The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
The impact of aging and gender on brain viscoelasticity
Abstract
Viscoelasticity is a sensitive measure of the microstructural constitution of soft biological tissue and is increasingly used as a diagnostic marker, e.g. in staging liver fibrosis or characterizing breast tumors. In this study, multifrequency magnetic resonance elastography was used to investigate the in vivo viscoelasticity of healthy human brain in 55 volunteers (23 females) ranging in age from 18 to 88 years. The application of four vibration frequencies in an acoustic range from 25 to 62.5 Hz revealed for the first time how physiological aging changes the global viscosity and elasticity of the brain. Using the rheological springpot model, viscosity and elasticity are combined in a parameter mu that describes the solid-fluid behavior of the tissue and a parameter alpha related to the tissue's microstructure. It is shown that the healthy adult brain undergoes steady parenchymal 'liquefaction' characterized by a continuous decline in mu of 0.8% per year (P<0.001), whereas alpha remains unchanged. Furthermore, significant sex differences were found with female brains being on average 9% more solid-like than their male counterparts rendering women more than a decade 'younger' than men with respect to brain mechanics (P=0.016). These results set the background for using cerebral multifrequency elastography in diagnosing subtle neurodegenerative processes not detectable by other diagnostic methods.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Aging-associated neuroanatomical changes also revealed sexual dimorphism in that males were likely to undergo greater reduction in brain elasticity and stiffness than their female counterparts (Arani et al, 2015;Sack et al, 2009).”
From Microglia Priming with Aging and Stress (2017) · cites this paper as Sack et al, 2009
Citations
Cites
Tissue Cells Feel and Respond to the Stiffness of Their Substrate
Discher, D. E., Janmey, P., & Wang, Y.-L. (2005) · Science · doi:10.1126/science.1116995 · Cited by 6,382
Biomechanics. Mechanical Properties of Living Tissues
Fung, Y. C., & Skalak, R. (1982) · Journal of Applied Mechanics · doi:10.1115/1.3162171 · Cited by 6,040
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
A tension-based theory of morphogenesis and compact wiring in the central nervous system
Essen, D. C. V. (1997) · Nature · doi:10.1038/385313a0 · Cited by 1,668
Applications of Fractional Calculus to the Theory of Viscoelasticity
Koeller, R. C. (1984) · Journal of Applied Mechanics · doi:10.1115/1.3167616 · Cited by 1,456
Life and Death of Neurons in the Aging Brain
Morrison, J. H., & Hof, P. R. (1997) · Science · doi:10.1126/science.278.5337.412 · Cited by 1,344
The Phenomenological Theory of Linear Viscoelastic Behavior
Tschoegl, N. W. (1989) · Springer eBooks · doi:10.1007/978-3-642-73602-5 · Cited by 1,337
Dekaban, A. S., & Sadowsky, D. (1978) · Annals of Neurology · doi:10.1002/ana.410040410 · Cited by 1,014
Neocortical cell counts in normal human adult aging
Terry, R. D., DeTeresa, R. M., & Hansen, L. A. (1987) · Annals of Neurology · doi:10.1002/ana.410210603 · Cited by 686
Neocortical glial cell numbers in human brains
Pelvig, D. P., Pakkenberg, H., Stark, A. K., & Pakkenberg, B. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.04.013 · Cited by 601
Flagged first, then by citations
Research works printed but not linked: 2
- Klatt, 2008, Assessment of the solid–liquid behavior of the liver for the diagnosis of diffuse disease using magnetic resonance elastography, Röfo, 180, 1106
- Wuerfel, 2008, elastography reveals tissue degeneration in Multiple Sclerosis patients. In: Proceedings 16th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Toronto, 1547
Cited by
Sorted by citations
Items 401–423 of 423
Nano-Based Probes for the Brain Extracellular Environment
Filteau, J. R., Butler, B., Schimek, N., & Nance, E. A. (2022) · Springer eBooks · doi:10.1007/978-3-031-11409-0_2
Low-Frequency Mr Elastography Reveals Deep Gray Matter Degradation in Multiple SclerosisPreprint
Kiss, C., Wurth, S., Heschl, B., Khalil, M., Gattringer, T., Enzinger, C., & Ropele, S. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4654106
Flé, G., Houten, E. E. W. V., Gilbert, G., & Cloutier, G. (2024) · Frontiers in Physics · doi:10.3389/fphy.2024.1324659
Wu, X., Pasupathy, P., & Pelegri, A. A. (2024) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2024.108381
The Extracellular Matrix as a Target for Biophysical and Molecular Magnetic Resonance Imaging
de Schellenberger, A. A., Bergs, J. W. J., Sack, I., & Taupitz, M. (2024) · Springer eBooks · doi:10.1007/978-3-031-61846-8_6
Self-citationIkhlef, A., Potekhina, Y. P., & Simenko, E. V. (2025) · Russian Osteopathic Journal · doi:10.32885/2220-0975-2025-3-134-150
Cardoso, C. G. S., Eggers, A., Wisch, M., Fernandes, F. A. O., & de Sousa, R. J. A. (2025) · Applied Sciences · doi:10.3390/app152111837
Russo, A., Tellone, E., Farsaci, C., & Farsaci, F. (2025) · Biology · doi:10.3390/biology15010070
Effects and Correction of Patient Bulk Motion in Cranial DENSE MRI
Doctor, C. A., Rivera‐Rivera, L. A., Eisenmenger, L. B., Johnson, S. C., & Johnson, K. M. (2026) · Magnetic Resonance in Medicine · doi:10.1002/mrm.70270
Inter-scanner reproducibility of brain multifrequency MR elastographyPreprint
Murk, S., Laun, F. B., Rampp, S., Vossiek, M., Schattenfroh, J., Guo, J., Sack, I., Doerfler, A., & Flé, G. (2026) · medRxiv · doi:10.64898/2026.04.13.26350765
Self-citationUckermann, O., Leonidou, T., Rix, J., Temme, A., Eyüpoglu, I. Y., & Galli, R. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.17.719181
Jin, C., Li, R., Wang, K.-W., Song, J., Yu, J.-M., & Ye, X. (2026) · Biomedical Technology · doi:10.1016/j.bmt.2026.100150
Ruhland, L., Reiter, N., Budday, S., & Willner, K. (2026) · Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · doi:10.1016/j.jmbbm.2026.107462
Diano, A., Cerjanic, A. M., Bailey, O. M., Kramer, M. K., Mojumder, J., Okamoto, R. J., Bayly, P. V., Pham, D. L., & Johnson, C. L. (2026) · Magnetic Resonance in Medicine · doi:10.1002/mrm.70447
Park, J. H., Han, M., Yeon, M., & Choi, J. W. (2026) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.mp.2025-0040
Sun, W., Yang, B., Zheng, H., Wang, Q., Shi, Y., Wang, G., Yin, W., Wang, H., Qi, X., Yao, Y., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71784
Liu, Z., Li, B., Yang, P., He, J., Wang, Y., Zou, G., Zhang, X., Li, X., & Gao, H. (2026) · Science China Physics Mechanics and Astronomy · doi:10.1007/s11433-026-3107-2
Abdi, H., Sánchez‐Molina, D., Vilana, S. G., Azizi, S., Rahimi-Movaghar, V., & Haghighi, M. (2026) · Brain Research · doi:10.1016/j.brainres.2026.150580
Analysis in magnetic resonance elastography: study and development of image processing techniques
Rua, C. (2012) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Metadata
- Authors
- Sack, I., Beierbach, B., Wuerfel, J., Klatt, D., Hamhaber, U., Papazoglou, S., Martus, P., & Braun, J.
- Affiliations
- Charité – Universitätsmedizin Berlin (DE)
- University of Lübeck (DE)
- Corresponding author
- Sack, Ingolf
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 46
- Issue
- 3
- Pages
- 652-657
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2035928670
- Cited by
- 423
- References
- 31
- Citations by year
- 2026: 19 · 2025: 22 · 2024: 26 · 2023: 26 · 2022: 29 · 2021: 30 · 2020: 27 · 2019: 26 · 2018: 25 · 2017: 30 · 2016: 23 · 2015: 20 · 2014: 17 · 2013: 25 · 2012: 28
- FWCI
- 19.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Ultrasound Imaging and Elastography
- 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
- Keywords
- brain viscoelasticity, brain aging, sex differences, brain microstructure, brain tissue stiffness, neurodegeneration, healthy human brain
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Brain, Computer Simulation, Female, Hardness, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Models, Neurological, Sex Factors, Viscosity, Elasticity Imaging Techniques, Elastic Modulus, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
