Literature DB >> 16418354

Influence of partial volume on venous output and arterial input function.

I van der Schaaf1, E-J Vonken, A Waaijer, B Velthuis, M Quist, T van Osch.   

Abstract

BACKGROUND: CT perfusion (CTP) is an important diagnostic tool for the imaging of cerebral hemodynamics. To obtain quantitative values of cerebral blood volume (CBV), blood flow (CBF), and mean transit time (MTT), measurement of the arterial input function (AIF) is required. To correct for partial volume effects (PVEs), it is common to normalize the AIF with respect to the venous output function (VOF). This correction assumes that measurement of the VOF is unhampered by PVEs. The purpose of this study was to evaluate the effect of PVE on the measurement of the AIF and VOF and, consequently, on the absolute perfusion parameters.
METHODS: In 10 patients the mean area under the curve (AUC) of the AIF and VOF were quantified for 3-, 6-, and 12-mm-thick sections. Differences in the mean (1) AUC of the VOF, (2) AUC of the AIF, and (3) width of the AIF were compared for the 3 section thicknesses, and the influence on the absolute values of CBV, CBF, and MTT were studied.
RESULTS: With thinner sections, the AUC of the VOF and the AIF increased significantly and the width of the AIF decreased slightly. Differences in AUC between the 3 section thicknesses were larger for the AIF than for the VOF.
CONCLUSION: PVEs affect not only the AIF, but also the VOF. This results in an overestimation of CBV and CBF when a thicker section is used. To avoid PVE, VOF measurements should be performed at lower section thicknesses.

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Year:  2006        PMID: 16418354      PMCID: PMC7976058     

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  21 in total

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Authors:  Richard E Latchaw; Howard Yonas; George J Hunter; William T C Yuh; Toshihiro Ueda; A Gregory Sorensen; Jeffrey L Sunshine; Jose Biller; Lawrence Wechsler; Randall Higashida; George Hademenos
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2.  On the theory of the indicator-dilution method for measurement of blood flow and volume.

Authors:  P MEIER; K L ZIERLER
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Review 3.  Quantitative assessment of regional cerebral blood flows by perfusion CT studies at low injection rates: a critical review of the underlying theoretical models.

Authors:  M Wintermark; P Maeder; J P Thiran; P Schnyder; R Meuli
Journal:  Eur Radiol       Date:  2001       Impact factor: 5.315

4.  Tissue mean transit time from dynamic computed tomography by a simple deconvolution technique.

Authors:  L Axel
Journal:  Invest Radiol       Date:  1983 Jan-Feb       Impact factor: 6.016

5.  Cerebral blood flow determination by rapid-sequence computed tomography: theoretical analysis.

Authors:  L Axel
Journal:  Radiology       Date:  1980-12       Impact factor: 11.105

6.  Measurement of cerebral perfusion with dual-echo multi-slice quantitative dynamic susceptibility contrast MRI.

Authors:  E J Vonken; M J van Osch; C J Bakker; M A Viergever
Journal:  J Magn Reson Imaging       Date:  1999-08       Impact factor: 4.813

7.  Prognostic accuracy of cerebral blood flow measurement by perfusion computed tomography, at the time of emergency room admission, in acute stroke patients.

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9.  Correlation of early dynamic CT perfusion imaging with whole-brain MR diffusion and perfusion imaging in acute hemispheric stroke.

Authors:  James D Eastwood; Michael H Lev; Max Wintermark; Clemens Fitzek; Daniel P Barboriak; David M Delong; Ting-Yim Lee; Tarek Azhari; Michael Herzau; Vani R Chilukuri; James M Provenzale
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10.  A multicenter validation of regional cerebral blood flow quantitation using [123I]iodoamphetamine and single photon emission computed tomography.

Authors:  H Iida; T Akutsu; K Endo; H Fukuda; T Inoue; H Ito; S Koga; A Komatani; Y Kuwabara; T Momose; S Nishizawa; I Odano; M Ohkubo; Y Sasaki; H Suzuki; S Tanada; H Toyama; Y Yonekura; T Yoshida; K Uemura
Journal:  J Cereb Blood Flow Metab       Date:  1996-09       Impact factor: 6.200

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  18 in total

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2.  A fast nonlinear regression method for estimating permeability in CT perfusion imaging.

Authors:  Edwin Bennink; Alan J Riordan; Alexander D Horsch; Jan Willem Dankbaar; Birgitta K Velthuis; Hugo W de Jong
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3.  Biopsy targeting with dynamic contrast-enhanced versus standard neuronavigation MRI in glioma: a prospective double-blinded evaluation of selection benefits.

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Journal:  J Neurooncol       Date:  2017-04-19       Impact factor: 4.130

4.  CT brain perfusion protocol to eliminate the need for selecting a venous output function.

Authors:  A J Riordan; E Bennink; M A Viergever; B K Velthuis; J W Dankbaar; H W A M de Jong
Journal:  AJNR Am J Neuroradiol       Date:  2013-01-31       Impact factor: 3.825

5.  Post-processing of computed tomography perfusion in patients with acute cerebral ischemia: variability of inter-reader, inter-region of interest, inter-input model, and inter-software.

Authors:  Zhong-Ping Chen; Zhen-Zhen Shi; Yun-Geng Li; Yan Guo; Dan Tong
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6.  Realization of reliable cerebral-blood-flow maps from low-dose CT perfusion images by statistical noise reduction using nonlinear diffusion filtering.

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7.  Reproducibility of quantitative CT brain perfusion measurements in patients with symptomatic unilateral carotid artery stenosis.

Authors:  A Waaijer; I C van der Schaaf; B K Velthuis; M Quist; M J P van Osch; E P A Vonken; M S van Leeuwen; M Prokop
Journal:  AJNR Am J Neuroradiol       Date:  2007-05       Impact factor: 3.825

8.  Use of cardiac output to improve measurement of input function in quantitative dynamic contrast-enhanced MRI.

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Review 9.  CT perfusion in acute stroke: know the mimics, potential pitfalls, artifacts, and technical errors.

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Journal:  Emerg Radiol       Date:  2013-06-15

10.  Statistical properties of cerebral CT perfusion imaging systems. Part II. Deconvolution-based systems.

Authors:  Ke Li; Guang-Hong Chen
Journal:  Med Phys       Date:  2019-09-23       Impact factor: 4.071

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