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Neuroradiology

, Volume 48, Issue 9, pp 670–677 | Cite as

Cerebral perfusion computerized tomography: influence of reference vessels, regions of interest and interobserver variability

  • Jean F. Soustiel
  • Nadav Mor
  • Menashe Zaaroor
  • Dorith Goldsher
Functional Neuroradiology

Abstract

Introduction

There are still no standardized guidelines for perfusion computerized tomography (PCT) analysis.

Methods

A total of 61 PCT studies were analyzed using either the anterior cerebral artery (ACA) or the middle cerebral artery (MCA) as the arterial reference, and the superior sagittal sinus (SSS) or the vein of Galen (VG) as the venous reference. The sizes of regions of interest (ROI) were investigated comparing PCT results obtained using a hemispheric ROI combined with vascular pixel elimination with those obtained using five smaller ROIs located over the cortex and basal ganglia. In addition, interobserver variations were explored using a standardized protocol.

Results

MCA-based measurements of cerebral blood flow (CBF) and blood volume (CBV) were in accordance with those obtained with the ACA except in 16 patients with ischemic stroke, in whom CBF was overestimated by the ipsilateral MCA. Venous maximal intensity was significantly lower with the VG when compared with the SSS, resulting in overestimation of CBF and CBV. However, in 13.3% of patients the VG ROI yielded higher maximal intensities than the SSS ROI. There was no difference in PCT results between hemispheric ROI and averaged separate ROI when vascular pixel elimination was used. Finally, interobserver variations were as high as 11% for CBF and 12% for CBV.

Conclusion

The present results suggest that pathological rather than anatomical considerations should dictate the choice of the arterial ROI. For venous ROI, although SSS seems to be adequate in most instances, deep cerebral veins may occasionally generate higher maximal intensities and should therefore be selected. Importantly, significant user-dependency should be taken into account.

Keywords

Computerized tomography perfusion Cerebral blood flow Cerebral blood volume 

Notes

Acknowledgments

The authors are particularly indebted to Aliza Turgeman, Pesah Ladovicz and Shmuel Weizman, technologists in the CT unit, for their outstanding technical support.

Conflict of interest statement

We declare that we have no conflict of interest.

References

  1. 1.
    Martin NA, Doberstein C (1994) Cerebral blood flow measurement in neurosurgical intensive care. Neurosurg Clin N Am 5:607–618PubMedGoogle Scholar
  2. 2.
    Hoeffner EG, Case I, Jain R, Gujar SK, Shah GV, Deveikis JP, Carlos RC, Thompson BG, Harrigan MR, Mukherji SK (2004) Cerebral perfusion CT: technique and clinical applications. Radiology 231:632–644PubMedCrossRefGoogle Scholar
  3. 3.
    Wintermark M, van Melle G, Schnyder P, Revelly JP, Porchet F, Regli L, Meuli R, Maeder P, Chiolero R (2004) Admission perfusion CT: prognostic value in patients with severe head trauma. Radiology 232:211–220PubMedCrossRefGoogle Scholar
  4. 4.
    Wintermark M, Chiolero R, van Melle G, Revelly JP, Porchet F, Regli L, Meuli R, Schnyder P, Maeder P (2004) Relationship between brain perfusion computed tomography variables and cerebral perfusion pressure in severe head trauma patients. Crit Care Med 32:1579–1587CrossRefPubMedGoogle Scholar
  5. 5.
    Bisdas S, Donnerstag F, Ahl B, Bohrer I, Weissenborn K, Becker H (2004) Comparison of perfusion computed tomography with diffusion-weighted magnetic resonance imaging in hyperacute ischemic stroke. J Comput Assist Tomogr 28:747–755CrossRefPubMedGoogle Scholar
  6. 6.
    Eastwood JD, Provenzale JM, Hurwitz LM, Lee TY (2001) Practical injection-rate CT perfusion imaging: deconvolution-derived hemodynamics in a case of stroke. Neuroradiology 43:223–226CrossRefPubMedGoogle Scholar
  7. 7.
    Eastwood JD, Lev MH, Azhari T, Lee TY, Barboriak DP, Delong DM, Fitzek C, Herzau M, Wintermark M, Meuli R, Brazier D, Provenzale JM (2002) CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke. Radiology 222:227–236PubMedCrossRefGoogle Scholar
  8. 8.
    Keith CJ, Griffiths M, Petersen B, Anderson RJ, Miles KA (2002) Computed tomography perfusion imaging in acute stroke. Australas Radiol 46:221–230CrossRefPubMedGoogle Scholar
  9. 9.
    Koenig M, Klotz E, Luka B, Venderink DJ, Spittler JF, Heuser L (1998) Perfusion CT of the brain: diagnostic approach for early detection of ischemic stroke. Radiology 209:85–93PubMedGoogle Scholar
  10. 10.
    Konig M (2003) Brain perfusion CT in acute stroke: current status. Eur J Radiol 45 [Suppl 1]:S11–S22CrossRefPubMedGoogle Scholar
  11. 11.
    Miles KA (2004) Brain perfusion: computed tomography applications. Neuroradiology 46 [Suppl 2]:s194–s200CrossRefPubMedGoogle Scholar
  12. 12.
    Wintermark M, Smith WS, Ko NU, Quist M, Schnyder P, Dillon WP (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
  13. 13.
    Wintermark M, Fischbein NJ, Smith WS, Ko NU, Quist M, Dillon WP (2005) Accuracy of dynamic perfusion CT with deconvolution in detecting acute hemispheric stroke. AJNR Am J Neuroradiol 26:104–112PubMedGoogle Scholar
  14. 14.
    Wintermark M, Maeder P, Verdun FR, Thiran JP, Valley JF, Schnyder P, Meuli R (2000) Using 80 kVp versus 120 kVp in perfusion CT measurement of regional cerebral blood flow. AJNR Am J Neuroradiol 21:1881–1884PubMedGoogle Scholar
  15. 15.
    Axel L (1983) Tissue mean transit time from dynamic computed tomography by a simple deconvolution technique. Invest Radiol 18:94–99PubMedCrossRefGoogle Scholar
  16. 16.
    Norman D, Axel L, Berninger WH, Edwards MS, Cann CE, Redington RW, Cox L (1981) Dynamic computed tomography of the brain: techniques, data analysis, and applications. AJR Am J Roentgenol 136:759–770PubMedGoogle Scholar
  17. 17.
    Sanelli PC, Lev MH, Eastwood JD, Gonzalez RG, Lee TY (2004) The effect of varying user-selected input parameters on quantitative values in CT perfusion maps. Acad Radiol 11:1085–1092CrossRefPubMedGoogle Scholar
  18. 18.
    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 11:1220–1230CrossRefPubMedGoogle Scholar
  19. 19.
    Kudo K, Terae S, Katoh C, Oka M, Shiga T, Tamaki N, Miyasaka K (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 24:419–426PubMedGoogle Scholar
  20. 20.
    Furukawa M, Kashiwagi S, Matsunaga N, Suzuki M, Kishimoto K, Shirao S (2002) Evaluation of cerebral perfusion parameters measured by perfusion CT in chronic cerebral ischemia: comparison with xenon CT. J Comput Assist Tomogr 26:272–278CrossRefPubMedGoogle Scholar
  21. 21.
    Sase S, Honda M, Machida K, Seiki Y (2005) Comparison of cerebral blood flow between perfusion computed tomography and xenon-enhanced computed tomography for normal subjects: territorial analysis. J Comput Assist Tomogr 29:270–277CrossRefPubMedGoogle Scholar
  22. 22.
    Wintermark M, Thiran JP, Maeder P, Schnyder P, Meuli R (2001) Simultaneous measurement of regional cerebral blood flow by perfusion CT and stable xenon CT: a validation study. AJNR Am J Neuroradiol 22:905–914PubMedGoogle Scholar
  23. 23.
    Wintermark M, Reichhart M, Thiran JP, Maeder P, Chalaron M, Schnyder P, Bogousslavsky J, Meuli R (2002) Prognostic accuracy of cerebral blood flow measurement by perfusion computed tomography, at the time of emergency room admission, in acute stroke patients. Ann Neurol 51:417–432CrossRefPubMedGoogle Scholar
  24. 24.
    Nabavi DG, Cenic A, Dool J, Smith RM, Espinosa F, Craen RA, Gelb AW, Lee TY (1999) Quantitative assessment of cerebral hemodynamics using CT: stability, accuracy, and precision studies in dogs. J Comput Assist Tomogr 23:506–515CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Jean F. Soustiel
    • 1
  • Nadav Mor
    • 1
  • Menashe Zaaroor
    • 1
  • Dorith Goldsher
    • 2
  1. 1.Department of Neurosurgery, Rambam Medical Center, Faculty of MedicineTechnion – Israel Institute of TechnologyHaifaIsrael
  2. 2.Department of Neuroradiology, Rambam Medical Center, Faculty of MedicineTechnion – Israel Institute of TechnologyHaifaIsrael

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