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    ORIGINAL RESEARCH

    Differences in CT Perfusion Maps Generated by Different Commercial Software: Quantitative Analysis by Using Identical Source Data of Acute Stroke Patients

    Published Online:Dec 14 2009https://doi.org/10.1148/radiol.254082000

    Abstract

    The abnormal area and relative values of CT perfusion imaging were significantly different among commercially available software packages provided by CT manufacturers.

    Purpose

    To examine the variability in the qualitative and quantitative results of computed tomographic (CT) perfusion imaging generated from identical source data of stroke patients by using commercially available software programs provided by various CT manufacturers.

    Materials and Methods

    Institutional review board approval and informed consent were obtained. CT perfusion imaging data of 10 stroke patients were postprocessed by using five commercial software packages, each of which had a different algorithm: singular-value decomposition (SVD), maximum slope (MS), inverse filter (IF), box modulation transfer function (bMTF), and by using custom-made original software with standard (sSVD) and block-circulant (bSVD) SVD methods. Areas showing abnormalities in cerebral blood flow (CBF), mean transit time (MTT), and cerebral blood volume (CBV) were compared with each other and with the final infarct areas. Differences among the ratios of quantitative values in the final infarct areas and those in the unaffected side were also examined.

    Results

    The areas with CBF or MTT abnormalities and the ratios of these values significantly varied among software, while those of CBV were stable. The areas with CBF or MTT abnormalities analyzed by using SVD or bMTF corresponded to those obtained with delay-sensitive sSVD, but overestimated the final infarct area. The values obtained from software by using MS or IF corresponded well with those obtained from the delay-insensitive bSVD and the final infarct area. Given the similarities between CBF and MTT, all software were separated in two groups (ie, sSVD and bSVD). The ratios of CBF or MTTs correlated well within both groups, but not across them.

    Conclusion

    CT perfusion imaging maps were significantly different among commercial software even when using identical source data, presumably because of differences in tracer-delay sensitivity.

    © RSNA, 2010

    Supplemental Material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.254082000/-/DC1

    References

    • 1 Klotz E, Konig M. Perfusion measurements of the brain: using dynamic CT for the quantitative assessment of cerebral ischemia in acute stroke. Eur J Radiol 1999;30:170–184.
      MedlineGoogle Scholar
    • 2 Mayer TE, Hamann GF, Baranczyk J, et al.. Dynamic CT perfusion imaging of acute stroke. AJNR Am J Neuroradiol 2000;21:1441–1449.
      MedlineGoogle Scholar
    • 3 Lev MH, Segal AZ, Farkas J, et al.. Utility of perfusion-weighted CT imaging in acute middle cerebral artery stroke treated with intra-arterial thrombolysis: prediction of final infarct volume and clinical outcome. Stroke 2001;32:2021–2028.
      MedlineGoogle Scholar
    • 4 Jain R, Hoeffner EG, Deveikis JP, Harrigan MR, Thompson BG, Mukherji SK. Carotid perfusion CT with balloon occlusion and acetazolamide challenge test: feasibility. Radiology 2004;231:906–913.
      Google Scholar
    • 5 Laslo AM, Eastwood JD, Chen FX, Lee TY. Dynamic CT perfusion imaging in subarachnoid hemorrhage-related vasospasm. AJNR Am J Neuroradiol 2006;27:624–631.
      MedlineGoogle Scholar
    • 6 Cenic A, Nabavi DG, Craen RA, Gelb AW, Lee TYA. CT method to measure hemodynamics in brain tumors: validation and application of cerebral blood flow maps. AJNR Am J Neuroradiol 2000;21:462–470.
      MedlineGoogle Scholar
    • 7 Wintermark M, Maeder P, Verdun FR, et al.. Using 80 kVp versus 120 kVp in perfusion CT measurement of regional cerebral blood flow. AJNR Am J Neuroradiol 2000;21:1881–1884.
      MedlineGoogle Scholar
    • 8 Hirata M, Sugawara Y, Fukutomi Y, et al.. Measurement of radiation dose in cerebral CT perfusion study. Radiat Med 2005;23:97–103.
      MedlineGoogle Scholar
    • 9 Wintermark M, Smith WS, Ko NU, Quist M, Schnyder P, Dillon WP. Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients. AJNR Am J Neuroradiol 2004;25:720–729.
      MedlineGoogle Scholar
    • 10 Sanelli PC, Lev MH, Eastwood JD, Gonzalez RG, Lee TY. The effect of varying user-selected input parameters on quantitative values in CT perfusion maps. Acad Radiol 2004;11:1085–1092.
      MedlineGoogle Scholar
    • 11 Fiorella D, Heiserman J, Prenger E, Partovi S. Assessment of the reproducibility of postprocessing dynamic CT perfusion data. AJNR Am J Neuroradiol 2004;25:97–107.
      MedlineGoogle Scholar
    • 12 Sasaki M, Kudo K, Ogasawara K, Fujiwara S. Tracer delay-insensitive algorithm can improve reliability of CT perfusion imaging for cerebrovascular steno-occlusive disease: comparison with quantitative single-photon emission CT. AJNR Am J Neuroradiol 2009;30:188–193.
      MedlineGoogle Scholar
    • 13 Kudo K, Sasaki M, Ogasawara K, Terae S, Ehara S, Shirato H. Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: quantitative evaluation with digital phantoms. Radiology 2009;251:241–249.
      Google Scholar
    • 14 Murphy BD, Fox AJ, Lee DH, et al.. White matter thresholds for ischemic penumbra and infarct core in patients with acute stroke: CT perfusion study. Radiology 2008;247:818–825.
      Google Scholar
    • 15 Omi Y, Miyazaki O, Yasuda S, Matsumura A. Development of advanced CT-perfusion software. In: Radiological Society of North America scientific assembly and annual meeting program. Oak Brook, Ill: Radiological Society of North America, 2003.
      Google Scholar
    • 16 Nambu K, Takehara R, Terada T. A method of regional cerebral blood perfusion measurement using dynamic CT with an iodinated contrast medium. Acta Neurol Scand Suppl 1996;93:28–31.
      Google Scholar
    • 17 Kudo K. Perfusion Mismatch Analyzer, version 3.0.0.0. ASIST-Japan web site. http://asist.umin.jp/index-e.htm Published November 2006Updated February 2009. Accessed February 20, 2009.
      Google Scholar
    • 18 ASIST-Japan Web site. http://asist.umin.jp/index-e.htm Published June 2005Updated March 2009. Accessed June 9, 2009.
      Google Scholar
    • 19 Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I. Mathematical approach and statistical analysis. Magn Reson Med 1996;36:715–725.
      MedlineGoogle Scholar
    • 20 Wu O, Ostergaard L, Weisskoff RM, Benner T, Rosen BR, Sorensen AG. 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 2003;50:164–174.
      MedlineGoogle Scholar
    • 21 Calamante F, Gadian DG, Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med 2000;44:466–473.
      MedlineGoogle Scholar
    • 22 Kudo K, Terae S, Katoh C, et al.. Quantitative cerebral blood flow measurement with dynamic perfusion CT using the vascular-pixel elimination method: comparison with H2(15)O positron emission tomography. AJNR Am J Neuroradiol 2003;24:419–426.
      MedlineGoogle Scholar
    • 23 Rose SE, Janke AL, Griffin M, Finnigan S, Chalk JB. Improved prediction of final infarct volume using bolus delay-corrected perfusion-weighted MRI: implications for the ischemic penumbra. Stroke 2004;35:2466–2471.
      MedlineGoogle Scholar
    • 24 Silvennoinen HM, Hamberg LM, Lindsberg PJ, Valanne L, Hunter GJ. CT perfusion identifies increased salvage of tissue in patients receiving intravenous recombinant tissue plasminogen activator within 3 hours of stroke onset. AJNR Am J Neuroradiol 2008;29:1118–1123.
      MedlineGoogle Scholar
    • 25 Kucinski T, Naumann D, Knab R, et al.. Tissue at risk is overestimated in perfusion-weighted imaging: MR imaging in acute stroke patients without vessel recanalization. AJNR Am J Neuroradiol 2005;26:815–819.
      MedlineGoogle Scholar
    • 26 Matsushima S, Kubota T, Yamada K, et al.. Effect of vascular stenosis on perfusion-weighted imaging; differences between calculation algorithms. J Magn Reson Imaging 2008;27:1103–1108.
      MedlineGoogle Scholar
    • 27 Firlik AD, Yonas H, Kaufmann AM, et al.. Relationship between cerebral blood flow and the development of swelling and life-threatening herniation in acute ischemic stroke. J Neurosurg 1998;89:243–249.
      MedlineGoogle Scholar
    • 28 Wintermark M, Albers GW, Alexandrov AV, et al.. Acute stroke imaging research roadmap. Stroke 2008;39:1621–1628.
      MedlineGoogle Scholar

    Article History

    Received November 12, 2008; revision requested February 4, 2009; revision received May 7; accepted June 2; final version accepted June 17.
    Published online: Dec 14 2009
    Published in print: Jan 2010