Evaluation of blood-brain barrier integrity by the analysis of dynamic contrast-enhanced MRI - a comparison of quantitative and semi-quantitative methods
Jazyk angličtina Země Česko Médium print
Typ dokumentu časopisecké články
PubMed
36647914
PubMed Central
PMC9906669
DOI
10.33549/physiolres.934998
PII: 934998
Knihovny.cz E-zdroje
- MeSH
- hematoencefalická bariéra * diagnostické zobrazování MeSH
- kontrastní látky MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- nemoci mozku * MeSH
- reprodukovatelnost výsledků MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- kontrastní látky MeSH
Disruption of the blood-brain barrier (BBB) is a key feature of various brain disorders. To assess its integrity a parametrization of dynamic magnetic resonance imaging (DCE MRI) with a contrast agent (CA) is broadly used. Parametrization can be done quantitatively or semi-quantitatively. Quantitative methods directly describe BBB permeability but exhibit several drawbacks such as high computation demands, reproducibility issues, or low robustness. Semi-quantitative methods are fast to compute, simply mathematically described, and robust, however, they do not describe the status of BBB directly but only as a variation of CA concentration in measured tissue. Our goal was to elucidate differences between five semi-quantitative parameters: maximal intensity (Imax), normalized permeability index (NPI), and difference in DCE values between three timepoints: baseline, 5 min, and 15 min (delta5-0, delta15-0, delta15-5) and two quantitative parameters: transfer constant (Ktrans) and an extravascular fraction (Ve). For the purpose of comparison, we analyzed DCE data of four patients 12-15 days after the stroke with visible CA enhancement. Calculated parameters showed abnormalities spatially corresponding with the ischemic lesion, however, findings in individual parameters morphometrically differed. Ktrans and Ve were highly correlated. Delta5-0 and delta15-0 were prominent in regions with rapid CA enhancement and highly correlated with Ktrans. Abnormalities in delta15-5 and NPI were more homogenous with less variable values, smoother borders, and less detail than Ktrans. Moreover, only delta15-5 and NPI were able to distinguish vessels from extravascular space. Our comparison provides important knowledge for understanding and interpreting parameters derived from DCE MRI by both quantitative and semi-quantitative methods.
Zobrazit více v PubMed
Cuenod CA, Fournier L, Balvay D, Guinebretière JM. Tumor angiogenesis: pathophysiology and implications for contrast-enhanced MRI and CT assessment. Abdom Imaging. 2006;31:188–193. doi: 10.1007/s00261-005-0386-5. PubMed DOI
Merali Z, Huang K, Mikulis D, Silver F, Kassner A. Evolution of blood-brain-barrier permeability after acute ischemic stroke. PLoS One. 2017;12:1–11. doi: 10.1371/journal.pone.0171558. PubMed DOI PMC
Jelescu IO, Leppert IR, Narayanan S, Araújo D, Arnold DL, Pike GB. Dual-temporal resolution dynamic contrast-enhanced MRI protocol for blood-brain barrier permeability measurement in enhancing multiple sclerosis lesions. J Magn Reson Imaging. 2011;33:1291–1300. doi: 10.1002/jmri.22565. PubMed DOI
Thrippleton MJ, Backes WH, Sourbron S, Ingrisch M, van Osch MJP, Dichgans M, Fazekas F, et al. Quantifying blood-brain barrier leakage in small vessel disease: Review and consensus recommendations. Alzheimer’s Dement. 2019;15:840–858. doi: 10.1016/j.jalz.2019.01.013. PubMed DOI PMC
Starr JM, Farrall AJ, Armitage P, McGurn B, Wardlaw J. Blood-brain barrier permeability in Alzheimer’s disease: a case-control MRI study. Psychiatry Res Neuroimaging. 2009;171:232–241. doi: 10.1016/j.pscychresns.2008.04.003. PubMed DOI
Starr JM. Increased blood-brain barrier permeability in type II diabetes demonstrated by gadolinium magnetic resonance imaging. J Neurol Neurosurg Psychiatry. 2003;74:70–76. doi: 10.1136/jnnp.74.1.70. PubMed DOI PMC
Kastrup A, Engelhorn T, Beaulieu C, De Crespigny A, Moseley ME. Dynamics of cerebral injury, perfusion, and blood-brain barrier changes after temporary and permanent middle cerebral artery occlusion in the rat. J Neurol Sci. 1999;166:91–99. doi: 10.1016/S0022-510X(99)00121-5. PubMed DOI
Líčeník R, Bednařík J, Tomek A, Bar M, Neumann J, Šaňák D, Nečas T, Búřilová P, Klugarová J, Pokorná A, Klugar M. Development of Czech National Stroke Guidelines. Int J Evid Based Healthc. 2019;17(Suppl 1):S9–S11. doi: 10.1097/XEB.0000000000000190. PubMed DOI
Harris NG, Gauden V, Fraser PA, Williams SR, Parker GJM. MRI measurement of blood-brain barrier permeability following spontaneous reperfusion in the starch microsphere model of ischemia. Magn Reson Imaging. 2002;20:221–230. doi: 10.1016/S0730-725X(02)00498-8. PubMed DOI
Durukan A, Marinkovic I, Strbian D, Pitkonen M, Pedrono E, Soinne L, Abo-Ramadan U, Tatlisumak T. Post-ischemic blood-brain barrier leakage in rats: One-week follow-up by MRI. Brain Res. 2009;1280:158–165. doi: 10.1016/j.brainres.2009.05.025. PubMed DOI
On NH, Savant S, Toews M, Miller DW. Rapid and reversible enhancement of blood-brain barrier permeability using lysophosphatidic acid. J Cereb Blood Flow Metab. 2013;33:1944–1954. doi: 10.1038/jcbfm.2013.154. PubMed DOI PMC
Whelan R, Hargaden GC, Knox AJS. Pharmaceutics modulating the blood-brain barrier: a comprehensive review. Pharmaceutics. 2021;13:1980. doi: 10.3390/pharmaceutics13111980. PubMed DOI PMC
Bernardo-Castro S, Sousa JA, Brás A, Cecília C, Rodrigues B, Almendra L, Machado C, et al. Pathophysiology of blood-brain barrier permeability throughout the different stages of ischemic stroke and its implication on hemorrhagic transformation and recovery. Front Neurol. 2020;11:1605. doi: 10.3389/fneur.2020.594672. PubMed DOI PMC
O’Brien MD. Ischemic cerebral edema. A review. Stroke. 1979;10:623–628. doi: 10.1161/01.STR.10.6.623. PubMed DOI
Rodriguez Gutierrez D, Wells K, Diaz Montesdeoca O, Moran Santana A, Mendichovszky IA, Gordon I. Partial volume effects in dynamic contrast magnetic resonance renal studies. Eur J Radiol. 2010;75:221–229. doi: 10.1016/j.ejrad.2009.04.073. PubMed DOI
Knight RA, Dereski MO, Helpern JA, Ordidge RJ, Chopp M. Magnetic resonance imaging assessment of evolving focal cerebral ischemia. Comparison with histopathology in rats. Stroke. 1994;25:1252–1261. doi: 10.1161/01.STR.25.6.1252. discussion 1261–1262. PubMed DOI
Srinivasan A, Goyal M, Al Azri F, Lum C. State-of-the-art imaging of acute stroke. RadioGraphics. 2006;26(Suppl_1):S75–S95. doi: 10.1148/rg.26si065501. PubMed DOI
Milidonis X, Marshall I, Macleod MR, Sena ES. Magnetic resonance imaging in experimental stroke and comparison with histology systematic review and meta-analysis. Stroke. 2015:843–851. doi: 10.1161/STROKEAHA.114.007560. PubMed DOI
Lansberg MG, Thijs VN, Brien MWO, Ali JO, DeCrespigny AJ, Tong DC, Moseley ME, Albers GW. Evolution of apparent diffusion coefficient, diffusion-weighted, and T2-weighted signal intensity of acute stroke. AJNR Am J Neuroradiol. 2001;22:637–644. PubMed PMC
Škoda O, Herzig R, Mikulík R, Neumann J, Václavík D, Bar M, Šaňák D, Tomek A, Školoudík D. Clinical Guideline for the Diagnostics and Treatment of Patients with Ischemic Stroke and Transitory Ischemic Attack - Version 2016. Česká a Slov Neurol a Neurochir. 2016;79(112):351–363. doi: 10.14735/amcsnn2016351. DOI
Barnes SL, Whisenant JG, Loveless ME, Yankeelov TE. Practical Dynamic Contrast Enhanced MRI in Small Animal Models of Cancer: Data Acquisition, Data Analysis, and Interpretation. Pharmaceutics. 2012;4:442–478. doi: 10.3390/pharmaceutics4030442. PubMed DOI PMC
Chassidim Y, Vazana U, Prager O, Veksler R, Bar-Klein G, Schoknecht K, Fassler M, Lublinsky S, Shelef I. Analyzing the blood-brain barrier: The benefits of medical imaging in research and clinical practice. Semin Cell Dev Biol. 2015;38:43–52. doi: 10.1016/j.semcdb.2014.11.007. PubMed DOI
Lavini C, de Jonge MC, van de Sande MGH, Tak PP, Nederveen AJ, Maas M. Pixel-by-pixel analysis of DCE MRI curve patterns and an illustration of its application to the imaging of the musculoskeletal system. Magn Reson Imaging. 2007;25:604–612. doi: 10.1016/j.mri.2006.10.021. PubMed DOI
Fabijańska A. A novel approach for quantification of time-intensity curves in a DCE-MRI image series with an application to prostate cancer. Comput Biol Med. 2016;73:119–130. doi: 10.1016/j.compbiomed.2016.04.010. PubMed DOI
Sourbron SP, Buckley DL. Tracer kinetic modelling in MRI: Estimating perfusion and capillary permeability. Phys Med Biol. 2012;57:R1–R33. doi: 10.1088/0031-9155/57/2/R1. PubMed DOI
Jones EF, Sinha SP, Newitt DC, Klifa C, Kornak J, Park CC, Hylton NM. MRI enhancement in stromal tissue surrounding breast tumors: Association with recurrence free survival following neoadjuvant chemotherapy. PLoS One. 2013;8:e61969. doi: 10.1371/journal.pone.0061969. PubMed DOI PMC
Veksler R, Vazana U, Serlin Y, Prager O, Ofer J, Shemen N, Fisher AM, et al. Slow blood-to-brain transport underlies enduring barrier dysfunction in American football players. Brain. 2020;143:1826–1842. doi: 10.1093/brain/awaa140. PubMed DOI PMC
Haar HJ, Jansen JFA, Jeukens CRLPN, Burgmans S, Buchem MA, Muller M, Hofman PAM, et al. Subtle blood-brain barrier leakage rate and spatial extent: Considerations for dynamic contrast-enhanced MRI. Med Phys. 2017;44:4112–4125. doi: 10.1002/mp.12328. PubMed DOI
Yang AC, Stevens MY, Chen MB, Lee DP, Stähli D, Gate D, Contrepois K, et al. Physiological blood-brain transport is impaired with age by a shift in transcytosis. Nature. 2020;583:425–430. doi: 10.1038/s41586-020-2453-z. PubMed DOI PMC
van den Kerkhof M, Voorter PHM, Canjels LPW, de Jong JJA, van Oostenbrugge RJ, Kroon AA, Jansen JFA, Backes WH. Time-efficient measurement of subtle blood-brain barrier leakage using a T1 mapping MRI protocol at 7T. Magn Reson Med. 2021;85:2761–2770. doi: 10.1002/mrm.28629. PubMed DOI PMC
Veksler R, Vazana U, Serlin Y, Prager O, Ofer J, Shemen N, Fisher AM, et al. Slow blood-to-brain transport underlies enduring barrier dysfunction in American football players. Brain. 2020;143:1826–1842. doi: 10.1093/brain/awaa140. PubMed DOI PMC
Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel’Farb G, Ouseph R, Dwyer AC. Models and methods for analyzing DCE-MRI: A review. Med Phys. 2014;41:124301. doi: 10.1118/1.4898202. PubMed DOI
Barnes SR, Ng TSC, Montagne A, Law M, Zlokovic BV, Jacobs RE. Optimal acquisition and modeling parameters for accurate assessment of low Ktrans blood-brain barrier permeability using dynamic contrast-enhanced MRI. Magn Reson Med. 2016;75:1967–1977. doi: 10.1002/mrm.25793. PubMed DOI PMC
Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, Larsson HB, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: Standardized quantities and symbols. J Magn Reson Imaging. 1999;10:223–232. doi: 10.1002/(SICI)1522-2586(199909)10:3<223::AID-JMRI2>3.0.CO;2-S. PubMed DOI
Buckley DL. Uncertainty in the analysis of tracer kinetics using dynamic contrast-enhanced T1-weighted MRI. Magn Reson Med. 2002;47:601–606. doi: 10.1002/mrm.10080. PubMed DOI
Ashton E, McShane T, Evelhoch J. Inter-operator variability in perfusion assessment of tumors in MRI using automated AIF detection. Med Image Comput Comput Assist Interv. 2005;8:451–458. doi: 10.1007/11566465_56. PubMed DOI
Lavini C, Verhoeff JJC. Reproducibility of the gadolinium concentration measurements and of the fitting parameters of the vascular input function in the superior sagittal sinus in a patient population. Magn Reson Imaging. 2010;28:1420–1430. doi: 10.1016/j.mri.2010.06.017. PubMed DOI
Keil VC, Mädler B, Gieseke J, Fimmers R, Hattingen E, Schild HH, Hadizadeh DR. Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI. Magn Reson Imaging. 2017;40:83–90. doi: 10.1016/j.mri.2017.04.006. PubMed DOI
Kim H, Mousa M, Schexnailder P, Hergenrother R, Bolding M, Ntsikoussalabongui B, Thomas V, Morgan DE. Portable perfusion phantom for quantitative DCE-MRI of the abdomen. Med Phys. 2017;44:5198–5209. doi: 10.1002/mp.12466. PubMed DOI PMC
Huang W, Li X, Chen Y, Li X, Chang MC, Oborski MJ, Malyarenko DI, et al. Variations of dynamic contrast-enhanced magnetic resonance imaging in evaluation of breast cancer therapy response: A multicenter data analysis challenge. Transl Oncol. 2014;7:153–166. doi: 10.1593/tlo.13838. PubMed DOI PMC
Guo Y, Zhu Y, Lingala SG, Lebel RM, Shiroishi M, Law M, Nayak K. Biomedical Optics & Medical Imaging. SPIE Newsroom; 2015. High-resolution whole-brain dynamic contrast-enhanced MRI using compressed sensing. DOI
Inglese M, Ordidge KL, Honeyfield L, Barwick TD, Aboagye EO, Waldman AD, Grech-Sollars M. Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models. Neuroradiology. 2019;61:1375–1386. doi: 10.1007/s00234-019-02265-2. PubMed DOI PMC
Morabito R, Alafaci C, Pergolizzi S, Pontoriero A, Iati G, Bonanno L, Gaeta M, Salpietro FM, Mormina E, Longo M, Granata F. DCE and DSC perfusion MRI diagnostic accuracy in the follow-up of primary and metastatic intra-axial brain tumors treated by radiosurgery with cyberknife. Radiat Oncol. 2019;14:1–9. doi: 10.1186/s13014-019-1271-7. PubMed DOI PMC
Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging. 1997;7:91–101. doi: 10.1002/jmri.1880070113. PubMed DOI
Barnes SR, Ng TSC, Santa-Maria N, Montagne A, Zlokovic BV, Jacobs RE. ROCKETSHIP: A flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies. BMC Med Imaging. 2015;15:19. doi: 10.1186/s12880-015-0062-3. PubMed DOI PMC
Villringer K, Grittner U, Brunecker P, Khalil AA. DCE-MRI blood - brain barrier assessment in acute ischemic stroke. Neurology. 2017;88:433–440. doi: 10.1212/WNL.0000000000003566. PubMed DOI
Tofts P. T1-weighted DCE Imaging Concepts: Modelling, Acquisition and Analysis. Signal. 2010;500:400.
Donaldson SB, West CML, Davidson SE, Carrington BM, Hutchison G, Jones AP, Sourbron SP, Buckley DL. A comparison of tracer kinetic models for T1-weighted dynamic contrast-enhanced MRI: Application in carcinoma of the cervix. Magn Reson Med. 2010;63:691–700. doi: 10.1002/mrm.22217. PubMed DOI
Syková E, Nicholson C. Diffusion in brain extracellular space. Physiol Rev. 2008;88:1277–1340. doi: 10.1152/physrev.00027.2007. PubMed DOI PMC