertheless, the revealed dependencies may indicate the alterations of Cr concentration in the brain tissue of patients with dementia, that is in accordance with the conceptions of energy metabolic changes in this category of patients. Thus, it is known that there is a decrease in the intensity of glucose metabolism in the parietal, temporal and frontal association cortical areas in BA patients with its relatively normal or increased metabolism in the primary sensorimotor and visual cortex, cerebellum, basal ganglia and thalamus. In addition, according to the results obtained in several research [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], BA and MCI is characterised with mitochondrial disfunctions and alteration of the adenosine triphosphate synthesis that can be revealed using 31P MRS.\u003c/p\u003e \u003cp\u003eIn the current research differences of Cr concentration ratio in white and gray matter in demented and non-demented groups were revealed. This fact brings into a question the use of Cr as an internal reference for the evaluation of other metabolites concentrations (NAA, Cho and others) for the patients with dementia and mild cognitive impaitment. For example, in case of simultaneous decrease of NAA and Cr concentrations the implementation of commonly used NAA/Cr ratio for the neuronal integrity evaluation will mask NAA decrease. Thus, the diagnostic significance of NAA/Cr ratio for the evaluation of neuronal integrity in such cases could have limited diagnostic value. The obtained results show that for the correct interpretation of MRS data both for the clinical and scientific purposes could be useful to evaluate not only traditional metabolites ratios, but also creatine concentration, ratios of metabolite concentrations in white and gray matter and the cortex atrophy level.\u003c/p\u003e \u003cp\u003eBesides that, ratios of creatine peaks in gray and in white matter could be considered as an additional indicator for assessing atrophy, especially considering the fact that the morphometric analysis requires significant time and computational resources. The revealed changes of metabolite ratios in patients with dementia possibly have the diagnostic value in neurodegenerative diseases, but follow-up studies are required to clarify their diagnostic significance.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations.\u003c/b\u003e Different nosologies are presented in the dementia group, however, the purpose of this work was not to study the features of MRS in different types of dementia, but the study of a possible new methodological approach to assessing data from multivoxel MRS. Another limitation is that there was no complete coincidence of the regions of interest for MRS and morphometry there the standard ROIs, embedded in atlases were used. It was due to the technical difficulties of transferring the exact coordinates of MRS voxels for each patient to the available MRI data. The authors will try to solve these technical difficulties in the subsequent work.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthical Approval\u003c/strong\u003e \u003cp\u003e The study was approved by the Ethical Committee of the N.P. Bechtereva Institute of the Human Brain of the Russian Academy of Sciences, Protocol No. 1, 01/19/2017. All participants signed an informed consent to participate and publish the results of the study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe research carried out according to the state assignment of of the N.P. Bechtereva Institute of the Human Brain of the Russian Academy of Sciences, N 0133-2016-0002.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.K. and G.K. wrote the main manuscript text and statistical data analysis, A.B. performed HMRS and MRI examination and analysis, E.C. made cognitive functions and clinical symptoms evaluation, all authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eClinical MR Spectroscopy: Techniques and Applications. Barker P.B., Bizzi A., De Stefano N., Gullapalli R.P., Lin D. M. Cambridge University Press (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagnetic Resonance Spectroscopy. Tools for Neuroscience Research and Emerging Clinical Applications/ Eds. C. Stagg, D. Rothman. 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Cereb Cortex 14, 11\u0026ndash;22 (2004).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"magnetic resonance spectroscopy, creatine, dementia, cognitive disorders, metabolites ratios","lastPublishedDoi":"10.21203/rs.3.rs-4472879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4472879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIt is wellknown that there are technical difficulties in assessing absolute metabolite concentrations from peak values during in vivo magnetic resonance spectroscopy. At the same time, in other neuroimaging methods, for example, positron emission tomography, relative evaluations are widely used, when a radiopharmaceutical accumulation in the region of interest is normalized to its accumulation in the reference area. In this study we used the same approach in multivoxel magnetic resonance spectroscopy and evaluated the metabolites ratios in gray and white matter. The ratios of N-acethylaspartate, creatine and choline in gray and white matter in supraventricular area were studied in patients with cognitive impairment and age-related healthy controls. The creatine ratios in white and gray matter differed significantly in the observed groups and correlated with the cognitive tests scores and cortex thickness. The obtained results show that for the correct interpretation of magnetic resonance spectroscopy data could be useful to evaluate not only traditional metabolites ratios, but also ratios of metabolite concentrations in white and gray matter.\u003c/p\u003e","manuscriptTitle":"Metabolite ratios in white and gray matter obtained with miltivoxel H-MRS in patients with cognitive impairment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-17 16:50:33","doi":"10.21203/rs.3.rs-4472879/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7935de36-b0b4-42c7-9418-ce51f943a803","owner":[],"postedDate":"June 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-25T07:32:40+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-17 16:50:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4472879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4472879","identity":"rs-4472879","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}