Tracer Delay–Insensitive Algorithm Can Improve Reliability of CT Perfusion Imaging for Cerebrovascular Steno-Occlusive Disease: Comparison with Quantitative Single-Photon Emission CT

Sasaki, Makoto; Kudo, Kohsuke; Ogasawara, Kuniaki; Fujiwara, Shunro

doi:10.3174/ajnr.a1274

Cited by 45 publications

(39 citation statements)

References 16 publications

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“…It does not matter if the reference is a mixture of GM and WM as long as the GM/WM ratio is nearly constant among diŠerent subjects by including a certain amount of volume in the reference. Most recently, Sasaki and associates demonstrated that CBFratio referencing to the healthy hemisphere was better than the absolute CBF obtained with cSVD, even by CT perfusion, 34 for intersubject comparison among ischemic patients. Chen also demonstrated that the rescaling approach for SVD and the Fourier Transform-based method using CBF＝22 mL/100 cc/min of normal WM reduced error in CBF except for MTT dependency.…”

Section: D) Vascular Modelmentioning

confidence: 99%

Reference-based Maximum Upslope: A CBF Quantification Method without Using Arterial Input Function in Dynamic Susceptibility Contrast MRI

Kimura

Kusahara

2009

magn reson med sci

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Purpose: We assessed errors in cerebral blood ‰ow (CBF) obtained from our proposed reference-based method without using arterial input function (AIF) indices in dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI).Materials and Methods: We calculated CBF and the referential tissue-related ratio (CBFratio) using numerical simulation and 3 nondeconvolution methods and a deconvolution method of block-circulant singular value decomposition (cSVD). We compared errors with and without simulated noise as parameters of mean transit time (MTT), AIF delay and temporal resolution, and clinical DSC-MRI maps.Results: The errors in CBF obtained using maximum upslope (US) were smallest among the nondeconvolution methods and almost equivalent to errors in the cSVD method under practical imaging conditions. In addition, errors in the CBFratio obtained using referencebased US (Ref-US) referring to white matter were smallest, even compared to all errors in CBF and CBFratio. The Ref-US method introduced less error than the cSVD method, especially at low ‰ow rates, was further robust against AIF noise and coarse temporal resolution, and was comparably robust against transit delay. In pixel-by-pixel correlations between absolute value maps for US and for cSVD-CBF in clinical DSC-MRI, those correlation coe‹cients (r) between the 2 maps were stable, rÀ0.9, despite variation in the slopes of the linear regression line, so the 2 CBFratio maps were visually well correlated in any case.Conclusion: The Ref-US technique without AIF measurement can become a practical perfusion methodology for DSC-MRI in patients even with acute stroke because it balances robustness with systematic and random errors and it is simply performed.

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Section: D) Vascular Modelmentioning

confidence: 99%

Reference-based Maximum Upslope: A CBF Quantification Method without Using Arterial Input Function in Dynamic Susceptibility Contrast MRI

Kimura

Kusahara

2009

magn reson med sci

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“…Horizontally in the tiles the MTT was varied (24,12,8 Prior to analysis, the slices in the phantom were filtered with a two-dimensional (2-D) Gaussian kernel with a standard deviation of 2.5 pixels. No additional filtering was applied.…”

Section: Digital Perfusion Phantommentioning

confidence: 99%

“…A previous study also reported that bSVD underestimates quantitative CBF values, presumably due to image noise. 24 More quantitative methods could lower the variability in CTP measurements due to observers, scanners, acquisition protocols, reconstruction methods, and analysis software. This may in turn result in more robust predictions of infarct core and penumbra, and minimizing the need for situation-specific thresholds and other software-calibration.…”

Section: Clinical Datamentioning

confidence: 99%

Fast nonlinear regression method for CT brain perfusion analysis

et al. 2016

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Abstract. Although computed tomography (CT) perfusion (CTP) imaging enables rapid diagnosis and prognosis of ischemic stroke, current CTP analysis methods have several shortcomings. We propose a fast nonlinear regression method with a box-shaped model (boxNLR) that has important advantages over the current state-of-the-art method, block-circulant singular value decomposition (bSVD). These advantages include improved robustness to attenuation curve truncation, extensibility, and unified estimation of perfusion parameters. The method is compared with bSVD and with a commercial SVD-based method. The three methods were quantitatively evaluated by means of a digital perfusion phantom, described by Kudo et al. and qualitatively with the aid of 50 clinical CTP scans. All three methods yielded high Pearson correlation coefficients (>0.9) with the ground truth in the phantom. The boxNLR perfusion maps of the clinical scans showed higher correlation with bSVD than the perfusion maps from the commercial method. Furthermore, it was shown that boxNLR estimates are robust to noise, truncation, and tracer delay. The proposed method provides a fast and reliable way of estimating perfusion parameters from CTP scans. This suggests it could be a viable alternative to current commercial and academic methods.

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“…4,13,14,22 Different corrective functions for partial-volume effects (inaccurate measurements of contrast media concentration that occur due to the small size or location of cerebral vessels) cause significantly different CT perfusion results. 25 Computed tomography perfusion software that uses a corrective technique called vascular pixel elimination was found to more closely correlate with PET results than software that does not incorporate this technique.…”

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confidence: 99%

Sources of variability in computed tomography perfusion: implications for acute stroke management

Zussman

Jabbour²,

Talekar

et al. 2011

FOC

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Object Although dynamic, first-pass cerebral CT perfusion is used in the evaluation of acute ischemic stroke, a lack of standardization restricts the value of this imaging modality in clinical decision-making. The purpose of this study was to comprehensively review the reported sources of variability and error in cerebral CT perfusion results. Methods A systematic literature review was conducted, 120 articles were reviewed, and 23 published original research articles were included. Sources of variability and error were thematically categorized and presented within the context of the 3 stages of a typical CT perfusion study: data acquisition, postprocessing, and results interpretation. Results Seven factors that caused variability were identified and described in detail: 1) contrast media, the iodinated compound injected intravascularly to permit imaging of the cerebral vessels; 2) data acquisition rate, the number of images obtained by CT scan per unit time; 3) user inputs, the subjective selections that operators make; 4) observer variation, the failure of operators to repeatedly measure a perfusion parameter with precision; 5) software operational mode, manual, semiautomatic, or automatic; 6) software design, the mathematical algorithms used to perform postprocessing; and 7) value type, absolute versus relative values. Conclusions Standardization at all 3 stages of the CT perfusion study cycle is warranted. At present, caution should be exercised when interpreting CT perfusion results as these values may vary considerably depending on a variety of factors. Future research is needed to define the role of CT perfusion in clinical decision-making for acute stroke patients and to determine the clinically acceptable limits of variability in CT perfusion results.

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Tracer Delay–Insensitive Algorithm Can Improve Reliability of CT Perfusion Imaging for Cerebrovascular Steno-Occlusive Disease: Comparison with Quantitative Single-Photon Emission CT

Cited by 45 publications

References 16 publications

Reference-based Maximum Upslope: A CBF Quantification Method without Using Arterial Input Function in Dynamic Susceptibility Contrast MRI

Reference-based Maximum Upslope: A CBF Quantification Method without Using Arterial Input Function in Dynamic Susceptibility Contrast MRI

Fast nonlinear regression method for CT brain perfusion analysis

Sources of variability in computed tomography perfusion: implications for acute stroke management

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