Elsevier

Academic Radiology

Volume 11, Issue 10, October 2004, Pages 1085-1092
Academic Radiology

Original investigations
The effect of varying user-selected input parameters on quantitative values in CT perfusion maps1

https://doi.org/10.1016/j.acra.2004.07.002Get rights and content

Rationale and objectives

Deconvolution-based software can be used to calculate quantitative maps of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) from first-pass computed tomography perfusion (CTP) datasets. The application of this software requires the user to select multiple input variables. The purpose of this study was to investigate the degree to which both major and minor variations of these user-defined inputs would affect the final quantitative values of CBF, CBV, and MTT.

Materials and methods

A neuroradiologist constructed CBF, CBV, and MTT maps using standard methodology with commercially available software (GE Functool Version 1.9s) from CTP datasets of three acute stroke patients. Each map was reconstructed multiple times by systematically and independently varying the following parameters: postenhancement and preenhancement cutoff values, arterial and venous region-of-interest (ROI) placement, and arterial and venous ROI size. The resulting quantitative CTP values were compared using identical ROIs placed at the infarct core.

Results

Major variations of either arterial ROI placement or arterial and venous ROI size had no significant effect on the mean CBF, CBV, and MTT values at the infarct core (p > .05). Even minor variations, however, in the choice of venous ROI placement or in pre- and postenhancement cutoff values significantly altered the quantitative values for each of the CTP maps, by as much as threefold.

Conclusion

Even minor variations of user-defined inputs can significantly influence the quantitative, deconvolution-based CTP map values of acute stroke patients. Although quantitation was robust to the choice of arterial ROI placement and arterial or venous ROI size, it was strongly dependent on the choice of venous ROI location and pre- and postenhancement cut-off values. Awareness of these results by clinicians may be important in the creation of quantitatively accurate CTP maps.

Section snippets

Materials and methods

CT perfusion datasets from three patients were analyzed in this study. All patients presented with acute middle cerebral artery infarction; two on the right side and one on the left side. Two male and one female patients were included in the study. The age range was 30–63 years of age. These three datasets were acquired at two different institutions on GE HiSpeed and LightSpeed CT scanners (General Electric Medical Systems, Milwaukee, WI). The protocol for performing CT perfusion used cine mode

Results

All three patients had acute middle cerebral artery territory infarctions identified on MR diffusion-weighted imaging. A total of 192 CTP maps were constructed (64 maps per patient).

Overall, the changes in the CTP quantitative values were most significant in the infarct core compared with the unaffected gray and white matter sampled from the contralateral side. The unaffected gray and white matter did not necessarily reflect these changes, likely because of their higher quantitative values. In

Discussion

In this article, we have confirmed and underscored the theoretical prediction that major variations of either arterial ROI placement or arterial and venous ROI size had no significant effect on the mean CBF, CBV, and MTT values at the infarct core (P > .05). Even minor variations, however, in the choice of venous ROI placement, or in pre- and postenhancement cut-off time point values significantly altered the quantitative values for each of the deconvolution based CTP maps by as much as

Conclusion

To limit potential quantitative error in constructing deconvolution-based CT perfusion maps, we recommend using a standardized procedure for the selection of the user-defined parameters that are required to calculate the CBV, CBF, and MTT maps. Two specific guidelines for constructing CT perfusion maps include: (1) avoid partial volume averaging by selecting the largest vessel perpendicular to the imaging plane for the arterial and venous ROIs, choosing an ROI pixel size to fit the lumen of the

References (9)

  • G. Schlaug et al.

    The ischemic penumbra operationally defined by diffusion and perfusion MRI

    Neurology

    (1999)
  • J.P. Muzielaar et al.

    A new method for quantitative regional cerebral blood volume measurements using computed tomography

    Stroke

    (1997)
  • T.E. Mayer et al.

    Dynamic CT perfusion imaging in hyperacute stroke

    Stroke

    (1998)
  • M.H. Lev et al.

    Utility of perfusion weighted CT imaging in acute MCA stroke treated with intra-arterial thrombolysisprediction of final infarct volume and clinical outcome

    Stroke

    (2001)
There are more references available in the full text version of this article.

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