Cited by 33Advanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

In vivo whole-brain T1-rho mapping across adulthood: normative values and age dependence

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Watts, Richard, Andrews, Trevor, Hipko, Scott, Gonyea, Jay V., Filippi, Christopher G.·2014·Journal of Magnetic Resonance Imaging

Abstract

Purpose: To report a systematic investigation of variations in brain T 1ρ (T1‐rho) values over adulthood, and present normative values for cortical gray matter, juxtacortical white matter, selected white matter tracts and subcortical structures. Materials and Methods: Forty‐one healthy control subjects (23 males aged 18–76 years and 18 females aged 21–73 years) were imaged at 3.0 Tesla (T) using a novel whole‐brain T 1ρ‐weighted fluid suppressed three‐dimensional turbo spin echo technique. T 1ρ maps were calculated and atlas‐based segmentation used to determine regional T 1ρ values. Linear regression was used to determine changes in T 1ρ with age. Results: T 1ρ values showed significant decreases with age in cortical gray matter (P < 0.001), left and right caudate (P = 0.004/0.006), putamen (P = 0.001, P < 0.001), hippocampus (P = 0.039/0.010), amygdala (P = 0.002/0.001), and nucleus accumbens (P = 0.001/0.002). Significant increases with age (P < 0.05) were observed in all the white matter tracts considered, except the corticospinal tracts and forceps major. Conclusion: T 1ρ demonstrates changes related to the processes of normal aging. J. Magn. Reson. Imaging 2014;40:376–382. © 2013 Wiley Periodicals, Inc.

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  • Watts et al. found ~7-10% lower T1ρ value both in GM and WM compared to the current study.

    “In addition, Watts et al. have found ~7–10% lower T1ρ value both in GM and WM compared to the current study.”

    From T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease (2015) · cites this paper as Watts et al., 2014

    Table 1 (page not provided) reports mean T1ρ values for cortical GM and for juxtacortical WM and major WM tracts. The paper does not give the citing study’s values, so its text cannot establish that these measurements are approximately 7–10% lower. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Watts et al. observed a positive correlation between WM T1ρ and age while GM T1ρ showed negative correlation with age.

    “Recently, Watts et al., have evaluated the age dependence changes in GM and WM T1ρ relaxation times in brain of normal human volunteers on a 3-T MRI scanner (Watts et al., 2014). They have observed a positive correlation between WM T1ρ and age while the GM T1ρ showed negative correlation with age.”

    From T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease (2015) · cites this paper as Watts et al., 2014

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  1. Nishioka H, Hirose J, Nakamura E, et al. T1rho and T2 mapping reveal the in vivo extracellular matrix of articular cartilage. J Magn Reson Imaging 2012;35:147-155.
  2. Borthakur A, Maurer PM, Fenty M, et al. T1rho magnetic reso- nance imaging and discography pressure as novel biomarkers for disc degeneration and low back pain. Spine 2011;36:2190-2196.
  3. Sirlin CB. Science to practice: can T1rho imaging be used to diag- nose and assess the severity of hepatic fibrosis? Radiology 2011; 259:619-620.
  4. Buck FM, Bae WC, Diaz E, et al. Comparison of T1rho measure- ments in agarose phantoms and human patellar cartilage using 2D multislice spiral and 3D magnetization prepared partitioned k-space spoiled gradient-echo snapshot techniques at 3 T. AJR Am J Roentgenol 2011;196:W174-W179.
  5. Keenan KE, Besier TF, Pauly JM, et al. Prediction of glycosamino- glycan content in human cartilage by age, T1rho and T2 MRI. Osteoarthritis cartilage 2011;19:171-179.
  6. Borthakur A, Wheaton AJ, Gougoutas AJ, et al. In vivo measure- ment of T1rho dispersion in the human brain at 1.5 tesla. J Magn Reson Imaging 2004;19:403-409.
  7. Borthakur A, Gur T, Wheaton AJ, et al. In vivo measurement of plaque burden in a mouse model of Alzheimer's disease. J Magn Reson Imaging 2006;24:1011-1017.
  8. Borthakur A, Sochor M, Davatzikos C, Trojanowski JQ, Clark CM. T1rho MRI of Alzheimer's disease. Neuroimage 2008;41: 1199-1205.
  9. Haris M, McArdle E, Fenty M, et al. Early marker for Alzheimer's disease: hippocampus T1rho (T(1rho)) estimation. J Magn Reson Imaging 2009;29:1008-1012.
  10. Haris M, Singh A, Cai K, et al. T1rho (T1rho) MR imaging in Alz- heimer's disease and Parkinson's disease with and without dementia. J Neurol 2011;258:380-385.
  11. Nestrasil I, Michaeli S, Liimatainen T, et al. T1rho and T2rho MRI in the evaluation of Parkinson's disease. J Neurol 2010;257:964-968.
  12. Jokivarsi KT, Hiltunen Y, Grohn H, Tuunanen P, Grohn OH, Kauppinen RA. Estimation of the onset time of cerebral ischemia using T1rho and T2 MRI in rats. Stroke 2010;41:2335-2340.
  13. Kettunen MI, Grohn OH, Penttonen M, Kauppinen RA. Cerebral T1rho relaxation time increases immediately upon global ische- mia in the rat independently of blood glucose and anoxic depola- rization. Magn Reson Med 2001;46:565-572.
  14. Duvvuri U, Poptani H, Feldman M, et al. Quantitative T1rho mag- netic resonance imaging of RIF-1 tumors in vivo: detection of early response to cyclophosphamide therapy. Cancer Res 2001; 61:7747-7753.
  15. Poptani H, Duvvuri U, Miller CG, et al. T1rho imaging of murine brain tumors at 4 T. Acad Radiol 2001;8:42-47.
  16. Witschey WR Jr, Borthakur A, Elliott MA, et al. Artifacts in T1 rho-weighted imaging: compensation for B(1) and B(0) field imperfections. J Magn Reson 2007;186:75-85.
  17. Friston KJ. Commentary and opinion: II. Statistical parametric mapping: ontology and current issues. J Cereb Blood Flow Metab 1995;15:361-370.
  18. Ashburner J, Friston KJ. Unified segmentation. Neuroimage 2005;26:839-851.
  19. Ashburner J, Friston KJ. Nonlinear spatial normalization using basis functions. Hum Brain Mapp 1999;7:254-266.
  20. Hua K, Zhang J, Wakana S, et al. Tract probability maps in ste- reotaxic spaces: analyses of white matter anatomy and tract- specific quantification. Neuroimage 2008;39:336-347.
  21. Wakana S, Caprihan A, Panzenboeck MM, et al. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 2007;36:630-644.
  22. Patenaude B, Smith SM, Kennedy DN, Jenkinson M. A Bayesian model of shape and appearance for subcortical brain segmenta- tion. Neuroimage 2011;56:907-922.
  23. Hasan KM, Walimuni IS, Kramer LA, Frye RE. Human brain atlas-based volumetry and relaxometry: application to healthy development and natural aging. Magn Reson Med 2010;64:1382- 1389.
  24. Lebel C, Gee M, Camicioli R, Wieler M, Martin W, Beaulieu C. Dif- fusion tensor imaging of white matter tract evolution over the life- span. Neuroimage 2012;60:340-352.
  25. Peelle JE, Cusack R, Henson RN. Adjusting for global effects in voxel-based morphometry: gray matter decline in normal aging. Neuroimage 2012;60:1503-1516.
  26. Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, Toga AW. Mapping cortical change across the human life span. Nat Neurosci 2003;6:309-315.
  27. Taki Y, Thyreau B, Kinomura S, et al. A longitudinal study of age-and gender-related annual rate of volume changes in regional gray matter in healthy adults. Human brain mapping 2012. [Epub ahead of print] DOI 10.1002/hbm.22067. · DOI
  28. Kettunen MI, Sierra A, Narvainen MJ, et al. Low spin-lock field T1 relaxation in the rotating frame as a sensitive MR imaging marker for gene therapy treatment response in rat glioma. Radiol- ogy 2007;243:796-803.
  29. Makela HI, Grohn OHJ, Kettunen MI, Kauppinen RA. Proton exchange as a relaxation mechanism for T(1) in the rotating frame in native and immobilized protein solutions. Biochem Biophs Res Commun 2001;289:813-818.
  30. Magnotta VA, Heo HY, Dlouhy BJ, et al. Detecting activity-evoked pH changes in human brain. Proc Natl Acad Sci U S A 2012;109: 8270-8273.
  31. Jin T, Autio J, Obata T, Kim SG. Spin-locking versus chemical exchange saturation transfer MRI for Investigating chemical exchange process between water and labile metabolite protons. Magn Reson Med 2011;65:1448-1460.
  32. Yuan J, Zhou JY, Ahuja AT, Jwang YX. MR chemical exchange imaging with spin-lock technique (CESL): a theoretical analysis of the Z-spectrum using a two-pool R-1 rho relaxation model beyond the fast-exchange limit. Phys Med Biol 2012;57:8185-8200.
  33. Tuite PJ, Mangia S, Tyan AE, Lee MK, Garwood M, Michaeli S. Magnetization transfer and adiabatic R-1 rho MRI in the brain- stem of Parkinson's disease. Parkinsonism Relat Disord 2012;18: 623-625.

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Authors
Watts, R., Andrews, T., Hipko, S., Gonyea, J. V., & Filippi, C. G.
Affiliations
University of Vermont (US)
Corresponding author
Watts, Richard
Venue
Journal of Magnetic Resonance Imaging
Publisher
Wiley
Published
2013-11-13
Volume
40
Issue
2
Pages
376-382
ISSN
  • 1053-1807 (ISSN-L)
  • 1522-2586
OpenAlex
W1768199660
Cited by
33
References
1
Citations by year
2026: 2 · 2025: 1 · 2024: 2 · 2023: 3 · 2022: 2 · 2021: 3 · 2020: 3 · 2019: 1 · 2018: 4 · 2017: 3 · 2016: 4 · 2015: 5
FWCI
2.33
Type
journal article
Language
en
Open access
Locations
  • Journal of Magnetic Resonance Imaging (publishedVersion)
  • PubMed (publishedVersion)
Funders
U.S. Department of Energy (DESC0001753)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
T1rho mapping, brain aging, reference values, cortical gray matter, white matter tracts, caudate nucleus, putamen, hippocampus, amygdala, nucleus accumbens, age-related changes
MeSH terms
Adolescent, Adult, Aged, Aging, Brain, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Reference Values, Sensitivity and Specificity, Reproducibility of Results

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