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DCE-MRI blood–brain barrier assessment in acute ischemic stroke
Abstract
Objective To quantitatively evaluate blood-brain barrier changes in ischemic stroke patients using dynamic contrast-enhanced (DCE) MRI. Methods We examined 54 stroke patients (clinicaltrials.gov NCT00715533, NCT02077582) in a 3T MRI scanner within 48 hours after symptom onset. Twenty-eight patients had a follow-up examination on day 5-7. DCE T1 mapping and Patlak analysis were employed to assess BBB permeability changes. Results Median stroke K trans values (0.7 × 10 -3 min -1 [interquartile range (IQR) 0.4-1.8] × 10 -3 min -1 ) were more than 3-fold higher compared to median mirror K trans values (0.2 × 10 -3 min -1 , IQR 0.1-0.7 × 10 -3 min -1 , p -3 min -1 , IQR 0.8-4.6 × 10 -3 min -1 , p trans values decreased over time with a clear interaction of timepoint and stroke/mirror side (p trans values were 2.5 times lower than in hemorrhagic transformed regions (0.7 vs 1.8 × 10 -3 min -1 ; p = 0.055). There was no association between stroke K trans values and the delay from symptom onset to baseline examination, age, and presence of hyperintense acute reperfusion marker. Conclusion BBB in acute stroke patients can be successfully assessed quantitatively. The decrease of BBB permeability in unaffected regions at follow-up may be an indicator of global BBB leakage even in vessel territories remote from the index infarct.
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“Disruption of the BBB, using techniques such as osmotic disruption, biochemical disruption, and ultrasound-mediated disruption, is effective to introduce drugs into the brain; however, these transient BBB openings also allows for the leakage of plasma proteins into the brain, leading to neurotoxicity, vascular pathology, and chronic neuropathologic changes in the brain (1, 7, 11).”
From Neurotransmitter-derived lipidoids (NT-lipidoids) for enhanced brain delivery through intravenous injection (2020) · cites this paper as [11]
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“Disruption of the BBB, using techniques such as osmotic disruption, biochemical disruption, and ultrasound-mediated disruption, is effective to introduce drugs into the brain; however, these transient BBB openings also allows for the leakage of plasma proteins into the brain, leading to neurotoxicity, vascular pathology, and chronic neuropathologic changes in the brain (1, 7, 11).”
From Neurotransmitter-derived lipidoids (NT-lipidoids) for enhanced brain delivery through intravenous injection (2020) · cites this paper as [11]
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Fitting Linear Mixed-Effects Models Using lme4
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
Adams, H. P., Bendixen, B. H., Kappelle, L. J., Biller, J., Love, B. B., Gordon, D., & Marsh, E. E. (1993) · Stroke · doi:10.1161/01.str.24.1.35 · Cited by 12,350
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 7,018
Hacke, W., Kaste, M., Fieschi, C., von Kummer, R., Davalos, A., Meier, D., Larrue, V., Bluhmki, E., Davis, S., Donnan, G., et al. (1998) · The Lancet · doi:10.1016/s0140-6736(98)08020-9 · Cited by 3,662
Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data
Patlak, C. S., Blasberg, R. G., & Fenstermacher, J. D. (1983) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1983.1 · Cited by 3,565
Research works printed but not linked: 1
- Barboriak DP MacFall JR Padua AO York GE Viglianti BL Dewhirst MW. Standardized software for calculation of Ktrans and vp from dynamic T1-weighted MR images. Presented at the International Society for Magnetic Resonance in Medicine Workshop on MR in Drug Development: From Discovery to Clinical Therapeutic Trials McLean Virginia April 2004.
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Zhang, X., Wang, T., Bai, Y., Li, Z., Zhu, D., Cheng, A., Li, Y., & Lu, Q. (2023) · Research Square · doi:10.21203/rs.3.rs-2655218/v1
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Düzel, E., & Bernal, J. (2025) · Elsevier eBooks · doi:10.1016/b978-0-12-822240-9.00015-6
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Tireli, E. D., Cramer, S., Lindberg, U., Tireli, D., Vestergaard, M., & Larsson, H. (2026) · bioRxiv · doi:10.64898/2026.02.15.705995
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Ling, R., Shi, F., & Zhu, Y. (2026) · Reviews in the Neurosciences · doi:10.1515/revneuro-2025-0141
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aksoy, S., Kulaç, İ., Selçuk, H., Kara, B., Kızılırmak, A. B., Yılmaz, B., Ozdemir, Y. G., Vural, A., & Soysal, A. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2026.1723099
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Jones, O. A., Dickie, B., Berks, M., Al–Bachari, S., Emsley, H. C. A., & Parkes, L. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.29.728495
Han, J., Zhao, W., Deng, R., Wang, Y., Gong, W., Wang, Z., Sun, G., Liu, H., Geng, M., & Zhang, Y. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1880590
Ronaldson, P. T., & Davis, T. P. (2026) · Fluids and Barriers of the CNS · doi:10.1186/s12987-026-00848-9
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Metadata
- Authors
- Villringer, K., Sanz Cuesta, B. E., Ostwaldt, A.-C., Grittner, U., Brunecker, P., Khalil, A. A., Schindler, K., Eisenblätter, O., Audebert, H., & Fiebach, J. B.
- Affiliations
- Hospital La Paz Institute for Health Research (ES)
- From the Center for Stroke Research (K.V., A.-C.O., U.G., P.B., A.A.K., K.S., O.E., H.A., J.B.F.), Department of Biostatistics and Clinical Epidemiology (U.G.), NeuroCure Cluster of Excellence (A.A.K.), and Department of Neurology (H.A.), Charite-Universitätsmedizin, Berlin, Germany; and Department of Neurology and Stroke Center (B.E.S.C.), La Paz University Hospital, Neuroscience Area of IdiPAZ Health Research Institute, Autonomous University of Madrid, Spain.
- ORCID
- Venue
- Neurology
- Published
- 2017-01-31
- Volume
- 88
- Issue
- 5
- Pages
- 433-440
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2567404406
- Cited by
- 119
- References
- 37
- Citations by year
- 2026: 13 · 2025: 17 · 2024: 10 · 2023: 15 · 2022: 7 · 2021: 26 · 2020: 15 · 2019: 9 · 2018: 5 · 2017: 2
- FWCI
- 2.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Neurology › Barrier Structure and Function Studies
- Health Sciences › Medicine › Clinical Neurology › Acute Ischemic Stroke Management
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- blood-brain barrier permeability, acute ischemic stroke, dynamic contrast-enhanced MRI, Patlak analysis, Ktrans, hemorrhagic transformation, reperfusion, T1 mapping
- MeSH terms
- Aged, Blood-Brain Barrier, Capillary Permeability, Brain Ischemia, Contrast Media, Female, Follow-Up Studies, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Stroke
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