Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging.

Rempp, Katrin; Brix, Gunnar; Wenz, Frederik; Becker, Carl; Gückel, F.; Lorenz, Werner

doi:10.1148/radiology.193.3.7972800

Cited by 582 publications

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“…CBV was given by the tissue concentration time integral divided by the measured AIF time integral (not corrected for partial volume effects), and the obtained ratio was corrected for differences between capillary and arterial haematocrit values [17].…”

Section: Methodsmentioning

confidence: 99%

Correlation between arterial blood volume obtained by arterial spin labelling and cerebral blood volume in intracranial tumours

Westen

Petersen

Wirestam

et al. 2011

Magn Reson Mater Phy

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Objective: To compare measurements of the arterial blood volume (aBV), a perfusion parameter calculated from arterial spin labelling (ASL), and cerebral blood volume (CBV), calculated from dynamic susceptibility contrast (DSC) MRI. In the clinic, CBV is used for grading of intracranial tumours Conclusion:These results suggest that measurement of aBV is a potential tool for non-invasive assessment of blood volume in intracranial tumours.

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Section: Methodsmentioning

confidence: 99%

Correlation between arterial blood volume obtained by arterial spin labelling and cerebral blood volume in intracranial tumours

Westen

Petersen

Wirestam

et al. 2011

Magn Reson Mater Phy

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“…C͑t͒ ϭ C est ͑t͒ h*͑t͒ (10) where C est is the estimated concentration time curve that undergoes delay and/or dispersion during the passage from the point of the measurement to the tissue voxel. Artificial noise was added in the same way as in the simulations of arterial delay described above.…”

Section: Simulationsmentioning

confidence: 99%

“…For example, Rempp et al (10) assigned certain criteria to the full width at half maximum (FWHM), the maximum concentration (MC), and the moment of MC (MMC) of the concentration time curves. Only concentration curves that met the criteria and showed an MC of at least 75% of the highest value observed were selected, and the mean of these concentration time curves was used as the AIF.…”

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confidence: 99%

Calculation of cerebral perfusion parameters using regional arterial input functions identified by factor analysis

Knutsson

Larsson

Thilmann

et al. 2006

Magnetic Resonance Imaging

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Purpose: To calculate regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and regional mean transit time (rMTT) accurately, an arterial input function (AIF) is required. In this study we identified a number of AIFs using factor analysis of dynamic studies (FADS), and performed the cerebral perfusion calculation pixel by pixel using the AIF that was located geometrically closest to a certain voxel. Materials and Methods:To verify the robustness of the method, simulated images were generated in which dispersion or delay was added in some arteries and in the corresponding cerebral gray matter (GM), white matter (WM), and ischemic tissue. Thereafter, AIFs were determined using the FADS method and simulations were performed using different signal-to-noise ratios (SNRs). Simulations were also carried out using an AIF from a single pixel that was manually selected. In vivo results were obtained from normal volunteers and patients. Results:The FADS method reduced the underestimation of rCBF due to dispersion or delay that often occurs when only one AIF represents the entire brain. Conclusion:This study indicates that the use of FADS and the nearest-AIF method is preferable to manual selection of one single AIF.

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“…Voxel-based measurements of the bolus passage in tissue give information about local cerebral blood flow, cerebral blood volume and subsequently the mean transit time (1,2). These local perfusion estimates are useful, for example, for staging tumors and assessing the tissue at risk of permanent damage after a stroke (3,4).…”

mentioning

confidence: 99%

“…Deconvolution with a local AIF produces residue functions that are less affected by delay and dispersion effects due to the transport of the contrast agent from the location of the AIF determination to the beginning of the capillary bed (12). The former can be corrected for by using delay-insensitive deconvolution techniques, but dispersion corrupts the perfusion estimates (2,13,14). In addition, local AIF measurements are flow territory specific, which can be especially beneficial when there is a stenosed or occluded large artery, since such large vessel pathologies lead to additional delay and dispersion in the corresponding flow territory (15).…”

mentioning

confidence: 99%

Evaluation of signal formation in local arterial input function measurements of dynamic susceptibility contrast MRI

Bleeker

Webb

Walderveen

et al. 2011

Magnetic Resonance in Med

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Correct arterial input function (AIF) measurements in dynamic susceptibility contrast-MRI are crucial for quantification of the hemodynamic parameters. Often a single global AIF is selected near a large brain-feeding artery. Alternatively, local AIF measurements aim for voxel-specific AIFs from smaller arteries. Because local AIFs are measured higher in the arterial-tree, it is assumed that these will reflect the true input of the microvasculature much better. However, do the measured local AIFs reflect the true concentration-time curves of small arteries? To answer this question, in vivo data were used to evaluate local AIF candidates selected based on two different types of angiograms. For interpretation purposes, a 3D numerical model that simulated partial-volume effects in local AIF measurements was created and the simulated local AIFs were compared to the ground truth. The findings are 2-fold. First, the in vivo data showed that the shape-characteristics of local AIFs are similar to the shape-characteristics of gray matter concentration-time curves. Second, these findings are supported by the simulations showing broadening of the measured local AIFs compared to the ground truth. These findings are suggesting that local AIF measurements do not necessarily reflect the true concentration-time curve in small arteries. Magn Reson Med 67:1324-1331,

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Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging.

Cited by 582 publications

References 0 publications

Correlation between arterial blood volume obtained by arterial spin labelling and cerebral blood volume in intracranial tumours

Correlation between arterial blood volume obtained by arterial spin labelling and cerebral blood volume in intracranial tumours

Calculation of cerebral perfusion parameters using regional arterial input functions identified by factor analysis

Evaluation of signal formation in local arterial input function measurements of dynamic susceptibility contrast MRI

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