Method for improving the accuracy of quantitative cerebral perfusion imaging

Sakaie, Kenneth Earl; Shin, Wanyong; Curtin, Kenneth R.; McCarthy, Richard M.; Cashen, Ty A.; Carroll, Timothy J.

doi:10.1002/jmri.20305

Cited by 59 publications

(98 citation statements)

References 37 publications

(50 reference statements)

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“…Recently, some techniques have been derived to address quantification issues arising from AIF PVE (11,20). However, these advanced methods have not yet been widely adopted in clinical practice, in part because they are new, but also because they complicate the perfusion methodology in clinical practice and, when used individually, only address AIF PVE error, obviating the need for the extra effort.…”

Section: Discussionmentioning

confidence: 99%

“…The accuracy of CBF CC is simply then reflected in the variation of the control distribution. As an example, Sakaie et al (11) combined results from two previous PET studies and reported that normal WM CBF was 23.7 Ϯ 3.79 mL/minute/100 g (mean and standard deviation). Therefore, for normal subjects cross-calibrated to this normal WM CBF distribution, each voxel on the CBF CC map would have a relative standard error of 100% ⅐ 3.79/23.7 ϭ 16.0%.…”

Section: Discussionmentioning

confidence: 99%

“…Recent in vivo studies comparing DSC-MR and PET are conflicting: one suggested that DSC-MR CBF quantification was not possible at all (7), while another reported that DSC-MR CBF estimates are physiologically believable with the exception of some GM regions that were overestimated (8). Many other studies have also reported overestimated absolute DSC-MR CBF measurements (3,(11)(12)(13). DSC-MR simulation and in vivo experimental results do not seem to predict the same degree of absolute CBF error, which implies that the DSC-MR perfusion model is still not understood (8).…”

Section: Discussionmentioning

confidence: 99%

“…However, acquisition limitations in the measurement of the tracer concentration from arterial blood (called the arterial input function [AIF]) is a cause of large errors in absolute DSC-MR CBF estimates derived by deconvolution (10). If left uncorrected, these AIF CBF errors generally cause large, physiologically unreasonable CBF estimates relative to gold standard techniques (e.g., positron emission tomography [PET]) (3,7,9,(11)(12)(13). As a result, DSC-MR CBF maps are often scaled to correspond to PET using either a constant conversion factor derived from normal patients (14) or are cross-calibrated by setting a reference region (or cross-calibration region [CCR]) to a known population-based CBF average assumed to have low variation (15)(16)(17) in order to provide CBF estimates suitable for between-subject comparisons.…”

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confidence: 99%

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Cerebral blood flow estimation in vivo using local tissue reference functions

Kosior¹,

Smith²,

Kosior³

et al. 2008

Magnetic Resonance Imaging

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Purpose:To evaluate the use of bolus signals obtained from tissue as reference functions (or local reference functions [LRFs]) rather than arterial input functions (AIFs) when deriving cross-calibrated cerebral blood flow (CBF CC ) estimates via deconvolution. Materials and Methods:AIF and white matter (WM) LRF CBF CC maps (cross-calibrated so that normal WM was 23.7 mL/minute/100 g) derived using singular value decomposition (SVD) were examined in 28 ischemic stroke patients. Median CBF CC estimates from normal gray matter (GM) and ischemic tissue were obtained.Results: AIF and LRF median CBF CC estimates resembled one another for all 28 patients (average paired CBF CC difference 0.4 Ϯ 1.7 mL/minute/100 g and -0.4 Ϯ 1.4 mL/ minute/100 g in GM and ischemic tissue, respectively). Wilcoxon signed-rank comparisons of patient median CBF CC measurements revealed no statistically significant differences between using AIFs and LRFs (P Ͼ 0.05). Conclusion:If CBF is quantified using a patient-specific cross-calibration factor, then LRF CBF estimates are at least as accurate as those from AIFs. Therefore, until AIF quantification is achievable in vivo, perfusion protocols tailored for LRFs would simplify the methodology and provide more reliable perfusion information.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Cerebral blood flow estimation in vivo using local tissue reference functions

Kosior¹,

Smith²,

Kosior³

et al. 2008

Magnetic Resonance Imaging

View full text Add to dashboard Cite

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“…In the previously proposed Bookend method [7,8], CBV is estimated using steady-state measurements of T1 before and after contrast agent (CA) administration to determine the CF. The Bookend method has previously been compared to positron emission tomography (PET), which is commonly regarded as the gold standard method for CBF measurements, and a good correlation between the two methods was observed [9].…”

Section: Introductionmentioning

confidence: 99%

Absolute quantification of perfusion by dynamic susceptibility contrast MRI using Bookend and VASO steady-state CBV calibration: a comparison with pseudo-continuous ASL

Lindgren

Wirestam

Bloch

et al. 2014

Magn Reson Mater Phy

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General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal AbstractObjective: Dynamic susceptibility-contrast MRI (DSC-MRI) tends to return elevated estimates of cerebral blood flow (CBF) and cerebral blood volume (CBV). In this study, subject-specific calibration factors (CFs), based on steady-state CBV measurements, were applied to rescale the absolute level of DSC-MRI CBF. Materials and Methods:Twenty healthy volunteers were scanned in a test-retest approach. Independent CBV measurements, for calibration, were accomplished using a T1-based contrast agent steady-state method (referred to as Bookend) as well as a blood-nulling vascular space occupancy (VASO) approach. Calibrated DSC-MRI was compared with pseudo-continuous arterial spin labeling (pCASL).Results: For segmented grey matter (GM) regions of interests (ROIs), pCASL-based CBF was 63±11 ml/(min100g) (mean±SD). Nominal CBF from non-calibrated DSC-MRI was 277±61 ml/(min100g), while calibrations resulted in 56±23 ml/(min100g) (Bookend) and 52±16 ml/(min100g) (VASO). Calibration tended to eliminate the overestimation, although the repeatability was, generally, moderate and the correlation between calibrated DSC-MRI and pCASL was low (r<0.25). However, using GM instead of WM ROIs for extraction of CFs resulted in improved repeatability. Conclusion:Both calibration approaches provided reasonable absolute levels of GM CBF, although the calibration methods suffered from low signal-to-noise ratio, resulting in weak repeatability and difficulties in showing high degrees of correlation with pCASL measurements.3

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Anterior–posterior cerebral blood volume gradient in human subiculum

et al. 2014

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The human hippocampal formation is characterized by anterior-posterior gradients of cell density, neurochemistry and hemodynamics. In addition, some functions are associated with specific subfields (subiculum, CA1–4, dentate gyrus) and regions (anterior and posterior). We performed contrast-enhanced, high-resolution T1-weighted 3T steady state (SS) imaging to investigate cerebral blood volume (CBV) gradients of the hippocampal formation. We studied 14 healthy subjects and found significant CBV gradients (anterior > posterior) in the subiculum but not in other hippocampal subfields. Since CBV is a marker of basal metabolism, these results indicate a greater baseline activity in the anterior compared to the posterior subiculum. This gradient might be related to the role of the subiculum as the main outflow station of the hippocampal formation and might have implications for the mechanisms of neuropsychiatric disorders.

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Method for improving the accuracy of quantitative cerebral perfusion imaging

Cited by 59 publications

References 37 publications

Cerebral blood flow estimation in vivo using local tissue reference functions

Cerebral blood flow estimation in vivo using local tissue reference functions

Absolute quantification of perfusion by dynamic susceptibility contrast MRI using Bookend and VASO steady-state CBV calibration: a comparison with pseudo-continuous ASL

Anterior–posterior cerebral blood volume gradient in human subiculum

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