1
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Rogala J, Dreszer J, Sińczuk M, Miciuk Ł, Piątkowska-Janko E, Bogorodzki P, Wolak T, Wróbel A, Konarzewski M. Local variation in brain temperature explains gender-specificity of working memory performance. Front Hum Neurosci 2024; 18:1398034. [PMID: 39132677 PMCID: PMC11310161 DOI: 10.3389/fnhum.2024.1398034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/05/2024] [Indexed: 08/13/2024] Open
Abstract
Introduction Exploring gender differences in cognitive abilities offers vital insights into human brain functioning. Methods Our study utilized advanced techniques like magnetic resonance thermometry, standard working memory n-back tasks, and functional MRI to investigate if gender-based variations in brain temperature correlate with distinct neuronal responses and working memory capabilities. Results We observed a significant decrease in average brain temperature in males during working memory tasks, a phenomenon not seen in females. Although changes in female brain temperature were significantly lower than in males, we found an inverse relationship between the absolute temperature change (ATC) and cognitive performance, alongside a correlation with blood oxygen level dependent (BOLD) signal change induced by neural activity. This suggests that in females, ATC is a crucial determinant for the link between cognitive performance and BOLD responses, a linkage not evident in males. However, we also observed additional female specific BOLD responses aligned with comparable task performance to that of males. Discussion Our results suggest that females compensate for their brain's heightened temperature sensitivity by activating additional neuronal networks to support working memory. This study not only underscores the complexity of gender differences in cognitive processing but also opens new avenues for understanding how temperature fluctuations influence brain functionality.
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Affiliation(s)
- Jacek Rogala
- Centre for Research on Culture, Language, and Mind, University of Warsaw, Warsaw, Poland
- The Centre for Systemic Risk Analysis, University of Warsaw, Warsaw, Poland
| | - Joanna Dreszer
- Faculty of Philosophy and Social Sciences, Institute of Psychology, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Marcin Sińczuk
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Łukasz Miciuk
- Faculty of Philosophy and Social Sciences, Institute of Psychology, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Ewa Piątkowska-Janko
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Piotr Bogorodzki
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Tomasz Wolak
- Bioimaging Research Center, World Hearing Center, Institute of Physiology and Pathology of Hearing, Kajetany, Poland
| | - Andrzej Wróbel
- Nencki Institute of Experimental Biology, Warsaw, Poland
- Faculty of Philosophy, University of Warsaw, Warsaw, Poland
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2
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Mueller C, Nenert R, Catiul C, Pilkington J, Szaflarski JP, Amara AW. Brain metabolites are associated with sleep architecture and cognitive functioning in older adults. Brain Commun 2024; 6:fcae245. [PMID: 39104903 PMCID: PMC11300014 DOI: 10.1093/braincomms/fcae245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 05/09/2024] [Accepted: 07/17/2024] [Indexed: 08/07/2024] Open
Abstract
Sleep deficits are a possible risk factor for development of cognitive decline and dementia in older age. Research suggests that neuroinflammation may be a link between the two. This observational, cross-sectional study evaluated relationships between sleep architecture, neuroinflammation and cognitive functioning in healthy older adults. Twenty-two adults aged ≥60 years underwent whole-brain magnetic resonance spectroscopic imaging (in vivo method of visualizing increased brain temperatures as a proxy for neuroinflammation), supervised laboratory-based polysomnography, and comprehensive neurocognitive testing. Multiple regressions were used to assess relationships between magnetic resonance spectroscopic imaging-derived brain temperature and metabolites related to inflammation (choline; myo-inositol; N-acetylaspartate), sleep efficiency, time and % N3 sleep and cognitive performance. Choline, myo-inositol and N-acetylaspartate were associated with sleep efficiency and cognitive performance. Higher choline and myo-inositol in the bilateral frontal lobes were associated with slower processing speed and lower sleep efficiency. Higher choline and myo-inositol in bilateral frontoparietal regions were associated with better cognitive performance. Higher N-acetylaspartate around the temporoparietal junction and adjacent white matter was associated with better visuospatial function. Brain temperature was not related to cognitive or sleep outcomes. Our findings are consistent with the limited literature regarding neuroinflammation and its relationships with sleep and cognition in older age, which has implicated ageing microglia and astrocytes in circadian dysregulation, impaired glymphatic clearance and increased blood-brain barrier integrity, with downstream effects of neurodegeneration and cognitive decline. Inflammatory processes remain difficult to measure in the clinical setting, but magnetic resonance spectroscopic imaging may serve as a marker of the relationship between neuroinflammation, sleep and cognitive decline in older adults.
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Affiliation(s)
- Christina Mueller
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Rodolphe Nenert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Corina Catiul
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Jennifer Pilkington
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Jerzy P Szaflarski
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Amy W Amara
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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3
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Instrella R, Juchem C. Uncertainty propagation in absolute metabolite quantification for in vivo MRS of the human brain. Magn Reson Med 2024; 91:1284-1300. [PMID: 38029371 PMCID: PMC11062627 DOI: 10.1002/mrm.29903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 09/27/2023] [Accepted: 10/06/2023] [Indexed: 12/01/2023]
Abstract
PURPOSE Absolute spectral quantification is the standard method for deriving estimates of the concentration from metabolite signals measured using in vivo proton MRS (1 H-MRS). This method is often reported with minimum variance estimators, specifically the Cramér-Rao lower bound (CRLB) of the metabolite signal amplitude's scaling factor from linear combination modeling. This value serves as a proxy for SD and is commonly reported in MRS experiments. Characterizing the uncertainty of absolute quantification, however, depends on more than simply the CRLB. The uncertainties of metabolite-specific (T1m , T2m ), reference-specific (T1ref , T2ref ), and sequence-specific (TR , TE ) parameters are generally ignored, potentially leading to an overestimation of precision. In this study, the propagation of uncertainty is used to derive a comprehensive estimate of the overall precision of concentrations from an internal reference. METHODS The propagated uncertainty is calculated using analytical derivations and Monte Carlo simulations and subsequently analyzed across a set of commonly measured metabolites and macromolecules. The effect of measurement error from experimentally obtained quantification parameters is estimated using published uncertainties and CRLBs from in vivo 1 H-MRS literature. RESULTS The additive effect of propagated measurement uncertainty from applied quantification correction factors can result in up to a fourfold increase in the concentration estimate's coefficient of variation compared to the CRLB alone. A case study analysis reveals similar multifold increases across both metabolites and macromolecules. CONCLUSION The precision of absolute metabolite concentrations derived from 1 H-MRS experiments is systematically overestimated if the uncertainties of commonly applied corrections are neglected as sources of error.
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Affiliation(s)
- Ronald Instrella
- Department of Biomedical Engineering, Columbia University,
New York, NY, USA
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University,
New York, NY, USA
- Department of Radiology, Columbia University Irving Medical
Center, New York, NY, USA
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4
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Gudmundson AT, Koo A, Virovka A, Amirault AL, Soo M, Cho JH, Oeltzschner G, Edden RAE, Stark CEL. Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease. Anal Biochem 2023; 676:115227. [PMID: 37423487 PMCID: PMC10561665 DOI: 10.1016/j.ab.2023.115227] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023]
Abstract
Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.
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Affiliation(s)
- Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Annie Koo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Anna Virovka
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Alyssa L Amirault
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Madelene Soo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Jocelyn H Cho
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA.
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5
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Mueller C, Jordan I, Jones C, Lawson P, Younger JW. Abnormal immune system response in the brain of women with Fibromyalgia after experimental endotoxin challenge. Brain Behav Immun Health 2023; 30:100624. [PMID: 37114015 PMCID: PMC10126845 DOI: 10.1016/j.bbih.2023.100624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 03/13/2023] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Background The pathophysiology of fibromyalgia (FM) is thought to include an overactive immune system, leading to central nervous system sensitization, allodynia, and hyperalgesia. We aimed to test this theory using an experimental immune system activation procedure and neuroimaging with magnetic resonance spectroscopic imaging (MRSI). Methods Twelve women with FM and 13 healthy women (healthy controls; HC) received 0.3 or 0.4 ng/kg endotoxin and underwent MRSI before and after the infusion. Changes in brain levels of choline (CHO), myo-inositol (MI), N-Acetylaspartate (NAA), and MRSI-derived brain temperature were compared between groups and dosage levels using mixed analyses of variance. Results Significant group-by-time interactions in brain temperature were found in the right thalamus. Post-hoc testing revealed that brain temperature increased by 0.55 °C in the right thalamus in FM (t(10) = -3.483, p = 0.006), but not in HCs (p > 0.05). Dose-by-time interactions revealed brain temperature increases in the right insula after 0.4 ng/kg (t(12) = -4.074, p = 0.002), but not after 0.3 ng/kg (p > 0.05). Dose-by-time interactions revealed decreased CHO in the right Rolandic operculum after 0.4 ng/kg endotoxin (t(13) = 3.242, p = 0.006) but not 0.3 ng/kg. In the left paracentral lobule, CHO decreased after 0.3 ng/kg (t(9) = 2.574, p = 0.030) but not 0.4 ng/kg. Dose-by-time interactions affected MI in several brain regions. MI increased after 0.3 ng/kg in the right Rolandic operculum (t(10) = -2.374, p = 0.039), left supplementary motor area (t(9) = -2.303, p = 0.047), and left occipital lobe (t(10) = -3.757, p = 0.004), with no changes after 0.4 ng/kg (p > 0.05). Group-by time interactions revealed decreased NAA in the left Rolandic operculum in FM (t(13) = 2.664, p = 0.019), but not in HCs (p > 0.05). A dose-by-time interaction showed decreased NAA in the left paracentral lobule after 0.3 ng/kg (t(9) = 3.071, p = 0.013) but not after 0.4 ng/kg (p > 0.05). In the combined sample, there was a main effect of time whereby NAA decreased in the left anterior cingulate (F[1,21] = 4.458, p = 0.047) and right parietal lobe (F[1,21] = 5.457, p = 0.029). Conclusion We found temperature increases and NAA decreases in FM that were not seen in HCs, suggesting that FM patients may have abnormal immune responses in the brain. The 0.3 and 0.4 ng/kg had differential effects on brain temperature and metabolites, with neither dose effecting a stronger response overall. There is insufficient evidence provided by the study to determine whether FM involves abnormal central responses to low-level immune challenges.
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Affiliation(s)
- Christina Mueller
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Indonesia Jordan
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Chloe Jones
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Prentiss Lawson
- Department of Anesthesiology and Perioperative Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jarred W. Younger
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
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6
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Sung D, Rejimon A, Allen JW, Fedorov AG, Fleischer CC. Predicting brain temperature in humans using bioheat models: Progress and outlook. J Cereb Blood Flow Metab 2023; 43:833-842. [PMID: 36883416 PMCID: PMC10196749 DOI: 10.1177/0271678x231162173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 03/09/2023]
Abstract
Brain temperature, regulated by the balance between blood circulation and metabolic heat generation, is an important parameter related to neural activity, cerebral hemodynamics, and neuroinflammation. A key challenge for integrating brain temperature into clinical practice is the lack of reliable and non-invasive brain thermometry. The recognized importance of brain temperature and thermoregulation in both health and disease, combined with limited availability of experimental methods, has motivated the development of computational thermal models using bioheat equations to predict brain temperature. In this mini-review, we describe progress and the current state-of-the-art in brain thermal modeling in humans and discuss potential avenues for clinical applications.
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Affiliation(s)
- Dongsuk Sung
- Department of Biomedical
Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA,
USA
- Department of Radiology and Imaging
Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Abinand Rejimon
- Department of Biomedical
Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA,
USA
- Department of Radiology and Imaging
Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Jason W Allen
- Department of Biomedical
Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA,
USA
- Department of Radiology and Imaging
Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory
University School of Medicine, Atlanta, GA, USA
| | - Andrei G Fedorov
- Woodruff School of Mechanical
Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Petit Institute for Bioengineering
and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
| | - Candace C Fleischer
- Department of Biomedical
Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA,
USA
- Department of Radiology and Imaging
Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Petit Institute for Bioengineering
and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
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7
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Sung D, Risk BB, Wang KJ, Allen JW, Fleischer CC. Resting-State Brain Temperature: Dynamic Fluctuations in Brain Temperature and the Brain-Body Temperature Gradient. J Magn Reson Imaging 2023; 57:1222-1228. [PMID: 35904094 PMCID: PMC9884314 DOI: 10.1002/jmri.28376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/14/2022] [Accepted: 07/15/2022] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND While fluctuations in healthy brain temperature have been investigated over time periods of weeks to months, dynamics over shorter time periods are less clear. PURPOSE To identify physiological fluctuations in brain temperature in healthy volunteers over time scales of approximately 1 hour. STUDY TYPE Prospective. SUBJECTS A total of 30 healthy volunteers (15 female; 26 ± 4 years old). SEQUENCE AND FIELD STRENGTH 3 T; T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) and semi-localized by adiabatic selective refocusing (sLASER) single-voxel spectroscopy. ASSESSMENTS Brain temperature was calculated from the chemical shift difference between N-acetylaspartate and water. To evaluate within-scan repeatability of brain temperature and the brain-body temperature difference, 128 spectral transients were divided into two sets of 64-spectra. Between-scan repeatability was evaluated using two time periods, ~1-1.5 hours apart. STATISTICAL TESTS A hierarchical linear mixed model was used to calculate within-scan and between-scan correlations (Rw and Rb , respectively). Significance was determined at P ≤ .05. Values are reported as the mean ± standard deviation. RESULTS A significant difference in brain temperature was observed between scans (-0.4 °C) but body temperature was stable (P = .59). Brain temperature (37.9 ± 0.7 °C) was higher than body temperature (36.5 ± 0.5 °C) for all but one subject. Within-scan correlation was high for brain temperature (Rw = 0.95) and brain-body temperature differences (Rw = 0.96). Between scans, variability was high for both brain temperature (Rb = 0.30) and brain-body temperature differences (Rb = 0.41). DATA CONCLUSION Significant changes in brain temperature over time scales of ~1 hour were observed. High short-term repeatability suggests temperature changes appear to be due to physiology rather than measurement error. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Dongsuk Sung
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University
| | - Benjamin B. Risk
- Department of Biostatistics and Bioinformatics, Emory University
| | - Kelly J. Wang
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
- Department of Neuroscience, Georgia Institute of Technology
| | - Jason W. Allen
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University
| | - Candace C. Fleischer
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University
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Chen AM, Gerhalter T, Dehkharghani S, Peralta R, Gajdošík M, Gajdošík M, Tordjman M, Zabludovsky J, Sheriff S, Ahn S, Babb JS, Bushnik T, Zarate A, Silver JM, Im BS, Wall SP, Madelin G, Kirov II. Replicability of proton MR spectroscopic imaging findings in mild traumatic brain injury: Implications for clinical applications. Neuroimage Clin 2023; 37:103325. [PMID: 36724732 PMCID: PMC9898311 DOI: 10.1016/j.nicl.2023.103325] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/06/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023]
Abstract
PURPOSE Proton magnetic resonance spectroscopy (1H MRS) offers biomarkers of metabolic damage after mild traumatic brain injury (mTBI), but a lack of replicability studies hampers clinical translation. In a conceptual replication study design, the results reported in four previous publications were used as the hypotheses (H1-H7), specifically: abnormalities in patients are diffuse (H1), confined to white matter (WM) (H2), comprise low N-acetyl-aspartate (NAA) levels and normal choline (Cho), creatine (Cr) and myo-inositol (mI) (H3), and correlate with clinical outcome (H4); additionally, a lack of findings in regional subcortical WM (H5) and deep gray matter (GM) structures (H6), except for higher mI in patients' putamen (H7). METHODS 26 mTBI patients (20 female, age 36.5 ± 12.5 [mean ± standard deviation] years), within two months from injury and 21 age-, sex-, and education-matched healthy controls were scanned at 3 Tesla with 3D echo-planar spectroscopic imaging. To test H1-H3, global analysis using linear regression was used to obtain metabolite levels of GM and WM in each brain lobe. For H4, patients were stratified into non-recovered and recovered subgroups using the Glasgow Outcome Scale Extended. To test H5-H7, regional analysis using spectral averaging estimated metabolite levels in four GM and six WM structures segmented from T1-weighted MRI. The Mann-Whitney U test and weighted least squares analysis of covariance were used to examine mean group differences in metabolite levels between all patients and all controls (H1-H3, H5-H7), and between recovered and non-recovered patients and their respectively matched controls (H4). Replicability was defined as the support or failure to support the null hypotheses in accordance with the content of H1-H7, and was further evaluated using percent differences, coefficients of variation, and effect size (Cohen's d). RESULTS Patients' occipital lobe WM Cho and Cr levels were 6.0% and 4.6% higher than controls', respectively (Cho, d = 0.37, p = 0.04; Cr, d = 0.63, p = 0.03). The same findings, i.e., higher patients' occipital lobe WM Cho and Cr (both p = 0.01), but with larger percent differences (Cho, 8.6%; Cr, 6.3%) and effect sizes (Cho, d = 0.52; Cr, d = 0.88) were found in the comparison of non-recovered patients to their matched controls. For the lobar WM Cho and Cr comparisons without statistical significance (frontal, parietal, temporal), unidirectional effect sizes were observed (Cho, d = 0.07 - 0.37; Cr, d = 0.27 - 0.63). No differences were found in any metabolite in any lobe in the comparison between recovered patients and their matched controls. In the regional analyses, no differences in metabolite levels were found in any GM or WM region, but all WM regions (posterior, frontal, corona radiata, and the genu, body, and splenium of the corpus callosum) exhibited unidirectional effect sizes for Cho and Cr (Cho, d = 0.03 - 0.34; Cr, d = 0.16 - 0.51). CONCLUSIONS We replicated findings of diffuse WM injury, which correlated with clinical outcome (supporting H1-H2, H4). These findings, however, were among the glial markers Cho and Cr, not the neuronal marker NAA (not supporting H3). No differences were found in regional GM and WM metabolite levels (supporting H5-H6), nor in putaminal mI (not supporting H7). Unidirectional effect sizes of higher patients' Cho and Cr within all WM analyses suggest widespread injury, and are in line with the conclusion from the previous publications, i.e., that detection of WM injury may be more dependent upon sensitivity of the 1H MRS technique than on the selection of specific regions. The findings lend further support to the corollary that clinic-ready 1H MRS biomarkers for mTBI may best be achieved by using high signal-to-noise-ratio single-voxels placed anywhere within WM. The biochemical signature of the injury, however, may differ and therefore absolute levels, rather than ratios may be preferred. Future replication efforts should further test the generalizability of these findings.
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Affiliation(s)
- Anna M Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Teresa Gerhalter
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Seena Dehkharghani
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA
| | - Rosemary Peralta
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mia Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Martin Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mickael Tordjman
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Radiology, Hôpital Cochin, Paris, France
| | - Julia Zabludovsky
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sinyeob Ahn
- Siemens Medical Solutions USA Inc., Malvern, PA, USA
| | - James S Babb
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Tamara Bushnik
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Alejandro Zarate
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Jonathan M Silver
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Brian S Im
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Guillaume Madelin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
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9
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Sung D, Risk BB, Kottke PA, Allen JW, Nahab F, Fedorov AG, Fleischer CC. Comparisons of healthy human brain temperature predicted from biophysical modeling and measured with whole brain MR thermometry. Sci Rep 2022; 12:19285. [PMID: 36369468 PMCID: PMC9652378 DOI: 10.1038/s41598-022-22599-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022] Open
Abstract
Brain temperature is an understudied parameter relevant to brain injury and ischemia. To advance our understanding of thermal dynamics in the human brain, combined with the challenges of routine experimental measurements, a biophysical modeling framework was developed to facilitate individualized brain temperature predictions. Model-predicted brain temperatures using our fully conserved model were compared with whole brain chemical shift thermometry acquired in 30 healthy human subjects (15 male and 15 female, age range 18-36 years old). Magnetic resonance (MR) thermometry, as well as structural imaging, angiography, and venography, were acquired prospectively on a Siemens Prisma whole body 3 T MR scanner. Bland-Altman plots demonstrate agreement between model-predicted and MR-measured brain temperatures at the voxel-level. Regional variations were similar between predicted and measured temperatures (< 0.55 °C for all 10 cortical and 12 subcortical regions of interest), and subcortical white matter temperatures were higher than cortical regions. We anticipate the advancement of brain temperature as a marker of health and injury will be facilitated by a well-validated computational model which can enable predictions when experiments are not feasible.
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Affiliation(s)
- Dongsuk Sung
- grid.213917.f0000 0001 2097 4943Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA
| | - Benjamin B. Risk
- grid.189967.80000 0001 0941 6502Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA USA
| | - Peter A. Kottke
- grid.213917.f0000 0001 2097 4943Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA USA
| | - Jason W. Allen
- grid.213917.f0000 0001 2097 4943Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Neurology, Emory University School of Medicine, Atlanta, GA USA
| | - Fadi Nahab
- grid.189967.80000 0001 0941 6502Department of Neurology, Emory University School of Medicine, Atlanta, GA USA
| | - Andrei G. Fedorov
- grid.213917.f0000 0001 2097 4943Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA USA ,grid.213917.f0000 0001 2097 4943Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA USA
| | - Candace C. Fleischer
- grid.213917.f0000 0001 2097 4943Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA USA ,grid.213917.f0000 0001 2097 4943Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Wesley Woods Health Center, Emory University School of Medicine, 1841 Clifton Road, Atlanta, GA 30329 USA
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Brain temperature as an indicator of neuroinflammation induced by typhoid vaccine: Assessment using whole-brain magnetic resonance spectroscopy in a randomised crossover study. Neuroimage Clin 2022; 35:103053. [PMID: 35617872 PMCID: PMC9136180 DOI: 10.1016/j.nicl.2022.103053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 11/23/2022]
Abstract
MRSI-derived whole-brain temperature did not detect low-level neuroinflammation. Regional brain temperature was a more sensitive measure of neuroinflammation. MRSI/EPSI might be a useful measure of neuroinflammation in psychiatric disorders.
Prior studies indicate a pathogenic role of neuroinflammation in psychiatric disorders; however, there are no accepted methods that can reliably measure low-level neuroinflammation non-invasively in these individuals. Magnetic resonance spectroscopic imaging (MRSI) is a versatile, non-invasive neuroimaging technique that demonstrates sensitivity to brain inflammation. MRSI in conjunction with echo-planar spectroscopic imaging (EPSI) measures brain metabolites to derive whole-brain and regional brain temperatures, which may increase in neuroinflammation. The validity of MRSI/EPSI for measurement of low level neuroinflammation was tested using a safe experimental model of human brain inflammation – intramuscular administration of typhoid vaccine. Twenty healthy volunteers participated in a double-blind, placebo-controlled crossover study including MRSI/EPSI scans before and 3 h after vaccine/placebo administration. Body temperature and mood, assessed using the Profile of Mood States, were measured every hour up to four hours post-treatment administration. A mixed model analysis of variance was used to test for treatment effects. A significant proportion of brain regions (44/47) increased in temperature post-vaccine compared to post-placebo (p < 0.0001). For temperature change in the brain as a whole, there was no significant treatment effect. Significant associations were seen between mood scores assessed at 4 h and whole brain and regional temperatures post-treatment. Findings indicate that regional brain temperature may be a more sensitive measure of low-level neuroinflammation than whole-brain temperature. Future work where these measurement techniques are applied to populations with psychiatric disorders would be of clinical interest.
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Hangel G, Spurny-Dworak B, Lazen P, Cadrien C, Sharma S, Hingerl L, Hečková E, Strasser B, Motyka S, Lipka A, Gruber S, Brandner C, Lanzenberger R, Rössler K, Trattnig S, Bogner W. Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T. NMR IN BIOMEDICINE 2021; 34:e4596. [PMID: 34382280 DOI: 10.1002/nbm.4596] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/14/2021] [Accepted: 07/14/2021] [Indexed: 05/13/2023]
Abstract
PURPOSE Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. METHODS We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs. RESULTS Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate. DISCUSSION We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.
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Affiliation(s)
- Gilbert Hangel
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Benjamin Spurny-Dworak
- Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Philipp Lazen
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Cornelius Cadrien
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Sukrit Sharma
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Eva Hečková
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexandra Lipka
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
| | - Stephan Gruber
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christoph Brandner
- High-field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Karl Rössler
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
| | - Wolfgang Bogner
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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Sharma AA, Nenert R, Mueller C, Maudsley AA, Younger JW, Szaflarski JP. Repeatability and Reproducibility of in-vivo Brain Temperature Measurements. Front Hum Neurosci 2020; 14:598435. [PMID: 33424566 PMCID: PMC7785722 DOI: 10.3389/fnhum.2020.598435] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 11/30/2020] [Indexed: 12/11/2022] Open
Abstract
Background: Magnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that may be useful for non-invasive mapping of brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range. Methods: Healthy participants aged 23-46 years (N = 18; 7 females) were scanned at two time points ~12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values. Results: The mean global brain temperature over all subjects was 37.2°C with spatial variations across ROIs. There was a significant main effect for time [F (1, 1,591) = 37.0, p < 0.0001] and for brain region [F (46, 1,591) = 2.66, p < 0.0001]. The time*brain region interaction was not significant [F (46, 1,591) = 0.80, p = 0.83]. Participants' TCRE was stable for each ROI across both time points, with ROIs' COVrep ranging from 0.81 to 3.08% (mean COVrep = 1.92%); majority of ROIs had a COVrep <2.0%. Conclusions: Brain temperature measurements were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring brain temperature changes in health and disease. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.
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Affiliation(s)
- Ayushe A. Sharma
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
| | - Rodolphe Nenert
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
- Department of Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Christina Mueller
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Jarred W. Younger
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Jerzy P. Szaflarski
- Department of Neurobiology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
- Department of Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- Department of Neurosurgery, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
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