Abstract
The five questions answered in this article revolve around the different parameters resulting from perfusion imaging processing, and this clarifies the frequently confusing terminology used to describe these parameters. More specifically, the article discusses the different imaging techniques and main mathematical models behind perfusion imaging, reviews the perfusion attributes of brain tissue, and proposes a standardized parameter terminology to facilitate understanding and avoid common misinterpretations.
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Konstas AA, Goldmakher GV, Lee TY, Lev MH (2009) Theoretic basis and technical implementations of CT perfusion in acute ischemic stroke, part 2: technical implementations. AJNR Am J Neuroradiol 30:885–892
Wintermark M, Maeder P, Thiran JP, Schnyder P, Meuli R (2001) Quantitative assessment of regional cerebral blood flows by perfusion CT studies at low injection rates: a critical review of the underlying theoretical models. Eur Radiol 11:1220–1230
Eastwood JD, Provenzale JM, Hurwitz LM, Lee TY (2001) Practical injection-rate CT perfusion imaging: deconvolution-derived hemodynamics in a case of stroke. Neuroradiology 43:223–226
Copen WA, Sorensen AG (2003) Perfusion-weighted MRI in Stroke. In: Davis S, Fisher M, Warach S (eds) Magnetic resonance imaging in stroke, 1st edn. Cambridge University Press, Cambridge, pp 147–159
Kane I, Carpenter T, Chappell F et al (2007) Comparison of 10 different magnetic resonance perfusion imaging processing methods in acute ischemic stroke: effect on lesion size, proportion of patients with diffusion/perfusion mismatch, clinical scores, and radiologic outcomes. Stroke 38:3158–3164
Schaefer P, Copen WA, Gonzalez RG (2006) Perfusion MRI of acute stroke. In: Gonzalez RG, Hirsch JA, Koroshetz WJ, Lev MH, Schaefer P (eds) Acute ischemic stroke imaging and intervention. Springer, Berlin, pp 173–197
Calamante F, Christensen S, Desmond PM, Ostergaard L, Davis SM, Connelly A (2010) The physiological significance of the time-to-maximum (Tmax) parameter in perfusion MRI. Stroke 41:1169–1174
Roberts HC, Roberts TP, Brasch RC, Dillon WP (2000) Quantitative measurement of microvascular permeability in human brain tumors achieved using dynamic contrast-enhanced MR imaging: correlation with histologic grade. AJNR Am J Neuroradiol 21:891–899
Lev MH, Rosen BR (1999) Clinical applications of intracranial perfusion MR imaging. Neuroimaging Clin N Am 9:309–331
Lacerda S, Law M (2009) Magnetic resonance perfusion and permeability imaging in brain tumors. Neuroimaging Clin N Am 19:527–557
Wintermark M, Flanders AE, Velthuis B et al (2006) Perfusion-CT assessment of infarct core and penumbra: receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke 37:979–985
Sobesky J, Zaro Weber O, Lehnhardt FG et al (2004) Which time-to-peak threshold best identifies penumbral flow? A comparison of perfusion-weighted magnetic resonance imaging and positron emission tomography in acute ischemic stroke. Stroke 35:2843–2847
Yamada K, Wu O, Gonzalez RG et al (2002) Magnetic resonance perfusion-weighted imaging of acute cerebral infarction: effect of the calculation methods and underlying vasculopathy. Stroke 33:87–94
Grandin CB, Duprez TP, Smith AM et al (2002) Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements. Radiology 223:361–370
Kudo K, Sasaki M, Yamada K et al (2010) Differences in CT perfusion maps generated by different commercial software: quantitative analysis by using identical source data of acute stroke patients. Radiology 254:200–209
Kudo K, Sasaki M, Ogasawara K, Terae S, Ehara S, Shirato H (2009) Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: quantitative evaluation with digital phantoms. Radiology 251:241–249
Konstas AA, Lev MH (2010) CT perfusion imaging of acute stroke: the need for arrival time, delay insensitive, and standardized postprocessing algorithms? Radiology 254:22–25
Sourbron S (2010) Technical aspects of MR perfusion. Eur J Radiol 3:304–313
Wu O, Ostergaard L, Weisskoff RM, Benner T, Rosen BR, Sorensen AG (2003) Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med 50:164–174
Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR (1996) High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: mathematical approach and statistical analysis. Magn Reson Med 36:715–725
Ibaraki M, Shimosegawa E, Toyoshima H, Takahashi K, Miura S, Kanno I (2005) Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI. J Cereb Blood Flow Metab 25:378–390
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Leiva-Salinas, C., Provenzale, J.M., Kudo, K. et al. The alphabet soup of perfusion CT and MR imaging: terminology revisited and clarified in five questions. Neuroradiology 54, 907–918 (2012). https://doi.org/10.1007/s00234-012-1028-6
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DOI: https://doi.org/10.1007/s00234-012-1028-6