Emergency Radiology

, Volume 21, Issue 1, pp 49–65 | Cite as

CT perfusion in acute stroke: Know the mimics, potential pitfalls, artifacts, and technical errors

  • Rajiv Mangla
  • Sven Ekhom
  • Babak S. Jahromi
  • Jeevak Almast
  • Manisha Mangla
  • Per-Lennart Westesson
Pictorial Essay

Abstract

The CT perfusion (CTP) imaging of brain has been established as a clinically useful tool in multimodality imaging of acute stroke. All abnormalities seen on perfusion CT are not specifically related to acute infarct. There are many neurologic diseases causing symptoms simulating cerebrovascular disease produce an alteration of brain perfusion and thus can result in perfusion CT abnormalities. There are many pitfalls and artifacts in acquiring the data, calculation of maps and choosing arterial input function. We analyze and classify all these aspects, to allow the technician and the radiologist to know exactly what to avoid and what to choose, and we indicate the way to improve the quality of examination. The knowledge of mimics and pitfalls in acute stroke imaging can be helpful in accurate interpretation of these examinations.

Keywords

CT perfusion Acute stroke Technical pitfalls 

Abbreviation

CT

Computed tomography

CTP

CT perfusion

CBV

Cerebral blood volume

MTT

Mean transit time

CBF

Cerebral blood flow

ACA

Anterior cerebral artery

MCA

Middle cerebral artery

DWI

Diffusion-weighted imaging

ICA

Internal carotid artery

NCCT

Noncontrast CT

Notes

Acknowledgement

The authors are grateful to Sarah Peangatelli, Radiology Graphics Imaging Specialist for providing assistant with images.

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Adams HP Jr, del Zoppo G, Alberts MJ et al (2007) Guidelines for the early management of adults with ischemic stroke: a guideline from the American Heart Association/American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology and Intervention Council, and the Atherosclerotic Peripheral Vascular Disease and Quality of Care Outcomes in Research Interdisciplinary Working Groups: the American Academy of Neurology affirms the value of this guideline as an educational tool for neurologists. Stroke 38:1655–1711PubMedCrossRefGoogle Scholar
  2. 2.
    de Lucas EM, Sanchez E, Gutierrez A et al (2008) CT protocol for acute stroke: tips and tricks for general radiologists. Radiographics 28:1673–1687PubMedCrossRefGoogle Scholar
  3. 3.
    Leiva-Salinas C, Provenzale JM, Kudo K, Sasaki M, Wintermark M (2012) The alphabet soup of perfusion CT and MR imaging: terminology revisited and clarified in five questions. Neuroradiology Apr 10. [Epub ahead of print]Google Scholar
  4. 4.
    Zussman BM, Boghosian G, Gorniak RJ et al (2011) The relative effect of vendor variability in CT perfusion results: a method comparison study. AJR Am J Roentgenol 197(2):468–473PubMedCrossRefGoogle Scholar
  5. 5.
    Fiorella D, Heiserman J, Prenger E et al (2004) Assessment of the reproducibility of postprocessing dynamic CT perfusion data. AJNR Am J Neuroradiol 25:97–107PubMedGoogle Scholar
  6. 6.
    Goldmakher GV, Kamalian S, Schaefer PW, et al. (2006) Fully automated processing of stroke CT perfusion maps is fast and accurate. In: Radiological Society of North america scientific assembly and annual meeting program. Oak Brook, Ill: November 29Google Scholar
  7. 7.
    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 37:979–985PubMedCrossRefGoogle Scholar
  8. 8.
    Kamalian S, Kamalian S, Konstas AA et al (2012) CT perfusion mean transit time maps optimally distinguish benign oligemia from true “at-risk” ischemic penumbra, but thresholds vary by postprocessing technique. AJNR Am J Neuroradiol 33(3):545–549, Epub 2011 Dec 22PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Sanelli PC, Lev MH, Eastwood JD et al (2004) The effect of varying user-selected input parameters on quantitative values in CT perfusion maps. Acad Radiol 11:1085–1092PubMedCrossRefGoogle Scholar
  10. 10.
    Wintermark M, Lau BC, Chien J, Arora S (2008) The anterior cerebral artery is an appropriate arterial input function for perfusion-CT processing in patients with acute stroke. Neuroradiology 50:227–236PubMedCrossRefGoogle Scholar
  11. 11.
    Sheikh K, Schipper MJ, Hoeffner EG (2009) Feasibility of superficial temporal artery as the input artery for cerebral perfusion CT. AJR Am J Roentgenol 192:W321–W329PubMedCrossRefGoogle Scholar
  12. 12.
    van der Schaaf I, Vonken EJ, Waaijer A, Velthuis B, Quist M, van Osch T (2006) Influence of partial volume on venous output and arterial input function. AJNR 27:46–50PubMedGoogle Scholar
  13. 13.
    Kudo K, Terae S, Katoh C et al (2003) 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 24:419PubMedGoogle Scholar
  14. 14.
    Wintermark M, Albers GW, Alexandrov AV et al (2008) Acute stroke imaging research roadmap. Stroke 39:1621–1628PubMedCrossRefGoogle Scholar
  15. 15.
    Konstas AA, Lev MH (2010) CT perfusion imaging of acute stroke: the need for arrival time, delay insensitive, and standardized postprocessing algorithms? Radiology 254:22–25PubMedCrossRefGoogle Scholar
  16. 16.
    Wintermark M, Lev MH (2010) FDA investigates the safety of brain perfusion CT. AJNR Am J Neuroradiol 31:2–3PubMedCrossRefGoogle Scholar
  17. 17.
    Wintermark M, Maeder P, Verdun FR et al (2000) Using 80 kVp versus 120 kVp in perfusion CT measurement of regional cerebral blood flow. AJNR 21:1881–1884PubMedGoogle Scholar
  18. 18.
    Wintermark M, Smith WS, Ko NU et al (2004) Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients. AJNR Am J Neuroradiol 25:720–729PubMedGoogle Scholar
  19. 19.
    Wentland AL, Rowley HA, Vigen KK, Field AS (2010) Fetal origin of the posterior cerebral artery produces left–right asymmetry on perfusion imaging AJNR Am. J Neuroradiol 31:448–453Google Scholar
  20. 20.
    Schöning M, Walter J, Scheel P (1994) Estimation of cerebral blood flow through color duplex sonography of the carotid and vertebral arteries in healthy adults. Stroke 25:17–22PubMedCrossRefGoogle Scholar
  21. 21.
    Best AC, Acosta NR, Fraser JE, Borges MT, Brega KE, Anderson T, Neumann RT, Ree A, Bert RJ (2012) Recognizing false ischemic penumbras in CT brain perfusion studies. Radiographics 32(4):1179–1196PubMedCrossRefGoogle Scholar
  22. 22.
    Leiva-Salinas C, Provenzale JM, Wintermark M (2011) Responses to the 10 most frequently asked questions about perfusion CT. AJR Am J Roentgenol 196:53–60PubMedCrossRefGoogle Scholar
  23. 23.
    Marchal G, Young AR, Baron JC (1999) Early postischemic hyperperfusion: pathophysiologic insights from positron emission tomography. J Cereb Blood Flow Metab 19:467–482PubMedCrossRefGoogle Scholar
  24. 24.
    Nagar VA, McKinney AM, Karagulle AT (2009) Reperfusion phenomenon masking acute and subacute infarcts at dynamic perfusion CT: confirmation by fusion of CT and diffusion-weighted MR images. AJR Am J Roentgenol 193:1629–1638PubMedCrossRefGoogle Scholar
  25. 25.
    Oberndorfer S, Wober C, Nasel C et al (2004) Familial hemiplegic migraine: follow-up findings of diffusion-weighted magnetic resonance imaging (MRI), perfusion-MRI and [99mTc] HMPAO-SPECT in a patient with prolonged hemiplegic aura. Cephalalgia 24:533–539PubMedCrossRefGoogle Scholar
  26. 26.
    Hsu DA, Stafstrom CE, Rowley HA et al (2008) Hemiplegic migraine: hyperperfusion and abortive therapy with intravenous verapamil. Brain Dev 30:86–90PubMedCrossRefGoogle Scholar
  27. 27.
    Ellika SK, Jain R, Patel SC et al (2007) Role of perfusion CT in glioma grading and comparison with conventional MR imaging features. Am J Neuroradiol 28:1981–1987PubMedCrossRefGoogle Scholar
  28. 28.
    Abels B, Klotz E, Tomandl BF et al (2010) Perfusion CT in acute ischemic stroke: a qualitative and quantitative comparison of deconvolution and maximum slope approach. AJNR Am J Neuroradiol 31:1690–1698, Epub 2010 Jun 25PubMedCrossRefGoogle Scholar
  29. 29.
    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(1):200–209PubMedCrossRefGoogle Scholar
  30. 30.
    Ho CY, Hussain S, Alam Tet al. (2013) Accuracy of CT cerebral perfusion in predicting infarct in the emergency department: lesion characterization on CT perfusion based on commercially available software. Emerg Radiol. Jan 16. [Epub ahead of print]Google Scholar
  31. 31.
    Suzuki K, Morita S, Masukawa A et al (2011) Utility of CTperfusion with 64-row multi-detector CT for acute ischemic brain stroke. Emerg Radiol 18(2):95–101PubMedCrossRefGoogle Scholar
  32. 32.
    Sanelli PC, Jacobs MA, Ougorets I, Mifsud MJ (2005) Posterior reversible encephalopathy syndrome on computed tomography perfusion in a patient on “Triple H” therapy. Neurocrit Care 3(1):46–50. doi: 10.1385/NCC:3:1:046 PubMedCrossRefGoogle Scholar

Copyright information

© Am Soc Emergency Radiol 2013

Authors and Affiliations

  • Rajiv Mangla
    • 1
  • Sven Ekhom
    • 1
  • Babak S. Jahromi
    • 1
    • 2
    • 3
  • Jeevak Almast
    • 1
  • Manisha Mangla
    • 1
  • Per-Lennart Westesson
    • 1
  1. 1.Department of Imaging SciencesUniversity of Rochester, School of Medicine and DentistryRochesterUSA
  2. 2.Department of NeurosurgeryUniversity of Rochester, School of Medicine and DentistryRochesterUSA
  3. 3.Department of NeurologyUniversity of Rochester, School of Medicine and DentistryRochesterUSA

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